From fa0deededa5c27cfbc190b207009626c3c00aabc Mon Sep 17 00:00:00 2001
From: Jin Kim <golbin@gmail.com>
Date: Mon, 9 Sep 2024 10:53:23 +0900
Subject: [PATCH 001/135] Add voice options and make to use InputParams for
 Cartesia.

---
 .../07d-interruptible-cartesia.py             |  4 +-
 .../12c-describe-video-anthropic.py           |  4 +-
 examples/studypal/studypal.py                 |  4 +-
 src/pipecat/services/cartesia.py              | 45 +++++++++++++------
 4 files changed, 40 insertions(+), 17 deletions(-)

diff --git a/examples/foundational/07d-interruptible-cartesia.py b/examples/foundational/07d-interruptible-cartesia.py
index 6b8bbcc5f..7bcc7476b 100644
--- a/examples/foundational/07d-interruptible-cartesia.py
+++ b/examples/foundational/07d-interruptible-cartesia.py
@@ -52,7 +52,9 @@ async def main():
         tts = CartesiaTTSService(
             api_key=os.getenv("CARTESIA_API_KEY"),
             voice_id="a0e99841-438c-4a64-b679-ae501e7d6091",  # Barbershop Man
-            sample_rate=44100,
+            params=CartesiaTTSService.InputParams(
+                sample_rate=44100,
+            ),
         )
 
         llm = OpenAILLMService(
diff --git a/examples/foundational/12c-describe-video-anthropic.py b/examples/foundational/12c-describe-video-anthropic.py
index cc1f14c92..8531debf8 100644
--- a/examples/foundational/12c-describe-video-anthropic.py
+++ b/examples/foundational/12c-describe-video-anthropic.py
@@ -78,7 +78,9 @@ async def main():
         tts = CartesiaTTSService(
             api_key=os.getenv("CARTESIA_API_KEY"),
             voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
-            sample_rate=16000,
+            params=CartesiaTTSService.InputParams(
+                sample_rate=16000,
+            ),
         )
 
         @transport.event_handler("on_first_participant_joined")
diff --git a/examples/studypal/studypal.py b/examples/studypal/studypal.py
index 8adfe2954..f14bd3def 100644
--- a/examples/studypal/studypal.py
+++ b/examples/studypal/studypal.py
@@ -124,7 +124,9 @@ async def main():
             api_key=os.getenv("CARTESIA_API_KEY"),
             voice_id=os.getenv("CARTESIA_VOICE_ID", "4d2fd738-3b3d-4368-957a-bb4805275bd9"),
             # British Narration Lady: 4d2fd738-3b3d-4368-957a-bb4805275bd9
-            sample_rate=44100,
+            params=CartesiaTTSService.InputParams(
+                sample_rate=44100,
+            ),
         )
 
         llm = OpenAILLMService(
diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index e3541ccea..927da53f0 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -10,7 +10,8 @@ import base64
 import asyncio
 import time
 
-from typing import AsyncGenerator, Mapping
+from typing import AsyncGenerator, Optional
+from pydantic.main import BaseModel
 
 from pipecat.frames.frames import (
     CancelFrame,
@@ -61,6 +62,14 @@ def language_to_cartesia_language(language: Language) -> str | None:
 
 
 class CartesiaTTSService(TTSService):
+    class InputParams(BaseModel):
+        model_id: Optional[str] = "sonic-english"
+        encoding: Optional[str] = "pcm_s16le"
+        sample_rate: Optional[int] = 16000
+        container: Optional[str] = "raw"
+        language: Optional[str] = "en"
+        speed: Optional[str] = None
+        emotion: Optional[list[str]] = []
 
     def __init__(
             self,
@@ -69,10 +78,7 @@ class CartesiaTTSService(TTSService):
             voice_id: str,
             cartesia_version: str = "2024-06-10",
             url: str = "wss://api.cartesia.ai/tts/websocket",
-            model_id: str = "sonic-english",
-            encoding: str = "pcm_s16le",
-            sample_rate: int = 16000,
-            language: str = "en",
+            params: InputParams = InputParams(),
             **kwargs):
         super().__init__(**kwargs)
 
@@ -92,13 +98,15 @@ class CartesiaTTSService(TTSService):
         self._cartesia_version = cartesia_version
         self._url = url
         self._voice_id = voice_id
-        self._model_id = model_id
+        self._model_id = params.model_id
         self._output_format = {
-            "container": "raw",
-            "encoding": encoding,
-            "sample_rate": sample_rate,
+            "container": params.container,
+            "encoding": params.encoding,
+            "sample_rate": params.sample_rate,
         }
-        self._language = language
+        self._language = params.language
+        self._speed = params.speed
+        self._emotion = params.emotion
 
         self._websocket = None
         self._context_id = None
@@ -249,15 +257,24 @@ class CartesiaTTSService(TTSService):
                 await self.start_ttfb_metrics()
                 self._context_id = str(uuid.uuid4())
 
+            voice_config = {
+                "mode": "id",
+                "id": self._voice_id
+            }
+
+            if self._speed or self._emotion:
+                voice_config["__experimental_controls"] = {}
+                if self._speed:
+                    voice_config["__experimental_controls"]["speed"] = self._speed
+                if self._emotion:
+                    voice_config["__experimental_controls"]["emotion"] = self._emotion
+
             msg = {
                 "transcript": text + " ",
                 "continue": True,
                 "context_id": self._context_id,
                 "model_id": self._model_id,
-                "voice": {
-                    "mode": "id",
-                    "id": self._voice_id
-                },
+                "voice": voice_config,
                 "output_format": self._output_format,
                 "language": self._language,
                 "add_timestamps": True,

From 3cbe97d346c42d5694ba06f35ec92d2c5feeab00 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Thu, 12 Sep 2024 00:31:23 -0700
Subject: [PATCH 002/135] clocks: added new BaseClock and SystemClock

---
 src/pipecat/clocks/__init__.py         |  0
 src/pipecat/clocks/base_clock.py       | 18 ++++++++++++++++++
 src/pipecat/clocks/system_clock.py     | 21 +++++++++++++++++++++
 src/pipecat/transcriptions/__init__.py |  0
 4 files changed, 39 insertions(+)
 create mode 100644 src/pipecat/clocks/__init__.py
 create mode 100644 src/pipecat/clocks/base_clock.py
 create mode 100644 src/pipecat/clocks/system_clock.py
 create mode 100644 src/pipecat/transcriptions/__init__.py

diff --git a/src/pipecat/clocks/__init__.py b/src/pipecat/clocks/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/src/pipecat/clocks/base_clock.py b/src/pipecat/clocks/base_clock.py
new file mode 100644
index 000000000..aa7b7b806
--- /dev/null
+++ b/src/pipecat/clocks/base_clock.py
@@ -0,0 +1,18 @@
+#
+# Copyright (c) 2024, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+from abc import ABC, abstractmethod
+
+
+class BaseClock(ABC):
+
+    @abstractmethod
+    def get_time(self) -> int:
+        pass
+
+    @abstractmethod
+    def start(self):
+        pass
diff --git a/src/pipecat/clocks/system_clock.py b/src/pipecat/clocks/system_clock.py
new file mode 100644
index 000000000..20319cff6
--- /dev/null
+++ b/src/pipecat/clocks/system_clock.py
@@ -0,0 +1,21 @@
+#
+# Copyright (c) 2024, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import time
+
+from pipecat.clocks.base_clock import BaseClock
+
+
+class SystemClock(BaseClock):
+
+    def __init__(self):
+        self._time = 0
+
+    def get_time(self) -> int:
+        return time.monotonic_ns() - self._time if self._time > 0 else 0
+
+    def start(self):
+        self._time = time.monotonic_ns()
diff --git a/src/pipecat/transcriptions/__init__.py b/src/pipecat/transcriptions/__init__.py
new file mode 100644
index 000000000..e69de29bb

From 72f231b32732ab572c35291262c67e903815efbb Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Thu, 12 Sep 2024 00:17:04 -0700
Subject: [PATCH 003/135] frames: add a presentation timestamp (pts) to each
 frame

---
 src/pipecat/frames/frames.py | 58 ++++++++++++++++++++++++++++++------
 src/pipecat/utils/time.py    | 17 +++++++++++
 2 files changed, 66 insertions(+), 9 deletions(-)

diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py
index 13c2f53f1..9cad1268d 100644
--- a/src/pipecat/frames/frames.py
+++ b/src/pipecat/frames/frames.py
@@ -8,19 +8,27 @@ from typing import Any, List, Mapping, Optional, Tuple
 
 from dataclasses import dataclass, field
 
+from pipecat.clocks.base_clock import BaseClock
 from pipecat.transcriptions.language import Language
+from pipecat.utils.time import nanoseconds_to_str
 from pipecat.utils.utils import obj_count, obj_id
 from pipecat.vad.vad_analyzer import VADParams
 
 
+def format_pts(pts: int | None):
+    return nanoseconds_to_str(pts) if pts else None
+
+
 @dataclass
 class Frame:
     id: int = field(init=False)
     name: str = field(init=False)
+    pts: Optional[int] = field(init=False)
 
     def __post_init__(self):
         self.id: int = obj_id()
         self.name: str = f"{self.__class__.__name__}#{obj_count(self)}"
+        self.pts: Optional[int] = None
 
     def __str__(self):
         return self.name
@@ -46,7 +54,14 @@ class AudioRawFrame(DataFrame):
         self.num_frames = int(len(self.audio) / (self.num_channels * 2))
 
     def __str__(self):
-        return f"{self.name}(size: {len(self.audio)}, frames: {self.num_frames}, sample_rate: {self.sample_rate}, channels: {self.num_channels})"
+        pts = format_pts(self.pts)
+        return f"{
+            self.name}(pts: {pts}, size: {
+            len(
+                self.audio)}, frames: {
+                self.num_frames}, sample_rate: {
+                    self.sample_rate}, channels: {
+                        self.num_channels})"
 
 
 @dataclass
@@ -60,7 +75,8 @@ class ImageRawFrame(DataFrame):
     format: str | None
 
     def __str__(self):
-        return f"{self.name}(size: {self.size}, format: {self.format})"
+        pts = format_pts(self.pts)
+        return f"{self.name}(pts: {pts}, size: {self.size}, format: {self.format})"
 
 
 @dataclass
@@ -72,7 +88,8 @@ class URLImageRawFrame(ImageRawFrame):
     url: str | None
 
     def __str__(self):
-        return f"{self.name}(url: {self.url}, size: {self.size}, format: {self.format})"
+        pts = format_pts(self.pts)
+        return f"{self.name}(pts: {pts}, url: {self.url}, size: {self.size}, format: {self.format})"
 
 
 @dataclass
@@ -84,7 +101,12 @@ class VisionImageRawFrame(ImageRawFrame):
     text: str | None
 
     def __str__(self):
-        return f"{self.name}(text: {self.text}, size: {self.size}, format: {self.format})"
+        pts = format_pts(self.pts)
+        return f"{
+            self.name}(pts: {pts}, text: {
+            self.text}, size: {
+            self.size}, format: {
+                self.format})"
 
 
 @dataclass
@@ -96,7 +118,12 @@ class UserImageRawFrame(ImageRawFrame):
     user_id: str
 
     def __str__(self):
-        return f"{self.name}(user: {self.user_id}, size: {self.size}, format: {self.format})"
+        pts = format_pts(self.pts)
+        return f"{
+            self.name}(pts: {pts}, user: {
+            self.user_id}, size: {
+            self.size}, format: {
+                self.format})"
 
 
 @dataclass
@@ -109,7 +136,8 @@ class SpriteFrame(Frame):
     images: List[ImageRawFrame]
 
     def __str__(self):
-        return f"{self.name}(size: {len(self.images)})"
+        pts = format_pts(self.pts)
+        return f"{self.name}(pts: {pts}, size: {len(self.images)})"
 
 
 @dataclass
@@ -121,7 +149,8 @@ class TextFrame(DataFrame):
     text: str
 
     def __str__(self):
-        return f"{self.name}(text: {self.text})"
+        pts = format_pts(self.pts)
+        return f"{self.name}(pts: {pts}, text: {self.text})"
 
 
 @dataclass
@@ -135,7 +164,12 @@ class TranscriptionFrame(TextFrame):
     language: Language | None = None
 
     def __str__(self):
-        return f"{self.name}(user: {self.user_id}, text: {self.text}, language: {self.language}, timestamp: {self.timestamp})"
+        return f"{
+            self.name}(user: {
+            self.user_id}, text: {
+            self.text}, language: {
+                self.language}, timestamp: {
+                    self.timestamp})"
 
 
 @dataclass
@@ -147,7 +181,12 @@ class InterimTranscriptionFrame(TextFrame):
     language: Language | None = None
 
     def __str__(self):
-        return f"{self.name}(user: {self.user_id}, text: {self.text}, language: {self.language}, timestamp: {self.timestamp})"
+        return f"{
+            self.name}(user: {
+            self.user_id}, text: {
+                self.text}, language: {
+                    self.language}, timestamp: {
+                        self.timestamp})"
 
 
 @dataclass
@@ -326,6 +365,7 @@ class ControlFrame(Frame):
 @dataclass
 class StartFrame(ControlFrame):
     """This is the first frame that should be pushed down a pipeline."""
+    clock: BaseClock
     allow_interruptions: bool = False
     enable_metrics: bool = False
     enable_usage_metrics: bool = False
diff --git a/src/pipecat/utils/time.py b/src/pipecat/utils/time.py
index af493e77b..0f6ca1076 100644
--- a/src/pipecat/utils/time.py
+++ b/src/pipecat/utils/time.py
@@ -9,3 +9,20 @@ import datetime
 
 def time_now_iso8601() -> str:
     return datetime.datetime.now(datetime.timezone.utc).isoformat(timespec="milliseconds")
+
+
+def seconds_to_nanoseconds(seconds: float) -> int:
+    return int(seconds * 1_000_000_000)
+
+
+def nanoseconds_to_seconds(nanoseconds: int) -> float:
+    return nanoseconds / 1_000_000_000
+
+
+def nanoseconds_to_str(nanoseconds: int) -> str:
+    total_seconds = nanoseconds_to_seconds(nanoseconds)
+    hours = int(total_seconds // 3600)
+    minutes = int((total_seconds % 3600) // 60)
+    seconds = int(total_seconds % 60)
+    microseconds = int((total_seconds - int(total_seconds)) * 1_000_000)
+    return f"{hours}:{minutes:02}:{seconds:02}.{microseconds:06}"

From 7807cbeb397804ad0c500432d39b24ee10f21743 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Thu, 12 Sep 2024 00:18:24 -0700
Subject: [PATCH 004/135] pipeline(task): add a clock to the pipeline task

---
 src/pipecat/pipeline/task.py | 14 ++++++++++++--
 1 file changed, 12 insertions(+), 2 deletions(-)

diff --git a/src/pipecat/pipeline/task.py b/src/pipecat/pipeline/task.py
index 102b4528b..03fd5c734 100644
--- a/src/pipecat/pipeline/task.py
+++ b/src/pipecat/pipeline/task.py
@@ -10,6 +10,8 @@ from typing import AsyncIterable, Iterable
 
 from pydantic import BaseModel
 
+from pipecat.clocks.base_clock import BaseClock
+from pipecat.clocks.system_clock import SystemClock
 from pipecat.frames.frames import (
     CancelFrame,
     EndFrame,
@@ -60,11 +62,16 @@ class Source(FrameProcessor):
 
 class PipelineTask:
 
-    def __init__(self, pipeline: BasePipeline, params: PipelineParams = PipelineParams()):
+    def __init__(
+            self,
+            pipeline: BasePipeline,
+            params: PipelineParams = PipelineParams(),
+            clock: BaseClock = SystemClock()):
         self.id: int = obj_id()
         self.name: str = f"{self.__class__.__name__}#{obj_count(self)}"
 
         self._pipeline = pipeline
+        self._clock = clock
         self._params = params
         self._finished = False
 
@@ -116,11 +123,14 @@ class PipelineTask:
         return MetricsFrame(ttfb=ttfb, processing=processing)
 
     async def _process_down_queue(self):
+        self._clock.start()
+
         start_frame = StartFrame(
             allow_interruptions=self._params.allow_interruptions,
             enable_metrics=self._params.enable_metrics,
             enable_usage_metrics=self._params.enable_metrics,
-            report_only_initial_ttfb=self._params.report_only_initial_ttfb
+            report_only_initial_ttfb=self._params.report_only_initial_ttfb,
+            clock=self._clock
         )
         await self._source.process_frame(start_frame, FrameDirection.DOWNSTREAM)
 

From 7749692f72181916725bfa075002bfb6b3f8cd59 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Thu, 12 Sep 2024 00:18:29 -0700
Subject: [PATCH 005/135] processors: get pipeline clock from StartFrame

---
 src/pipecat/processors/frame_processor.py | 13 ++++++++++++-
 1 file changed, 12 insertions(+), 1 deletion(-)

diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py
index 156e1c0ae..e228ec6b4 100644
--- a/src/pipecat/processors/frame_processor.py
+++ b/src/pipecat/processors/frame_processor.py
@@ -9,6 +9,7 @@ import time
 
 from enum import Enum
 
+from pipecat.clocks.base_clock import BaseClock
 from pipecat.frames.frames import (
     ErrorFrame,
     Frame,
@@ -69,7 +70,10 @@ class FrameProcessorMetrics:
 
     async def start_llm_usage_metrics(self, tokens: dict):
         logger.debug(
-            f"{self._name} prompt tokens: {tokens['prompt_tokens']}, completion tokens: {tokens['completion_tokens']}")
+            f"{
+                self._name} prompt tokens: {
+                tokens['prompt_tokens']}, completion tokens: {
+                tokens['completion_tokens']}")
         return MetricsFrame(tokens=[tokens])
 
     async def start_tts_usage_metrics(self, text: str):
@@ -96,6 +100,9 @@ class FrameProcessor:
         self._next: "FrameProcessor" | None = None
         self._loop: asyncio.AbstractEventLoop = loop or asyncio.get_running_loop()
 
+        # Clock
+        self._clock: BaseClock | None = None
+
         # Properties
         self._allow_interruptions = False
         self._enable_metrics = False
@@ -177,8 +184,12 @@ class FrameProcessor:
     def get_parent(self) -> "FrameProcessor":
         return self._parent
 
+    def get_clock(self) -> BaseClock:
+        return self._clock
+
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         if isinstance(frame, StartFrame):
+            self._clock = frame.clock
             self._allow_interruptions = frame.allow_interruptions
             self._enable_metrics = frame.enable_metrics
             self._enable_usage_metrics = frame.enable_usage_metrics

From 02d926e9bd75dd011cad844645087a0365842441 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Thu, 12 Sep 2024 00:18:55 -0700
Subject: [PATCH 006/135] services: create AsyncTTSService and
 AsyncWordTTSService

---
 src/pipecat/services/ai_services.py | 74 ++++++++++++++++++++++++++++-
 1 file changed, 73 insertions(+), 1 deletion(-)

diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index c5cb7cc0d..72a8828c2 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -6,10 +6,11 @@
 
 import asyncio
 import io
+import time
 import wave
 
 from abc import abstractmethod
-from typing import AsyncGenerator, Optional
+from typing import AsyncGenerator, List, Optional, Tuple
 
 from pipecat.frames.frames import (
     AudioRawFrame,
@@ -37,9 +38,12 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.transcriptions.language import Language
 from pipecat.utils.audio import calculate_audio_volume
 from pipecat.utils.string import match_endofsentence
+from pipecat.utils.time import seconds_to_nanoseconds
 from pipecat.utils.utils import exp_smoothing
 from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 
+from loguru import logger
+
 
 class AIService(FrameProcessor):
     def __init__(self, **kwargs):
@@ -303,6 +307,74 @@ class TTSService(AIService):
             pass
 
 
+class AsyncTTSService(TTSService):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+
+    @abstractmethod
+    async def flush_audio(self):
+        pass
+
+
+class AsyncWordTTSService(AsyncTTSService):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+        self._start_word_timestamp = None
+        self._words_queue = asyncio.Queue()
+        self._words_task = self.get_event_loop().create_task(self._words_task_handler())
+
+    def init_word_timestamps(self):
+        if not self._start_word_timestamp:
+            self._start_word_timestamp = self.get_clock().get_time()
+
+    def reset_word_timestamps(self):
+        self._start_word_timestamp = None
+        self._word_timestamps = []
+
+    async def add_word_timestamps(self, word_times: List[Tuple[str, float]]):
+        for (word, timestamp) in word_times:
+            await self._words_queue.put((word, seconds_to_nanoseconds(timestamp)))
+
+    async def stop(self, frame: EndFrame):
+        await super().stop(frame)
+        await self._stop_words_task()
+
+    async def cancel(self, frame: CancelFrame):
+        await super().cancel(frame)
+        await self._stop_words_task()
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        if isinstance(frame, LLMFullResponseEndFrame) or isinstance(frame, EndFrame):
+            await self.flush_audio()
+
+    async def _handle_interruption(self, frame: StartInterruptionFrame, direction: FrameDirection):
+        await super()._handle_interruption(frame, direction)
+        self.reset_word_timestamps()
+
+    async def _stop_words_task(self):
+        if self._words_task:
+            self._words_task.cancel()
+            await self._words_task
+
+    async def _words_task_handler(self):
+        while True:
+            try:
+                (word, timestamp) = await self._words_queue.get()
+                if word == "LLMFullResponseEndFrame" and timestamp == 0:
+                    await self.push_frame(LLMFullResponseEndFrame())
+                else:
+                    frame = TextFrame(word)
+                    frame.pts = self._start_word_timestamp + timestamp
+                    await self.push_frame(frame)
+                self._words_queue.task_done()
+            except asyncio.CancelledError:
+                break
+            except Exception as e:
+                logger.exception(f"{self} exception: {e}")
+
+
 class STTService(AIService):
     """STTService is a base class for speech-to-text services."""
 

From 80f6d74e808e4b7ddeb347aed792eda47cfa14d0 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Thu, 12 Sep 2024 00:19:37 -0700
Subject: [PATCH 007/135] services(cartesia): change to subclass of
 AsyncWordTTSService

---
 src/pipecat/services/cartesia.py | 69 ++++++++------------------------
 1 file changed, 16 insertions(+), 53 deletions(-)

diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index 429e7b3e4..f263db60d 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -27,7 +27,7 @@ from pipecat.frames.frames import (
 )
 from pipecat.processors.frame_processor import FrameDirection
 from pipecat.transcriptions.language import Language
-from pipecat.services.ai_services import TTSService
+from pipecat.services.ai_services import AsyncWordTTSService
 
 from loguru import logger
 
@@ -60,7 +60,7 @@ def language_to_cartesia_language(language: Language) -> str | None:
     return None
 
 
-class CartesiaTTSService(TTSService):
+class CartesiaTTSService(AsyncWordTTSService):
 
     def __init__(
             self,
@@ -74,19 +74,17 @@ class CartesiaTTSService(TTSService):
             sample_rate: int = 16000,
             language: str = "en",
             **kwargs):
-        super().__init__(**kwargs)
-
         # Aggregating sentences still gives cleaner-sounding results and fewer
-        # artifacts than streaming one word at a time. On average, waiting for
-        # a full sentence should only "cost" us 15ms or so with GPT-4o or a Llama 3
-        # model, and it's worth it for the better audio quality.
-        self._aggregate_sentences = True
-
-        # we don't want to automatically push LLM response text frames, because the
-        # context aggregators will add them to the LLM context even if we're
-        # interrupted. cartesia gives us word-by-word timestamps. we can use those
-        # to generate text frames ourselves aligned with the playout timing of the audio!
-        self._push_text_frames = False
+        # artifacts than streaming one word at a time. On average, waiting for a
+        # full sentence should only "cost" us 15ms or so with GPT-4o or a Llama
+        # 3 model, and it's worth it for the better audio quality.
+        #
+        # We also don't want to automatically push LLM response text frames,
+        # because the context aggregators will add them to the LLM context even
+        # if we're interrupted. Cartesia gives us word-by-word timestamps. We
+        # can use those to generate text frames ourselves aligned with the
+        # playout timing of the audio!
+        super().__init__(aggregate_sentences=True, push_text_frames=False, **kwargs)
 
         self._api_key = api_key
         self._cartesia_version = cartesia_version
@@ -102,10 +100,7 @@ class CartesiaTTSService(TTSService):
 
         self._websocket = None
         self._context_id = None
-        self._context_id_start_timestamp = None
-        self._timestamped_words_buffer = []
         self._receive_task = None
-        self._context_appending_task = None
 
     def can_generate_metrics(self) -> bool:
         return True
@@ -140,7 +135,6 @@ class CartesiaTTSService(TTSService):
                 f"{self._url}?api_key={self._api_key}&cartesia_version={self._cartesia_version}"
             )
             self._receive_task = self.get_event_loop().create_task(self._receive_task_handler())
-            self._context_appending_task = self.get_event_loop().create_task(self._context_appending_task_handler())
         except Exception as e:
             logger.exception(f"{self} initialization error: {e}")
             self._websocket = None
@@ -149,10 +143,6 @@ class CartesiaTTSService(TTSService):
         try:
             await self.stop_all_metrics()
 
-            if self._context_appending_task:
-                self._context_appending_task.cancel()
-                await self._context_appending_task
-                self._context_appending_task = None
             if self._receive_task:
                 self._receive_task.cancel()
                 await self._receive_task
@@ -162,18 +152,14 @@ class CartesiaTTSService(TTSService):
                 self._websocket = None
 
             self._context_id = None
-            self._context_id_start_timestamp = None
-            self._timestamped_words_buffer = []
         except Exception as e:
             logger.exception(f"{self} error closing websocket: {e}")
 
     async def _handle_interruption(self, frame: StartInterruptionFrame, direction: FrameDirection):
         await super()._handle_interruption(frame, direction)
-        self._context_id = None
-        self._context_id_start_timestamp = None
-        self._timestamped_words_buffer = []
         await self.stop_all_metrics()
         await self.push_frame(LLMFullResponseEndFrame())
+        self._context_id = None
 
     async def _receive_task_handler(self):
         try:
@@ -188,16 +174,14 @@ class CartesiaTTSService(TTSService):
                     # because we are likely still playing out audio and need the
                     # timestamp to set send context frames.
                     self._context_id = None
-                    self._timestamped_words_buffer.append(("LLMFullResponseEndFrame", 0))
+                    await self.add_word_timestamps([("LLMFullResponseEndFrame", 0)])
                 elif msg["type"] == "timestamps":
-                    # logger.debug(f"TIMESTAMPS: {msg}")
-                    self._timestamped_words_buffer.extend(
+                    await self.add_word_timestamps(
                         list(zip(msg["word_timestamps"]["words"], msg["word_timestamps"]["end"]))
                     )
                 elif msg["type"] == "chunk":
                     await self.stop_ttfb_metrics()
-                    if not self._context_id_start_timestamp:
-                        self._context_id_start_timestamp = time.time()
+                    self.init_word_timestamps()
                     frame = AudioRawFrame(
                         audio=base64.b64decode(msg["data"]),
                         sample_rate=self._output_format["sample_rate"],
@@ -216,27 +200,6 @@ class CartesiaTTSService(TTSService):
         except Exception as e:
             logger.exception(f"{self} exception: {e}")
 
-    async def _context_appending_task_handler(self):
-        try:
-            while True:
-                await asyncio.sleep(0.1)
-                if not self._context_id_start_timestamp:
-                    continue
-                elapsed_seconds = time.time() - self._context_id_start_timestamp
-                # Pop all words from self._timestamped_words_buffer that are
-                # older than the elapsed time and print a message about them to
-                # the console.
-                while self._timestamped_words_buffer and self._timestamped_words_buffer[0][1] <= elapsed_seconds:
-                    word, timestamp = self._timestamped_words_buffer.pop(0)
-                    if word == "LLMFullResponseEndFrame" and timestamp == 0:
-                        await self.push_frame(LLMFullResponseEndFrame())
-                        continue
-                    await self.push_frame(TextFrame(word))
-        except asyncio.CancelledError:
-            pass
-        except Exception as e:
-            logger.exception(f"{self} exception: {e}")
-
     async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
         logger.debug(f"Generating TTS: [{text}]")
 

From a98d78cdea6402253f7c417a68c08d3656138f47 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Thu, 12 Sep 2024 00:20:06 -0700
Subject: [PATCH 008/135] services(lmnt): change to subclass of AsyncTTSService

---
 src/pipecat/services/lmnt.py | 8 +++-----
 1 file changed, 3 insertions(+), 5 deletions(-)

diff --git a/src/pipecat/services/lmnt.py b/src/pipecat/services/lmnt.py
index f7afd6a41..59dd0aa5f 100644
--- a/src/pipecat/services/lmnt.py
+++ b/src/pipecat/services/lmnt.py
@@ -20,7 +20,7 @@ from pipecat.frames.frames import (
     TTSStartedFrame,
     TTSStoppedFrame,
 )
-from pipecat.services.ai_services import TTSService
+from pipecat.services.ai_services import AsyncTTSService
 
 from loguru import logger
 
@@ -34,7 +34,7 @@ except ModuleNotFoundError as e:
     raise Exception(f"Missing module: {e}")
 
 
-class LmntTTSService(TTSService):
+class LmntTTSService(AsyncTTSService):
 
     def __init__(
             self,
@@ -44,11 +44,9 @@ class LmntTTSService(TTSService):
             sample_rate: int = 24000,
             language: str = "en",
             **kwargs):
-        super().__init__(**kwargs)
-
         # Let TTSService produce TTSStoppedFrames after a short delay of
         # no activity.
-        self._push_stop_frames = True
+        super().__init__(push_stop_frames=True, **kwargs)
 
         self._api_key = api_key
         self._voice_id = voice_id

From 3665734972f525e0fafc22f86ad758b3c082212f Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Thu, 12 Sep 2024 00:22:32 -0700
Subject: [PATCH 009/135] transports(output): initial sink clock
 synchronization

---
 src/pipecat/transports/base_output.py | 100 +++++++++++++++++++-------
 1 file changed, 76 insertions(+), 24 deletions(-)

diff --git a/src/pipecat/transports/base_output.py b/src/pipecat/transports/base_output.py
index d2c6add2b..a24c9f4d2 100644
--- a/src/pipecat/transports/base_output.py
+++ b/src/pipecat/transports/base_output.py
@@ -8,6 +8,7 @@
 import asyncio
 import itertools
 import time
+import sys
 
 from PIL import Image
 from typing import List
@@ -30,11 +31,14 @@ from pipecat.frames.frames import (
     SystemFrame,
     TTSStartedFrame,
     TTSStoppedFrame,
+    TextFrame,
     TransportMessageFrame)
 from pipecat.transports.base_transport import TransportParams
 
 from loguru import logger
 
+from pipecat.utils.time import nanoseconds_to_seconds
+
 
 class BaseOutputTransport(FrameProcessor):
 
@@ -64,7 +68,7 @@ class BaseOutputTransport(FrameProcessor):
         # Create sink frame task. This is the task that will actually write
         # audio or video frames. We write audio/video in a task so we can keep
         # generating frames upstream while, for example, the audio is playing.
-        self._create_sink_task()
+        self._create_sink_tasks()
 
         # Create push frame task. This is the task that will push frames in
         # order. We also guarantee that all frames are pushed in the same task.
@@ -149,6 +153,7 @@ class BaseOutputTransport(FrameProcessor):
             await self._sink_queue.put(frame)
             await self.start(frame)
         elif isinstance(frame, EndFrame):
+            await self._sink_clock_queue.put((sys.maxsize, frame.id, frame))
             await self._sink_queue.put(frame)
             await self.stop(frame)
         # Other frames.
@@ -158,6 +163,9 @@ class BaseOutputTransport(FrameProcessor):
             await self._handle_image(frame)
         elif isinstance(frame, TransportMessageFrame) and frame.urgent:
             await self.send_message(frame)
+        # TODO(aleix): Images and audio should support presentation timestamps.
+        elif frame.pts:
+            await self._sink_clock_queue.put((frame.pts, frame.id, frame))
         else:
             await self._sink_queue.put(frame)
 
@@ -166,10 +174,14 @@ class BaseOutputTransport(FrameProcessor):
             return
 
         if isinstance(frame, StartInterruptionFrame):
-            # Stop sink task.
+            # Stop sink tasks.
             self._sink_task.cancel()
             await self._sink_task
-            self._create_sink_task()
+            # Stop sink clock tasks.
+            self._sink_clock_task.cancel()
+            await self._sink_clock_task
+            # Create sink tasks.
+            self._create_sink_tasks()
             # Stop push task.
             self._push_frame_task.cancel()
             await self._push_frame_task
@@ -201,43 +213,83 @@ class BaseOutputTransport(FrameProcessor):
         else:
             await self._sink_queue.put(frame)
 
-    def _create_sink_task(self):
+    #
+    # Sink tasks
+    #
+
+    def _create_sink_tasks(self):
         loop = self.get_event_loop()
         self._sink_queue = asyncio.Queue()
         self._sink_task = loop.create_task(self._sink_task_handler())
+        self._sink_clock_queue = asyncio.PriorityQueue()
+        self._sink_clock_task = loop.create_task(self._sink_clock_task_handler())
+
+    async def _sink_frame_handler(self, frame: Frame):
+        if isinstance(frame, AudioRawFrame):
+            await self.write_raw_audio_frames(frame.audio)
+            await self._internal_push_frame(frame)
+            await self.push_frame(BotSpeakingFrame(), FrameDirection.UPSTREAM)
+        elif isinstance(frame, ImageRawFrame):
+            await self._set_camera_image(frame)
+        elif isinstance(frame, SpriteFrame):
+            await self._set_camera_images(frame.images)
+        elif isinstance(frame, TransportMessageFrame):
+            await self.send_message(frame)
+        elif isinstance(frame, TTSStartedFrame):
+            await self._bot_started_speaking()
+            await self._internal_push_frame(frame)
+        elif isinstance(frame, TTSStoppedFrame):
+            await self._bot_stopped_speaking()
+            await self._internal_push_frame(frame)
+        else:
+            await self._internal_push_frame(frame)
 
     async def _sink_task_handler(self):
         running = True
         while running:
             try:
                 frame = await self._sink_queue.get()
-                if isinstance(frame, AudioRawFrame):
-                    await self.write_raw_audio_frames(frame.audio)
-                    await self._internal_push_frame(frame)
-                    await self.push_frame(BotSpeakingFrame(), FrameDirection.UPSTREAM)
-                elif isinstance(frame, ImageRawFrame):
-                    await self._set_camera_image(frame)
-                elif isinstance(frame, SpriteFrame):
-                    await self._set_camera_images(frame.images)
-                elif isinstance(frame, TransportMessageFrame):
-                    await self.send_message(frame)
-                elif isinstance(frame, TTSStartedFrame):
-                    await self._bot_started_speaking()
-                    await self._internal_push_frame(frame)
-                elif isinstance(frame, TTSStoppedFrame):
-                    await self._bot_stopped_speaking()
-                    await self._internal_push_frame(frame)
-                else:
-                    await self._internal_push_frame(frame)
-
+                await self._sink_frame_handler(frame)
                 running = not isinstance(frame, EndFrame)
-
                 self._sink_queue.task_done()
             except asyncio.CancelledError:
                 break
             except Exception as e:
                 logger.exception(f"{self} error processing sink queue: {e}")
 
+    async def _sink_clock_frame_handler(self, frame: Frame):
+        # TODO(aleix): For now we just process TextFrame. But we should process
+        # audio and video as well.
+        if isinstance(frame, TextFrame):
+            await self._internal_push_frame(frame)
+
+    async def _sink_clock_task_handler(self):
+        running = True
+        while running:
+            try:
+                timestamp, _, frame = await self._sink_clock_queue.get()
+
+                # If we hit an EndFrame, we cna finish right away.
+                running = not isinstance(frame, EndFrame)
+
+                # If we have a frame we check it's presentation timestamp. If it
+                # has already passed we process it, otherwise we wait until it's
+                # time to process it.
+                if running:
+                    current_time = self.get_clock().get_time()
+                    if timestamp <= current_time:
+                        await self._sink_clock_frame_handler(frame)
+                    else:
+                        wait_time = nanoseconds_to_seconds(timestamp - current_time)
+                        await asyncio.sleep(wait_time)
+                        await self._sink_frame_handler(frame)
+
+                self._sink_clock_queue.task_done()
+            except asyncio.CancelledError:
+                break
+            except Exception as e:
+                logger.exception(f"{self} error processing sink clock queue: {e}")
+
     async def _bot_started_speaking(self):
         logger.debug("Bot started speaking")
         self._bot_speaking = True

From f08b25dbb2132939c7c0cef107c3370a6a859dda Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Thu, 12 Sep 2024 00:29:43 -0700
Subject: [PATCH 010/135] examples: assistant aggregator should always goes
 after transport

---
 examples/foundational/07d-interruptible-cartesia.py | 2 +-
 examples/studypal/studypal.py                       | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/examples/foundational/07d-interruptible-cartesia.py b/examples/foundational/07d-interruptible-cartesia.py
index 6b8bbcc5f..6bf5f9bd9 100644
--- a/examples/foundational/07d-interruptible-cartesia.py
+++ b/examples/foundational/07d-interruptible-cartesia.py
@@ -74,8 +74,8 @@ async def main():
             tma_in,              # User responses
             llm,                 # LLM
             tts,                 # TTS
-            tma_out,             # Goes before the transport because cartesia has word-level timestamps!
             transport.output(),  # Transport bot output
+            tma_out              # Assistant spoken responses
         ])
 
         task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True, enable_metrics=True))
diff --git a/examples/studypal/studypal.py b/examples/studypal/studypal.py
index 8adfe2954..368a9b072 100644
--- a/examples/studypal/studypal.py
+++ b/examples/studypal/studypal.py
@@ -147,8 +147,8 @@ Your task is to help the user understand and learn from this article in 2 senten
             tma_in,
             llm,
             tts,
-            tma_out,
             transport.output(),
+            tma_out,
         ])
 
         task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True, enable_metrics=True))

From 434493b8aad79c17e65d20f7acc7512aec77477b Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Fri, 13 Sep 2024 09:31:35 -0700
Subject: [PATCH 011/135] services(elevenlabs): implement word-by-word support
 through websockets

---
 .../07d-interruptible-cartesia.py             |  97 --------
 pyproject.toml                                |   2 +-
 src/pipecat/services/ai_services.py           |  15 +-
 src/pipecat/services/cartesia.py              |   2 +-
 src/pipecat/services/elevenlabs.py            | 232 ++++++++++++++++--
 src/pipecat/services/lmnt.py                  |   2 +
 6 files changed, 216 insertions(+), 134 deletions(-)
 delete mode 100644 examples/foundational/07d-interruptible-cartesia.py

diff --git a/examples/foundational/07d-interruptible-cartesia.py b/examples/foundational/07d-interruptible-cartesia.py
deleted file mode 100644
index 6bf5f9bd9..000000000
--- a/examples/foundational/07d-interruptible-cartesia.py
+++ /dev/null
@@ -1,97 +0,0 @@
-#
-# Copyright (c) 2024, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import aiohttp
-import asyncio
-import os
-import sys
-
-from pipecat.frames.frames import LLMMessagesFrame
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator, LLMUserResponseAggregator)
-from pipecat.services.cartesia import CartesiaTTSService
-from pipecat.services.openai import OpenAILLMService
-from pipecat.transports.services.daily import DailyParams, DailyTransport
-from pipecat.vad.silero import SileroVADAnalyzer
-
-
-from runner import configure
-
-from loguru import logger
-
-from dotenv import load_dotenv
-load_dotenv(override=True)
-
-logger.remove(0)
-logger.add(sys.stderr, level="DEBUG")
-
-
-async def main():
-    async with aiohttp.ClientSession() as session:
-        (room_url, token) = await configure(session)
-
-        transport = DailyTransport(
-            room_url,
-            token,
-            "Respond bot",
-            DailyParams(
-                audio_out_sample_rate=44100,
-                audio_out_enabled=True,
-                transcription_enabled=True,
-                vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
-        )
-
-        tts = CartesiaTTSService(
-            api_key=os.getenv("CARTESIA_API_KEY"),
-            voice_id="a0e99841-438c-4a64-b679-ae501e7d6091",  # Barbershop Man
-            sample_rate=44100,
-        )
-
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
-
-        messages = [
-            {
-                "role": "system",
-                "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
-            },
-        ]
-
-        tma_in = LLMUserResponseAggregator(messages)
-        tma_out = LLMAssistantResponseAggregator(messages)
-
-        pipeline = Pipeline([
-            transport.input(),   # Transport user input
-            tma_in,              # User responses
-            llm,                 # LLM
-            tts,                 # TTS
-            transport.output(),  # Transport bot output
-            tma_out              # Assistant spoken responses
-        ])
-
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True, enable_metrics=True))
-
-        @transport.event_handler("on_first_participant_joined")
-        async def on_first_participant_joined(transport, participant):
-            transport.capture_participant_transcription(participant["id"])
-            # Kick off the conversation.
-            messages.append(
-                {"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
-
-        runner = PipelineRunner()
-
-        await runner.run(task)
-
-
-if __name__ == "__main__":
-    asyncio.run(main())
diff --git a/pyproject.toml b/pyproject.toml
index 73c643ddc..8a1e3a800 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -39,7 +39,7 @@ azure = [ "azure-cognitiveservices-speech~=1.40.0" ]
 cartesia = [ "websockets~=12.0" ]
 daily = [ "daily-python~=0.10.1" ]
 deepgram = [ "deepgram-sdk~=3.5.0" ]
-elevenlabs = [ "elevenlabs~=1.7.0" ]
+elevenlabs = [ "websockets~=12.0" ]
 examples = [ "python-dotenv~=1.0.1", "flask~=3.0.3", "flask_cors~=4.0.1" ]
 fal = [ "fal-client~=0.4.1" ]
 gladia = [ "websockets~=12.0" ]
diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index 72a8828c2..dcba578c5 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -6,7 +6,6 @@
 
 import asyncio
 import io
-import time
 import wave
 
 from abc import abstractmethod
@@ -171,7 +170,7 @@ class TTSService(AIService):
             # if True, TTSService will push TTSStoppedFrames, otherwise subclass must do it
             push_stop_frames: bool = False,
             # if push_stop_frames is True, wait for this idle period before pushing TTSStoppedFrame
-            stop_frame_timeout_s: float = 0.8,
+            stop_frame_timeout_s: float = 1.0,
             **kwargs):
         super().__init__(**kwargs)
         self._aggregate_sentences: bool = aggregate_sentences
@@ -319,16 +318,16 @@ class AsyncTTSService(TTSService):
 class AsyncWordTTSService(AsyncTTSService):
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
-        self._start_word_timestamp = None
+        self._initial_word_timestamp = -1
         self._words_queue = asyncio.Queue()
         self._words_task = self.get_event_loop().create_task(self._words_task_handler())
 
-    def init_word_timestamps(self):
-        if not self._start_word_timestamp:
-            self._start_word_timestamp = self.get_clock().get_time()
+    def start_word_timestamps(self):
+        if self._initial_word_timestamp == -1:
+            self._initial_word_timestamp = self.get_clock().get_time()
 
     def reset_word_timestamps(self):
-        self._start_word_timestamp = None
+        self._initial_word_timestamp = -1
         self._word_timestamps = []
 
     async def add_word_timestamps(self, word_times: List[Tuple[str, float]]):
@@ -366,7 +365,7 @@ class AsyncWordTTSService(AsyncTTSService):
                     await self.push_frame(LLMFullResponseEndFrame())
                 else:
                     frame = TextFrame(word)
-                    frame.pts = self._start_word_timestamp + timestamp
+                    frame.pts = self._initial_word_timestamp + timestamp
                     await self.push_frame(frame)
                 self._words_queue.task_done()
             except asyncio.CancelledError:
diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index f263db60d..b15f266e9 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -181,7 +181,7 @@ class CartesiaTTSService(AsyncWordTTSService):
                     )
                 elif msg["type"] == "chunk":
                     await self.stop_ttfb_metrics()
-                    self.init_word_timestamps()
+                    self.start_word_timestamps()
                     frame = AudioRawFrame(
                         audio=base64.b64decode(msg["data"]),
                         sample_rate=self._output_format["sample_rate"],
diff --git a/src/pipecat/services/elevenlabs.py b/src/pipecat/services/elevenlabs.py
index ed8041fcf..ded746144 100644
--- a/src/pipecat/services/elevenlabs.py
+++ b/src/pipecat/services/elevenlabs.py
@@ -4,17 +4,30 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-from typing import AsyncGenerator, Literal
+import asyncio
+import base64
+import json
+
+from typing import Any, AsyncGenerator, List, Literal, Mapping, Tuple
 from pydantic import BaseModel
 
-from pipecat.frames.frames import AudioRawFrame, Frame, TTSStartedFrame, TTSStoppedFrame
-from pipecat.services.ai_services import TTSService
+from pipecat.frames.frames import (
+    AudioRawFrame,
+    CancelFrame,
+    EndFrame,
+    Frame,
+    StartFrame,
+    StartInterruptionFrame,
+    TTSStartedFrame,
+    TTSStoppedFrame)
+from pipecat.processors.frame_processor import FrameDirection
+from pipecat.services.ai_services import AsyncWordTTSService
 
 from loguru import logger
 
 # See .env.example for ElevenLabs configuration needed
 try:
-    from elevenlabs.client import AsyncElevenLabs
+    import websockets
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
@@ -35,7 +48,35 @@ def sample_rate_from_output_format(output_format: str) -> int:
     return 16000
 
 
-class ElevenLabsTTSService(TTSService):
+def calculate_word_times(
+        alignment_info: Mapping[str, Any], cumulative_time: float
+) -> List[Tuple[str, float]]:
+    end_times = [
+        s + d for s,
+        d in zip(
+            alignment_info["charStartTimesMs"],
+            alignment_info["charDurationsMs"])]
+    zipped_end_times = list(zip(alignment_info["chars"], end_times))
+
+    # Get the start time of every character that appears after a space and
+    # match this to the word
+    words = "".join(alignment_info["chars"]).split(" ")
+
+    # Calculate end time for each word. We do this by finding a space character
+    # and using the previous word time, also taking into account there might not
+    # be a space at the end.
+    times = []
+    for (i, (a, b)) in enumerate(zipped_end_times):
+        if a == " " or i == len(zipped_end_times) - 1:
+            t = cumulative_time + (zipped_end_times[i - 1][1] / 1000.0)
+            times.append(t)
+
+    word_times = list(zip(words, times))
+
+    return word_times
+
+
+class ElevenLabsTTSService(AsyncWordTTSService):
     class InputParams(BaseModel):
         output_format: Literal["pcm_16000", "pcm_22050", "pcm_24000", "pcm_44100"] = "pcm_16000"
 
@@ -45,49 +86,186 @@ class ElevenLabsTTSService(TTSService):
             api_key: str,
             voice_id: str,
             model: str = "eleven_turbo_v2_5",
+            url: str = "wss://api.elevenlabs.io",
             params: InputParams = InputParams(),
             **kwargs):
-        super().__init__(**kwargs)
+        # Aggregating sentences still gives cleaner-sounding results and fewer
+        # artifacts than streaming one word at a time. On average, waiting for a
+        # full sentence should only "cost" us 15ms or so with GPT-4o or a Llama
+        # 3 model, and it's worth it for the better audio quality.
+        #
+        # We also don't want to automatically push LLM response text frames,
+        # because the context aggregators will add them to the LLM context even
+        # if we're interrupted. ElevenLabs gives us word-by-word timestamps. We
+        # can use those to generate text frames ourselves aligned with the
+        # playout timing of the audio!
+        #
+        # Finally, ElevenLabs doesn't provide information on when the bot stops
+        # speaking for a while, so we want the parent class to send TTSStopFrame
+        # after a short period not receiving any audio.
+        super().__init__(
+            aggregate_sentences=True,
+            push_text_frames=False,
+            push_stop_frames=True,
+            stop_frame_timeout_s=2.0,
+            **kwargs
+        )
 
+        self._api_key = api_key
         self._voice_id = voice_id
         self._model = model
+        self._url = url
         self._params = params
-        self._client = AsyncElevenLabs(api_key=api_key)
         self._sample_rate = sample_rate_from_output_format(params.output_format)
 
+        # Websocket connection to ElevenLabs.
+        self._websocket = None
+        # Indicates if we have sent TTSStartedFrame. It will reset to False when
+        # there's an interruption or TTSStoppedFrame.
+        self._started = False
+        self._cumulative_time = 0
+
     def can_generate_metrics(self) -> bool:
         return True
 
     async def set_model(self, model: str):
         logger.debug(f"Switching TTS model to: [{model}]")
         self._model = model
+        await self._disconnect()
+        await self._connect()
 
     async def set_voice(self, voice: str):
         logger.debug(f"Switching TTS voice to: [{voice}]")
         self._voice_id = voice
+        await self._disconnect()
+        await self._connect()
+
+    async def start(self, frame: StartFrame):
+        await super().start(frame)
+        await self._connect()
+
+    async def stop(self, frame: EndFrame):
+        await super().stop(frame)
+        await self._disconnect()
+
+    async def cancel(self, frame: CancelFrame):
+        await super().cancel(frame)
+        await self._disconnect()
+
+    async def flush_audio(self):
+        if self._websocket:
+            msg = {"text": " ", "flush": True}
+            await self._websocket.send(json.dumps(msg))
+
+    async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM):
+        await super().push_frame(frame, direction)
+        if isinstance(frame, (TTSStoppedFrame, StartInterruptionFrame)):
+            self._started = False
+            if isinstance(frame, TTSStoppedFrame):
+                await self.add_word_timestamps([("LLMFullResponseEndFrame", 0)])
+
+    async def _connect(self):
+        try:
+            voice_id = self._voice_id
+            model = self._model
+            output_format = self._params.output_format
+            url = f"{
+                self._url}/v1/text-to-speech/{voice_id}/stream-input?model_id={model}&output_format={output_format}"
+            self._websocket = await websockets.connect(url)
+            self._receive_task = self.get_event_loop().create_task(self._receive_task_handler())
+            self._keepalive_task = self.get_event_loop().create_task(self._keepalive_task_handler())
+
+            # According to ElevenLabs, we should always start with a single space.
+            msg = {
+                "text": " ",
+                "xi_api_key": self._api_key,
+            }
+            await self._websocket.send(json.dumps(msg))
+        except Exception as e:
+            logger.exception(f"{self} initialization error: {e}")
+            self._websocket = None
+
+    async def _disconnect(self):
+        try:
+            await self.stop_all_metrics()
+
+            if self._receive_task:
+                self._receive_task.cancel()
+                await self._receive_task
+                self._receive_task = None
+
+            if self._keepalive_task:
+                self._keepalive_task.cancel()
+                await self._keepalive_task
+                self._keepalive_task = None
+
+            if self._websocket:
+                await self._websocket.close()
+                self._websocket = None
+
+            self._started = False
+        except Exception as e:
+            logger.exception(f"{self} error closing websocket: {e}")
+
+    async def _receive_task_handler(self):
+        try:
+            async for message in self._websocket:
+                msg = json.loads(message)
+                if msg.get("audio"):
+                    await self.stop_ttfb_metrics()
+                    self.start_word_timestamps()
+
+                    audio = base64.b64decode(msg["audio"])
+                    frame = AudioRawFrame(audio, self._sample_rate, 1)
+                    await self.push_frame(frame)
+
+                if msg.get("alignment"):
+                    word_times = calculate_word_times(msg["alignment"], self._cumulative_time)
+                    await self.add_word_timestamps(word_times)
+                    self._cumulative_time = word_times[-1][1]
+
+        except asyncio.CancelledError:
+            pass
+        except Exception as e:
+            logger.exception(f"{self} exception: {e}")
+
+    async def _keepalive_task_handler(self):
+        while True:
+            try:
+                await asyncio.sleep(10)
+                await self._send_text("")
+            except asyncio.CancelledError:
+                break
+            except Exception as e:
+                logger.exception(f"{self} exception: {e}")
+
+    async def _send_text(self, text: str):
+        if self._websocket:
+            msg = {"text": text + " "}
+            await self._websocket.send(json.dumps(msg))
 
     async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
         logger.debug(f"Generating TTS: [{text}]")
 
-        await self.start_tts_usage_metrics(text)
-        await self.start_ttfb_metrics()
+        try:
+            if not self._websocket:
+                await self._connect()
 
-        results = await self._client.generate(
-            text=text,
-            voice=self._voice_id,
-            model=self._model,
-            output_format=self._params.output_format
-        )
+            try:
+                if not self._started:
+                    await self.push_frame(TTSStartedFrame())
+                    await self.start_ttfb_metrics()
+                    self._started = True
+                    self._cumulative_time = 0
 
-        tts_started = False
-        async for audio in results:
-            # This is so we send TTSStartedFrame when we have the first audio
-            # bytes.
-            if not tts_started:
-                await self.push_frame(TTSStartedFrame())
-                tts_started = True
-            await self.stop_ttfb_metrics()
-            frame = AudioRawFrame(audio, self._sample_rate, 1)
-            yield frame
-
-        await self.push_frame(TTSStoppedFrame())
+                await self._send_text(text)
+                await self.start_tts_usage_metrics(text)
+            except Exception as e:
+                logger.error(f"{self} error sending message: {e}")
+                await self.push_frame(TTSStoppedFrame())
+                await self._disconnect()
+                await self._connect()
+                return
+            yield None
+        except Exception as e:
+            logger.exception(f"{self} exception: {e}")
diff --git a/src/pipecat/services/lmnt.py b/src/pipecat/services/lmnt.py
index 59dd0aa5f..f5ad8aa1a 100644
--- a/src/pipecat/services/lmnt.py
+++ b/src/pipecat/services/lmnt.py
@@ -60,6 +60,8 @@ class LmntTTSService(AsyncTTSService):
         self._speech = None
         self._connection = None
         self._receive_task = None
+        # Indicates if we have sent TTSStartedFrame. It will reset to False when
+        # there's an interruption or TTSStoppedFrame.
         self._started = False
 
     def can_generate_metrics(self) -> bool:

From 5acc4928febeb7e3566e67ab32b29bdae30ce73a Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Fri, 13 Sep 2024 09:43:18 -0700
Subject: [PATCH 012/135] examples: add 07d-interruptible-elevenlabs.py

---
 .../07d-interruptible-elevenlabs.py           | 99 +++++++++++++++++++
 1 file changed, 99 insertions(+)
 create mode 100644 examples/foundational/07d-interruptible-elevenlabs.py

diff --git a/examples/foundational/07d-interruptible-elevenlabs.py b/examples/foundational/07d-interruptible-elevenlabs.py
new file mode 100644
index 000000000..19bd4ad01
--- /dev/null
+++ b/examples/foundational/07d-interruptible-elevenlabs.py
@@ -0,0 +1,99 @@
+#
+# Copyright (c) 2024, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import aiohttp
+import os
+import sys
+
+from pipecat.frames.frames import LLMMessagesFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.llm_response import (
+    LLMAssistantResponseAggregator, LLMUserResponseAggregator)
+from pipecat.services.elevenlabs import ElevenLabsTTSService
+from pipecat.services.openai import OpenAILLMService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+from pipecat.vad.silero import SileroVADAnalyzer
+
+from runner import configure
+
+from loguru import logger
+
+from dotenv import load_dotenv
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, token) = await configure(session)
+
+        transport = DailyTransport(
+            room_url,
+            token,
+            "Respond bot",
+            DailyParams(
+                audio_out_enabled=True,
+                transcription_enabled=True,
+                vad_enabled=True,
+                vad_analyzer=SileroVADAnalyzer()
+            )
+        )
+
+        tts = ElevenLabsTTSService(
+            api_key=os.getenv("ELEVENLABS_API_KEY", ""),
+            voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""),
+        )
+
+        llm = OpenAILLMService(
+            api_key=os.getenv("OPENAI_API_KEY"),
+            model="gpt-4o")
+
+        messages = [
+            {
+                "role": "system",
+                "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+            },
+        ]
+
+        tma_in = LLMUserResponseAggregator(messages)
+        tma_out = LLMAssistantResponseAggregator(messages)
+
+        pipeline = Pipeline([
+            transport.input(),   # Transport user input
+            tma_in,              # User responses
+            llm,                 # LLM
+            tts,                 # TTS
+            transport.output(),  # Transport bot output
+            tma_out              # Assistant spoken responses
+        ])
+
+        task = PipelineTask(pipeline, PipelineParams(
+            allow_interruptions=True,
+            enable_metrics=True,
+            enable_usage_metrics=True,
+            report_only_initial_ttfb=True,
+        ))
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            transport.capture_participant_transcription(participant["id"])
+            # Kick off the conversation.
+            messages.append(
+                {"role": "system", "content": "Please introduce yourself to the user."})
+            await task.queue_frames([LLMMessagesFrame(messages)])
+
+        runner = PipelineRunner()
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

From cb36a71381ea511ef84f17ac75d4177741761750 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Fri, 13 Sep 2024 09:50:05 -0700
Subject: [PATCH 013/135] fix some linting

---
 src/pipecat/frames/frames.py              | 34 ++++-------------------
 src/pipecat/processors/frame_processor.py |  5 +---
 src/pipecat/services/elevenlabs.py        |  5 +---
 3 files changed, 7 insertions(+), 37 deletions(-)

diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py
index 9cad1268d..51770dff1 100644
--- a/src/pipecat/frames/frames.py
+++ b/src/pipecat/frames/frames.py
@@ -55,13 +55,7 @@ class AudioRawFrame(DataFrame):
 
     def __str__(self):
         pts = format_pts(self.pts)
-        return f"{
-            self.name}(pts: {pts}, size: {
-            len(
-                self.audio)}, frames: {
-                self.num_frames}, sample_rate: {
-                    self.sample_rate}, channels: {
-                        self.num_channels})"
+        return f"{self.name}(pts: {pts}, size: {len(self.audio)}, frames: {self.num_frames}, sample_rate: {self.sample_rate}, channels: {self.num_channels})"
 
 
 @dataclass
@@ -102,11 +96,7 @@ class VisionImageRawFrame(ImageRawFrame):
 
     def __str__(self):
         pts = format_pts(self.pts)
-        return f"{
-            self.name}(pts: {pts}, text: {
-            self.text}, size: {
-            self.size}, format: {
-                self.format})"
+        return f"{self.name}(pts: {pts}, text: {self.text}, size: {self.size}, format: {self.format})"
 
 
 @dataclass
@@ -119,11 +109,7 @@ class UserImageRawFrame(ImageRawFrame):
 
     def __str__(self):
         pts = format_pts(self.pts)
-        return f"{
-            self.name}(pts: {pts}, user: {
-            self.user_id}, size: {
-            self.size}, format: {
-                self.format})"
+        return f"{self.name}(pts: {pts}, user: {self.user_id}, size: {self.size}, format: {self.format})"
 
 
 @dataclass
@@ -164,12 +150,7 @@ class TranscriptionFrame(TextFrame):
     language: Language | None = None
 
     def __str__(self):
-        return f"{
-            self.name}(user: {
-            self.user_id}, text: {
-            self.text}, language: {
-                self.language}, timestamp: {
-                    self.timestamp})"
+        return f"{self.name}(user: {self.user_id}, text: {self.text}, language: {self.language}, timestamp: {self.timestamp})"
 
 
 @dataclass
@@ -181,12 +162,7 @@ class InterimTranscriptionFrame(TextFrame):
     language: Language | None = None
 
     def __str__(self):
-        return f"{
-            self.name}(user: {
-            self.user_id}, text: {
-                self.text}, language: {
-                    self.language}, timestamp: {
-                        self.timestamp})"
+        return f"{self.name}(user: {self.user_id}, text: {self.text}, language: {self.language}, timestamp: {self.timestamp})"
 
 
 @dataclass
diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py
index e228ec6b4..dfdee7d40 100644
--- a/src/pipecat/processors/frame_processor.py
+++ b/src/pipecat/processors/frame_processor.py
@@ -70,10 +70,7 @@ class FrameProcessorMetrics:
 
     async def start_llm_usage_metrics(self, tokens: dict):
         logger.debug(
-            f"{
-                self._name} prompt tokens: {
-                tokens['prompt_tokens']}, completion tokens: {
-                tokens['completion_tokens']}")
+            f"{self._name} prompt tokens: {tokens['prompt_tokens']}, completion tokens: {tokens['completion_tokens']}")
         return MetricsFrame(tokens=[tokens])
 
     async def start_tts_usage_metrics(self, text: str):
diff --git a/src/pipecat/services/elevenlabs.py b/src/pipecat/services/elevenlabs.py
index ded746144..ae3021ab6 100644
--- a/src/pipecat/services/elevenlabs.py
+++ b/src/pipecat/services/elevenlabs.py
@@ -58,8 +58,6 @@ def calculate_word_times(
             alignment_info["charDurationsMs"])]
     zipped_end_times = list(zip(alignment_info["chars"], end_times))
 
-    # Get the start time of every character that appears after a space and
-    # match this to the word
     words = "".join(alignment_info["chars"]).split(" ")
 
     # Calculate end time for each word. We do this by finding a space character
@@ -169,8 +167,7 @@ class ElevenLabsTTSService(AsyncWordTTSService):
             voice_id = self._voice_id
             model = self._model
             output_format = self._params.output_format
-            url = f"{
-                self._url}/v1/text-to-speech/{voice_id}/stream-input?model_id={model}&output_format={output_format}"
+            url = f"{self._url}/v1/text-to-speech/{voice_id}/stream-input?model_id={model}&output_format={output_format}"
             self._websocket = await websockets.connect(url)
             self._receive_task = self.get_event_loop().create_task(self._receive_task_handler())
             self._keepalive_task = self.get_event_loop().create_task(self._keepalive_task_handler())

From 1fe940bd6b6b2e8be70057bac390340341c9fc78 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Fri, 13 Sep 2024 13:10:44 -0700
Subject: [PATCH 014/135] servceis(cartesia,elevenlabs): use word start times
 instead

---
 src/pipecat/services/cartesia.py   |  2 +-
 src/pipecat/services/elevenlabs.py | 15 +++++----------
 2 files changed, 6 insertions(+), 11 deletions(-)

diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index b15f266e9..ac02ea469 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -177,7 +177,7 @@ class CartesiaTTSService(AsyncWordTTSService):
                     await self.add_word_timestamps([("LLMFullResponseEndFrame", 0)])
                 elif msg["type"] == "timestamps":
                     await self.add_word_timestamps(
-                        list(zip(msg["word_timestamps"]["words"], msg["word_timestamps"]["end"]))
+                        list(zip(msg["word_timestamps"]["words"], msg["word_timestamps"]["start"]))
                     )
                 elif msg["type"] == "chunk":
                     await self.stop_ttfb_metrics()
diff --git a/src/pipecat/services/elevenlabs.py b/src/pipecat/services/elevenlabs.py
index ae3021ab6..6a3b85914 100644
--- a/src/pipecat/services/elevenlabs.py
+++ b/src/pipecat/services/elevenlabs.py
@@ -51,22 +51,17 @@ def sample_rate_from_output_format(output_format: str) -> int:
 def calculate_word_times(
         alignment_info: Mapping[str, Any], cumulative_time: float
 ) -> List[Tuple[str, float]]:
-    end_times = [
-        s + d for s,
-        d in zip(
-            alignment_info["charStartTimesMs"],
-            alignment_info["charDurationsMs"])]
-    zipped_end_times = list(zip(alignment_info["chars"], end_times))
+    zipped_times = list(zip(alignment_info["chars"], alignment_info["charStartTimesMs"]))
 
     words = "".join(alignment_info["chars"]).split(" ")
 
-    # Calculate end time for each word. We do this by finding a space character
+    # Calculate start time for each word. We do this by finding a space character
     # and using the previous word time, also taking into account there might not
     # be a space at the end.
     times = []
-    for (i, (a, b)) in enumerate(zipped_end_times):
-        if a == " " or i == len(zipped_end_times) - 1:
-            t = cumulative_time + (zipped_end_times[i - 1][1] / 1000.0)
+    for (i, (a, b)) in enumerate(zipped_times):
+        if a == " " or i == len(zipped_times) - 1:
+            t = cumulative_time + (zipped_times[i - 1][1] / 1000.0)
             times.append(t)
 
     word_times = list(zip(words, times))

From bce87f8717683393820cb806effc9a6fadd4337a Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Fri, 13 Sep 2024 13:50:03 -0700
Subject: [PATCH 015/135] update CHANGELOG.md

---
 CHANGELOG.md | 16 ++++++++++++++++
 1 file changed, 16 insertions(+)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 9badb6c70..a757c7ffd 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,6 +9,16 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 
+- A clock can now be specified to `PipelineTask` (defaults to
+  `SystemClock`). This clock will be passed to each frame processor via the
+  `StartFrame`.
+
+- Added pipeline clocks. A pipeline clock is used by the output transport to
+  know when a frame needs to be presented. For that, all frames now have an
+  optional `pts` field (prensentation timestamp). There's currently just one
+  clock implementation `SystemClock` and the `pts` field is currently only used
+  for `TextFrame`s (audio and image frames will be next).
+
 - `DailyTransport` now supports setting the audio bitrate to improve audio
   quality through the `DailyParams.audio_out_bitrate` parameter. The new
   default is 96kbps.
@@ -30,6 +40,12 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Changed
 
+- `CartesiaTTSService` and `ElevenLabsTTSService` now add presentation
+  timestamps to their text output. This allows the output transport to push the
+  text frames downstream at almost the same time the words are spoken. We say
+  "almost" because currently the audio frames don't have presentation timestamp
+  but they should be played at roughly the same time.
+
 - `DailyTransport.on_joined` event now returns the full session data instead of
   just the participant.
 

From adaac003e544dec6107b244b6a2b2db4ebf8420e Mon Sep 17 00:00:00 2001
From: Kunal Shah <kunal.shah@cartesia.ai>
Date: Mon, 16 Sep 2024 15:59:06 -0700
Subject: [PATCH 016/135] [Cartesia] Fix streaming truncation bug with Twilio
 Fast API WS

---
 src/pipecat/services/cartesia.py              | 52 +++++++++++--------
 .../transports/network/fastapi_websocket.py   | 10 ++--
 2 files changed, 36 insertions(+), 26 deletions(-)

diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index ac02ea469..6713a3825 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -4,33 +4,24 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-import json
-import uuid
-import base64
 import asyncio
+import base64
+import io
+import json
 import time
-
+import uuid
 from typing import AsyncGenerator
 
-from pipecat.frames.frames import (
-    CancelFrame,
-    ErrorFrame,
-    Frame,
-    AudioRawFrame,
-    StartInterruptionFrame,
-    StartFrame,
-    EndFrame,
-    TTSStartedFrame,
-    TTSStoppedFrame,
-    TextFrame,
-    LLMFullResponseEndFrame
-)
-from pipecat.processors.frame_processor import FrameDirection
-from pipecat.transcriptions.language import Language
-from pipecat.services.ai_services import AsyncWordTTSService
-
 from loguru import logger
 
+from pipecat.frames.frames import (AudioRawFrame, CancelFrame, EndFrame,
+                                   ErrorFrame, Frame, LLMFullResponseEndFrame,
+                                   StartFrame, StartInterruptionFrame,
+                                   TextFrame, TTSStartedFrame, TTSStoppedFrame)
+from pipecat.processors.frame_processor import FrameDirection
+from pipecat.services.ai_services import AsyncWordTTSService
+from pipecat.transcriptions.language import Language
+
 # See .env.example for Cartesia configuration needed
 try:
     import websockets
@@ -161,6 +152,25 @@ class CartesiaTTSService(AsyncWordTTSService):
         await self.push_frame(LLMFullResponseEndFrame())
         self._context_id = None
 
+    async def flush_audio(self):
+        if not self._context_id or not self._websocket:
+            return
+        logger.debug("Flushing audio")
+        msg = {
+                "transcript": "",
+                "continue": False,
+                "context_id": self._context_id,
+                "model_id": self._model_id,
+                "voice": {
+                    "mode": "id",
+                    "id": self._voice_id
+                },
+                "output_format": self._output_format,
+                "language": self._language,
+                "add_timestamps": True,
+            }
+        await self._websocket.send(json.dumps(msg))
+
     async def _receive_task_handler(self):
         try:
             async for message in self._websocket:
diff --git a/src/pipecat/transports/network/fastapi_websocket.py b/src/pipecat/transports/network/fastapi_websocket.py
index 16c5e81fc..b5bcfe7ed 100644
--- a/src/pipecat/transports/network/fastapi_websocket.py
+++ b/src/pipecat/transports/network/fastapi_websocket.py
@@ -8,19 +8,19 @@
 import asyncio
 import io
 import wave
-
 from typing import Awaitable, Callable
+
+from loguru import logger
 from pydantic.main import BaseModel
 
-from pipecat.frames.frames import AudioRawFrame, CancelFrame, EndFrame, Frame, StartFrame, StartInterruptionFrame
+from pipecat.frames.frames import (AudioRawFrame, CancelFrame, EndFrame, Frame,
+                                   StartFrame, StartInterruptionFrame)
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.serializers.base_serializer import FrameSerializer
 from pipecat.transports.base_input import BaseInputTransport
 from pipecat.transports.base_output import BaseOutputTransport
 from pipecat.transports.base_transport import BaseTransport, TransportParams
 
-from loguru import logger
-
 try:
     from fastapi import WebSocket
     from starlette.websockets import WebSocketState
@@ -101,7 +101,7 @@ class FastAPIWebsocketOutputTransport(BaseOutputTransport):
 
     async def write_raw_audio_frames(self, frames: bytes):
         self._websocket_audio_buffer += frames
-        while len(self._websocket_audio_buffer) >= self._params.audio_frame_size:
+        while len(self._websocket_audio_buffer):
             frame = AudioRawFrame(
                 audio=self._websocket_audio_buffer[:
                                                    self._params.audio_frame_size],

From 0a26b650c000ae675eddd99b7871302613d87d75 Mon Sep 17 00:00:00 2001
From: Kunal Shah <kunal.shah@cartesia.ai>
Date: Mon, 16 Sep 2024 16:06:25 -0700
Subject: [PATCH 017/135] Undo sorting

---
 src/pipecat/services/cartesia.py | 31 ++++++++++++++++++++-----------
 1 file changed, 20 insertions(+), 11 deletions(-)

diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index 6713a3825..a9d5aae67 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -4,23 +4,32 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-import asyncio
-import base64
-import io
 import json
-import time
 import uuid
+import base64
+import asyncio
+import time
+
 from typing import AsyncGenerator
 
-from loguru import logger
-
-from pipecat.frames.frames import (AudioRawFrame, CancelFrame, EndFrame,
-                                   ErrorFrame, Frame, LLMFullResponseEndFrame,
-                                   StartFrame, StartInterruptionFrame,
-                                   TextFrame, TTSStartedFrame, TTSStoppedFrame)
+from pipecat.frames.frames import (
+    CancelFrame,
+    ErrorFrame,
+    Frame,
+    AudioRawFrame,
+    StartInterruptionFrame,
+    StartFrame,
+    EndFrame,
+    TTSStartedFrame,
+    TTSStoppedFrame,
+    TextFrame,
+    LLMFullResponseEndFrame
+)
 from pipecat.processors.frame_processor import FrameDirection
-from pipecat.services.ai_services import AsyncWordTTSService
 from pipecat.transcriptions.language import Language
+from pipecat.services.ai_services import AsyncWordTTSService
+
+from loguru import logger
 
 # See .env.example for Cartesia configuration needed
 try:

From 540cad4844711147699ee2f231b361125504a0e6 Mon Sep 17 00:00:00 2001
From: Kunal Shah <kunal.shah@cartesia.ai>
Date: Mon, 16 Sep 2024 16:07:19 -0700
Subject: [PATCH 018/135] Undo sorting

---
 src/pipecat/transports/network/fastapi_websocket.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/src/pipecat/transports/network/fastapi_websocket.py b/src/pipecat/transports/network/fastapi_websocket.py
index b5bcfe7ed..2c4bd187b 100644
--- a/src/pipecat/transports/network/fastapi_websocket.py
+++ b/src/pipecat/transports/network/fastapi_websocket.py
@@ -8,19 +8,19 @@
 import asyncio
 import io
 import wave
-from typing import Awaitable, Callable
 
-from loguru import logger
+from typing import Awaitable, Callable
 from pydantic.main import BaseModel
 
-from pipecat.frames.frames import (AudioRawFrame, CancelFrame, EndFrame, Frame,
-                                   StartFrame, StartInterruptionFrame)
+from pipecat.frames.frames import AudioRawFrame, CancelFrame, EndFrame, Frame, StartFrame, StartInterruptionFrame
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.serializers.base_serializer import FrameSerializer
 from pipecat.transports.base_input import BaseInputTransport
 from pipecat.transports.base_output import BaseOutputTransport
 from pipecat.transports.base_transport import BaseTransport, TransportParams
 
+from loguru import logger
+
 try:
     from fastapi import WebSocket
     from starlette.websockets import WebSocketState

From 20c019ae1612a7aac76994a1842b3a80d407970b Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Mon, 16 Sep 2024 23:54:21 -0700
Subject: [PATCH 019/135] services(cartesia,elevenlabs): close websocket before
 the receiving task

---
 src/pipecat/services/cartesia.py   | 41 +++++++++++++++---------------
 src/pipecat/services/elevenlabs.py | 20 +++++++--------
 2 files changed, 31 insertions(+), 30 deletions(-)

diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index a9d5aae67..7b4463812 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -136,24 +136,25 @@ class CartesiaTTSService(AsyncWordTTSService):
             )
             self._receive_task = self.get_event_loop().create_task(self._receive_task_handler())
         except Exception as e:
-            logger.exception(f"{self} initialization error: {e}")
+            logger.error(f"{self} initialization error: {e}")
             self._websocket = None
 
     async def _disconnect(self):
         try:
             await self.stop_all_metrics()
 
-            if self._receive_task:
-                self._receive_task.cancel()
-                await self._receive_task
-                self._receive_task = None
             if self._websocket:
                 await self._websocket.close()
                 self._websocket = None
 
+            if self._receive_task:
+                self._receive_task.cancel()
+                await self._receive_task
+                self._receive_task = None
+
             self._context_id = None
         except Exception as e:
-            logger.exception(f"{self} error closing websocket: {e}")
+            logger.error(f"{self} error closing websocket: {e}")
 
     async def _handle_interruption(self, frame: StartInterruptionFrame, direction: FrameDirection):
         await super()._handle_interruption(frame, direction)
@@ -166,18 +167,18 @@ class CartesiaTTSService(AsyncWordTTSService):
             return
         logger.debug("Flushing audio")
         msg = {
-                "transcript": "",
-                "continue": False,
-                "context_id": self._context_id,
-                "model_id": self._model_id,
-                "voice": {
-                    "mode": "id",
-                    "id": self._voice_id
-                },
-                "output_format": self._output_format,
-                "language": self._language,
-                "add_timestamps": True,
-            }
+            "transcript": "",
+            "continue": False,
+            "context_id": self._context_id,
+            "model_id": self._model_id,
+            "voice": {
+                "mode": "id",
+                "id": self._voice_id
+            },
+            "output_format": self._output_format,
+            "language": self._language,
+            "add_timestamps": True,
+        }
         await self._websocket.send(json.dumps(msg))
 
     async def _receive_task_handler(self):
@@ -217,7 +218,7 @@ class CartesiaTTSService(AsyncWordTTSService):
         except asyncio.CancelledError:
             pass
         except Exception as e:
-            logger.exception(f"{self} exception: {e}")
+            logger.error(f"{self} exception: {e}")
 
     async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
         logger.debug(f"Generating TTS: [{text}]")
@@ -255,4 +256,4 @@ class CartesiaTTSService(AsyncWordTTSService):
                 return
             yield None
         except Exception as e:
-            logger.exception(f"{self} exception: {e}")
+            logger.error(f"{self} exception: {e}")
diff --git a/src/pipecat/services/elevenlabs.py b/src/pipecat/services/elevenlabs.py
index 6a3b85914..a7a80033e 100644
--- a/src/pipecat/services/elevenlabs.py
+++ b/src/pipecat/services/elevenlabs.py
@@ -174,13 +174,18 @@ class ElevenLabsTTSService(AsyncWordTTSService):
             }
             await self._websocket.send(json.dumps(msg))
         except Exception as e:
-            logger.exception(f"{self} initialization error: {e}")
+            logger.error(f"{self} initialization error: {e}")
             self._websocket = None
 
     async def _disconnect(self):
         try:
             await self.stop_all_metrics()
 
+            if self._websocket:
+                await self._websocket.send(json.dumps({"text": ""}))
+                await self._websocket.close()
+                self._websocket = None
+
             if self._receive_task:
                 self._receive_task.cancel()
                 await self._receive_task
@@ -191,13 +196,9 @@ class ElevenLabsTTSService(AsyncWordTTSService):
                 await self._keepalive_task
                 self._keepalive_task = None
 
-            if self._websocket:
-                await self._websocket.close()
-                self._websocket = None
-
             self._started = False
         except Exception as e:
-            logger.exception(f"{self} error closing websocket: {e}")
+            logger.error(f"{self} error closing websocket: {e}")
 
     async def _receive_task_handler(self):
         try:
@@ -215,11 +216,10 @@ class ElevenLabsTTSService(AsyncWordTTSService):
                     word_times = calculate_word_times(msg["alignment"], self._cumulative_time)
                     await self.add_word_timestamps(word_times)
                     self._cumulative_time = word_times[-1][1]
-
         except asyncio.CancelledError:
             pass
         except Exception as e:
-            logger.exception(f"{self} exception: {e}")
+            logger.error(f"{self} exception: {e}")
 
     async def _keepalive_task_handler(self):
         while True:
@@ -229,7 +229,7 @@ class ElevenLabsTTSService(AsyncWordTTSService):
             except asyncio.CancelledError:
                 break
             except Exception as e:
-                logger.exception(f"{self} exception: {e}")
+                logger.error(f"{self} exception: {e}")
 
     async def _send_text(self, text: str):
         if self._websocket:
@@ -260,4 +260,4 @@ class ElevenLabsTTSService(AsyncWordTTSService):
                 return
             yield None
         except Exception as e:
-            logger.exception(f"{self} exception: {e}")
+            logger.error(f"{self} exception: {e}")

From 2da0ecbe3c7326d180125d16f32ee8f95113f847 Mon Sep 17 00:00:00 2001
From: Jin Kim <golbin@gmail.com>
Date: Wed, 18 Sep 2024 00:38:12 +0900
Subject: [PATCH 020/135] Revert "model_id" as a main argument

---
 src/pipecat/services/cartesia.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index 25f54bf11..45e42470e 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -63,7 +63,6 @@ def language_to_cartesia_language(language: Language) -> str | None:
 
 class CartesiaTTSService(AsyncWordTTSService):
     class InputParams(BaseModel):
-        model_id: Optional[str] = "sonic-english"
         encoding: Optional[str] = "pcm_s16le"
         sample_rate: Optional[int] = 16000
         container: Optional[str] = "raw"
@@ -78,6 +77,7 @@ class CartesiaTTSService(AsyncWordTTSService):
             voice_id: str,
             cartesia_version: str = "2024-06-10",
             url: str = "wss://api.cartesia.ai/tts/websocket",
+            model_id: str = "sonic-english",
             params: InputParams = InputParams(),
             **kwargs):
         # Aggregating sentences still gives cleaner-sounding results and fewer
@@ -96,7 +96,7 @@ class CartesiaTTSService(AsyncWordTTSService):
         self._cartesia_version = cartesia_version
         self._url = url
         self._voice_id = voice_id
-        self._model_id = params.model_id
+        self._model_id = model_id
         self._output_format = {
             "container": params.container,
             "encoding": params.encoding,

From 75008d8f115ccab562a9b564e7415bdcb024a850 Mon Sep 17 00:00:00 2001
From: Jin Kim <golbin@gmail.com>
Date: Wed, 18 Sep 2024 00:51:45 +0900
Subject: [PATCH 021/135] Add speed and emotion setting method to Cartesia TTS
 service

---
 src/pipecat/services/cartesia.py | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index 45e42470e..6cec9c06d 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -121,6 +121,14 @@ class CartesiaTTSService(AsyncWordTTSService):
         logger.debug(f"Switching TTS voice to: [{voice}]")
         self._voice_id = voice
 
+    async def set_speed(self, speed: str):
+        logger.debug(f"Switching TTS speed to: [{speed}]")
+        self._speed = speed
+
+    async def set_emotion(self, emotion: list[str]):
+        logger.debug(f"Switching TTS emotion to: [{emotion}]")
+        self._emotion = emotion
+
     async def set_language(self, language: Language):
         logger.debug(f"Switching TTS language to: [{language}]")
         self._language = language_to_cartesia_language(language)

From 71202e3cd570078e3009e2c7ad0d38266d0f1923 Mon Sep 17 00:00:00 2001
From: Lewis Wolfgang <lewis@daily.co>
Date: Tue, 17 Sep 2024 16:48:52 -0400
Subject: [PATCH 022/135] Remove torch dependency for using silero_vad

---
 pyproject.toml                       |   2 +-
 src/pipecat/vad/data/__init__.py     |   0
 src/pipecat/vad/data/silero_vad.onnx | Bin 0 -> 2327524 bytes
 src/pipecat/vad/silero.py            | 103 +++++++++++++++++++++++++--
 4 files changed, 98 insertions(+), 7 deletions(-)
 create mode 100644 src/pipecat/vad/data/__init__.py
 create mode 100644 src/pipecat/vad/data/silero_vad.onnx

diff --git a/pyproject.toml b/pyproject.toml
index 8a1e3a800..6322a482d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -54,7 +54,7 @@ moondream = [ "einops~=0.8.0", "timm~=1.0.8", "transformers~=4.44.0" ]
 openai = [ "openai~=1.37.2" ]
 openpipe = [ "openpipe~=4.24.0" ]
 playht = [ "pyht~=0.0.28" ]
-silero = [ "silero-vad~=5.1" ]
+silero = [ "onnxruntime>=1.16.1" ]
 together = [ "together~=1.2.7" ]
 websocket = [ "websockets~=12.0", "fastapi~=0.112.1" ]
 whisper = [ "faster-whisper~=1.0.3" ]
diff --git a/src/pipecat/vad/data/__init__.py b/src/pipecat/vad/data/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/src/pipecat/vad/data/silero_vad.onnx b/src/pipecat/vad/data/silero_vad.onnx
new file mode 100644
index 0000000000000000000000000000000000000000..b3e3a900c0d70e67b5e2b90a33ad856ee7947930
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HcmV?d00001

diff --git a/src/pipecat/vad/silero.py b/src/pipecat/vad/silero.py
index 08d3534ea..c07ee2ae9 100644
--- a/src/pipecat/vad/silero.py
+++ b/src/pipecat/vad/silero.py
@@ -14,17 +14,94 @@ from pipecat.vad.vad_analyzer import VADAnalyzer, VADParams, VADState
 
 from loguru import logger
 
+# How often should we reset internal model state
+_MODEL_RESET_STATES_TIME = 5.0
+
 try:
-    from silero_vad import load_silero_vad
-    import torch
+    import onnxruntime
 
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error("In order to use Silero VAD, you need to `pip install pipecat-ai[silero]`.")
     raise Exception(f"Missing module(s): {e}")
 
-# How often should we reset internal model state
-_MODEL_RESET_STATES_TIME = 5.0
+
+class SileroOnnxModel():
+
+    def __init__(self, path, force_onnx_cpu=True):
+        import numpy as np
+        global np
+
+        opts = onnxruntime.SessionOptions()
+        opts.inter_op_num_threads = 1
+        opts.intra_op_num_threads = 1
+
+        if force_onnx_cpu and 'CPUExecutionProvider' in onnxruntime.get_available_providers():
+            self.session = onnxruntime.InferenceSession(
+                path, providers=['CPUExecutionProvider'], sess_options=opts)
+        else:
+            self.session = onnxruntime.InferenceSession(path, sess_options=opts)
+
+        self.reset_states()
+        self.sample_rates = [8000, 16000]
+
+    def _validate_input(self, x, sr: int):
+        if np.ndim(x) == 1:
+            x = np.expand_dims(x, 0)
+        if np.ndim(x) > 2:
+            raise ValueError(f"Too many dimensions for input audio chunk {x.dim()}")
+
+        if sr not in self.sample_rates:
+            raise ValueError(
+                f"Supported sampling rates: {self.sample_rates} (or multiply of 16000)")
+        if sr / np.shape(x)[1] > 31.25:
+            raise ValueError("Input audio chunk is too short")
+
+        return x, sr
+
+    def reset_states(self, batch_size=1):
+        self._state = np.zeros((2, batch_size, 128), dtype='float32')
+        self._context = np.zeros((batch_size, 0), dtype='float32')
+        self._last_sr = 0
+        self._last_batch_size = 0
+
+    def __call__(self, x, sr: int):
+
+        x, sr = self._validate_input(x, sr)
+        num_samples = 512 if sr == 16000 else 256
+
+        if np.shape(x)[-1] != num_samples:
+            raise ValueError(
+                f"Provided number of samples is {np.shape(x)[-1]} (Supported values: 256 for 8000 sample rate, 512 for 16000)")
+
+        batch_size = np.shape(x)[0]
+        context_size = 64 if sr == 16000 else 32
+
+        if not self._last_batch_size:
+            self.reset_states(batch_size)
+        if (self._last_sr) and (self._last_sr != sr):
+            self.reset_states(batch_size)
+        if (self._last_batch_size) and (self._last_batch_size != batch_size):
+            self.reset_states(batch_size)
+
+        if not np.shape(self._context)[1]:
+            self._context = np.zeros((batch_size, context_size), dtype='float32')
+
+        x = np.concatenate((self._context, x), axis=1)
+
+        if sr in [8000, 16000]:
+            ort_inputs = {'input': x, 'state': self._state, 'sr': np.array(sr, dtype='int64')}
+            ort_outs = self.session.run(None, ort_inputs)
+            out, state = ort_outs
+            self._state = state
+        else:
+            raise ValueError()
+
+        self._context = x[..., -context_size:]
+        self._last_sr = sr
+        self._last_batch_size = batch_size
+
+        return out
 
 
 class SileroVADAnalyzer(VADAnalyzer):
@@ -41,7 +118,21 @@ class SileroVADAnalyzer(VADAnalyzer):
 
         logger.debug("Loading Silero VAD model...")
 
-        self._model = load_silero_vad()
+        model_name = 'silero_vad.onnx'
+        package_path = "pipecat.vad.data"
+
+        try:
+            import importlib_resources as impresources
+            model_file_path = str(impresources.files(package_path).joinpath(model_name))
+        except BaseException:
+            from importlib import resources as impresources
+            try:
+                with impresources.path(package_path, model_name) as f:
+                    model_file_path = f
+            except BaseException:
+                model_file_path = str(impresources.files(package_path).joinpath(model_name))
+
+        self._model = SileroOnnxModel(model_file_path, force_onnx_cpu=True)
 
         self._last_reset_time = 0
 
@@ -59,7 +150,7 @@ class SileroVADAnalyzer(VADAnalyzer):
             audio_int16 = np.frombuffer(buffer, np.int16)
             # Divide by 32768 because we have signed 16-bit data.
             audio_float32 = np.frombuffer(audio_int16, dtype=np.int16).astype(np.float32) / 32768.0
-            new_confidence = self._model(torch.from_numpy(audio_float32), self.sample_rate).item()
+            new_confidence = self._model(audio_float32, self.sample_rate)[0]
 
             # We need to reset the model from time to time because it doesn't
             # really need all the data and memory will keep growing otherwise.

From eadd68d40b6233e4bffeb0bfa7171f2cdc0758c4 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Wed, 18 Sep 2024 14:19:04 -0400
Subject: [PATCH 023/135] Add sample_rate setting to TTS services

---
 src/pipecat/services/ai_services.py |  6 ++++++
 src/pipecat/services/azure.py       | 14 +++++++++---
 src/pipecat/services/cartesia.py    |  2 +-
 src/pipecat/services/elevenlabs.py  |  4 ++--
 src/pipecat/services/lmnt.py        |  2 +-
 src/pipecat/services/openai.py      | 33 ++++++++++++++++++++++-------
 src/pipecat/services/playht.py      | 17 ++++++++++++---
 7 files changed, 60 insertions(+), 18 deletions(-)

diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index dcba578c5..7291e7db9 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -171,6 +171,7 @@ class TTSService(AIService):
             push_stop_frames: bool = False,
             # if push_stop_frames is True, wait for this idle period before pushing TTSStoppedFrame
             stop_frame_timeout_s: float = 1.0,
+            sample_rate: int = 16000,
             **kwargs):
         super().__init__(**kwargs)
         self._aggregate_sentences: bool = aggregate_sentences
@@ -180,6 +181,11 @@ class TTSService(AIService):
         self._stop_frame_task: Optional[asyncio.Task] = None
         self._stop_frame_queue: asyncio.Queue = asyncio.Queue()
         self._current_sentence: str = ""
+        self._sample_rate: int = sample_rate
+
+    @property
+    def sample_rate(self) -> int:
+        return self._sample_rate
 
     @abstractmethod
     async def set_model(self, model: str):
diff --git a/src/pipecat/services/azure.py b/src/pipecat/services/azure.py
index 76e884992..c2f984b75 100644
--- a/src/pipecat/services/azure.py
+++ b/src/pipecat/services/azure.py
@@ -72,13 +72,21 @@ class AzureLLMService(BaseOpenAILLMService):
 
 
 class AzureTTSService(TTSService):
-    def __init__(self, *, api_key: str, region: str, voice="en-US-SaraNeural", **kwargs):
-        super().__init__(**kwargs)
+    def __init__(
+            self,
+            *,
+            api_key: str,
+            region: str,
+            voice="en-US-SaraNeural",
+            sample_rate: int = 16000,
+            **kwargs):
+        super().__init__(sample_rate=sample_rate, **kwargs)
 
         speech_config = SpeechConfig(subscription=api_key, region=region)
         self._speech_synthesizer = SpeechSynthesizer(speech_config=speech_config, audio_config=None)
 
         self._voice = voice
+        self._sample_rate = sample_rate
 
     def can_generate_metrics(self) -> bool:
         return True
@@ -109,7 +117,7 @@ class AzureTTSService(TTSService):
             await self.stop_ttfb_metrics()
             await self.push_frame(TTSStartedFrame())
             # Azure always sends a 44-byte header. Strip it off.
-            yield AudioRawFrame(audio=result.audio_data[44:], sample_rate=16000, num_channels=1)
+            yield AudioRawFrame(audio=result.audio_data[44:], sample_rate=self._sample_rate, num_channels=1)
             await self.push_frame(TTSStoppedFrame())
         elif result.reason == ResultReason.Canceled:
             cancellation_details = result.cancellation_details
diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index 7b4463812..ea790fab7 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -84,7 +84,7 @@ class CartesiaTTSService(AsyncWordTTSService):
         # if we're interrupted. Cartesia gives us word-by-word timestamps. We
         # can use those to generate text frames ourselves aligned with the
         # playout timing of the audio!
-        super().__init__(aggregate_sentences=True, push_text_frames=False, **kwargs)
+        super().__init__(aggregate_sentences=True, push_text_frames=False, sample_rate=sample_rate, **kwargs)
 
         self._api_key = api_key
         self._cartesia_version = cartesia_version
diff --git a/src/pipecat/services/elevenlabs.py b/src/pipecat/services/elevenlabs.py
index a7a80033e..081a6bf5d 100644
--- a/src/pipecat/services/elevenlabs.py
+++ b/src/pipecat/services/elevenlabs.py
@@ -101,6 +101,7 @@ class ElevenLabsTTSService(AsyncWordTTSService):
             push_text_frames=False,
             push_stop_frames=True,
             stop_frame_timeout_s=2.0,
+            sample_rate=sample_rate_from_output_format(params.output_format),
             **kwargs
         )
 
@@ -109,7 +110,6 @@ class ElevenLabsTTSService(AsyncWordTTSService):
         self._model = model
         self._url = url
         self._params = params
-        self._sample_rate = sample_rate_from_output_format(params.output_format)
 
         # Websocket connection to ElevenLabs.
         self._websocket = None
@@ -209,7 +209,7 @@ class ElevenLabsTTSService(AsyncWordTTSService):
                     self.start_word_timestamps()
 
                     audio = base64.b64decode(msg["audio"])
-                    frame = AudioRawFrame(audio, self._sample_rate, 1)
+                    frame = AudioRawFrame(audio, self.sample_rate, 1)
                     await self.push_frame(frame)
 
                 if msg.get("alignment"):
diff --git a/src/pipecat/services/lmnt.py b/src/pipecat/services/lmnt.py
index f5ad8aa1a..638e394a1 100644
--- a/src/pipecat/services/lmnt.py
+++ b/src/pipecat/services/lmnt.py
@@ -46,7 +46,7 @@ class LmntTTSService(AsyncTTSService):
             **kwargs):
         # Let TTSService produce TTSStoppedFrames after a short delay of
         # no activity.
-        super().__init__(push_stop_frames=True, **kwargs)
+        super().__init__(push_stop_frames=True, sample_rate=sample_rate, **kwargs)
 
         self._api_key = api_key
         self._voice_id = voice_id
diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py
index 2d0a24589..a03b350ba 100644
--- a/src/pipecat/services/openai.py
+++ b/src/pipecat/services/openai.py
@@ -11,7 +11,7 @@ import json
 import httpx
 from dataclasses import dataclass
 
-from typing import AsyncGenerator, List, Literal
+from typing import AsyncGenerator, Dict, List, Literal
 
 from loguru import logger
 from PIL import Image
@@ -55,6 +55,17 @@ except ModuleNotFoundError as e:
         "In order to use OpenAI, you need to `pip install pipecat-ai[openai]`. Also, set `OPENAI_API_KEY` environment variable.")
     raise Exception(f"Missing module: {e}")
 
+ValidVoice = Literal["alloy", "echo", "fable", "onyx", "nova", "shimmer"]
+
+VALID_VOICES: Dict[str, ValidVoice] = {
+    "alloy": "alloy",
+    "echo": "echo",
+    "fable": "fable",
+    "onyx": "onyx",
+    "nova": "nova",
+    "shimmer": "shimmer",
+}
+
 
 class OpenAIUnhandledFunctionException(Exception):
     pass
@@ -182,8 +193,8 @@ class BaseOpenAILLMService(LLMService):
             if self.has_function(function_name):
                 await self._handle_function_call(context, tool_call_id, function_name, arguments)
             else:
-                raise OpenAIUnhandledFunctionException(
-                    f"The LLM tried to call a function named '{function_name}', but there isn't a callback registered for that function.")
+                raise OpenAIUnhandledFunctionException(f"The LLM tried to call a function named '{
+                    function_name}', but there isn't a callback registered for that function.")
 
     async def _handle_function_call(
             self,
@@ -307,13 +318,15 @@ class OpenAITTSService(TTSService):
             self,
             *,
             api_key: str | None = None,
-            voice: Literal["alloy", "echo", "fable", "onyx", "nova", "shimmer"] = "alloy",
+            voice: str = "alloy",
             model: Literal["tts-1", "tts-1-hd"] = "tts-1",
+            sample_rate: int = 24000,
             **kwargs):
-        super().__init__(**kwargs)
+        super().__init__(sample_rate=sample_rate, **kwargs)
 
-        self._voice = voice
+        self._voice: ValidVoice = VALID_VOICES.get(voice, "alloy")
         self._model = model
+        self._sample_rate = sample_rate
 
         self._client = AsyncOpenAI(api_key=api_key)
 
@@ -322,7 +335,11 @@ class OpenAITTSService(TTSService):
 
     async def set_voice(self, voice: str):
         logger.debug(f"Switching TTS voice to: [{voice}]")
-        self._voice = voice
+        self._voice = VALID_VOICES.get(voice, self._voice)
+
+    async def set_model(self, model: str):
+        logger.debug(f"Switching TTS model to: [{model}]")
+        self._model = model
 
     async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
         logger.debug(f"Generating TTS: [{text}]")
@@ -348,7 +365,7 @@ class OpenAITTSService(TTSService):
                 async for chunk in r.iter_bytes(8192):
                     if len(chunk) > 0:
                         await self.stop_ttfb_metrics()
-                        frame = AudioRawFrame(chunk, 24_000, 1)
+                        frame = AudioRawFrame(chunk, self.sample_rate, 1)
                         yield frame
                 await self.push_frame(TTSStoppedFrame())
         except BadRequestError as e:
diff --git a/src/pipecat/services/playht.py b/src/pipecat/services/playht.py
index 2f4ae9851..c3200fee9 100644
--- a/src/pipecat/services/playht.py
+++ b/src/pipecat/services/playht.py
@@ -27,8 +27,15 @@ except ModuleNotFoundError as e:
 
 class PlayHTTTSService(TTSService):
 
-    def __init__(self, *, api_key: str, user_id: str, voice_url: str, **kwargs):
-        super().__init__(**kwargs)
+    def __init__(
+            self,
+            *,
+            api_key: str,
+            user_id: str,
+            voice_url: str,
+            sample_rate: int = 16000,
+            **kwargs):
+        super().__init__(sample_rate=sample_rate, **kwargs)
 
         self._user_id = user_id
         self._speech_key = api_key
@@ -39,13 +46,17 @@ class PlayHTTTSService(TTSService):
         )
         self._options = TTSOptions(
             voice=voice_url,
-            sample_rate=16000,
+            sample_rate=sample_rate,
             quality="higher",
             format=Format.FORMAT_WAV)
 
     def can_generate_metrics(self) -> bool:
         return True
 
+    async def set_voice(self, voice: str):
+        logger.debug(f"Switching TTS voice to: [{voice}]")
+        self._options.voice = voice
+
     async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
         logger.debug(f"Generating TTS: [{text}]")
 

From 337f048864d154dc3a70e4ae38eb3fc54f69abbe Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Fri, 30 Aug 2024 16:24:04 -0700
Subject: [PATCH 024/135] introduce synchronous and asynchronous frame
 processors

Pipecat has a pipeline-based architecture. The pipeline consists of frame
processors linked to each other. The elements travelling across the pipeline are
called frames.

To have a deterministic behavior the frames travelling through the pipeline
should always be ordered, except system frames which are out-of-band frames. To
achieve that, each frame processor should only output frames from a single task.

There are synchronous and asynchronous frame processors. The synchronous
processors push output frames from the same task that they receive input frames,
and therefore only pushing frames from one task. Asynchrnous frame processors
can have internal tasks to perform things asynchrnously (e.g. receiving data
from a websocket) but they also have a single task where they push frames from.
---
 examples/foundational/17-detect-user-idle.py  |  2 +-
 .../processors/aggregators/llm_response.py    |  1 -
 .../processors/async_frame_processor.py       | 64 -------------
 src/pipecat/processors/frame_processor.py     | 55 ++++++++++-
 src/pipecat/processors/frameworks/rtvi.py     | 34 +------
 .../processors/gstreamer/pipeline_source.py   | 50 ++--------
 .../processors/idle_frame_processor.py        | 19 +---
 src/pipecat/processors/user_idle_processor.py | 16 +---
 src/pipecat/services/ai_services.py           | 27 +-----
 src/pipecat/services/azure.py                 | 22 ++---
 src/pipecat/services/deepgram.py              |  2 +-
 src/pipecat/services/gladia.py                | 35 +++----
 src/pipecat/services/lmnt.py                  |  2 +-
 src/pipecat/transports/base_input.py          | 91 ++++---------------
 src/pipecat/transports/base_output.py         | 60 +++---------
 .../transports/network/websocket_server.py    |  4 +-
 src/pipecat/transports/services/daily.py      |  6 +-
 17 files changed, 130 insertions(+), 360 deletions(-)
 delete mode 100644 src/pipecat/processors/async_frame_processor.py

diff --git a/examples/foundational/17-detect-user-idle.py b/examples/foundational/17-detect-user-idle.py
index 903f35f4e..66fcfb200 100644
--- a/examples/foundational/17-detect-user-idle.py
+++ b/examples/foundational/17-detect-user-idle.py
@@ -70,7 +70,7 @@ async def main():
         async def user_idle_callback(user_idle: UserIdleProcessor):
             messages.append(
                 {"role": "system", "content": "Ask the user if they are still there and try to prompt for some input, but be short."})
-            await user_idle.queue_frame(LLMMessagesFrame(messages))
+            await user_idle.push_frame(LLMMessagesFrame(messages))
 
         user_idle = UserIdleProcessor(callback=user_idle_callback, timeout=5.0)
 
diff --git a/src/pipecat/processors/aggregators/llm_response.py b/src/pipecat/processors/aggregators/llm_response.py
index ab0552578..379394120 100644
--- a/src/pipecat/processors/aggregators/llm_response.py
+++ b/src/pipecat/processors/aggregators/llm_response.py
@@ -4,7 +4,6 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-import sys
 from typing import List
 
 from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContextFrame, OpenAILLMContext
diff --git a/src/pipecat/processors/async_frame_processor.py b/src/pipecat/processors/async_frame_processor.py
deleted file mode 100644
index 28a27d255..000000000
--- a/src/pipecat/processors/async_frame_processor.py
+++ /dev/null
@@ -1,64 +0,0 @@
-#
-# Copyright (c) 2024, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import asyncio
-
-from pipecat.frames.frames import EndFrame, Frame, StartInterruptionFrame
-from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
-
-
-class AsyncFrameProcessor(FrameProcessor):
-
-    def __init__(
-            self,
-            *,
-            name: str | None = None,
-            loop: asyncio.AbstractEventLoop | None = None,
-            **kwargs):
-        super().__init__(name=name, loop=loop, **kwargs)
-
-        self._create_push_task()
-
-    async def process_frame(self, frame: Frame, direction: FrameDirection):
-        await super().process_frame(frame, direction)
-
-        if isinstance(frame, StartInterruptionFrame):
-            await self._handle_interruptions(frame)
-
-    async def queue_frame(
-            self,
-            frame: Frame,
-            direction: FrameDirection = FrameDirection.DOWNSTREAM):
-        await self._push_queue.put((frame, direction))
-
-    async def cleanup(self):
-        self._push_frame_task.cancel()
-        await self._push_frame_task
-
-    async def _handle_interruptions(self, frame: Frame):
-        # Cancel the task. This will stop pushing frames downstream.
-        self._push_frame_task.cancel()
-        await self._push_frame_task
-        # Push an out-of-band frame (i.e. not using the ordered push
-        # frame task).
-        await self.push_frame(frame)
-        # Create a new queue and task.
-        self._create_push_task()
-
-    def _create_push_task(self):
-        self._push_queue = asyncio.Queue()
-        self._push_frame_task = self.get_event_loop().create_task(self._push_frame_task_handler())
-
-    async def _push_frame_task_handler(self):
-        running = True
-        while running:
-            try:
-                (frame, direction) = await self._push_queue.get()
-                await self.push_frame(frame, direction)
-                running = not isinstance(frame, EndFrame)
-                self._push_queue.task_done()
-            except asyncio.CancelledError:
-                break
diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py
index dfdee7d40..72924776c 100644
--- a/src/pipecat/processors/frame_processor.py
+++ b/src/pipecat/processors/frame_processor.py
@@ -11,12 +11,14 @@ from enum import Enum
 
 from pipecat.clocks.base_clock import BaseClock
 from pipecat.frames.frames import (
+    EndFrame,
     ErrorFrame,
     Frame,
     MetricsFrame,
     StartFrame,
     StartInterruptionFrame,
-    UserStoppedSpeakingFrame)
+    StopInterruptionFrame,
+    SystemFrame)
 from pipecat.utils.utils import obj_count, obj_id
 
 from loguru import logger
@@ -88,6 +90,7 @@ class FrameProcessor:
             self,
             *,
             name: str | None = None,
+            sync: bool = True,
             loop: asyncio.AbstractEventLoop | None = None,
             **kwargs):
         self.id: int = obj_id()
@@ -96,6 +99,7 @@ class FrameProcessor:
         self._prev: "FrameProcessor" | None = None
         self._next: "FrameProcessor" | None = None
         self._loop: asyncio.AbstractEventLoop = loop or asyncio.get_running_loop()
+        self._sync = sync
 
         # Clock
         self._clock: BaseClock | None = None
@@ -109,6 +113,14 @@ class FrameProcessor:
         # Metrics
         self._metrics = FrameProcessorMetrics(name=self.name)
 
+        # Every processor in Pipecat should only output frames from a single
+        # task. This avoid problems like audio overlapping. System frames are
+        # the exception to this rule.
+        #
+        # This create this task.
+        if not self._sync:
+            self.__create_push_task()
+
     @property
     def interruptions_allowed(self):
         return self._allow_interruptions
@@ -192,14 +204,38 @@ class FrameProcessor:
             self._enable_usage_metrics = frame.enable_usage_metrics
             self._report_only_initial_ttfb = frame.report_only_initial_ttfb
         elif isinstance(frame, StartInterruptionFrame):
+            await self._start_interruption()
             await self.stop_all_metrics()
-        elif isinstance(frame, UserStoppedSpeakingFrame):
+        elif isinstance(frame, StopInterruptionFrame):
             self._should_report_ttfb = True
 
     async def push_error(self, error: ErrorFrame):
         await self.push_frame(error, FrameDirection.UPSTREAM)
 
     async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM):
+        if self._sync or isinstance(frame, SystemFrame):
+            await self.__internal_push_frame(frame, direction)
+        else:
+            await self.__push_queue.put((frame, direction))
+
+    #
+    # Handle interruptions
+    #
+
+    async def _start_interruption(self):
+        if not self._sync:
+            # Cancel the task. This will stop pushing frames downstream.
+            self.__push_frame_task.cancel()
+            await self.__push_frame_task
+
+            # Create a new queue and task.
+            self.__create_push_task()
+
+    async def _stop_interruption(self):
+        # Nothing to do right now.
+        pass
+
+    async def __internal_push_frame(self, frame: Frame, direction: FrameDirection):
         try:
             if direction == FrameDirection.DOWNSTREAM and self._next:
                 logger.trace(f"Pushing {frame} from {self} to {self._next}")
@@ -210,5 +246,20 @@ class FrameProcessor:
         except Exception as e:
             logger.exception(f"Uncaught exception in {self}: {e}")
 
+    def __create_push_task(self):
+        self.__push_queue = asyncio.Queue()
+        self.__push_frame_task = self.get_event_loop().create_task(self.__push_frame_task_handler())
+
+    async def __push_frame_task_handler(self):
+        running = True
+        while running:
+            try:
+                (frame, direction) = await self.__push_queue.get()
+                await self.__internal_push_frame(frame, direction)
+                running = not isinstance(frame, EndFrame)
+                self.__push_queue.task_done()
+            except asyncio.CancelledError:
+                break
+
     def __str__(self):
         return self.name
diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py
index dd28e7252..d32f0f640 100644
--- a/src/pipecat/processors/frameworks/rtvi.py
+++ b/src/pipecat/processors/frameworks/rtvi.py
@@ -272,8 +272,9 @@ class RTVIProcessor(FrameProcessor):
     def __init__(self,
                  *,
                  config: RTVIConfig = RTVIConfig(config=[]),
-                 params: RTVIProcessorParams = RTVIProcessorParams()):
-        super().__init__()
+                 params: RTVIProcessorParams = RTVIProcessorParams(),
+                 **kwargs):
+        super().__init__(sync=False, **kwargs)
         self._config = config
         self._params = params
 
@@ -286,9 +287,6 @@ class RTVIProcessor(FrameProcessor):
         self._registered_actions: Dict[str, RTVIAction] = {}
         self._registered_services: Dict[str, RTVIService] = {}
 
-        self._push_frame_task = self.get_event_loop().create_task(self._push_frame_task_handler())
-        self._push_queue = asyncio.Queue()
-
         self._message_task = self.get_event_loop().create_task(self._message_task_handler())
         self._message_queue = asyncio.Queue()
 
@@ -335,12 +333,6 @@ class RTVIProcessor(FrameProcessor):
         message = RTVILLMFunctionCallStartMessage(data=fn)
         await self._push_transport_message(message, exclude_none=False)
 
-    async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM):
-        if isinstance(frame, SystemFrame):
-            await super().push_frame(frame, direction)
-        else:
-            await self._internal_push_frame(frame, direction)
-
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
@@ -394,30 +386,10 @@ class RTVIProcessor(FrameProcessor):
         # processing EndFrames.
         self._message_task.cancel()
         await self._message_task
-        await self._push_frame_task
 
     async def _cancel(self, frame: CancelFrame):
         self._message_task.cancel()
         await self._message_task
-        self._push_frame_task.cancel()
-        await self._push_frame_task
-
-    async def _internal_push_frame(
-            self,
-            frame: Frame | None,
-            direction: FrameDirection | None = FrameDirection.DOWNSTREAM):
-        await self._push_queue.put((frame, direction))
-
-    async def _push_frame_task_handler(self):
-        running = True
-        while running:
-            try:
-                (frame, direction) = await self._push_queue.get()
-                await super().push_frame(frame, direction)
-                self._push_queue.task_done()
-                running = not isinstance(frame, EndFrame)
-            except asyncio.CancelledError:
-                break
 
     async def _push_transport_message(self, model: BaseModel, exclude_none: bool = True):
         frame = TransportMessageFrame(
diff --git a/src/pipecat/processors/gstreamer/pipeline_source.py b/src/pipecat/processors/gstreamer/pipeline_source.py
index eef0d56cc..5f0ee089b 100644
--- a/src/pipecat/processors/gstreamer/pipeline_source.py
+++ b/src/pipecat/processors/gstreamer/pipeline_source.py
@@ -41,7 +41,7 @@ class GStreamerPipelineSource(FrameProcessor):
         clock_sync: bool = True
 
     def __init__(self, *, pipeline: str, out_params: OutputParams = OutputParams(), **kwargs):
-        super().__init__(**kwargs)
+        super().__init__(sync=False, **kwargs)
 
         self._out_params = out_params
 
@@ -62,10 +62,6 @@ class GStreamerPipelineSource(FrameProcessor):
         bus.add_signal_watch()
         bus.connect("message", self._on_gstreamer_message)
 
-        # Create push frame task. This is the task that will push frames in
-        # order. We also guarantee that all frames are pushed in the same task.
-        self._create_push_task()
-
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
@@ -80,60 +76,28 @@ class GStreamerPipelineSource(FrameProcessor):
         elif isinstance(frame, StartFrame):
             # Push StartFrame before start(), because we want StartFrame to be
             # processed by every processor before any other frame is processed.
-            await self._internal_push_frame(frame, direction)
+            await self.push_frame(frame, direction)
             await self._start(frame)
         elif isinstance(frame, EndFrame):
             # Push EndFrame before stop(), because stop() waits on the task to
             # finish and the task finishes when EndFrame is processed.
-            await self._internal_push_frame(frame, direction)
+            await self.push_frame(frame, direction)
             await self._stop(frame)
         # Other frames
         else:
-            await self._internal_push_frame(frame, direction)
+            await self.push_frame(frame, direction)
 
     async def _start(self, frame: StartFrame):
         self._player.set_state(Gst.State.PLAYING)
 
     async def _stop(self, frame: EndFrame):
         self._player.set_state(Gst.State.NULL)
-        # Wait for the push frame task to finish. It will finish when the
-        # EndFrame is actually processed.
-        await self._push_frame_task
 
     async def _cancel(self, frame: CancelFrame):
         self._player.set_state(Gst.State.NULL)
-        # Cancel all the tasks and wait for them to finish.
-        self._push_frame_task.cancel()
-        await self._push_frame_task
 
     #
-    # Push frames task
-    #
-
-    def _create_push_task(self):
-        loop = self.get_event_loop()
-        self._push_queue = asyncio.Queue()
-        self._push_frame_task = loop.create_task(self._push_frame_task_handler())
-
-    async def _internal_push_frame(
-            self,
-            frame: Frame | None,
-            direction: FrameDirection | None = FrameDirection.DOWNSTREAM):
-        await self._push_queue.put((frame, direction))
-
-    async def _push_frame_task_handler(self):
-        running = True
-        while running:
-            try:
-                (frame, direction) = await self._push_queue.get()
-                await self.push_frame(frame, direction)
-                running = not isinstance(frame, EndFrame)
-                self._push_queue.task_done()
-            except asyncio.CancelledError:
-                break
-
-    #
-    # GStreaner
+    # GStreamer
     #
 
     def _on_gstreamer_message(self, bus: Gst.Bus, message: Gst.Message):
@@ -221,7 +185,7 @@ class GStreamerPipelineSource(FrameProcessor):
         frame = AudioRawFrame(audio=info.data,
                               sample_rate=self._out_params.audio_sample_rate,
                               num_channels=self._out_params.audio_channels)
-        asyncio.run_coroutine_threadsafe(self._internal_push_frame(frame), self.get_event_loop())
+        asyncio.run_coroutine_threadsafe(self.push_frame(frame), self.get_event_loop())
         buffer.unmap(info)
         return Gst.FlowReturn.OK
 
@@ -232,6 +196,6 @@ class GStreamerPipelineSource(FrameProcessor):
             image=info.data,
             size=(self._out_params.video_width, self._out_params.video_height),
             format="RGB")
-        asyncio.run_coroutine_threadsafe(self._internal_push_frame(frame), self.get_event_loop())
+        asyncio.run_coroutine_threadsafe(self.push_frame(frame), self.get_event_loop())
         buffer.unmap(info)
         return Gst.FlowReturn.OK
diff --git a/src/pipecat/processors/idle_frame_processor.py b/src/pipecat/processors/idle_frame_processor.py
index 40304a5c6..42b81517e 100644
--- a/src/pipecat/processors/idle_frame_processor.py
+++ b/src/pipecat/processors/idle_frame_processor.py
@@ -8,19 +8,14 @@ import asyncio
 
 from typing import Awaitable, Callable, List
 
-from pipecat.frames.frames import Frame, SystemFrame
-from pipecat.processors.async_frame_processor import AsyncFrameProcessor
-from pipecat.processors.frame_processor import FrameDirection
+from pipecat.frames.frames import Frame
+from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 
 
-class IdleFrameProcessor(AsyncFrameProcessor):
+class IdleFrameProcessor(FrameProcessor):
     """This class waits to receive any frame or list of desired frames within a
     given timeout. If the timeout is reached before receiving any of those
     frames the provided callback will be called.
-
-    The callback can then be used to push frames downstream by using
-    `queue_frame()` (or `push_frame()` for system frames).
-
     """
 
     def __init__(
@@ -30,7 +25,7 @@ class IdleFrameProcessor(AsyncFrameProcessor):
             timeout: float,
             types: List[type] = [],
             **kwargs):
-        super().__init__(**kwargs)
+        super().__init__(sync=False, **kwargs)
 
         self._callback = callback
         self._timeout = timeout
@@ -41,10 +36,7 @@ class IdleFrameProcessor(AsyncFrameProcessor):
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
-        if isinstance(frame, SystemFrame):
-            await self.push_frame(frame, direction)
-        else:
-            await self.queue_frame(frame, direction)
+        await self.push_frame(frame, direction)
 
         # If we are not waiting for any specific frame set the event, otherwise
         # check if we have received one of the desired frames.
@@ -55,7 +47,6 @@ class IdleFrameProcessor(AsyncFrameProcessor):
                 if isinstance(frame, t):
                     self._idle_event.set()
 
-        # If we are not waiting for any specific frame set the event, otherwise
     async def cleanup(self):
         self._idle_task.cancel()
         await self._idle_task
diff --git a/src/pipecat/processors/user_idle_processor.py b/src/pipecat/processors/user_idle_processor.py
index 7deda2555..36c394a5d 100644
--- a/src/pipecat/processors/user_idle_processor.py
+++ b/src/pipecat/processors/user_idle_processor.py
@@ -11,21 +11,16 @@ from typing import Awaitable, Callable
 from pipecat.frames.frames import (
     BotSpeakingFrame,
     Frame,
-    SystemFrame,
     UserStartedSpeakingFrame,
     UserStoppedSpeakingFrame)
-from pipecat.processors.async_frame_processor import AsyncFrameProcessor
-from pipecat.processors.frame_processor import FrameDirection
+from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 
 
-class UserIdleProcessor(AsyncFrameProcessor):
+class UserIdleProcessor(FrameProcessor):
     """This class is useful to check if the user is interacting with the bot
     within a given timeout. If the timeout is reached before any interaction
     occurred the provided callback will be called.
 
-    The callback can then be used to push frames downstream by using
-    `queue_frame()` (or `push_frame()` for system frames).
-
     """
 
     def __init__(
@@ -34,7 +29,7 @@ class UserIdleProcessor(AsyncFrameProcessor):
             callback: Callable[["UserIdleProcessor"], Awaitable[None]],
             timeout: float,
             **kwargs):
-        super().__init__(**kwargs)
+        super().__init__(sync=False, **kwargs)
 
         self._callback = callback
         self._timeout = timeout
@@ -46,10 +41,7 @@ class UserIdleProcessor(AsyncFrameProcessor):
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
-        if isinstance(frame, SystemFrame):
-            await self.push_frame(frame, direction)
-        else:
-            await self.queue_frame(frame, direction)
+        await self.push_frame(frame, direction)
 
         # We shouldn't call the idle callback if the user or the bot are speaking.
         if isinstance(frame, UserStartedSpeakingFrame):
diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index 7291e7db9..d7226dba3 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -32,7 +32,6 @@ from pipecat.frames.frames import (
     UserImageRequestFrame,
     VisionImageRawFrame
 )
-from pipecat.processors.async_frame_processor import AsyncFrameProcessor
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.transcriptions.language import Language
 from pipecat.utils.audio import calculate_audio_volume
@@ -67,7 +66,7 @@ class AIService(FrameProcessor):
         elif isinstance(frame, EndFrame):
             await self.stop(frame)
 
-    async def process_generator(self, generator: AsyncGenerator[Frame, None]):
+    async def process_generator(self, generator: AsyncGenerator[Frame | None, None]):
         async for f in generator:
             if f:
                 if isinstance(f, ErrorFrame):
@@ -76,30 +75,6 @@ class AIService(FrameProcessor):
                     await self.push_frame(f)
 
 
-class AsyncAIService(AsyncFrameProcessor):
-    def __init__(self, **kwargs):
-        super().__init__(**kwargs)
-
-    async def start(self, frame: StartFrame):
-        pass
-
-    async def stop(self, frame: EndFrame):
-        pass
-
-    async def cancel(self, frame: CancelFrame):
-        pass
-
-    async def process_frame(self, frame: Frame, direction: FrameDirection):
-        await super().process_frame(frame, direction)
-
-        if isinstance(frame, StartFrame):
-            await self.start(frame)
-        elif isinstance(frame, CancelFrame):
-            await self.cancel(frame)
-        elif isinstance(frame, EndFrame):
-            await self.stop(frame)
-
-
 class LLMService(AIService):
     """This class is a no-op but serves as a base class for LLM services."""
 
diff --git a/src/pipecat/services/azure.py b/src/pipecat/services/azure.py
index c2f984b75..90674fcc4 100644
--- a/src/pipecat/services/azure.py
+++ b/src/pipecat/services/azure.py
@@ -18,13 +18,11 @@ from pipecat.frames.frames import (
     ErrorFrame,
     Frame,
     StartFrame,
-    SystemFrame,
     TTSStartedFrame,
     TTSStoppedFrame,
     TranscriptionFrame,
     URLImageRawFrame)
-from pipecat.processors.frame_processor import FrameDirection
-from pipecat.services.ai_services import AsyncAIService, TTSService, ImageGenService
+from pipecat.services.ai_services import STTService, TTSService, ImageGenService
 from pipecat.services.openai import BaseOpenAILLMService
 from pipecat.utils.time import time_now_iso8601
 
@@ -126,7 +124,7 @@ class AzureTTSService(TTSService):
                 logger.error(f"{self} error: {cancellation_details.error_details}")
 
 
-class AzureSTTService(AsyncAIService):
+class AzureSTTService(STTService):
     def __init__(
             self,
             *,
@@ -149,15 +147,11 @@ class AzureSTTService(AsyncAIService):
             speech_config=speech_config, audio_config=audio_config)
         self._speech_recognizer.recognized.connect(self._on_handle_recognized)
 
-    async def process_frame(self, frame: Frame, direction: FrameDirection):
-        await super().process_frame(frame, direction)
-
-        if isinstance(frame, SystemFrame):
-            await self.push_frame(frame, direction)
-        elif isinstance(frame, AudioRawFrame):
-            self._audio_stream.write(frame.audio)
-        else:
-            await self._push_queue.put((frame, direction))
+    async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]:
+        await self.start_processing_metrics()
+        self._audio_stream.write(audio)
+        await self.stop_processing_metrics()
+        yield None
 
     async def start(self, frame: StartFrame):
         await super().start(frame)
@@ -176,7 +170,7 @@ class AzureSTTService(AsyncAIService):
     def _on_handle_recognized(self, event):
         if event.result.reason == ResultReason.RecognizedSpeech and len(event.result.text) > 0:
             frame = TranscriptionFrame(event.result.text, "", time_now_iso8601())
-            asyncio.run_coroutine_threadsafe(self.queue_frame(frame), self.get_event_loop())
+            asyncio.run_coroutine_threadsafe(self.push_frame(frame), self.get_event_loop())
 
 
 class AzureImageGenServiceREST(ImageGenService):
diff --git a/src/pipecat/services/deepgram.py b/src/pipecat/services/deepgram.py
index d899d4bdb..708c3c511 100644
--- a/src/pipecat/services/deepgram.py
+++ b/src/pipecat/services/deepgram.py
@@ -161,8 +161,8 @@ class DeepgramSTTService(STTService):
     async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]:
         await self.start_processing_metrics()
         await self._connection.send(audio)
-        yield None
         await self.stop_processing_metrics()
+        yield None
 
     async def _connect(self):
         if await self._connection.start(self._live_options):
diff --git a/src/pipecat/services/gladia.py b/src/pipecat/services/gladia.py
index 886300897..ead8f63dc 100644
--- a/src/pipecat/services/gladia.py
+++ b/src/pipecat/services/gladia.py
@@ -7,20 +7,17 @@
 import base64
 import json
 
-from typing import Optional
+from typing import AsyncGenerator, Optional
 from pydantic.main import BaseModel
 
 from pipecat.frames.frames import (
-    AudioRawFrame,
     CancelFrame,
     EndFrame,
     Frame,
     InterimTranscriptionFrame,
     StartFrame,
-    SystemFrame,
     TranscriptionFrame)
-from pipecat.processors.frame_processor import FrameDirection
-from pipecat.services.ai_services import AsyncAIService
+from pipecat.services.ai_services import STTService
 from pipecat.utils.time import time_now_iso8601
 
 from loguru import logger
@@ -35,7 +32,7 @@ except ModuleNotFoundError as e:
     raise Exception(f"Missing module: {e}")
 
 
-class GladiaSTTService(AsyncAIService):
+class GladiaSTTService(STTService):
     class InputParams(BaseModel):
         sample_rate: Optional[int] = 16000
         language: Optional[str] = "english"
@@ -50,23 +47,13 @@ class GladiaSTTService(AsyncAIService):
                  confidence: float = 0.5,
                  params: InputParams = InputParams(),
                  **kwargs):
-        super().__init__(**kwargs)
+        super().__init__(sync=False, **kwargs)
 
         self._api_key = api_key
         self._url = url
         self._params = params
         self._confidence = confidence
 
-    async def process_frame(self, frame: Frame, direction: FrameDirection):
-        await super().process_frame(frame, direction)
-
-        if isinstance(frame, SystemFrame):
-            await self.push_frame(frame, direction)
-        elif isinstance(frame, AudioRawFrame):
-            await self._send_audio(frame)
-        else:
-            await self.queue_frame(frame, direction)
-
     async def start(self, frame: StartFrame):
         await super().start(frame)
         self._websocket = await websockets.connect(self._url)
@@ -81,6 +68,12 @@ class GladiaSTTService(AsyncAIService):
         await super().cancel(frame)
         await self._websocket.close()
 
+    async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]:
+        await self.start_processing_metrics()
+        await self._send_audio(audio)
+        await self.stop_processing_metrics()
+        yield None
+
     async def _setup_gladia(self):
         configuration = {
             "x_gladia_key": self._api_key,
@@ -92,9 +85,9 @@ class GladiaSTTService(AsyncAIService):
 
         await self._websocket.send(json.dumps(configuration))
 
-    async def _send_audio(self, frame: AudioRawFrame):
+    async def _send_audio(self, audio: bytes):
         message = {
-            'frames': base64.b64encode(frame.audio).decode("utf-8")
+            'frames': base64.b64encode(audio).decode("utf-8")
         }
         await self._websocket.send(json.dumps(message))
 
@@ -113,6 +106,6 @@ class GladiaSTTService(AsyncAIService):
                 transcript = utterance["transcription"]
                 if confidence >= self._confidence:
                     if type == "final":
-                        await self.queue_frame(TranscriptionFrame(transcript, "", time_now_iso8601()))
+                        await self.push_frame(TranscriptionFrame(transcript, "", time_now_iso8601()))
                     else:
-                        await self.queue_frame(InterimTranscriptionFrame(transcript, "", time_now_iso8601()))
+                        await self.push_frame(InterimTranscriptionFrame(transcript, "", time_now_iso8601()))
diff --git a/src/pipecat/services/lmnt.py b/src/pipecat/services/lmnt.py
index 638e394a1..60f0cb7df 100644
--- a/src/pipecat/services/lmnt.py
+++ b/src/pipecat/services/lmnt.py
@@ -46,7 +46,7 @@ class LmntTTSService(AsyncTTSService):
             **kwargs):
         # Let TTSService produce TTSStoppedFrames after a short delay of
         # no activity.
-        super().__init__(push_stop_frames=True, sample_rate=sample_rate, **kwargs)
+        super().__init__(sync=False, push_stop_frames=True, sample_rate=sample_rate, **kwargs)
 
         self._api_key = api_key
         self._voice_id = voice_id
diff --git a/src/pipecat/transports/base_input.py b/src/pipecat/transports/base_input.py
index 3d1d0c4d7..8836fbd1e 100644
--- a/src/pipecat/transports/base_input.py
+++ b/src/pipecat/transports/base_input.py
@@ -31,16 +31,12 @@ from loguru import logger
 class BaseInputTransport(FrameProcessor):
 
     def __init__(self, params: TransportParams, **kwargs):
-        super().__init__(**kwargs)
+        super().__init__(sync=False, **kwargs)
 
         self._params = params
 
         self._executor = ThreadPoolExecutor(max_workers=5)
 
-        # Create push frame task. This is the task that will push frames in
-        # order. We also guarantee that all frames are pushed in the same task.
-        self._create_push_task()
-
     async def start(self, frame: StartFrame):
         # Create audio input queue and task if needed.
         if self._params.audio_in_enabled or self._params.vad_enabled:
@@ -53,10 +49,6 @@ class BaseInputTransport(FrameProcessor):
             self._audio_task.cancel()
             await self._audio_task
 
-        # Wait for the push frame task to finish. It will finish when the
-        # EndFrame is actually processed.
-        await self._push_frame_task
-
     async def cancel(self, frame: CancelFrame):
         # Cancel all the tasks and wait for them to finish.
 
@@ -64,9 +56,6 @@ class BaseInputTransport(FrameProcessor):
             self._audio_task.cancel()
             await self._audio_task
 
-        self._push_frame_task.cancel()
-        await self._push_frame_task
-
     def vad_analyzer(self) -> VADAnalyzer | None:
         return self._params.vad_analyzer
 
@@ -86,11 +75,8 @@ class BaseInputTransport(FrameProcessor):
             await self.cancel(frame)
             await self.push_frame(frame, direction)
         elif isinstance(frame, BotInterruptionFrame):
-            await self._handle_interruptions(frame, False)
-        elif isinstance(frame, StartInterruptionFrame):
+            logger.debug("Bot interruption")
             await self._start_interruption()
-        elif isinstance(frame, StopInterruptionFrame):
-            await self._stop_interruption()
         # All other system frames
         elif isinstance(frame, SystemFrame):
             await self.push_frame(frame, direction)
@@ -98,12 +84,12 @@ class BaseInputTransport(FrameProcessor):
         elif isinstance(frame, StartFrame):
             # Push StartFrame before start(), because we want StartFrame to be
             # processed by every processor before any other frame is processed.
-            await self._internal_push_frame(frame, direction)
+            await self.push_frame(frame, direction)
             await self.start(frame)
         elif isinstance(frame, EndFrame):
             # Push EndFrame before stop(), because stop() waits on the task to
             # finish and the task finishes when EndFrame is processed.
-            await self._internal_push_frame(frame, direction)
+            await self.push_frame(frame, direction)
             await self.stop(frame)
         elif isinstance(frame, VADParamsUpdateFrame):
             vad_analyzer = self.vad_analyzer()
@@ -111,73 +97,28 @@ class BaseInputTransport(FrameProcessor):
                 vad_analyzer.set_params(frame.params)
         # Other frames
         else:
-            await self._internal_push_frame(frame, direction)
-
-    #
-    # Push frames task
-    #
-
-    def _create_push_task(self):
-        loop = self.get_event_loop()
-        self._push_queue = asyncio.Queue()
-        self._push_frame_task = loop.create_task(self._push_frame_task_handler())
-
-    async def _internal_push_frame(
-            self,
-            frame: Frame | None,
-            direction: FrameDirection | None = FrameDirection.DOWNSTREAM):
-        await self._push_queue.put((frame, direction))
-
-    async def _push_frame_task_handler(self):
-        running = True
-        while running:
-            try:
-                (frame, direction) = await self._push_queue.get()
-                await self.push_frame(frame, direction)
-                running = not isinstance(frame, EndFrame)
-                self._push_queue.task_done()
-            except asyncio.CancelledError:
-                break
+            await self.push_frame(frame, direction)
 
     #
     # Handle interruptions
     #
 
-    async def _start_interruption(self):
-        if not self.interruptions_allowed:
-            return
-
-        # Cancel the task. This will stop pushing frames downstream.
-        self._push_frame_task.cancel()
-        await self._push_frame_task
-        # Push an out-of-band frame (i.e. not using the ordered push
-        # frame task) to stop everything, specially at the output
-        # transport.
-        await self.push_frame(StartInterruptionFrame())
-        # Create a new queue and task.
-        self._create_push_task()
-
-    async def _stop_interruption(self):
-        if not self.interruptions_allowed:
-            return
-
-        await self.push_frame(StopInterruptionFrame())
-
-    async def _handle_interruptions(self, frame: Frame, push_frame: bool):
+    async def _handle_interruptions(self, frame: Frame):
         if self.interruptions_allowed:
-            # Make sure we notify about interruptions quickly out-of-band
-            if isinstance(frame, BotInterruptionFrame):
-                logger.debug("Bot interruption")
-                await self._start_interruption()
-            elif isinstance(frame, UserStartedSpeakingFrame):
+            # Make sure we notify about interruptions quickly out-of-band.
+            if isinstance(frame, UserStartedSpeakingFrame):
                 logger.debug("User started speaking")
                 await self._start_interruption()
+                # Push an out-of-band frame (i.e. not using the ordered push
+                # frame task) to stop everything, specially at the output
+                # transport.
+                await self.push_frame(StartInterruptionFrame())
             elif isinstance(frame, UserStoppedSpeakingFrame):
                 logger.debug("User stopped speaking")
                 await self._stop_interruption()
+                await self.push_frame(StopInterruptionFrame())
 
-        if push_frame:
-            await self._internal_push_frame(frame)
+        await self.push_frame(frame)
 
     #
     # Audio input
@@ -201,7 +142,7 @@ class BaseInputTransport(FrameProcessor):
                 frame = UserStoppedSpeakingFrame()
 
             if frame:
-                await self._handle_interruptions(frame, True)
+                await self._handle_interruptions(frame)
 
             vad_state = new_vad_state
         return vad_state
@@ -222,7 +163,7 @@ class BaseInputTransport(FrameProcessor):
 
                 # Push audio downstream if passthrough.
                 if audio_passthrough:
-                    await self._internal_push_frame(frame)
+                    await self.push_frame(frame)
 
                 self._audio_in_queue.task_done()
             except asyncio.CancelledError:
diff --git a/src/pipecat/transports/base_output.py b/src/pipecat/transports/base_output.py
index a24c9f4d2..bc683721a 100644
--- a/src/pipecat/transports/base_output.py
+++ b/src/pipecat/transports/base_output.py
@@ -43,7 +43,7 @@ from pipecat.utils.time import nanoseconds_to_seconds
 class BaseOutputTransport(FrameProcessor):
 
     def __init__(self, params: TransportParams, **kwargs):
-        super().__init__(**kwargs)
+        super().__init__(sync=False, **kwargs)
 
         self._params = params
 
@@ -70,10 +70,6 @@ class BaseOutputTransport(FrameProcessor):
         # generating frames upstream while, for example, the audio is playing.
         self._create_sink_tasks()
 
-        # Create push frame task. This is the task that will push frames in
-        # order. We also guarantee that all frames are pushed in the same task.
-        self._create_push_task()
-
     async def start(self, frame: StartFrame):
         # Create camera output queue and task if needed.
         if self._params.camera_out_enabled:
@@ -95,9 +91,8 @@ class BaseOutputTransport(FrameProcessor):
             self._audio_out_task.cancel()
             await self._audio_out_task
 
-        # Wait for the push frame and sink tasks to finish. They will finish when
-        # the EndFrame is actually processed.
-        await self._push_frame_task
+        # Wait for the sink task to finish. They will finish when the EndFrame
+        # is actually processed.
         await self._sink_task
 
     async def cancel(self, frame: CancelFrame):
@@ -107,9 +102,6 @@ class BaseOutputTransport(FrameProcessor):
             self._camera_out_task.cancel()
             await self._camera_out_task
 
-        self._push_frame_task.cancel()
-        await self._push_frame_task
-
         self._sink_task.cancel()
         await self._sink_task
 
@@ -182,10 +174,6 @@ class BaseOutputTransport(FrameProcessor):
             await self._sink_clock_task
             # Create sink tasks.
             self._create_sink_tasks()
-            # Stop push task.
-            self._push_frame_task.cancel()
-            await self._push_frame_task
-            self._create_push_task()
             # Let's send a bot stopped speaking if we have to.
             if self._bot_speaking:
                 await self._bot_stopped_speaking()
@@ -227,7 +215,7 @@ class BaseOutputTransport(FrameProcessor):
     async def _sink_frame_handler(self, frame: Frame):
         if isinstance(frame, AudioRawFrame):
             await self.write_raw_audio_frames(frame.audio)
-            await self._internal_push_frame(frame)
+            await self.push_frame(frame)
             await self.push_frame(BotSpeakingFrame(), FrameDirection.UPSTREAM)
         elif isinstance(frame, ImageRawFrame):
             await self._set_camera_image(frame)
@@ -237,12 +225,12 @@ class BaseOutputTransport(FrameProcessor):
             await self.send_message(frame)
         elif isinstance(frame, TTSStartedFrame):
             await self._bot_started_speaking()
-            await self._internal_push_frame(frame)
+            await self.push_frame(frame)
         elif isinstance(frame, TTSStoppedFrame):
             await self._bot_stopped_speaking()
-            await self._internal_push_frame(frame)
+            await self.push_frame(frame)
         else:
-            await self._internal_push_frame(frame)
+            await self.push_frame(frame)
 
     async def _sink_task_handler(self):
         running = True
@@ -261,7 +249,7 @@ class BaseOutputTransport(FrameProcessor):
         # TODO(aleix): For now we just process TextFrame. But we should process
         # audio and video as well.
         if isinstance(frame, TextFrame):
-            await self._internal_push_frame(frame)
+            await self.push_frame(frame)
 
     async def _sink_clock_task_handler(self):
         running = True
@@ -293,38 +281,12 @@ class BaseOutputTransport(FrameProcessor):
     async def _bot_started_speaking(self):
         logger.debug("Bot started speaking")
         self._bot_speaking = True
-        await self._internal_push_frame(BotStartedSpeakingFrame(), FrameDirection.UPSTREAM)
+        await self.push_frame(BotStartedSpeakingFrame(), FrameDirection.UPSTREAM)
 
     async def _bot_stopped_speaking(self):
         logger.debug("Bot stopped speaking")
         self._bot_speaking = False
-        await self._internal_push_frame(BotStoppedSpeakingFrame(), FrameDirection.UPSTREAM)
-
-    #
-    # Push frames task
-    #
-
-    def _create_push_task(self):
-        loop = self.get_event_loop()
-        self._push_queue = asyncio.Queue()
-        self._push_frame_task = loop.create_task(self._push_frame_task_handler())
-
-    async def _internal_push_frame(
-            self,
-            frame: Frame | None,
-            direction: FrameDirection | None = FrameDirection.DOWNSTREAM):
-        await self._push_queue.put((frame, direction))
-
-    async def _push_frame_task_handler(self):
-        running = True
-        while running:
-            try:
-                (frame, direction) = await self._push_queue.get()
-                await self.push_frame(frame, direction)
-                running = not isinstance(frame, EndFrame)
-                self._push_queue.task_done()
-            except asyncio.CancelledError:
-                break
+        await self.push_frame(BotStoppedSpeakingFrame(), FrameDirection.UPSTREAM)
 
     #
     # Camera out
@@ -408,7 +370,7 @@ class BaseOutputTransport(FrameProcessor):
             try:
                 frame = await self._audio_out_queue.get()
                 await self.write_raw_audio_frames(frame.audio)
-                await self._internal_push_frame(frame)
+                await self.push_frame(frame)
                 await self.push_frame(BotSpeakingFrame(), FrameDirection.UPSTREAM)
             except asyncio.CancelledError:
                 break
diff --git a/src/pipecat/transports/network/websocket_server.py b/src/pipecat/transports/network/websocket_server.py
index 08ca9719a..819950d72 100644
--- a/src/pipecat/transports/network/websocket_server.py
+++ b/src/pipecat/transports/network/websocket_server.py
@@ -98,9 +98,9 @@ class WebsocketServerInputTransport(BaseInputTransport):
                 continue
 
             if isinstance(frame, AudioRawFrame):
-                await self.push_audio_frame(frame)
+                await self.queue_audio_frame(frame)
             else:
-                await self._internal_push_frame(frame)
+                await self.push_frame(frame)
 
         # Notify disconnection
         await self._callbacks.on_client_disconnected(websocket)
diff --git a/src/pipecat/transports/services/daily.py b/src/pipecat/transports/services/daily.py
index 7cf330b9e..210cc7341 100644
--- a/src/pipecat/transports/services/daily.py
+++ b/src/pipecat/transports/services/daily.py
@@ -625,11 +625,11 @@ class DailyInputTransport(BaseInputTransport):
     #
 
     async def push_transcription_frame(self, frame: TranscriptionFrame | InterimTranscriptionFrame):
-        await self._internal_push_frame(frame)
+        await self.push_frame(frame)
 
     async def push_app_message(self, message: Any, sender: str):
         frame = DailyTransportMessageFrame(message=message, participant_id=sender)
-        await self._internal_push_frame(frame)
+        await self.push_frame(frame)
 
     #
     # Audio in
@@ -692,7 +692,7 @@ class DailyInputTransport(BaseInputTransport):
                 image=buffer,
                 size=size,
                 format=format)
-            await self._internal_push_frame(frame)
+            await self.push_frame(frame)
 
         self._video_renderers[participant_id]["timestamp"] = curr_time
 

From 0ed3d118d6cfbafe513f5f5dba5441e8ef245615 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Sun, 1 Sep 2024 15:10:08 -0700
Subject: [PATCH 025/135] services(moondream); update revision to 2024-08-26

---
 CHANGELOG.md                      | 2 ++
 src/pipecat/services/moondream.py | 2 +-
 2 files changed, 3 insertions(+), 1 deletion(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index a757c7ffd..f2618edab 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -40,6 +40,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Changed
 
+- Updated `MoondreamService` revision to `2024-08-26`.
+
 - `CartesiaTTSService` and `ElevenLabsTTSService` now add presentation
   timestamps to their text output. This allows the output transport to push the
   text frames downstream at almost the same time the words are spoken. We say
diff --git a/src/pipecat/services/moondream.py b/src/pipecat/services/moondream.py
index cff8d3172..10ac3353e 100644
--- a/src/pipecat/services/moondream.py
+++ b/src/pipecat/services/moondream.py
@@ -48,7 +48,7 @@ class MoondreamService(VisionService):
         self,
             *,
         model="vikhyatk/moondream2",
-        revision="2024-04-02",
+        revision="2024-08-26",
         use_cpu=False
     ):
         super().__init__()

From 23d6eed5ea92dfa3bed2ecb58f21b1a10281a9c5 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Wed, 18 Sep 2024 22:34:24 -0700
Subject: [PATCH 026/135] transports: input()/output() return subclass instead
 of base class

---
 src/pipecat/transports/local/tk.py                  | 4 ++--
 src/pipecat/transports/network/fastapi_websocket.py | 4 ++--
 src/pipecat/transports/network/websocket_server.py  | 4 ++--
 src/pipecat/transports/services/daily.py            | 4 ++--
 4 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/src/pipecat/transports/local/tk.py b/src/pipecat/transports/local/tk.py
index 588e7d2ae..e7dc04902 100644
--- a/src/pipecat/transports/local/tk.py
+++ b/src/pipecat/transports/local/tk.py
@@ -141,12 +141,12 @@ class TkLocalTransport(BaseTransport):
     # BaseTransport
     #
 
-    def input(self) -> FrameProcessor:
+    def input(self) -> TkInputTransport:
         if not self._input:
             self._input = TkInputTransport(self._pyaudio, self._params)
         return self._input
 
-    def output(self) -> FrameProcessor:
+    def output(self) -> TkOutputTransport:
         if not self._output:
             self._output = TkOutputTransport(self._tk_root, self._pyaudio, self._params)
         return self._output
diff --git a/src/pipecat/transports/network/fastapi_websocket.py b/src/pipecat/transports/network/fastapi_websocket.py
index 2c4bd187b..7169c73bd 100644
--- a/src/pipecat/transports/network/fastapi_websocket.py
+++ b/src/pipecat/transports/network/fastapi_websocket.py
@@ -164,10 +164,10 @@ class FastAPIWebsocketTransport(BaseTransport):
         self._register_event_handler("on_client_connected")
         self._register_event_handler("on_client_disconnected")
 
-    def input(self) -> FrameProcessor:
+    def input(self) -> FastAPIWebsocketInputTransport:
         return self._input
 
-    def output(self) -> FrameProcessor:
+    def output(self) -> FastAPIWebsocketOutputTransport:
         return self._output
 
     async def _on_client_connected(self, websocket):
diff --git a/src/pipecat/transports/network/websocket_server.py b/src/pipecat/transports/network/websocket_server.py
index 819950d72..c17818898 100644
--- a/src/pipecat/transports/network/websocket_server.py
+++ b/src/pipecat/transports/network/websocket_server.py
@@ -190,13 +190,13 @@ class WebsocketServerTransport(BaseTransport):
         self._register_event_handler("on_client_connected")
         self._register_event_handler("on_client_disconnected")
 
-    def input(self) -> FrameProcessor:
+    def input(self) -> WebsocketServerInputTransport:
         if not self._input:
             self._input = WebsocketServerInputTransport(
                 self._host, self._port, self._params, self._callbacks, name=self._input_name)
         return self._input
 
-    def output(self) -> FrameProcessor:
+    def output(self) -> WebsocketServerOutputTransport:
         if not self._output:
             self._output = WebsocketServerOutputTransport(self._params, name=self._output_name)
         return self._output
diff --git a/src/pipecat/transports/services/daily.py b/src/pipecat/transports/services/daily.py
index 210cc7341..2a45adf36 100644
--- a/src/pipecat/transports/services/daily.py
+++ b/src/pipecat/transports/services/daily.py
@@ -811,12 +811,12 @@ class DailyTransport(BaseTransport):
     # BaseTransport
     #
 
-    def input(self) -> FrameProcessor:
+    def input(self) -> DailyInputTransport:
         if not self._input:
             self._input = DailyInputTransport(self._client, self._params, name=self._input_name)
         return self._input
 
-    def output(self) -> FrameProcessor:
+    def output(self) -> DailyOutputTransport:
         if not self._output:
             self._output = DailyOutputTransport(self._client, self._params, name=self._output_name)
         return self._output

From f078d156de65f674effa7df8418c168c00a288cf Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Wed, 18 Sep 2024 22:36:59 -0700
Subject: [PATCH 027/135] frames: StartFrame is now a SystemFrame

---
 CHANGELOG.md                                  |  4 ++++
 src/pipecat/frames/frames.py                  | 20 +++++++++----------
 src/pipecat/processors/frameworks/rtvi.py     | 12 +++++------
 .../processors/gstreamer/pipeline_source.py   | 12 +++++------
 src/pipecat/transports/base_input.py          | 12 +++++------
 src/pipecat/transports/base_output.py         | 10 ++++++----
 6 files changed, 38 insertions(+), 32 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index f2618edab..e1c6bbadc 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -40,6 +40,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Changed
 
+- `StartFrame` is back a system frame so we make sure it's processed immediately
+  by all processors. `EndFrame` stays a control frame since it needs to be
+  ordered allowing the frames in the pipeline to be processed.
+
 - Updated `MoondreamService` revision to `2024-08-26`.
 
 - `CartesiaTTSService` and `ElevenLabsTTSService` now add presentation
diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py
index 51770dff1..a400d68d9 100644
--- a/src/pipecat/frames/frames.py
+++ b/src/pipecat/frames/frames.py
@@ -248,6 +248,16 @@ class SystemFrame(Frame):
     pass
 
 
+@dataclass
+class StartFrame(SystemFrame):
+    """This is the first frame that should be pushed down a pipeline."""
+    clock: BaseClock
+    allow_interruptions: bool = False
+    enable_metrics: bool = False
+    enable_usage_metrics: bool = False
+    report_only_initial_ttfb: bool = False
+
+
 @dataclass
 class CancelFrame(SystemFrame):
     """Indicates that a pipeline needs to stop right away."""
@@ -338,16 +348,6 @@ class ControlFrame(Frame):
     pass
 
 
-@dataclass
-class StartFrame(ControlFrame):
-    """This is the first frame that should be pushed down a pipeline."""
-    clock: BaseClock
-    allow_interruptions: bool = False
-    enable_metrics: bool = False
-    enable_usage_metrics: bool = False
-    report_only_initial_ttfb: bool = False
-
-
 @dataclass
 class EndFrame(ControlFrame):
     """Indicates that a pipeline has ended and frame processors and pipelines
diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py
index d32f0f640..66adb9ad0 100644
--- a/src/pipecat/processors/frameworks/rtvi.py
+++ b/src/pipecat/processors/frameworks/rtvi.py
@@ -337,7 +337,12 @@ class RTVIProcessor(FrameProcessor):
         await super().process_frame(frame, direction)
 
         # Specific system frames
-        if isinstance(frame, CancelFrame):
+        if isinstance(frame, StartFrame):
+            # Push StartFrame before start(), because we want StartFrame to be
+            # processed by every processor before any other frame is processed.
+            await self.push_frame(frame, direction)
+            await self._start(frame)
+        elif isinstance(frame, CancelFrame):
             await self._cancel(frame)
             await self.push_frame(frame, direction)
         elif isinstance(frame, ErrorFrame):
@@ -347,11 +352,6 @@ class RTVIProcessor(FrameProcessor):
         elif isinstance(frame, SystemFrame):
             await self.push_frame(frame, direction)
         # Control frames
-        elif isinstance(frame, StartFrame):
-            # Push StartFrame before start(), because we want StartFrame to be
-            # processed by every processor before any other frame is processed.
-            await self.push_frame(frame, direction)
-            await self._start(frame)
         elif isinstance(frame, EndFrame):
             # Push EndFrame before stop(), because stop() waits on the task to
             # finish and the task finishes when EndFrame is processed.
diff --git a/src/pipecat/processors/gstreamer/pipeline_source.py b/src/pipecat/processors/gstreamer/pipeline_source.py
index 5f0ee089b..8d46105a7 100644
--- a/src/pipecat/processors/gstreamer/pipeline_source.py
+++ b/src/pipecat/processors/gstreamer/pipeline_source.py
@@ -66,18 +66,18 @@ class GStreamerPipelineSource(FrameProcessor):
         await super().process_frame(frame, direction)
 
         # Specific system frames
-        if isinstance(frame, CancelFrame):
+        if isinstance(frame, StartFrame):
+            # Push StartFrame before start(), because we want StartFrame to be
+            # processed by every processor before any other frame is processed.
+            await self.push_frame(frame, direction)
+            await self._start(frame)
+        elif isinstance(frame, CancelFrame):
             await self._cancel(frame)
             await self.push_frame(frame, direction)
         # All other system frames
         elif isinstance(frame, SystemFrame):
             await self.push_frame(frame, direction)
         # Control frames
-        elif isinstance(frame, StartFrame):
-            # Push StartFrame before start(), because we want StartFrame to be
-            # processed by every processor before any other frame is processed.
-            await self.push_frame(frame, direction)
-            await self._start(frame)
         elif isinstance(frame, EndFrame):
             # Push EndFrame before stop(), because stop() waits on the task to
             # finish and the task finishes when EndFrame is processed.
diff --git a/src/pipecat/transports/base_input.py b/src/pipecat/transports/base_input.py
index 8836fbd1e..de1ec8884 100644
--- a/src/pipecat/transports/base_input.py
+++ b/src/pipecat/transports/base_input.py
@@ -71,7 +71,12 @@ class BaseInputTransport(FrameProcessor):
         await super().process_frame(frame, direction)
 
         # Specific system frames
-        if isinstance(frame, CancelFrame):
+        if isinstance(frame, StartFrame):
+            # Push StartFrame before start(), because we want StartFrame to be
+            # processed by every processor before any other frame is processed.
+            await self.push_frame(frame, direction)
+            await self.start(frame)
+        elif isinstance(frame, CancelFrame):
             await self.cancel(frame)
             await self.push_frame(frame, direction)
         elif isinstance(frame, BotInterruptionFrame):
@@ -81,11 +86,6 @@ class BaseInputTransport(FrameProcessor):
         elif isinstance(frame, SystemFrame):
             await self.push_frame(frame, direction)
         # Control frames
-        elif isinstance(frame, StartFrame):
-            # Push StartFrame before start(), because we want StartFrame to be
-            # processed by every processor before any other frame is processed.
-            await self.push_frame(frame, direction)
-            await self.start(frame)
         elif isinstance(frame, EndFrame):
             # Push EndFrame before stop(), because stop() waits on the task to
             # finish and the task finishes when EndFrame is processed.
diff --git a/src/pipecat/transports/base_output.py b/src/pipecat/transports/base_output.py
index bc683721a..461f0567d 100644
--- a/src/pipecat/transports/base_output.py
+++ b/src/pipecat/transports/base_output.py
@@ -129,7 +129,12 @@ class BaseOutputTransport(FrameProcessor):
         # immediately. Other frames require order so they are put in the sink
         # queue.
         #
-        if isinstance(frame, CancelFrame):
+        if isinstance(frame, StartFrame):
+            # Push StartFrame before start(), because we want StartFrame to be
+            # processed by every processor before any other frame is processed.
+            await self.push_frame(frame, direction)
+            await self.start(frame)
+        elif isinstance(frame, CancelFrame):
             await self.cancel(frame)
             await self.push_frame(frame, direction)
         elif isinstance(frame, StartInterruptionFrame) or isinstance(frame, StopInterruptionFrame):
@@ -141,9 +146,6 @@ class BaseOutputTransport(FrameProcessor):
         elif isinstance(frame, SystemFrame):
             await self.push_frame(frame, direction)
         # Control frames.
-        elif isinstance(frame, StartFrame):
-            await self._sink_queue.put(frame)
-            await self.start(frame)
         elif isinstance(frame, EndFrame):
             await self._sink_clock_queue.put((sys.maxsize, frame.id, frame))
             await self._sink_queue.put(frame)

From fbf6eef68ff5c723d7a24a4e57f014a253f52af4 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Wed, 18 Sep 2024 22:40:52 -0700
Subject: [PATCH 028/135] transports(base_output): wait for sink tasks before
 canceling audio/video tasks

---
 CHANGELOG.md                          |  4 ++++
 src/pipecat/transports/base_output.py | 31 ++++++++++++++++++---------
 2 files changed, 25 insertions(+), 10 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index e1c6bbadc..2d9fcadaf 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -66,6 +66,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Fixed
 
+- Fixed a `BaseOutputTransport` issue that would stop audio and video rendering
+  tasks (after receiving and `EndFrame`) before the internal queue was emptied,
+  causing the pipeline to finish prematurely.
+
 - `StartFrame` should be the first frame every processor receives to avoid
   situations where things are not initialized (because initialization happens on
   `StartFrame`) and other frames come in resulting in undesired behavior.
diff --git a/src/pipecat/transports/base_output.py b/src/pipecat/transports/base_output.py
index 461f0567d..9b1b9c29e 100644
--- a/src/pipecat/transports/base_output.py
+++ b/src/pipecat/transports/base_output.py
@@ -81,6 +81,13 @@ class BaseOutputTransport(FrameProcessor):
             self._audio_out_task = self.get_event_loop().create_task(self._audio_out_task_handler())
 
     async def stop(self, frame: EndFrame):
+        # At this point we have enqueued an EndFrame and we need to wait for
+        # that EndFrame to be processed by the sink tasks. We also need to wait
+        # for these tasks before cancelling the camera and audio tasks below
+        # because they might be still rendering.
+        await self._sink_task
+        await self._sink_clock_task
+
         # Cancel and wait for the camera output task to finish.
         if self._params.camera_out_enabled:
             self._camera_out_task.cancel()
@@ -91,19 +98,23 @@ class BaseOutputTransport(FrameProcessor):
             self._audio_out_task.cancel()
             await self._audio_out_task
 
-        # Wait for the sink task to finish. They will finish when the EndFrame
-        # is actually processed.
-        await self._sink_task
-
     async def cancel(self, frame: CancelFrame):
-        # Cancel all the tasks and wait for them to finish.
+        # Since we are cancelling everything it doesn't matter if we cancel sink
+        # tasks first or not.
+        self._sink_task.cancel()
+        self._sink_clock_task.cancel()
+        await self._sink_task
+        await self._sink_clock_task
 
+        # Cancel and wait for the camera output task to finish.
         if self._params.camera_out_enabled:
             self._camera_out_task.cancel()
             await self._camera_out_task
 
-        self._sink_task.cancel()
-        await self._sink_task
+        # Cancel and wait for the audio output task to finish.
+        if self._params.audio_out_enabled and self._params.audio_out_is_live:
+            self._audio_out_task.cancel()
+            await self._audio_out_task
 
     async def send_message(self, frame: TransportMessageFrame):
         pass
@@ -259,7 +270,7 @@ class BaseOutputTransport(FrameProcessor):
             try:
                 timestamp, _, frame = await self._sink_clock_queue.get()
 
-                # If we hit an EndFrame, we cna finish right away.
+                # If we hit an EndFrame, we can finish right away.
                 running = not isinstance(frame, EndFrame)
 
                 # If we have a frame we check it's presentation timestamp. If it
@@ -327,9 +338,9 @@ class BaseOutputTransport(FrameProcessor):
                 elif self._camera_images:
                     image = next(self._camera_images)
                     await self._draw_image(image)
-                    await asyncio.sleep(1.0 / self._params.camera_out_framerate)
+                    await asyncio.sleep(self._camera_out_frame_duration)
                 else:
-                    await asyncio.sleep(1.0 / self._params.camera_out_framerate)
+                    await asyncio.sleep(self._camera_out_frame_duration)
             except asyncio.CancelledError:
                 break
             except Exception as e:

From 8224538372d192d677313e3229a115ac86b56fc1 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Wed, 18 Sep 2024 22:46:13 -0700
Subject: [PATCH 029/135] services(cartesia): added CartesiaHttpTTSService

---
 CHANGELOG.md                     |  4 ++
 pyproject.toml                   |  2 +-
 src/pipecat/services/cartesia.py | 88 ++++++++++++++++++++++++++++++--
 3 files changed, 89 insertions(+), 5 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 2d9fcadaf..752666c07 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,6 +9,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 
+- Added `CartesiaHttpTTSService`. This is a synchronous frame processor
+  (i.e. given an input text frame it will wait for the whole output before
+  returning).
+
 - A clock can now be specified to `PipelineTask` (defaults to
   `SystemClock`). This clock will be passed to each frame processor via the
   `StartFrame`.
diff --git a/pyproject.toml b/pyproject.toml
index 8a1e3a800..170ecd326 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -36,7 +36,7 @@ Website = "https://pipecat.ai"
 [project.optional-dependencies]
 anthropic = [ "anthropic~=0.34.0" ]
 azure = [ "azure-cognitiveservices-speech~=1.40.0" ]
-cartesia = [ "websockets~=12.0" ]
+cartesia = [ "cartesia~=1.0.13", "websockets~=12.0" ]
 daily = [ "daily-python~=0.10.1" ]
 deepgram = [ "deepgram-sdk~=3.5.0" ]
 elevenlabs = [ "websockets~=12.0" ]
diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index ea790fab7..078926235 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -8,7 +8,6 @@ import json
 import uuid
 import base64
 import asyncio
-import time
 
 from typing import AsyncGenerator
 
@@ -22,17 +21,17 @@ from pipecat.frames.frames import (
     EndFrame,
     TTSStartedFrame,
     TTSStoppedFrame,
-    TextFrame,
     LLMFullResponseEndFrame
 )
 from pipecat.processors.frame_processor import FrameDirection
 from pipecat.transcriptions.language import Language
-from pipecat.services.ai_services import AsyncWordTTSService
+from pipecat.services.ai_services import AsyncWordTTSService, TTSService
 
 from loguru import logger
 
 # See .env.example for Cartesia configuration needed
 try:
+    from cartesia import AsyncCartesia
     import websockets
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
@@ -165,7 +164,7 @@ class CartesiaTTSService(AsyncWordTTSService):
     async def flush_audio(self):
         if not self._context_id or not self._websocket:
             return
-        logger.debug("Flushing audio")
+        logger.trace("Flushing audio")
         msg = {
             "transcript": "",
             "continue": False,
@@ -257,3 +256,84 @@ class CartesiaTTSService(AsyncWordTTSService):
             yield None
         except Exception as e:
             logger.error(f"{self} exception: {e}")
+
+
+class CartesiaHttpTTSService(TTSService):
+
+    def __init__(
+            self,
+            *,
+            api_key: str,
+            voice_id: str,
+            model_id: str = "sonic-english",
+            base_url: str = "https://api.cartesia.ai",
+            encoding: str = "pcm_s16le",
+            sample_rate: int = 16000,
+            language: str = "en",
+            **kwargs):
+        super().__init__(**kwargs)
+
+        self._api_key = api_key
+        self._voice_id = voice_id
+        self._model_id = model_id
+        self._output_format = {
+            "container": "raw",
+            "encoding": encoding,
+            "sample_rate": sample_rate,
+        }
+        self._language = language
+
+        self._client = AsyncCartesia(api_key=api_key, base_url=base_url)
+
+    def can_generate_metrics(self) -> bool:
+        return True
+
+    async def set_model(self, model: str):
+        logger.debug(f"Switching TTS model to: [{model}]")
+        self._model_id = model
+
+    async def set_voice(self, voice: str):
+        logger.debug(f"Switching TTS voice to: [{voice}]")
+        self._voice_id = voice
+
+    async def set_language(self, language: Language):
+        logger.debug(f"Switching TTS language to: [{language}]")
+        self._language = language_to_cartesia_language(language)
+
+    async def stop(self, frame: EndFrame):
+        await super().stop(frame)
+        await self._client.close()
+
+    async def cancel(self, frame: CancelFrame):
+        await super().cancel(frame)
+        await self._client.close()
+
+    async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
+        logger.debug(f"Generating TTS: [{text}]")
+
+        await self.push_frame(TTSStartedFrame())
+        await self.start_ttfb_metrics()
+
+        try:
+            output = await self._client.tts.sse(
+                model_id=self._model_id,
+                transcript=text,
+                voice_id=self._voice_id,
+                output_format=self._output_format,
+                language=self._language,
+                stream=False
+            )
+
+            await self.stop_ttfb_metrics()
+
+            frame = AudioRawFrame(
+                audio=output["audio"],
+                sample_rate=self._output_format["sample_rate"],
+                num_channels=1
+            )
+            yield frame
+        except Exception as e:
+            logger.error(f"{self} exception: {e}")
+
+        await self.start_tts_usage_metrics(text)
+        await self.push_frame(TTSStoppedFrame())

From 0e8f56c7525a7abc13949b4bb35dea3bd8a88d04 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Wed, 18 Sep 2024 22:47:17 -0700
Subject: [PATCH 030/135] services: move TTSService push_stop_frames to
 AsyncTTSService

---
 src/pipecat/services/ai_services.py | 42 ++++++++++++++++-------------
 1 file changed, 23 insertions(+), 19 deletions(-)

diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index d7226dba3..b63188512 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -140,21 +140,15 @@ class TTSService(AIService):
             self,
             *,
             aggregate_sentences: bool = True,
-            # if True, subclass is responsible for pushing TextFrames and LLMFullResponseEndFrames
+            # if True, TTSService will push TextFrames and LLMFullResponseEndFrames,
+            # otherwise subclass must do it
             push_text_frames: bool = True,
-            # if True, TTSService will push TTSStoppedFrames, otherwise subclass must do it
-            push_stop_frames: bool = False,
-            # if push_stop_frames is True, wait for this idle period before pushing TTSStoppedFrame
-            stop_frame_timeout_s: float = 1.0,
+            # TTS output sample rate
             sample_rate: int = 16000,
             **kwargs):
         super().__init__(**kwargs)
         self._aggregate_sentences: bool = aggregate_sentences
         self._push_text_frames: bool = push_text_frames
-        self._push_stop_frames: bool = push_stop_frames
-        self._stop_frame_timeout_s: float = stop_frame_timeout_s
-        self._stop_frame_task: Optional[asyncio.Task] = None
-        self._stop_frame_queue: asyncio.Queue = asyncio.Queue()
         self._current_sentence: str = ""
         self._sample_rate: int = sample_rate
 
@@ -199,7 +193,7 @@ class TTSService(AIService):
         if text:
             await self._push_tts_frames(text)
 
-    async def _push_tts_frames(self, text: str, text_passthrough: bool = True):
+    async def _push_tts_frames(self, text: str):
         text = text.strip()
         if not text:
             return
@@ -239,6 +233,25 @@ class TTSService(AIService):
         else:
             await self.push_frame(frame, direction)
 
+
+class AsyncTTSService(TTSService):
+    def __init__(
+            self,
+            # if True, TTSService will push TTSStoppedFrames, otherwise subclass must do it
+            push_stop_frames: bool = False,
+            # if push_stop_frames is True, wait for this idle period before pushing TTSStoppedFrame
+            stop_frame_timeout_s: float = 1.0,
+            **kwargs):
+        super().__init__(sync=False, **kwargs)
+        self._push_stop_frames: bool = push_stop_frames
+        self._stop_frame_timeout_s: float = stop_frame_timeout_s
+        self._stop_frame_task: Optional[asyncio.Task] = None
+        self._stop_frame_queue: asyncio.Queue = asyncio.Queue()
+
+    @abstractmethod
+    async def flush_audio(self):
+        pass
+
     async def start(self, frame: StartFrame):
         await super().start(frame)
         if self._push_stop_frames:
@@ -287,15 +300,6 @@ class TTSService(AIService):
             pass
 
 
-class AsyncTTSService(TTSService):
-    def __init__(self, **kwargs):
-        super().__init__(**kwargs)
-
-    @abstractmethod
-    async def flush_audio(self):
-        pass
-
-
 class AsyncWordTTSService(AsyncTTSService):
     def __init__(self, **kwargs):
         super().__init__(**kwargs)

From 3298f935ef5de51a9b701706535340577f7f5eec Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Wed, 18 Sep 2024 22:48:06 -0700
Subject: [PATCH 031/135] services(fal,moondream): add missing **kwargs

---
 src/pipecat/services/fal.py       | 3 ++-
 src/pipecat/services/moondream.py | 7 ++++---
 2 files changed, 6 insertions(+), 4 deletions(-)

diff --git a/src/pipecat/services/fal.py b/src/pipecat/services/fal.py
index 4d99f6066..672135d02 100644
--- a/src/pipecat/services/fal.py
+++ b/src/pipecat/services/fal.py
@@ -43,8 +43,9 @@ class FalImageGenService(ImageGenService):
         aiohttp_session: aiohttp.ClientSession,
         model: str = "fal-ai/fast-sdxl",
         key: str | None = None,
+        **kwargs
     ):
-        super().__init__()
+        super().__init__(**kwargs)
         self._model = model
         self._params = params
         self._aiohttp_session = aiohttp_session
diff --git a/src/pipecat/services/moondream.py b/src/pipecat/services/moondream.py
index 10ac3353e..3441aeeb9 100644
--- a/src/pipecat/services/moondream.py
+++ b/src/pipecat/services/moondream.py
@@ -46,12 +46,13 @@ def detect_device():
 class MoondreamService(VisionService):
     def __init__(
         self,
-            *,
+        *,
         model="vikhyatk/moondream2",
         revision="2024-08-26",
-        use_cpu=False
+        use_cpu=False,
+        **kwargs
     ):
-        super().__init__()
+        super().__init__(**kwargs)
 
         if not use_cpu:
             device, dtype = detect_device()

From 62e9a33a70ef504d557e19ad3cf88ca07ec84fde Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Wed, 18 Sep 2024 22:51:00 -0700
Subject: [PATCH 032/135] examples: use CartesiaHttpTTSService to synchronize
 frames

---
 examples/foundational/01-say-one-thing.py      | 8 ++++----
 examples/foundational/02-llm-say-one-thing.py  | 8 ++++----
 examples/foundational/06-listen-and-respond.py | 5 -----
 examples/foundational/06a-image-sync.py        | 8 ++++----
 examples/foundational/11-sound-effects.py      | 8 ++++----
 5 files changed, 16 insertions(+), 21 deletions(-)

diff --git a/examples/foundational/01-say-one-thing.py b/examples/foundational/01-say-one-thing.py
index 8102518f7..fce774822 100644
--- a/examples/foundational/01-say-one-thing.py
+++ b/examples/foundational/01-say-one-thing.py
@@ -9,11 +9,11 @@ import aiohttp
 import os
 import sys
 
-from pipecat.frames.frames import TextFrame
+from pipecat.frames.frames import EndFrame, TextFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.task import PipelineTask
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.services.cartesia import CartesiaTTSService
+from pipecat.services.cartesia import CartesiaHttpTTSService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 
 from runner import configure
@@ -34,7 +34,7 @@ async def main():
         transport = DailyTransport(
             room_url, None, "Say One Thing", DailyParams(audio_out_enabled=True))
 
-        tts = CartesiaTTSService(
+        tts = CartesiaHttpTTSService(
             api_key=os.getenv("CARTESIA_API_KEY"),
             voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
         )
@@ -48,7 +48,7 @@ async def main():
         @transport.event_handler("on_participant_joined")
         async def on_new_participant_joined(transport, participant):
             participant_name = participant["info"]["userName"] or ''
-            await task.queue_frame(TextFrame(f"Hello there, {participant_name}!"))
+            await task.queue_frames([TextFrame(f"Hello there, {participant_name}!"), EndFrame()])
 
         await runner.run(task)
 
diff --git a/examples/foundational/02-llm-say-one-thing.py b/examples/foundational/02-llm-say-one-thing.py
index e53aee9ae..00a1e9e51 100644
--- a/examples/foundational/02-llm-say-one-thing.py
+++ b/examples/foundational/02-llm-say-one-thing.py
@@ -9,11 +9,11 @@ import aiohttp
 import os
 import sys
 
-from pipecat.frames.frames import LLMMessagesFrame
+from pipecat.frames.frames import EndFrame, LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
-from pipecat.services.cartesia import CartesiaTTSService
+from pipecat.services.cartesia import CartesiaHttpTTSService
 from pipecat.services.openai import OpenAILLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 
@@ -38,7 +38,7 @@ async def main():
             "Say One Thing From an LLM",
             DailyParams(audio_out_enabled=True))
 
-        tts = CartesiaTTSService(
+        tts = CartesiaHttpTTSService(
             api_key=os.getenv("CARTESIA_API_KEY"),
             voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
         )
@@ -59,7 +59,7 @@ async def main():
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
-            await task.queue_frame(LLMMessagesFrame(messages))
+            await task.queue_frames([LLMMessagesFrame(messages), EndFrame()])
 
         await runner.run(task)
 
diff --git a/examples/foundational/06-listen-and-respond.py b/examples/foundational/06-listen-and-respond.py
index 35965185f..e99a95068 100644
--- a/examples/foundational/06-listen-and-respond.py
+++ b/examples/foundational/06-listen-and-respond.py
@@ -90,11 +90,6 @@ async def main():
         ])
 
         task = PipelineTask(pipeline)
-        task = PipelineTask(pipeline, PipelineParams(
-            allow_interruptions=True,
-            enable_metrics=True,
-            report_only_initial_ttfb=False,
-        ))
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
diff --git a/examples/foundational/06a-image-sync.py b/examples/foundational/06a-image-sync.py
index 812dab137..6b3e58cf7 100644
--- a/examples/foundational/06a-image-sync.py
+++ b/examples/foundational/06a-image-sync.py
@@ -20,8 +20,8 @@ from pipecat.processors.aggregators.llm_response import (
     LLMUserResponseAggregator,
 )
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
+from pipecat.services.cartesia import CartesiaHttpTTSService
 from pipecat.services.openai import OpenAILLMService
-from pipecat.services.elevenlabs import ElevenLabsTTSService
 from pipecat.transports.services.daily import DailyTransport
 from pipecat.vad.silero import SileroVADAnalyzer
 
@@ -78,9 +78,9 @@ async def main():
             )
         )
 
-        tts = ElevenLabsTTSService(
-            api_key=os.getenv("ELEVENLABS_API_KEY"),
-            voice_id=os.getenv("ELEVENLABS_VOICE_ID"),
+        tts = CartesiaHttpTTSService(
+            api_key=os.getenv("CARTESIA_API_KEY"),
+            voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
         )
 
         llm = OpenAILLMService(
diff --git a/examples/foundational/11-sound-effects.py b/examples/foundational/11-sound-effects.py
index 146b3bd09..9dc4dc99b 100644
--- a/examples/foundational/11-sound-effects.py
+++ b/examples/foundational/11-sound-effects.py
@@ -25,7 +25,7 @@ from pipecat.processors.aggregators.llm_response import (
 )
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.processors.logger import FrameLogger
-from pipecat.services.elevenlabs import ElevenLabsTTSService
+from pipecat.services.cartesia import CartesiaHttpTTSService
 from pipecat.services.openai import OpenAILLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 from pipecat.vad.silero import SileroVADAnalyzer
@@ -103,9 +103,9 @@ async def main():
             api_key=os.getenv("OPENAI_API_KEY"),
             model="gpt-4o")
 
-        tts = ElevenLabsTTSService(
-            api_key=os.getenv("ELEVENLABS_API_KEY"),
-            voice_id="ErXwobaYiN019PkySvjV",
+        tts = CartesiaHttpTTSService(
+            api_key=os.getenv("CARTESIA_API_KEY"),
+            voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
         )
 
         messages = [

From 4f1b06e6b2d731eb04934f68cc15723d07d681b1 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Wed, 18 Sep 2024 22:56:28 -0700
Subject: [PATCH 033/135] pipeline: renamed ParallelTask to
 SyncParallelPipeline

---
 CHANGELOG.md                                  |  8 ++++
 .../foundational/05-sync-speech-and-image.py  | 34 ++++++++---------
 .../05a-local-sync-speech-and-image.py        | 38 ++++++++++++-------
 ...llel_task.py => sync_parallel_pipeline.py} |  6 +--
 4 files changed, 51 insertions(+), 35 deletions(-)
 rename src/pipecat/pipeline/{parallel_task.py => sync_parallel_pipeline.py} (94%)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 752666c07..5d33b8257 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -44,6 +44,14 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Changed
 
+- `ParallelTask` has been renamed to `SyncParallelPipeline`. A
+  `SyncParallelPipeline` is a frame processor that contains a list of different
+  pipelines to be executed concurrently. The difference between a
+  `SyncParallelPipeline` and a `ParallelPipeline` is that, given an input frame,
+  the `SyncParallelPipeline` will wait for all the internal pipelines to
+  complete. This is achieved by ensuring all the processors in each of the
+  internal pipelines are synchronous.
+
 - `StartFrame` is back a system frame so we make sure it's processed immediately
   by all processors. `EndFrame` stays a control frame since it needs to be
   ordered allowing the frames in the pipeline to be processed.
diff --git a/examples/foundational/05-sync-speech-and-image.py b/examples/foundational/05-sync-speech-and-image.py
index ca3ff9557..07e54ab8a 100644
--- a/examples/foundational/05-sync-speech-and-image.py
+++ b/examples/foundational/05-sync-speech-and-image.py
@@ -14,21 +14,18 @@ from dataclasses import dataclass
 from pipecat.frames.frames import (
     AppFrame,
     Frame,
-    ImageRawFrame,
     LLMFullResponseStartFrame,
     LLMMessagesFrame,
     TextFrame
 )
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.sync_parallel_pipeline import SyncParallelPipeline
 from pipecat.pipeline.task import PipelineTask
-from pipecat.pipeline.parallel_task import ParallelTask
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
-from pipecat.processors.aggregators.gated import GatedAggregator
-from pipecat.processors.aggregators.llm_response import LLMFullResponseAggregator
 from pipecat.processors.aggregators.sentence import SentenceAggregator
+from pipecat.services.cartesia import CartesiaHttpTTSService
 from pipecat.services.openai import OpenAILLMService
-from pipecat.services.elevenlabs import ElevenLabsTTSService
 from pipecat.services.fal import FalImageGenService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 
@@ -88,9 +85,9 @@ async def main():
             )
         )
 
-        tts = ElevenLabsTTSService(
-            api_key=os.getenv("ELEVENLABS_API_KEY"),
-            voice_id=os.getenv("ELEVENLABS_VOICE_ID"),
+        tts = CartesiaHttpTTSService(
+            api_key=os.getenv("CARTESIA_API_KEY"),
+            voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
         )
 
         llm = OpenAILLMService(
@@ -105,24 +102,23 @@ async def main():
             key=os.getenv("FAL_KEY"),
         )
 
-        gated_aggregator = GatedAggregator(
-            gate_open_fn=lambda frame: isinstance(frame, ImageRawFrame),
-            gate_close_fn=lambda frame: isinstance(frame, LLMFullResponseStartFrame),
-            start_open=False
-        )
-
         sentence_aggregator = SentenceAggregator()
         month_prepender = MonthPrepender()
-        llm_full_response_aggregator = LLMFullResponseAggregator()
 
+        # With `SyncParallelPipeline` we synchronize audio and images by pushing
+        # them basically in order (e.g. I1 A1 A1 A1 I2 A2 A2 A2 A2 I3 A3). To do
+        # that, each pipeline runs concurrently and `SyncParallelPipeline` will
+        # wait for the input frame to be processed.
+        #
+        # Note that `SyncParallelPipeline` requires all processors in it to be
+        # synchronous (which is the default for most processors).
         pipeline = Pipeline([
             llm,                     # LLM
             sentence_aggregator,     # Aggregates LLM output into full sentences
-            ParallelTask(            # Run pipelines in parallel aggregating the result
-                [month_prepender, tts],                   # Create "Month: sentence" and output audio
-                [llm_full_response_aggregator, imagegen]  # Aggregate full LLM response
+            SyncParallelPipeline(    # Run pipelines in parallel aggregating the result
+                [month_prepender, tts],  # Create "Month: sentence" and output audio
+                [imagegen]               # Generate image
             ),
-            gated_aggregator,        # Queues everything until an image is available
             transport.output()       # Transport output
         ])
 
diff --git a/examples/foundational/05a-local-sync-speech-and-image.py b/examples/foundational/05a-local-sync-speech-and-image.py
index 63bcf1e9d..66a6e7f57 100644
--- a/examples/foundational/05a-local-sync-speech-and-image.py
+++ b/examples/foundational/05a-local-sync-speech-and-image.py
@@ -12,17 +12,17 @@ import sys
 import tkinter as tk
 
 from pipecat.frames.frames import AudioRawFrame, Frame, URLImageRawFrame, LLMMessagesFrame, TextFrame
-from pipecat.pipeline.parallel_pipeline import ParallelPipeline
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.sync_parallel_pipeline import SyncParallelPipeline
 from pipecat.pipeline.task import PipelineTask
-from pipecat.processors.aggregators.llm_response import LLMFullResponseAggregator
+from pipecat.processors.aggregators.sentence import SentenceAggregator
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
+from pipecat.services.cartesia import CartesiaHttpTTSService
 from pipecat.services.openai import OpenAILLMService
-from pipecat.services.elevenlabs import ElevenLabsTTSService
 from pipecat.services.fal import FalImageGenService
 from pipecat.transports.base_transport import TransportParams
-from pipecat.transports.local.tk import TkLocalTransport
+from pipecat.transports.local.tk import TkLocalTransport, TkOutputTransport
 
 from loguru import logger
 
@@ -60,6 +60,7 @@ async def main():
                 def __init__(self):
                     super().__init__()
                     self.audio = bytearray()
+                    self.frame = None
 
                 async def process_frame(self, frame: Frame, direction: FrameDirection):
                     await super().process_frame(frame, direction)
@@ -84,9 +85,10 @@ async def main():
                 api_key=os.getenv("OPENAI_API_KEY"),
                 model="gpt-4o")
 
-            tts = ElevenLabsTTSService(
-                api_key=os.getenv("ELEVENLABS_API_KEY"),
-                voice_id=os.getenv("ELEVENLABS_VOICE_ID"))
+            tts = CartesiaHttpTTSService(
+                api_key=os.getenv("CARTESIA_API_KEY"),
+                voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
+            )
 
             imagegen = FalImageGenService(
                 params=FalImageGenService.InputParams(
@@ -95,7 +97,7 @@ async def main():
                 aiohttp_session=session,
                 key=os.getenv("FAL_KEY"))
 
-            aggregator = LLMFullResponseAggregator()
+            sentence_aggregator = SentenceAggregator()
 
             description = ImageDescription()
 
@@ -103,12 +105,22 @@ async def main():
 
             image_grabber = ImageGrabber()
 
+            # With `SyncParallelPipeline` we synchronize audio and images by
+            # pushing them basically in order (e.g. I1 A1 A1 A1 I2 A2 A2 A2 A2
+            # I3 A3). To do that, each pipeline runs concurrently and
+            # `SyncParallelPipeline` will wait for the input frame to be
+            # processed.
+            #
+            # Note that `SyncParallelPipeline` requires all processors in it to
+            # be synchronous (which is the default for most processors).
             pipeline = Pipeline([
-                llm,
-                aggregator,
-                description,
-                ParallelPipeline([tts, audio_grabber],
-                                 [imagegen, image_grabber])
+                llm,                     # LLM
+                sentence_aggregator,     # Aggregates LLM output into full sentences
+                description,             # Store sentence
+                SyncParallelPipeline(
+                    [tts, audio_grabber],      # Generate and store audio for the given sentence
+                    [imagegen, image_grabber]  # Generate and storeimage for the given sentence
+                )
             ])
 
             task = PipelineTask(pipeline)
diff --git a/src/pipecat/pipeline/parallel_task.py b/src/pipecat/pipeline/sync_parallel_pipeline.py
similarity index 94%
rename from src/pipecat/pipeline/parallel_task.py
rename to src/pipecat/pipeline/sync_parallel_pipeline.py
index 724183b3b..d922134f4 100644
--- a/src/pipecat/pipeline/parallel_task.py
+++ b/src/pipecat/pipeline/sync_parallel_pipeline.py
@@ -49,12 +49,12 @@ class Sink(FrameProcessor):
                 await self._down_queue.put(frame)
 
 
-class ParallelTask(BasePipeline):
+class SyncParallelPipeline(BasePipeline):
     def __init__(self, *args):
         super().__init__()
 
         if len(args) == 0:
-            raise Exception(f"ParallelTask needs at least one argument")
+            raise Exception(f"SyncParallelPipeline needs at least one argument")
 
         self._sinks = []
         self._sources = []
@@ -66,7 +66,7 @@ class ParallelTask(BasePipeline):
         logger.debug(f"Creating {self} pipelines")
         for processors in args:
             if not isinstance(processors, list):
-                raise TypeError(f"ParallelTask argument {processors} is not a list")
+                raise TypeError(f"SyncParallelPipeline argument {processors} is not a list")
 
             # We add a source at the beginning of the pipeline and a sink at the end.
             source = Source(self._up_queue)

From 607a2465723ceab17e9e4b72f404b8acfba295d3 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Wed, 18 Sep 2024 23:08:22 -0700
Subject: [PATCH 034/135] updated CHANGELOG with sync/async frame processors

---
 CHANGELOG.md | 31 +++++++++++++++++++++++++------
 1 file changed, 25 insertions(+), 6 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 5d33b8257..985834aba 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,13 +9,24 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 
-- Added `CartesiaHttpTTSService`. This is a synchronous frame processor
-  (i.e. given an input text frame it will wait for the whole output before
-  returning).
+- Pipecat has a pipeline-based architecture. The pipeline consists of frame
+  processors linked to each other. The elements traveling across the pipeline
+  are called frames.
 
-- A clock can now be specified to `PipelineTask` (defaults to
-  `SystemClock`). This clock will be passed to each frame processor via the
-  `StartFrame`.
+  To have a deterministic behavior the frames traveling through the pipeline
+  should always be ordered, except system frames which are out-of-band
+  frames. To achieve that, each frame processor should only output frames from a
+  single task.
+
+  In this version we introduce synchronous and asynchronous frame
+  processors. The synchronous processors push output frames from the same task
+  that they receive input frames, and therefore only pushing frames from one
+  task. Asynchronous frame processors can have internal tasks to perform things
+  asynchronously (e.g. receiving data from a websocket) but they also have a
+  single task where they push frames from.
+
+  By default, frame processors are synchronous. To change a frame processor to
+  asynchronous you only need to pass `sync=False` to the base class constructor.
 
 - Added pipeline clocks. A pipeline clock is used by the output transport to
   know when a frame needs to be presented. For that, all frames now have an
@@ -23,6 +34,14 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   clock implementation `SystemClock` and the `pts` field is currently only used
   for `TextFrame`s (audio and image frames will be next).
 
+- A clock can now be specified to `PipelineTask` (defaults to
+  `SystemClock`). This clock will be passed to each frame processor via the
+  `StartFrame`.
+
+- Added `CartesiaHttpTTSService`. This is a synchronous frame processor
+  (i.e. given an input text frame it will wait for the whole output before
+  returning).
+
 - `DailyTransport` now supports setting the audio bitrate to improve audio
   quality through the `DailyParams.audio_out_bitrate` parameter. The new
   default is 96kbps.

From affbe9ac7d830f981489894408927955b6871568 Mon Sep 17 00:00:00 2001
From: Kwindla Hultman Kramer <kwindla@gmail.com>
Date: Thu, 19 Sep 2024 17:17:33 -0700
Subject: [PATCH 035/135] fix small issues that crept into main

---
 src/pipecat/services/ai_services.py | 2 +-
 src/pipecat/services/openai.py      | 3 +--
 2 files changed, 2 insertions(+), 3 deletions(-)

diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index b63188512..d91782e42 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -223,7 +223,7 @@ class TTSService(AIService):
             else:
                 await self.push_frame(frame, direction)
         elif isinstance(frame, TTSSpeakFrame):
-            await self._push_tts_frames(frame.text, False)
+            await self._push_tts_frames(frame.text)
         elif isinstance(frame, TTSModelUpdateFrame):
             await self.set_model(frame.model)
         elif isinstance(frame, TTSVoiceUpdateFrame):
diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py
index a03b350ba..d3f5fd280 100644
--- a/src/pipecat/services/openai.py
+++ b/src/pipecat/services/openai.py
@@ -193,8 +193,7 @@ class BaseOpenAILLMService(LLMService):
             if self.has_function(function_name):
                 await self._handle_function_call(context, tool_call_id, function_name, arguments)
             else:
-                raise OpenAIUnhandledFunctionException(f"The LLM tried to call a function named '{
-                    function_name}', but there isn't a callback registered for that function.")
+                raise OpenAIUnhandledFunctionException(f"The LLM tried to call a function named '{function_name}', but there isn't a callback registered for that function.")
 
     async def _handle_function_call(
             self,

From 50b45ac2da163f5763f24d9b90e3d9a952be039d Mon Sep 17 00:00:00 2001
From: mattie ruth backman <mattieruth@gmail.com>
Date: Thu, 19 Sep 2024 11:15:44 -0400
Subject: [PATCH 036/135] get the test infrastructure running again

disable broken tests for now
---
 .github/workflows/tests.yaml                  |  11 +-
 README.md                                     |   2 +-
 .../foundational/04-utterance-and-speech.py   |   4 +
 examples/foundational/08-bots-arguing.py      |  12 +-
 src/pipecat/frames/frames.py                  |   2 +-
 .../{ => to_be_updated}/merge_pipeline.py     |   2 +-
 src/pipecat/processors/aggregators/gated.py   |   9 +-
 .../processors/aggregators/sentence.py        |   3 +-
 .../processors/aggregators/user_response.py   |   2 +-
 .../aggregators/vision_image_frame.py         |   2 +-
 src/pipecat/services/openai.py                |   3 +-
 test-requirements.txt                         |  35 ++++
 tests/integration/integration_azure_llm.py    |  11 +-
 tests/integration/integration_ollama_llm.py   |  11 +-
 tests/test_aggregators.py                     |  51 ++---
 tests/test_daily_transport_service.py         |   1 +
 tests/test_openai_tts.py                      |   1 +
 tests/test_pipeline.py                        |  13 +-
 tests/test_protobuf_serializer.py             |   7 +-
 tests/test_websocket_transport.py             | 174 +++++++++---------
 20 files changed, 212 insertions(+), 144 deletions(-)
 rename src/pipecat/pipeline/{ => to_be_updated}/merge_pipeline.py (93%)
 create mode 100644 test-requirements.txt

diff --git a/.github/workflows/tests.yaml b/.github/workflows/tests.yaml
index 7e979b273..740848cee 100644
--- a/.github/workflows/tests.yaml
+++ b/.github/workflows/tests.yaml
@@ -20,14 +20,17 @@ jobs:
     name: "Unit and Integration Tests"
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - name: Checkout repo
+        uses: actions/checkout@v4
       - name: Set up Python
         id: setup_python
         uses: actions/setup-python@v4
         with:
           python-version: "3.10"
       - name: Install system packages
-        run: sudo apt-get install -y portaudio19-dev
+        id: install_system_packages
+        run: |
+          sudo apt-get install -y portaudio19-dev
       - name: Setup virtual environment
         run: |
           python -m venv .venv
@@ -35,8 +38,8 @@ jobs:
         run: |
           source .venv/bin/activate
           python -m pip install --upgrade pip
-          pip install -r dev-requirements.txt
+          pip install -r test-requirements.txt
       - name: Test with pytest
         run: |
           source .venv/bin/activate
-          pytest --doctest-modules --ignore-glob="*to_be_updated*" src tests
+          pytest --ignore-glob="*to_be_updated*" --ignore-glob=*pipeline_source* src tests
diff --git a/README.md b/README.md
index 681fd3b91..5dfc1ad95 100644
--- a/README.md
+++ b/README.md
@@ -165,7 +165,7 @@ pip install "path_to_this_repo[option,...]"
 From the root directory, run:
 
 ```shell
-pytest --doctest-modules --ignore-glob="*to_be_updated*" src tests
+pytest --doctest-modules --ignore-glob="*to_be_updated*" --ignore-glob=*pipeline_source* src tests
 ```
 
 ## Setting up your editor
diff --git a/examples/foundational/04-utterance-and-speech.py b/examples/foundational/04-utterance-and-speech.py
index 30ce4ef19..10a1dcf1c 100644
--- a/examples/foundational/04-utterance-and-speech.py
+++ b/examples/foundational/04-utterance-and-speech.py
@@ -4,6 +4,10 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
+#
+# This example broken on latest pipecat and needs updating.
+#
+
 import aiohttp
 import asyncio
 import os
diff --git a/examples/foundational/08-bots-arguing.py b/examples/foundational/08-bots-arguing.py
index 0186f2c8e..abf5a1d54 100644
--- a/examples/foundational/08-bots-arguing.py
+++ b/examples/foundational/08-bots-arguing.py
@@ -3,14 +3,14 @@ import aiohttp
 import asyncio
 import logging
 import os
-from pipecat.pipeline.aggregators import SentenceAggregator
+from pipecat.processors.aggregators import SentenceAggregator
 from pipecat.pipeline.pipeline import Pipeline
 
-from pipecat.transports.daily_transport import DailyTransport
-from pipecat.services.azure_ai_services import AzureLLMService, AzureTTSService
-from pipecat.services.elevenlabs_ai_services import ElevenLabsTTSService
-from pipecat.services.fal_ai_services import FalImageGenService
-from pipecat.pipeline.frames import AudioFrame, EndFrame, ImageFrame, LLMMessagesFrame, TextFrame
+from pipecat.transports.services.daily import DailyTransport
+from pipecat.services.azure import AzureLLMService, AzureTTSService
+from pipecat.services.elevenlabs import ElevenLabsTTSService
+from pipecat.services.fal import FalImageGenService
+from pipecat.frames.frames import AudioFrame, EndFrame, ImageFrame, LLMMessagesFrame, TextFrame
 
 from runner import configure
 
diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py
index a400d68d9..4d207fecd 100644
--- a/src/pipecat/frames/frames.py
+++ b/src/pipecat/frames/frames.py
@@ -420,7 +420,7 @@ class BotSpeakingFrame(ControlFrame):
 @dataclass
 class TTSStartedFrame(ControlFrame):
     """Used to indicate the beginning of a TTS response. Following
-    AudioRawFrames are part of the TTS response until an TTSEndFrame. These
+    AudioRawFrames are part of the TTS response until an TTSStoppedFrame. These
     frames can be used for aggregating audio frames in a transport to optimize
     the size of frames sent to the session, without needing to control this in
     the TTS service.
diff --git a/src/pipecat/pipeline/merge_pipeline.py b/src/pipecat/pipeline/to_be_updated/merge_pipeline.py
similarity index 93%
rename from src/pipecat/pipeline/merge_pipeline.py
rename to src/pipecat/pipeline/to_be_updated/merge_pipeline.py
index 019db55e1..f6f9a5ebd 100644
--- a/src/pipecat/pipeline/merge_pipeline.py
+++ b/src/pipecat/pipeline/to_be_updated/merge_pipeline.py
@@ -1,5 +1,5 @@
 from typing import List
-from pipecat.pipeline.frames import EndFrame, EndPipeFrame
+from pipecat.frames.frames import EndFrame, EndPipeFrame
 from pipecat.pipeline.pipeline import Pipeline
 
 
diff --git a/src/pipecat/processors/aggregators/gated.py b/src/pipecat/processors/aggregators/gated.py
index aaeedb592..7d784b14c 100644
--- a/src/pipecat/processors/aggregators/gated.py
+++ b/src/pipecat/processors/aggregators/gated.py
@@ -17,7 +17,8 @@ class GatedAggregator(FrameProcessor):
     Yields gate-opening frame before any accumulated frames, then ensuing frames
     until and not including the gate-closed frame.
 
-    >>> from pipecat.pipeline.frames import ImageFrame
+    Doctest: FIXME to work with asyncio
+    >>> from pipecat.frames.frames import ImageRawFrame
 
     >>> async def print_frames(aggregator, frame):
     ...     async for frame in aggregator.process_frame(frame):
@@ -28,12 +29,12 @@ class GatedAggregator(FrameProcessor):
 
     >>> aggregator = GatedAggregator(
     ...     gate_close_fn=lambda x: isinstance(x, LLMResponseStartFrame),
-    ...     gate_open_fn=lambda x: isinstance(x, ImageFrame),
+    ...     gate_open_fn=lambda x: isinstance(x, ImageRawFrame),
     ...     start_open=False)
     >>> asyncio.run(print_frames(aggregator, TextFrame("Hello")))
     >>> asyncio.run(print_frames(aggregator, TextFrame("Hello again.")))
-    >>> asyncio.run(print_frames(aggregator, ImageFrame(image=bytes([]), size=(0, 0))))
-    ImageFrame
+    >>> asyncio.run(print_frames(aggregator, ImageRawFrame(image=bytes([]), size=(0, 0))))
+    ImageRawFrame
     Hello
     Hello again.
     >>> asyncio.run(print_frames(aggregator, TextFrame("Goodbye.")))
diff --git a/src/pipecat/processors/aggregators/sentence.py b/src/pipecat/processors/aggregators/sentence.py
index 7ee641826..d0c593a83 100644
--- a/src/pipecat/processors/aggregators/sentence.py
+++ b/src/pipecat/processors/aggregators/sentence.py
@@ -16,7 +16,8 @@ class SentenceAggregator(FrameProcessor):
         TextFrame("Hello,") -> None
         TextFrame(" world.") -> TextFrame("Hello world.")
 
-    Doctest:
+    Doctest: FIXME to work with asyncio
+    >>> import asyncio
     >>> async def print_frames(aggregator, frame):
     ...     async for frame in aggregator.process_frame(frame):
     ...         print(frame.text)
diff --git a/src/pipecat/processors/aggregators/user_response.py b/src/pipecat/processors/aggregators/user_response.py
index d8ab1756c..002b6dd95 100644
--- a/src/pipecat/processors/aggregators/user_response.py
+++ b/src/pipecat/processors/aggregators/user_response.py
@@ -25,7 +25,7 @@ class ResponseAggregator(FrameProcessor):
         TranscriptionFrame(" world.") -> None
         UserStoppedSpeakingFrame() -> TextFrame("Hello world.")
 
-    Doctest:
+    Doctest: FIXME to work with asyncio
     >>> async def print_frames(aggregator, frame):
     ...     async for frame in aggregator.process_frame(frame):
     ...         if isinstance(frame, TextFrame):
diff --git a/src/pipecat/processors/aggregators/vision_image_frame.py b/src/pipecat/processors/aggregators/vision_image_frame.py
index f0c8a9c76..0bbb10841 100644
--- a/src/pipecat/processors/aggregators/vision_image_frame.py
+++ b/src/pipecat/processors/aggregators/vision_image_frame.py
@@ -12,7 +12,7 @@ class VisionImageFrameAggregator(FrameProcessor):
     """This aggregator waits for a consecutive TextFrame and an
     ImageFrame. After the ImageFrame arrives it will output a VisionImageFrame.
 
-    >>> from pipecat.pipeline.frames import ImageFrame
+    >>> from pipecat.frames.frames import ImageFrame
 
     >>> async def print_frames(aggregator, frame):
     ...     async for frame in aggregator.process_frame(frame):
diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py
index d3f5fd280..7483e2eb5 100644
--- a/src/pipecat/services/openai.py
+++ b/src/pipecat/services/openai.py
@@ -193,7 +193,8 @@ class BaseOpenAILLMService(LLMService):
             if self.has_function(function_name):
                 await self._handle_function_call(context, tool_call_id, function_name, arguments)
             else:
-                raise OpenAIUnhandledFunctionException(f"The LLM tried to call a function named '{function_name}', but there isn't a callback registered for that function.")
+                raise OpenAIUnhandledFunctionException(
+                    f"The LLM tried to call a function named '{function_name}', but there isn't a callback registered for that function.")
 
     async def _handle_function_call(
             self,
diff --git a/test-requirements.txt b/test-requirements.txt
new file mode 100644
index 000000000..7f52a49a1
--- /dev/null
+++ b/test-requirements.txt
@@ -0,0 +1,35 @@
+aiohttp~=3.10.3
+anthropic
+autopep8~=2.3.1
+azure-cognitiveservices-speech~=1.40.0
+build~=1.2.1
+daily-python~=0.10.1
+deepgram-sdk~=3.5.0
+fal-client~=0.4.1
+fastapi~=0.112.1
+faster-whisper~=1.0.3
+google-generativeai~=0.7.2
+grpcio-tools~=1.62.2
+langchain~=0.2.14
+livekit~=0.13.1
+lmnt~=1.1.4
+loguru~=0.7.2
+numpy~=1.26.4
+openai~=1.37.2
+openpipe~=4.24.0
+Pillow~=10.4.0
+pip-tools~=7.4.1
+pyaudio~=0.2.14
+pydantic~=2.8.2
+pyloudnorm~=0.1.1
+pyht~=0.0.28
+pyright~=1.1.376
+pytest~=8.3.2
+python-dotenv~=1.0.1
+resampy~=0.4.3
+setuptools~=72.2.0
+setuptools_scm~=8.1.0
+silero-vad~=5.1
+together~=1.2.7
+transformers~=4.44.0
+websockets~=12.0
diff --git a/tests/integration/integration_azure_llm.py b/tests/integration/integration_azure_llm.py
index 62527baa2..b2e7a50cf 100644
--- a/tests/integration/integration_azure_llm.py
+++ b/tests/integration/integration_azure_llm.py
@@ -1,14 +1,19 @@
+import unittest
+
 import asyncio
 import os
-from pipecat.pipeline.openai_frames import OpenAILLMContextFrame
-from pipecat.services.azure_ai_services import AzureLLMService
-from pipecat.services.openai_llm_context import OpenAILLMContext
+from pipecat.processors.aggregators.openai_llm_context import (
+    OpenAILLMContext,
+    OpenAILLMContextFrame
+)
+from pipecat.services.azure import AzureLLMService
 
 from openai.types.chat import (
     ChatCompletionSystemMessageParam,
 )
 
 if __name__ == "__main__":
+    @unittest.skip("Skip azure integration test")
     async def test_chat():
         llm = AzureLLMService(
             api_key=os.getenv("AZURE_CHATGPT_API_KEY"),
diff --git a/tests/integration/integration_ollama_llm.py b/tests/integration/integration_ollama_llm.py
index e85425f8e..cbafa6324 100644
--- a/tests/integration/integration_ollama_llm.py
+++ b/tests/integration/integration_ollama_llm.py
@@ -1,13 +1,18 @@
+import unittest
+
 import asyncio
-from pipecat.pipeline.openai_frames import OpenAILLMContextFrame
-from pipecat.services.openai_llm_context import OpenAILLMContext
+from pipecat.processors.aggregators.openai_llm_context import (
+    OpenAILLMContext,
+    OpenAILLMContextFrame
+)
 
 from openai.types.chat import (
     ChatCompletionSystemMessageParam,
 )
-from pipecat.services.ollama_ai_services import OLLamaLLMService
+from pipecat.services.ollama import OLLamaLLMService
 
 if __name__ == "__main__":
+    @unittest.skip("Skip azure integration test")
     async def test_chat():
         llm = OLLamaLLMService()
         context = OpenAILLMContext()
diff --git a/tests/test_aggregators.py b/tests/test_aggregators.py
index 47f65c90a..2fc6d226c 100644
--- a/tests/test_aggregators.py
+++ b/tests/test_aggregators.py
@@ -3,18 +3,18 @@ import doctest
 import functools
 import unittest
 
-from pipecat.pipeline.aggregators import (
-    GatedAggregator,
-    ParallelPipeline,
-    SentenceAggregator,
-    StatelessTextTransformer,
-)
-from pipecat.pipeline.frames import (
-    AudioFrame,
+from pipecat.processors.aggregators.gated import GatedAggregator
+from pipecat.processors.aggregators.sentence import SentenceAggregator
+from pipecat.processors.text_transformer import StatelessTextTransformer
+
+from pipecat.pipeline.parallel_pipeline import ParallelPipeline
+
+from pipecat.frames.frames import (
+    AudioRawFrame,
     EndFrame,
-    ImageFrame,
-    LLMResponseEndFrame,
-    LLMResponseStartFrame,
+    ImageRawFrame,
+    LLMFullResponseEndFrame,
+    LLMFullResponseStartFrame,
     Frame,
     TextFrame,
 )
@@ -23,6 +23,7 @@ from pipecat.pipeline.pipeline import Pipeline
 
 
 class TestDailyFrameAggregators(unittest.IsolatedAsyncioTestCase):
+    @unittest.skip("FIXME: This test is failing")
     async def test_sentence_aggregator(self):
         sentence = "Hello, world. How are you? I am fine"
         expected_sentences = ["Hello, world.", " How are you?", " I am fine "]
@@ -43,36 +44,38 @@ class TestDailyFrameAggregators(unittest.IsolatedAsyncioTestCase):
 
         self.assertEqual(expected_sentences, [])
 
+    @unittest.skip("FIXME: This test is failing")
     async def test_gated_accumulator(self):
         gated_aggregator = GatedAggregator(
             gate_open_fn=lambda frame: isinstance(
-                frame, ImageFrame), gate_close_fn=lambda frame: isinstance(
-                frame, LLMResponseStartFrame), start_open=False, )
+                frame, ImageRawFrame), gate_close_fn=lambda frame: isinstance(
+                frame, LLMFullResponseStartFrame), start_open=False, )
 
         frames = [
-            LLMResponseStartFrame(),
+            LLMFullResponseStartFrame(),
             TextFrame("Hello, "),
             TextFrame("world."),
-            AudioFrame(b"hello"),
-            ImageFrame(b"image", (0, 0)),
-            AudioFrame(b"world"),
-            LLMResponseEndFrame(),
+            AudioRawFrame(b"hello"),
+            ImageRawFrame(b"image", (0, 0)),
+            AudioRawFrame(b"world"),
+            LLMFullResponseEndFrame(),
         ]
 
         expected_output_frames = [
-            ImageFrame(b"image", (0, 0)),
-            LLMResponseStartFrame(),
+            ImageRawFrame(b"image", (0, 0)),
+            LLMFullResponseStartFrame(),
             TextFrame("Hello, "),
             TextFrame("world."),
-            AudioFrame(b"hello"),
-            AudioFrame(b"world"),
-            LLMResponseEndFrame(),
+            AudioRawFrame(b"hello"),
+            AudioRawFrame(b"world"),
+            LLMFullResponseEndFrame(),
         ]
         for frame in frames:
             async for out_frame in gated_aggregator.process_frame(frame):
                 self.assertEqual(out_frame, expected_output_frames.pop(0))
         self.assertEqual(expected_output_frames, [])
 
+    @unittest.skip("FIXME: This test is failing")
     async def test_parallel_pipeline(self):
 
         async def slow_add(sleep_time: float, name: str, x: str):
@@ -124,6 +127,6 @@ class TestDailyFrameAggregators(unittest.IsolatedAsyncioTestCase):
 
 def load_tests(loader, tests, ignore):
     """ Run doctests on the aggregators module. """
-    from pipecat.pipeline import aggregators
+    from pipecat.processors import aggregators
     tests.addTests(doctest.DocTestSuite(aggregators))
     return tests
diff --git a/tests/test_daily_transport_service.py b/tests/test_daily_transport_service.py
index b654f98d3..db85742c5 100644
--- a/tests/test_daily_transport_service.py
+++ b/tests/test_daily_transport_service.py
@@ -3,6 +3,7 @@ import unittest
 
 class TestDailyTransport(unittest.IsolatedAsyncioTestCase):
 
+    @unittest.skip("FIXME: This test is failing")
     async def test_event_handler(self):
         from pipecat.transports.daily_transport import DailyTransport
 
diff --git a/tests/test_openai_tts.py b/tests/test_openai_tts.py
index 5bbf449b9..5bb97b87d 100644
--- a/tests/test_openai_tts.py
+++ b/tests/test_openai_tts.py
@@ -12,6 +12,7 @@ load_dotenv()
 
 
 class TestWhisperOpenAIService(unittest.IsolatedAsyncioTestCase):
+    @unittest.skip("FIXME: This test is failing")
     async def test_whisper_tts(self):
         pa = pyaudio.PyAudio()
         stream = pa.open(format=pyaudio.paInt16,
diff --git a/tests/test_pipeline.py b/tests/test_pipeline.py
index c116b2c8f..35974d2a0 100644
--- a/tests/test_pipeline.py
+++ b/tests/test_pipeline.py
@@ -2,15 +2,17 @@ import asyncio
 import unittest
 from unittest.mock import Mock
 
-from pipecat.pipeline.aggregators import SentenceAggregator, StatelessTextTransformer
-from pipecat.pipeline.frame_processor import FrameProcessor
-from pipecat.pipeline.frames import EndFrame, TextFrame
+from pipecat.processors.aggregators.sentence import SentenceAggregator
+from pipecat.processors.text_transformer import StatelessTextTransformer
+from pipecat.processors.frame_processor import FrameProcessor
+from pipecat.frames.frames import EndFrame, TextFrame
 
 from pipecat.pipeline.pipeline import Pipeline
 
 
 class TestDailyPipeline(unittest.IsolatedAsyncioTestCase):
 
+    @unittest.skip("FIXME: This test is failing")
     async def test_pipeline_simple(self):
         aggregator = SentenceAggregator()
 
@@ -27,6 +29,7 @@ class TestDailyPipeline(unittest.IsolatedAsyncioTestCase):
         self.assertEqual(await outgoing_queue.get(), TextFrame("Hello, world."))
         self.assertIsInstance(await outgoing_queue.get(), EndFrame)
 
+    @unittest.skip("FIXME: This test is failing")
     async def test_pipeline_multiple_stages(self):
         sentence_aggregator = SentenceAggregator()
         to_upper = StatelessTextTransformer(lambda x: x.upper())
@@ -78,18 +81,21 @@ class TestLogFrame(unittest.TestCase):
         self.pipeline._name = 'MyClass'
         self.pipeline._logger = Mock()
 
+    @unittest.skip("FIXME: This test is failing")
     def test_log_frame_from_source(self):
         frame = Mock(__class__=Mock(__name__='MyFrame'))
         self.pipeline._log_frame(frame, depth=1)
         self.pipeline._logger.debug.assert_called_once_with(
             'MyClass  source -> MyFrame -> processor1')
 
+    @unittest.skip("FIXME: This test is failing")
     def test_log_frame_to_sink(self):
         frame = Mock(__class__=Mock(__name__='MyFrame'))
         self.pipeline._log_frame(frame, depth=3)
         self.pipeline._logger.debug.assert_called_once_with(
             'MyClass      processor2 -> MyFrame -> sink')
 
+    @unittest.skip("FIXME: This test is failing")
     def test_log_frame_repeated_log(self):
         frame = Mock(__class__=Mock(__name__='MyFrame'))
         self.pipeline._log_frame(frame, depth=2)
@@ -98,6 +104,7 @@ class TestLogFrame(unittest.TestCase):
         self.pipeline._log_frame(frame, depth=2)
         self.pipeline._logger.debug.assert_called_with('MyClass    ... repeated')
 
+    @unittest.skip("FIXME: This test is failing")
     def test_log_frame_reset_repeated_log(self):
         frame1 = Mock(__class__=Mock(__name__='MyFrame1'))
         frame2 = Mock(__class__=Mock(__name__='MyFrame2'))
diff --git a/tests/test_protobuf_serializer.py b/tests/test_protobuf_serializer.py
index 7109d7284..2e74e88f4 100644
--- a/tests/test_protobuf_serializer.py
+++ b/tests/test_protobuf_serializer.py
@@ -1,13 +1,14 @@
 import unittest
 
-from pipecat.pipeline.frames import AudioFrame, TextFrame, TranscriptionFrame
-from pipecat.serializers.protobuf_serializer import ProtobufFrameSerializer
+from pipecat.frames.frames import AudioRawFrame, TextFrame, TranscriptionFrame
+from pipecat.serializers.protobuf import ProtobufFrameSerializer
 
 
 class TestProtobufFrameSerializer(unittest.IsolatedAsyncioTestCase):
     def setUp(self):
         self.serializer = ProtobufFrameSerializer()
 
+    @unittest.skip("FIXME: This test is failing")
     async def test_roundtrip(self):
         text_frame = TextFrame(text='hello world')
         frame = self.serializer.deserialize(
@@ -20,7 +21,7 @@ class TestProtobufFrameSerializer(unittest.IsolatedAsyncioTestCase):
             self.serializer.serialize(transcription_frame))
         self.assertEqual(frame, transcription_frame)
 
-        audio_frame = AudioFrame(data=b'1234567890')
+        audio_frame = AudioRawFrame(data=b'1234567890')
         frame = self.serializer.deserialize(
             self.serializer.serialize(audio_frame))
         self.assertEqual(frame, audio_frame)
diff --git a/tests/test_websocket_transport.py b/tests/test_websocket_transport.py
index 601ba21ae..b24caa5b9 100644
--- a/tests/test_websocket_transport.py
+++ b/tests/test_websocket_transport.py
@@ -1,113 +1,113 @@
-import asyncio
-import unittest
-from unittest.mock import AsyncMock, patch, Mock
+# import asyncio
+# import unittest
+# from unittest.mock import AsyncMock, patch, Mock
 
-from pipecat.pipeline.frames import AudioFrame, EndFrame, TextFrame, TTSEndFrame, TTSStartFrame
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.transports.websocket_transport import WebSocketFrameProcessor, WebsocketTransport
+# from pipecat.pipeline.frames import AudioFrame, EndFrame, TextFrame, TTSEndFrame, TTSStartFrame
+# from pipecat.pipeline.pipeline import Pipeline
+# from pipecat.transports.websocket_transport import WebSocketFrameProcessor, WebsocketTransport
 
 
-class TestWebSocketTransportService(unittest.IsolatedAsyncioTestCase):
-    def setUp(self):
-        self.transport = WebsocketTransport(host="localhost", port=8765)
-        self.pipeline = Pipeline([])
-        self.sample_frame = TextFrame("Hello there!")
-        self.serialized_sample_frame = self.transport._serializer.serialize(
-            self.sample_frame)
+# class TestWebSocketTransportService(unittest.IsolatedAsyncioTestCase):
+#     def setUp(self):
+#         self.transport = WebsocketTransport(host="localhost", port=8765)
+#         self.pipeline = Pipeline([])
+#         self.sample_frame = TextFrame("Hello there!")
+#         self.serialized_sample_frame = self.transport._serializer.serialize(
+#             self.sample_frame)
 
-    async def queue_frame(self):
-        await asyncio.sleep(0.1)
-        await self.pipeline.queue_frames([self.sample_frame, EndFrame()])
+#     async def queue_frame(self):
+#         await asyncio.sleep(0.1)
+#         await self.pipeline.queue_frames([self.sample_frame, EndFrame()])
 
-    async def test_websocket_handler(self):
-        mock_websocket = AsyncMock()
+#     async def test_websocket_handler(self):
+#         mock_websocket = AsyncMock()
 
-        with patch("websockets.serve", return_value=AsyncMock()) as mock_serve:
-            mock_serve.return_value.__anext__.return_value = (
-                mock_websocket, "/")
+#         with patch("websockets.serve", return_value=AsyncMock()) as mock_serve:
+#             mock_serve.return_value.__anext__.return_value = (
+#                 mock_websocket, "/")
 
-            await self.transport._websocket_handler(mock_websocket, "/")
+#             await self.transport._websocket_handler(mock_websocket, "/")
 
-            await asyncio.gather(self.transport.run(self.pipeline), self.queue_frame())
-            self.assertEqual(mock_websocket.send.call_count, 1)
+#             await asyncio.gather(self.transport.run(self.pipeline), self.queue_frame())
+#             self.assertEqual(mock_websocket.send.call_count, 1)
 
-            self.assertEqual(
-                mock_websocket.send.call_args[0][0], self.serialized_sample_frame)
+#             self.assertEqual(
+#                 mock_websocket.send.call_args[0][0], self.serialized_sample_frame)
 
-    async def test_on_connection_decorator(self):
-        mock_websocket = AsyncMock()
+#     async def test_on_connection_decorator(self):
+#         mock_websocket = AsyncMock()
 
-        connection_handler_called = asyncio.Event()
+#         connection_handler_called = asyncio.Event()
 
-        @self.transport.on_connection
-        async def connection_handler():
-            connection_handler_called.set()
+#         @self.transport.on_connection
+#         async def connection_handler():
+#             connection_handler_called.set()
 
-        with patch("websockets.serve", return_value=AsyncMock()):
-            await self.transport._websocket_handler(mock_websocket, "/")
+#         with patch("websockets.serve", return_value=AsyncMock()):
+#             await self.transport._websocket_handler(mock_websocket, "/")
 
-        self.assertTrue(connection_handler_called.is_set())
+#         self.assertTrue(connection_handler_called.is_set())
 
-    async def test_frame_processor(self):
-        processor = WebSocketFrameProcessor(audio_frame_size=4)
+#     async def test_frame_processor(self):
+#         processor = WebSocketFrameProcessor(audio_frame_size=4)
 
-        source_frames = [
-            TTSStartFrame(),
-            AudioFrame(b"1234"),
-            AudioFrame(b"5678"),
-            TTSEndFrame(),
-            TextFrame("hello world")
-        ]
+#         source_frames = [
+#             TTSStartFrame(),
+#             AudioFrame(b"1234"),
+#             AudioFrame(b"5678"),
+#             TTSEndFrame(),
+#             TextFrame("hello world")
+#         ]
 
-        frames = []
-        for frame in source_frames:
-            async for output_frame in processor.process_frame(frame):
-                frames.append(output_frame)
+#         frames = []
+#         for frame in source_frames:
+#             async for output_frame in processor.process_frame(frame):
+#                 frames.append(output_frame)
 
-        self.assertEqual(len(frames), 3)
-        self.assertIsInstance(frames[0], AudioFrame)
-        self.assertEqual(frames[0].data, b"1234")
-        self.assertIsInstance(frames[1], AudioFrame)
-        self.assertEqual(frames[1].data, b"5678")
-        self.assertIsInstance(frames[2], TextFrame)
-        self.assertEqual(frames[2].text, "hello world")
+#         self.assertEqual(len(frames), 3)
+#         self.assertIsInstance(frames[0], AudioFrame)
+#         self.assertEqual(frames[0].data, b"1234")
+#         self.assertIsInstance(frames[1], AudioFrame)
+#         self.assertEqual(frames[1].data, b"5678")
+#         self.assertIsInstance(frames[2], TextFrame)
+#         self.assertEqual(frames[2].text, "hello world")
 
-    async def test_serializer_parameter(self):
-        mock_websocket = AsyncMock()
+#     async def test_serializer_parameter(self):
+#         mock_websocket = AsyncMock()
 
-        # Test with ProtobufFrameSerializer (default)
-        with patch("websockets.serve", return_value=AsyncMock()) as mock_serve:
-            mock_serve.return_value.__anext__.return_value = (
-                mock_websocket, "/")
+#         # Test with ProtobufFrameSerializer (default)
+#         with patch("websockets.serve", return_value=AsyncMock()) as mock_serve:
+#             mock_serve.return_value.__anext__.return_value = (
+#                 mock_websocket, "/")
 
-            await self.transport._websocket_handler(mock_websocket, "/")
+#             await self.transport._websocket_handler(mock_websocket, "/")
 
-            await asyncio.gather(self.transport.run(self.pipeline), self.queue_frame())
-            self.assertEqual(mock_websocket.send.call_count, 1)
-            self.assertEqual(
-                mock_websocket.send.call_args[0][0],
-                self.serialized_sample_frame,
-            )
+#             await asyncio.gather(self.transport.run(self.pipeline), self.queue_frame())
+#             self.assertEqual(mock_websocket.send.call_count, 1)
+#             self.assertEqual(
+#                 mock_websocket.send.call_args[0][0],
+#                 self.serialized_sample_frame,
+#             )
 
-        # Test with a mock serializer
-        mock_serializer = Mock()
-        mock_serializer.serialize.return_value = b"mock_serialized_data"
-        self.transport = WebsocketTransport(
-            host="localhost", port=8765, serializer=mock_serializer
-        )
-        mock_websocket.reset_mock()
-        with patch("websockets.serve", return_value=AsyncMock()) as mock_serve:
-            mock_serve.return_value.__anext__.return_value = (
-                mock_websocket, "/")
+#         # Test with a mock serializer
+#         mock_serializer = Mock()
+#         mock_serializer.serialize.return_value = b"mock_serialized_data"
+#         self.transport = WebsocketTransport(
+#             host="localhost", port=8765, serializer=mock_serializer
+#         )
+#         mock_websocket.reset_mock()
+#         with patch("websockets.serve", return_value=AsyncMock()) as mock_serve:
+#             mock_serve.return_value.__anext__.return_value = (
+#                 mock_websocket, "/")
 
-            await self.transport._websocket_handler(mock_websocket, "/")
-            await asyncio.gather(self.transport.run(self.pipeline), self.queue_frame())
-            self.assertEqual(mock_websocket.send.call_count, 1)
-            self.assertEqual(
-                mock_websocket.send.call_args[0][0], b"mock_serialized_data")
-            mock_serializer.serialize.assert_called_once_with(
-                TextFrame("Hello there!"))
+#             await self.transport._websocket_handler(mock_websocket, "/")
+#             await asyncio.gather(self.transport.run(self.pipeline), self.queue_frame())
+#             self.assertEqual(mock_websocket.send.call_count, 1)
+#             self.assertEqual(
+#                 mock_websocket.send.call_args[0][0], b"mock_serialized_data")
+#             mock_serializer.serialize.assert_called_once_with(
+#                 TextFrame("Hello there!"))
 
 
-if __name__ == "__main__":
-    unittest.main()
+# if __name__ == "__main__":
+#     unittest.main()

From a4edb3dab119bedb4d0ae1771a0b5b2f2f1661ca Mon Sep 17 00:00:00 2001
From: mattie ruth backman <mattieruth@gmail.com>
Date: Tue, 17 Sep 2024 14:49:08 -0400
Subject: [PATCH 037/135] Cleanup on aisle METRICS. Note: See below, this is a
 breaking change

1. Fleshed out MetricsFrames and broke it into a proper set of types
2. Add model_name as a property to the AIService so that it can be
   automatically included in metrics and also remove that
   overhead from all the various services themselves

Breaking change!

Because of the types improvements, the MetricsFrame type has
changed. Each frame will have a list of metrics simlilar to before
except each item in the list will only contain one type of metric:
"ttfb", "tokens", "characters", or "processing". Previously these
fields would be in every entry but set to None if they didn't apply.

While this changes internal handling of the MetricsFrame, it does NOT
break the RTVI/daily messaging of metrics. That format remains the same.

Also. Remember to use model_name for accessing a service's current
model and set_model_name for setting it.
---
 .../foundational/06-listen-and-respond.py     | 16 ++++-
 src/pipecat/frames/frames.py                  |  9 ++-
 src/pipecat/metrics/__init__.py               |  0
 src/pipecat/metrics/metrics.py                | 31 +++++++++
 src/pipecat/pipeline/task.py                  |  9 ++-
 src/pipecat/processors/frame_processor.py     | 67 ++++++++++++-------
 src/pipecat/services/ai_services.py           | 14 +++-
 src/pipecat/services/anthropic.py             | 23 +++----
 src/pipecat/services/azure.py                 |  4 +-
 src/pipecat/services/cartesia.py              | 17 +++--
 src/pipecat/services/deepgram.py              |  1 +
 src/pipecat/services/elevenlabs.py            |  6 +-
 src/pipecat/services/fal.py                   |  4 +-
 src/pipecat/services/fireworks.py             |  2 +-
 src/pipecat/services/google.py                |  1 +
 src/pipecat/services/moondream.py             |  4 +-
 src/pipecat/services/openai.py                | 27 ++++----
 src/pipecat/services/openpipe.py              |  2 +-
 src/pipecat/services/together.py              | 21 +++---
 src/pipecat/services/whisper.py               |  4 +-
 src/pipecat/transports/services/daily.py      | 26 ++++---
 21 files changed, 190 insertions(+), 98 deletions(-)
 create mode 100644 src/pipecat/metrics/__init__.py
 create mode 100644 src/pipecat/metrics/metrics.py

diff --git a/examples/foundational/06-listen-and-respond.py b/examples/foundational/06-listen-and-respond.py
index e99a95068..6a10f927c 100644
--- a/examples/foundational/06-listen-and-respond.py
+++ b/examples/foundational/06-listen-and-respond.py
@@ -10,6 +10,7 @@ import os
 import sys
 
 from pipecat.frames.frames import Frame, LLMMessagesFrame, MetricsFrame
+from pipecat.metrics.metrics import TTFBMetricsData, ProcessingMetricsData, LLMUsageMetricsData, TTSUsageMetricsData
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -37,8 +38,19 @@ logger.add(sys.stderr, level="DEBUG")
 class MetricsLogger(FrameProcessor):
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         if isinstance(frame, MetricsFrame):
-            print(
-                f"!!! MetricsFrame: {frame}, ttfb: {frame.ttfb}, processing: {frame.processing}, tokens: {frame.tokens}, characters: {frame.characters}")
+            for d in frame.data:
+                if isinstance(d, TTFBMetricsData):
+                    print(f"!!! MetricsFrame: {frame}, ttfb: {d.value}")
+                elif isinstance(d, ProcessingMetricsData):
+                    print(f"!!! MetricsFrame: {frame}, processing: {d.value}")
+                elif isinstance(d, LLMUsageMetricsData):
+                    tokens = d.value
+                    print(
+                        f"!!! MetricsFrame: {frame}, tokens: {
+                            tokens.prompt_tokens}, characters: {
+                            tokens.completion_tokens}")
+                elif isinstance(d, TTSUsageMetricsData):
+                    print(f"!!! MetricsFrame: {frame}, characters: {d.value}")
         await self.push_frame(frame, direction)
 
 
diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py
index 4d207fecd..adb3f88c6 100644
--- a/src/pipecat/frames/frames.py
+++ b/src/pipecat/frames/frames.py
@@ -4,11 +4,12 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-from typing import Any, List, Mapping, Optional, Tuple
+from typing import Any, List, Optional, Tuple
 
 from dataclasses import dataclass, field
 
 from pipecat.clocks.base_clock import BaseClock
+from pipecat.metrics.metrics import MetricsData
 from pipecat.transcriptions.language import Language
 from pipecat.utils.time import nanoseconds_to_str
 from pipecat.utils.utils import obj_count, obj_id
@@ -333,10 +334,8 @@ class BotInterruptionFrame(SystemFrame):
 class MetricsFrame(SystemFrame):
     """Emitted by processor that can compute metrics like latencies.
     """
-    ttfb: List[Mapping[str, Any]] | None = None
-    processing: List[Mapping[str, Any]] | None = None
-    tokens: List[Mapping[str, Any]] | None = None
-    characters: List[Mapping[str, Any]] | None = None
+    data: List[MetricsData]
+
 
 #
 # Control frames
diff --git a/src/pipecat/metrics/__init__.py b/src/pipecat/metrics/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/src/pipecat/metrics/metrics.py b/src/pipecat/metrics/metrics.py
new file mode 100644
index 000000000..053708998
--- /dev/null
+++ b/src/pipecat/metrics/metrics.py
@@ -0,0 +1,31 @@
+from typing import Optional
+from pydantic import BaseModel
+
+
+class MetricsData(BaseModel):
+    processor: str
+    model: Optional[str] = None
+
+
+class TTFBMetricsData(MetricsData):
+    value: float
+
+
+class ProcessingMetricsData(MetricsData):
+    value: float
+
+
+class LLMTokenUsage(BaseModel):
+    prompt_tokens: int
+    completion_tokens: int
+    total_tokens: int
+    cache_read_input_tokens: Optional[int] = None
+    cache_creation_input_tokens: Optional[int] = None
+
+
+class LLMUsageMetricsData(MetricsData):
+    value: LLMTokenUsage
+
+
+class TTSUsageMetricsData(MetricsData):
+    value: int
diff --git a/src/pipecat/pipeline/task.py b/src/pipecat/pipeline/task.py
index 03fd5c734..26e6e9f4f 100644
--- a/src/pipecat/pipeline/task.py
+++ b/src/pipecat/pipeline/task.py
@@ -20,6 +20,7 @@ from pipecat.frames.frames import (
     MetricsFrame,
     StartFrame,
     StopTaskFrame)
+from pipecat.metrics.metrics import TTFBMetricsData, ProcessingMetricsData
 from pipecat.pipeline.base_pipeline import BasePipeline
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.utils.utils import obj_count, obj_id
@@ -118,9 +119,11 @@ class PipelineTask:
 
     def _initial_metrics_frame(self) -> MetricsFrame:
         processors = self._pipeline.processors_with_metrics()
-        ttfb = [{"processor": p.name, "value": 0.0} for p in processors]
-        processing = [{"processor": p.name, "value": 0.0} for p in processors]
-        return MetricsFrame(ttfb=ttfb, processing=processing)
+        data = []
+        for p in processors:
+            data.append(TTFBMetricsData(processor=p.name, value=0.0))
+            data.append(ProcessingMetricsData(processor=p.name, value=0.0))
+        return MetricsFrame(data=data)
 
     async def _process_down_queue(self):
         self._clock.start()
diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py
index 72924776c..e44b8b0ff 100644
--- a/src/pipecat/processors/frame_processor.py
+++ b/src/pipecat/processors/frame_processor.py
@@ -19,6 +19,13 @@ from pipecat.frames.frames import (
     StartInterruptionFrame,
     StopInterruptionFrame,
     SystemFrame)
+from pipecat.metrics.metrics import (
+    LLMTokenUsage,
+    LLMUsageMetricsData,
+    MetricsData,
+    ProcessingMetricsData,
+    TTFBMetricsData,
+    TTSUsageMetricsData)
 from pipecat.utils.utils import obj_count, obj_id
 
 from loguru import logger
@@ -31,11 +38,20 @@ class FrameDirection(Enum):
 
 class FrameProcessorMetrics:
     def __init__(self, name: str):
-        self._name = name
+        self._core_metrics_data = MetricsData(processor=name)
         self._start_ttfb_time = 0
         self._start_processing_time = 0
         self._should_report_ttfb = True
 
+    def _processor_name(self):
+        return self._core_metrics_data.processor
+
+    def _model_name(self):
+        return self._core_metrics_data.model
+
+    def set_core_metrics_data(self, data: MetricsData):
+        self._core_metrics_data = data
+
     async def start_ttfb_metrics(self, report_only_initial_ttfb):
         if self._should_report_ttfb:
             self._start_ttfb_time = time.time()
@@ -46,13 +62,13 @@ class FrameProcessorMetrics:
             return None
 
         value = time.time() - self._start_ttfb_time
-        logger.debug(f"{self._name} TTFB: {value}")
-        ttfb = {
-            "processor": self._name,
-            "value": value
-        }
+        logger.debug(f"{self._processor_name()} TTFB: {value}")
+        ttfb = TTFBMetricsData(
+            processor=self._processor_name(),
+            value=value,
+            model=self._model_name())
         self._start_ttfb_time = 0
-        return MetricsFrame(ttfb=[ttfb])
+        return MetricsFrame(data=[ttfb])
 
     async def start_processing_metrics(self):
         self._start_processing_time = time.time()
@@ -62,26 +78,28 @@ class FrameProcessorMetrics:
             return None
 
         value = time.time() - self._start_processing_time
-        logger.debug(f"{self._name} processing time: {value}")
-        processing = {
-            "processor": self._name,
-            "value": value
-        }
+        logger.debug(f"{self._processor_name()} processing time: {value}")
+        processing = ProcessingMetricsData(
+            processor=self._processor_name(), value=value, model=self._model_name())
         self._start_processing_time = 0
-        return MetricsFrame(processing=[processing])
+        return MetricsFrame(data=[processing])
 
-    async def start_llm_usage_metrics(self, tokens: dict):
+    async def start_llm_usage_metrics(self, tokens: LLMTokenUsage):
         logger.debug(
-            f"{self._name} prompt tokens: {tokens['prompt_tokens']}, completion tokens: {tokens['completion_tokens']}")
-        return MetricsFrame(tokens=[tokens])
+            f"{self._processor_name()} prompt tokens: {tokens.prompt_tokens}, completion tokens: {tokens.completion_tokens}")
+        value = LLMUsageMetricsData(
+            processor=self._processor_name(),
+            model=self._model_name(),
+            value=tokens)
+        return MetricsFrame(data=[value])
 
     async def start_tts_usage_metrics(self, text: str):
-        characters = {
-            "processor": self._name,
-            "value": len(text),
-        }
-        logger.debug(f"{self._name} usage characters: {characters['value']}")
-        return MetricsFrame(characters=[characters])
+        characters = TTSUsageMetricsData(
+            processor=self._processor_name(),
+            model=self._model_name(),
+            value=len(text))
+        logger.debug(f"{self._processor_name()} usage characters: {characters.value}")
+        return MetricsFrame(data=[characters])
 
 
 class FrameProcessor:
@@ -140,6 +158,9 @@ class FrameProcessor:
     def can_generate_metrics(self) -> bool:
         return False
 
+    def set_core_metrics_data(self, data: MetricsData):
+        self._metrics.set_core_metrics_data(data)
+
     async def start_ttfb_metrics(self):
         if self.can_generate_metrics() and self.metrics_enabled:
             await self._metrics.start_ttfb_metrics(self._report_only_initial_ttfb)
@@ -160,7 +181,7 @@ class FrameProcessor:
             if frame:
                 await self.push_frame(frame)
 
-    async def start_llm_usage_metrics(self, tokens: dict):
+    async def start_llm_usage_metrics(self, tokens: LLMTokenUsage):
         if self.can_generate_metrics() and self.usage_metrics_enabled:
             frame = await self._metrics.start_llm_usage_metrics(tokens)
             if frame:
diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index d91782e42..0207b0511 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -32,6 +32,7 @@ from pipecat.frames.frames import (
     UserImageRequestFrame,
     VisionImageRawFrame
 )
+from pipecat.metrics.metrics import MetricsData
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.transcriptions.language import Language
 from pipecat.utils.audio import calculate_audio_volume
@@ -46,6 +47,15 @@ from loguru import logger
 class AIService(FrameProcessor):
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
+        self._model_name: str = ""
+
+    @property
+    def model_name(self) -> str:
+        return self._model_name
+
+    def set_model_name(self, model: str):
+        self._model_name = model
+        self.set_core_metrics_data(MetricsData(processor=self.name, model=self._model_name))
 
     async def start(self, frame: StartFrame):
         pass
@@ -158,7 +168,7 @@ class TTSService(AIService):
 
     @abstractmethod
     async def set_model(self, model: str):
-        pass
+        self.set_model_name(model)
 
     @abstractmethod
     async def set_voice(self, voice: str):
@@ -367,7 +377,7 @@ class STTService(AIService):
 
     @abstractmethod
     async def set_model(self, model: str):
-        pass
+        self.set_model_name(model)
 
     @abstractmethod
     async def set_language(self, language: Language):
diff --git a/src/pipecat/services/anthropic.py b/src/pipecat/services/anthropic.py
index 329959b1f..7935691ce 100644
--- a/src/pipecat/services/anthropic.py
+++ b/src/pipecat/services/anthropic.py
@@ -29,6 +29,7 @@ from pipecat.frames.frames import (
     FunctionCallInProgressFrame,
     StartInterruptionFrame
 )
+from pipecat.metrics.metrics import LLMTokenUsage
 from pipecat.processors.frame_processor import FrameDirection
 from pipecat.services.ai_services import LLMService
 from pipecat.processors.aggregators.openai_llm_context import (
@@ -84,7 +85,7 @@ class AnthropicLLMService(LLMService):
             **kwargs):
         super().__init__(**kwargs)
         self._client = AsyncAnthropic(api_key=api_key)
-        self._model = model
+        self.set_model_name(model)
         self._max_tokens = max_tokens
         self._enable_prompt_caching_beta = enable_prompt_caching_beta
 
@@ -137,7 +138,7 @@ class AnthropicLLMService(LLMService):
                 tools=context.tools or [],
                 system=context.system,
                 messages=messages,
-                model=self._model,
+                model=self.model_name,
                 max_tokens=self._max_tokens,
                 stream=True)
 
@@ -231,7 +232,7 @@ class AnthropicLLMService(LLMService):
             context = AnthropicLLMContext.from_image_frame(frame)
         elif isinstance(frame, LLMModelUpdateFrame):
             logger.debug(f"Switching LLM model to: [{frame.model}]")
-            self._model = frame.model
+            self.set_model_name(frame.model)
         elif isinstance(frame, LLMEnablePromptCachingFrame):
             logger.debug(f"Setting enable prompt caching to: [{frame.enable}]")
             self._enable_prompt_caching_beta = frame.enable
@@ -251,15 +252,13 @@ class AnthropicLLMService(LLMService):
             cache_creation_input_tokens: int,
             cache_read_input_tokens: int):
         if prompt_tokens or completion_tokens or cache_creation_input_tokens or cache_read_input_tokens:
-            tokens = {
-                "processor": self.name,
-                "model": self._model,
-                "prompt_tokens": prompt_tokens,
-                "completion_tokens": completion_tokens,
-                "cache_creation_input_tokens": cache_creation_input_tokens,
-                "cache_read_input_tokens": cache_read_input_tokens,
-                "total_tokens": prompt_tokens + completion_tokens
-            }
+            tokens = LLMTokenUsage(
+                prompt_tokens=prompt_tokens,
+                completion_tokens=completion_tokens,
+                cache_creation_input_tokens=cache_creation_input_tokens,
+                cache_read_input_tokens=cache_read_input_tokens,
+                total_tokens=prompt_tokens + completion_tokens
+            )
             await self.start_llm_usage_metrics(tokens)
 
 
diff --git a/src/pipecat/services/azure.py b/src/pipecat/services/azure.py
index 90674fcc4..daac57119 100644
--- a/src/pipecat/services/azure.py
+++ b/src/pipecat/services/azure.py
@@ -22,6 +22,8 @@ from pipecat.frames.frames import (
     TTSStoppedFrame,
     TranscriptionFrame,
     URLImageRawFrame)
+from pipecat.metrics.metrics import TTSUsageMetricsData
+from pipecat.processors.frame_processor import FrameDirection
 from pipecat.services.ai_services import STTService, TTSService, ImageGenService
 from pipecat.services.openai import BaseOpenAILLMService
 from pipecat.utils.time import time_now_iso8601
@@ -190,7 +192,7 @@ class AzureImageGenServiceREST(ImageGenService):
         self._api_key = api_key
         self._azure_endpoint = endpoint
         self._api_version = api_version
-        self._model = model
+        self.set_model_name(model)
         self._image_size = image_size
         self._aiohttp_session = aiohttp_session
 
diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index 078926235..ab6026052 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -89,7 +89,7 @@ class CartesiaTTSService(AsyncWordTTSService):
         self._cartesia_version = cartesia_version
         self._url = url
         self._voice_id = voice_id
-        self._model_id = model_id
+        self.set_model_name(model_id)
         self._output_format = {
             "container": "raw",
             "encoding": encoding,
@@ -105,8 +105,8 @@ class CartesiaTTSService(AsyncWordTTSService):
         return True
 
     async def set_model(self, model: str):
+        await super().set_model(model)
         logger.debug(f"Switching TTS model to: [{model}]")
-        self._model_id = model
 
     async def set_voice(self, voice: str):
         logger.debug(f"Switching TTS voice to: [{voice}]")
@@ -155,6 +155,11 @@ class CartesiaTTSService(AsyncWordTTSService):
         except Exception as e:
             logger.error(f"{self} error closing websocket: {e}")
 
+    def _get_websocket(self):
+        if self._websocket:
+            return self._websocket
+        raise Exception("Websocket not connected")
+
     async def _handle_interruption(self, frame: StartInterruptionFrame, direction: FrameDirection):
         await super()._handle_interruption(frame, direction)
         await self.stop_all_metrics()
@@ -169,7 +174,7 @@ class CartesiaTTSService(AsyncWordTTSService):
             "transcript": "",
             "continue": False,
             "context_id": self._context_id,
-            "model_id": self._model_id,
+            "model_id": self.model_name,
             "voice": {
                 "mode": "id",
                 "id": self._voice_id
@@ -182,7 +187,7 @@ class CartesiaTTSService(AsyncWordTTSService):
 
     async def _receive_task_handler(self):
         try:
-            async for message in self._websocket:
+            async for message in self._get_websocket():
                 msg = json.loads(message)
                 if not msg or msg["context_id"] != self._context_id:
                     continue
@@ -235,7 +240,7 @@ class CartesiaTTSService(AsyncWordTTSService):
                 "transcript": text + " ",
                 "continue": True,
                 "context_id": self._context_id,
-                "model_id": self._model_id,
+                "model_id": self.model_name,
                 "voice": {
                     "mode": "id",
                     "id": self._voice_id
@@ -245,7 +250,7 @@ class CartesiaTTSService(AsyncWordTTSService):
                 "add_timestamps": True,
             }
             try:
-                await self._websocket.send(json.dumps(msg))
+                await self._get_websocket().send(json.dumps(msg))
                 await self.start_tts_usage_metrics(text)
             except Exception as e:
                 logger.error(f"{self} error sending message: {e}")
diff --git a/src/pipecat/services/deepgram.py b/src/pipecat/services/deepgram.py
index 708c3c511..5aebdfbb3 100644
--- a/src/pipecat/services/deepgram.py
+++ b/src/pipecat/services/deepgram.py
@@ -135,6 +135,7 @@ class DeepgramSTTService(STTService):
         self._connection.on(LiveTranscriptionEvents.Transcript, self._on_message)
 
     async def set_model(self, model: str):
+        await super().set_model(model)
         logger.debug(f"Switching STT model to: [{model}]")
         self._live_options.model = model
         await self._disconnect()
diff --git a/src/pipecat/services/elevenlabs.py b/src/pipecat/services/elevenlabs.py
index 081a6bf5d..40aa25865 100644
--- a/src/pipecat/services/elevenlabs.py
+++ b/src/pipecat/services/elevenlabs.py
@@ -107,7 +107,7 @@ class ElevenLabsTTSService(AsyncWordTTSService):
 
         self._api_key = api_key
         self._voice_id = voice_id
-        self._model = model
+        self.set_model_name(model)
         self._url = url
         self._params = params
 
@@ -122,8 +122,8 @@ class ElevenLabsTTSService(AsyncWordTTSService):
         return True
 
     async def set_model(self, model: str):
+        await super().set_model(model)
         logger.debug(f"Switching TTS model to: [{model}]")
-        self._model = model
         await self._disconnect()
         await self._connect()
 
@@ -160,7 +160,7 @@ class ElevenLabsTTSService(AsyncWordTTSService):
     async def _connect(self):
         try:
             voice_id = self._voice_id
-            model = self._model
+            model = self.model_name
             output_format = self._params.output_format
             url = f"{self._url}/v1/text-to-speech/{voice_id}/stream-input?model_id={model}&output_format={output_format}"
             self._websocket = await websockets.connect(url)
diff --git a/src/pipecat/services/fal.py b/src/pipecat/services/fal.py
index 672135d02..58768180f 100644
--- a/src/pipecat/services/fal.py
+++ b/src/pipecat/services/fal.py
@@ -46,7 +46,7 @@ class FalImageGenService(ImageGenService):
         **kwargs
     ):
         super().__init__(**kwargs)
-        self._model = model
+        self.set_model_name(model)
         self._params = params
         self._aiohttp_session = aiohttp_session
         if key:
@@ -56,7 +56,7 @@ class FalImageGenService(ImageGenService):
         logger.debug(f"Generating image from prompt: {prompt}")
 
         response = await fal_client.run_async(
-            self._model,
+            self.model_name,
             arguments={"prompt": prompt, **self._params.model_dump(exclude_none=True)}
         )
 
diff --git a/src/pipecat/services/fireworks.py b/src/pipecat/services/fireworks.py
index 7fa4d64e8..87fddd838 100644
--- a/src/pipecat/services/fireworks.py
+++ b/src/pipecat/services/fireworks.py
@@ -22,4 +22,4 @@ class FireworksLLMService(BaseOpenAILLMService):
                  *,
                  model: str = "accounts/fireworks/models/firefunction-v1",
                  base_url: str = "https://api.fireworks.ai/inference/v1"):
-        super().__init__(model, base_url)
+        super().__init__(model=model, base_url=base_url)
diff --git a/src/pipecat/services/google.py b/src/pipecat/services/google.py
index 7f20f1b8f..b72169b70 100644
--- a/src/pipecat/services/google.py
+++ b/src/pipecat/services/google.py
@@ -50,6 +50,7 @@ class GoogleLLMService(LLMService):
         return True
 
     def _create_client(self, model: str):
+        self.set_model_name(model)
         self._client = gai.GenerativeModel(model)
 
     def _get_messages_from_openai_context(
diff --git a/src/pipecat/services/moondream.py b/src/pipecat/services/moondream.py
index 3441aeeb9..b6391cc93 100644
--- a/src/pipecat/services/moondream.py
+++ b/src/pipecat/services/moondream.py
@@ -54,6 +54,8 @@ class MoondreamService(VisionService):
     ):
         super().__init__(**kwargs)
 
+        self.set_model_name(model)
+
         if not use_cpu:
             device, dtype = detect_device()
         else:
@@ -73,7 +75,7 @@ class MoondreamService(VisionService):
 
     async def run_vision(self, frame: VisionImageRawFrame) -> AsyncGenerator[Frame, None]:
         if not self._model:
-            logger.error(f"{self} error: Moondream model not available")
+            logger.error(f"{self} error: Moondream model not available ({self.model_name})")
             yield ErrorFrame("Moondream model not available")
             return
 
diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py
index 7483e2eb5..6fe710b5e 100644
--- a/src/pipecat/services/openai.py
+++ b/src/pipecat/services/openai.py
@@ -33,6 +33,7 @@ from pipecat.frames.frames import (
     FunctionCallInProgressFrame,
     StartInterruptionFrame
 )
+from pipecat.metrics.metrics import LLMTokenUsage
 from pipecat.processors.aggregators.llm_response import LLMUserContextAggregator, LLMAssistantContextAggregator
 
 from pipecat.processors.aggregators.openai_llm_context import (
@@ -83,7 +84,7 @@ class BaseOpenAILLMService(LLMService):
 
     def __init__(self, *, model: str, api_key=None, base_url=None, **kwargs):
         super().__init__(**kwargs)
-        self._model: str = model
+        self.set_model_name(model)
         self._client = self.create_client(api_key=api_key, base_url=base_url, **kwargs)
 
     def create_client(self, api_key=None, base_url=None, **kwargs):
@@ -104,7 +105,7 @@ class BaseOpenAILLMService(LLMService):
             context: OpenAILLMContext,
             messages: List[ChatCompletionMessageParam]) -> AsyncStream[ChatCompletionChunk]:
         chunks = await self._client.chat.completions.create(
-            model=self._model,
+            model=self.model_name,
             stream=True,
             messages=messages,
             tools=context.tools,
@@ -148,13 +149,11 @@ class BaseOpenAILLMService(LLMService):
 
         async for chunk in chunk_stream:
             if chunk.usage:
-                tokens = {
-                    "processor": self.name,
-                    "model": self._model,
-                    "prompt_tokens": chunk.usage.prompt_tokens,
-                    "completion_tokens": chunk.usage.completion_tokens,
-                    "total_tokens": chunk.usage.total_tokens
-                }
+                tokens = LLMTokenUsage(
+                    prompt_tokens=chunk.usage.prompt_tokens,
+                    completion_tokens=chunk.usage.completion_tokens,
+                    total_tokens=chunk.usage.total_tokens
+                )
                 await self.start_llm_usage_metrics(tokens)
 
             if len(chunk.choices) == 0:
@@ -223,7 +222,7 @@ class BaseOpenAILLMService(LLMService):
             context = OpenAILLMContext.from_image_frame(frame)
         elif isinstance(frame, LLMModelUpdateFrame):
             logger.debug(f"Switching LLM model to: [{frame.model}]")
-            self._model = frame.model
+            self.set_model_name(frame.model)
         else:
             await self.push_frame(frame, direction)
 
@@ -273,7 +272,7 @@ class OpenAIImageGenService(ImageGenService):
         model: str = "dall-e-3",
     ):
         super().__init__()
-        self._model = model
+        self.set_model_name(model)
         self._image_size = image_size
         self._client = AsyncOpenAI(api_key=api_key)
         self._aiohttp_session = aiohttp_session
@@ -283,7 +282,7 @@ class OpenAIImageGenService(ImageGenService):
 
         image = await self._client.images.generate(
             prompt=prompt,
-            model=self._model,
+            model=self.model_name,
             n=1,
             size=self._image_size
         )
@@ -325,7 +324,7 @@ class OpenAITTSService(TTSService):
         super().__init__(sample_rate=sample_rate, **kwargs)
 
         self._voice: ValidVoice = VALID_VOICES.get(voice, "alloy")
-        self._model = model
+        self.set_model_name(model)
         self._sample_rate = sample_rate
 
         self._client = AsyncOpenAI(api_key=api_key)
@@ -348,7 +347,7 @@ class OpenAITTSService(TTSService):
 
             async with self._client.audio.speech.with_streaming_response.create(
                     input=text,
-                    model=self._model,
+                    model=self.model_name,
                     voice=self._voice,
                     response_format="pcm",
             ) as r:
diff --git a/src/pipecat/services/openpipe.py b/src/pipecat/services/openpipe.py
index ada7824fb..e4e14dc15 100644
--- a/src/pipecat/services/openpipe.py
+++ b/src/pipecat/services/openpipe.py
@@ -60,7 +60,7 @@ class OpenPipeLLMService(BaseOpenAILLMService):
             context: OpenAILLMContext,
             messages: List[ChatCompletionMessageParam]) -> AsyncStream[ChatCompletionChunk]:
         chunks = await self._client.chat.completions.create(
-            model=self._model,
+            model=self.model_name,
             stream=True,
             messages=messages,
             openpipe={
diff --git a/src/pipecat/services/together.py b/src/pipecat/services/together.py
index 49759cb01..004236ac8 100644
--- a/src/pipecat/services/together.py
+++ b/src/pipecat/services/together.py
@@ -18,9 +18,7 @@ from pipecat.frames.frames import (
     Frame,
     LLMModelUpdateFrame,
     TextFrame,
-    VisionImageRawFrame,
     UserImageRequestFrame,
-    UserImageRawFrame,
     LLMMessagesFrame,
     LLMFullResponseStartFrame,
     LLMFullResponseEndFrame,
@@ -28,6 +26,7 @@ from pipecat.frames.frames import (
     FunctionCallInProgressFrame,
     StartInterruptionFrame
 )
+from pipecat.metrics.metrics import LLMTokenUsage
 from pipecat.processors.frame_processor import FrameDirection
 from pipecat.services.ai_services import LLMService
 from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext, OpenAILLMContextFrame
@@ -69,7 +68,7 @@ class TogetherLLMService(LLMService):
             **kwargs):
         super().__init__(**kwargs)
         self._client = AsyncTogether(api_key=api_key)
-        self._model = model
+        self.set_model_name(model)
         self._max_tokens = max_tokens
 
     def can_generate_metrics(self) -> bool:
@@ -95,7 +94,7 @@ class TogetherLLMService(LLMService):
 
             stream = await self._client.chat.completions.create(
                 messages=context.messages,
-                model=self._model,
+                model=self.model_name,
                 max_tokens=self._max_tokens,
                 stream=True,
             )
@@ -108,13 +107,11 @@ class TogetherLLMService(LLMService):
             async for chunk in stream:
                 # logger.debug(f"Together LLM event: {chunk}")
                 if chunk.usage:
-                    tokens = {
-                        "processor": self.name,
-                        "model": self._model,
-                        "prompt_tokens": chunk.usage.prompt_tokens,
-                        "completion_tokens": chunk.usage.completion_tokens,
-                        "total_tokens": chunk.usage.total_tokens
-                    }
+                    tokens = LLMTokenUsage(
+                        prompt_tokens=chunk.usage.prompt_tokens,
+                        completion_tokens=chunk.usage.completion_tokens,
+                        total_tokens=chunk.usage.total_tokens
+                    )
                     await self.start_llm_usage_metrics(tokens)
 
                 if len(chunk.choices) == 0:
@@ -156,7 +153,7 @@ class TogetherLLMService(LLMService):
             context = TogetherLLMContext.from_messages(frame.messages)
         elif isinstance(frame, LLMModelUpdateFrame):
             logger.debug(f"Switching LLM model to: [{frame.model}]")
-            self._model = frame.model
+            self.set_model_name(frame.model)
         else:
             await self.push_frame(frame, direction)
 
diff --git a/src/pipecat/services/whisper.py b/src/pipecat/services/whisper.py
index 04f357a94..9f54f9ca0 100644
--- a/src/pipecat/services/whisper.py
+++ b/src/pipecat/services/whisper.py
@@ -52,7 +52,7 @@ class WhisperSTTService(SegmentedSTTService):
         super().__init__(**kwargs)
         self._device: str = device
         self._compute_type = compute_type
-        self._model_name: str | Model = model
+        self.set_model_name(model if isinstance(model, str) else model.value)
         self._no_speech_prob = no_speech_prob
         self._model: WhisperModel | None = None
         self._load()
@@ -65,7 +65,7 @@ class WhisperSTTService(SegmentedSTTService):
         this model is being run, it will take time to download."""
         logger.debug("Loading Whisper model...")
         self._model = WhisperModel(
-            self._model_name.value if isinstance(self._model_name, Enum) else self._model_name,
+            self.model_name,
             device=self._device,
             compute_type=self._compute_type)
         logger.debug("Loaded Whisper model")
diff --git a/src/pipecat/transports/services/daily.py b/src/pipecat/transports/services/daily.py
index 2a45adf36..e28fe6083 100644
--- a/src/pipecat/transports/services/daily.py
+++ b/src/pipecat/transports/services/daily.py
@@ -35,6 +35,7 @@ from pipecat.frames.frames import (
     TransportMessageFrame,
     UserImageRawFrame,
     UserImageRequestFrame)
+from pipecat.metrics.metrics import LLMUsageMetricsData, ProcessingMetricsData, TTFBMetricsData, TTSUsageMetricsData
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.transcriptions.language import Language
 from pipecat.transports.base_input import BaseInputTransport
@@ -731,14 +732,23 @@ class DailyOutputTransport(BaseOutputTransport):
 
     async def send_metrics(self, frame: MetricsFrame):
         metrics = {}
-        if frame.ttfb:
-            metrics["ttfb"] = frame.ttfb
-        if frame.processing:
-            metrics["processing"] = frame.processing
-        if frame.tokens:
-            metrics["tokens"] = frame.tokens
-        if frame.characters:
-            metrics["characters"] = frame.characters
+        for d in frame.data:
+            if isinstance(d, TTFBMetricsData):
+                if "ttfb" not in metrics:
+                    metrics["ttfb"] = []
+                metrics["ttfb"].append(d.model_dump())
+            elif isinstance(d, ProcessingMetricsData):
+                if "processing" not in metrics:
+                    metrics["processing"] = []
+                metrics["processing"].append(d.model_dump())
+            elif isinstance(d, LLMUsageMetricsData):
+                if "tokens" not in metrics:
+                    metrics["tokens"] = []
+                metrics["tokens"].append(d.value.model_dump(exclude_none=True))
+            elif isinstance(d, TTSUsageMetricsData):
+                if "characters" not in metrics:
+                    metrics["characters"] = []
+                metrics["characters"].append(d.model_dump())
 
         message = DailyTransportMessageFrame(message={
             "type": "pipecat-metrics",

From 7e39d9ad3d8ee7b38cc32911cb8e97b64a42a8c1 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Thu, 19 Sep 2024 19:31:56 -0700
Subject: [PATCH 038/135] introduce input/output audio and image frames

We now distinguish between input and output audio and image frames. We introduce
`InputAudioRawFrame`, `OutputAudioRawFrame`, `InputImageRawFrame` and
`OutputImageRawFrame` (and other subclasses of those). The input frames usually
come from an input transport and are meant to be processed inside the pipeline
to generate new frames. However, the input frames will not be sent through an
output transport. The output frames can also be processed by any frame processor
in the pipeline and they are allowed to be sent by the output transport.
---
 CHANGELOG.md                                  |  9 ++
 examples/dialin-chatbot/requirements.txt      |  2 +-
 .../05a-local-sync-speech-and-image.py        | 12 ++-
 examples/foundational/06a-image-sync.py       | 13 ++-
 examples/foundational/09-mirror.py            | 25 ++++-
 examples/foundational/09a-local-mirror.py     | 23 ++++-
 examples/foundational/11-sound-effects.py     |  6 +-
 examples/moondream-chatbot/bot.py             | 11 ++-
 examples/moondream-chatbot/requirements.txt   |  2 +-
 examples/patient-intake/bot.py                |  7 +-
 examples/patient-intake/requirements.txt      |  2 +-
 examples/simple-chatbot/bot.py                | 12 ++-
 examples/simple-chatbot/requirements.txt      |  2 +-
 .../storytelling-chatbot/requirements.txt     |  2 +-
 .../storytelling-chatbot/src/utils/helpers.py | 11 ++-
 examples/twilio-chatbot/README.md             |  2 +-
 examples/twilio-chatbot/bot.py                | 96 +++++++++----------
 examples/twilio-chatbot/requirements.txt      |  2 +-
 examples/websocket-server/bot.py              | 86 ++++++++---------
 examples/websocket-server/frames.proto        |  1 +
 examples/websocket-server/requirements.txt    |  2 +-
 src/pipecat/frames/frames.proto               |  1 +
 src/pipecat/frames/frames.py                  | 78 ++++++++++-----
 src/pipecat/frames/protobufs/frames_pb2.py    | 12 +--
 .../processors/aggregators/llm_response.py    |  6 +-
 .../aggregators/openai_llm_context.py         |  6 +-
 .../aggregators/vision_image_frame.py         | 12 ++-
 .../processors/gstreamer/pipeline_source.py   | 12 +--
 src/pipecat/serializers/livekit.py            | 13 ++-
 src/pipecat/serializers/protobuf.py           | 24 +++--
 src/pipecat/serializers/twilio.py             |  9 +-
 src/pipecat/services/ai_services.py           |  3 +-
 src/pipecat/services/azure.py                 |  4 +-
 src/pipecat/services/cartesia.py              |  6 +-
 src/pipecat/services/deepgram.py              |  5 +-
 src/pipecat/services/elevenlabs.py            |  4 +-
 src/pipecat/services/lmnt.py                  |  4 +-
 src/pipecat/services/openai.py                |  4 +-
 src/pipecat/services/playht.py                |  8 +-
 src/pipecat/services/together.py              | 12 +--
 src/pipecat/services/xtts.py                  |  6 +-
 src/pipecat/transports/base_input.py          |  6 +-
 src/pipecat/transports/base_output.py         | 39 ++++----
 src/pipecat/transports/local/audio.py         |  8 +-
 src/pipecat/transports/local/tk.py            | 13 ++-
 .../transports/network/fastapi_websocket.py   | 18 +++-
 .../transports/network/websocket_server.py    |  9 +-
 src/pipecat/transports/services/daily.py      | 20 ++--
 48 files changed, 410 insertions(+), 260 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 985834aba..1a89a97b8 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -63,6 +63,15 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Changed
 
+- We now distinguish between input and output audio and image frames. We
+  introduce `InputAudioRawFrame`, `OutputAudioRawFrame`, `InputImageRawFrame`
+  and `OutputImageRawFrame` (and other subclasses of those). The input frames
+  usually come from an input transport and are meant to be processed inside the
+  pipeline to generate new frames. However, the input frames will not be sent
+  through an output transport. The output frames can also be processed by any
+  frame processor in the pipeline and they are allowed to be sent by the output
+  transport.
+
 - `ParallelTask` has been renamed to `SyncParallelPipeline`. A
   `SyncParallelPipeline` is a frame processor that contains a list of different
   pipelines to be executed concurrently. The difference between a
diff --git a/examples/dialin-chatbot/requirements.txt b/examples/dialin-chatbot/requirements.txt
index e59a9c3d2..1e15004b1 100644
--- a/examples/dialin-chatbot/requirements.txt
+++ b/examples/dialin-chatbot/requirements.txt
@@ -1,4 +1,4 @@
-pipecat-ai[daily,openai,silero]
+pipecat-ai[daily,elevenlabs,openai,silero]
 fastapi
 uvicorn
 python-dotenv
diff --git a/examples/foundational/05a-local-sync-speech-and-image.py b/examples/foundational/05a-local-sync-speech-and-image.py
index 66a6e7f57..d9a0e792e 100644
--- a/examples/foundational/05a-local-sync-speech-and-image.py
+++ b/examples/foundational/05a-local-sync-speech-and-image.py
@@ -11,7 +11,13 @@ import sys
 
 import tkinter as tk
 
-from pipecat.frames.frames import AudioRawFrame, Frame, URLImageRawFrame, LLMMessagesFrame, TextFrame
+from pipecat.frames.frames import (
+    Frame,
+    OutputAudioRawFrame,
+    TTSAudioRawFrame,
+    URLImageRawFrame,
+    LLMMessagesFrame,
+    TextFrame)
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.sync_parallel_pipeline import SyncParallelPipeline
@@ -65,9 +71,9 @@ async def main():
                 async def process_frame(self, frame: Frame, direction: FrameDirection):
                     await super().process_frame(frame, direction)
 
-                    if isinstance(frame, AudioRawFrame):
+                    if isinstance(frame, TTSAudioRawFrame):
                         self.audio.extend(frame.audio)
-                        self.frame = AudioRawFrame(
+                        self.frame = OutputAudioRawFrame(
                             bytes(self.audio), frame.sample_rate, frame.num_channels)
 
             class ImageGrabber(FrameProcessor):
diff --git a/examples/foundational/06a-image-sync.py b/examples/foundational/06a-image-sync.py
index 6b3e58cf7..db48b709e 100644
--- a/examples/foundational/06a-image-sync.py
+++ b/examples/foundational/06a-image-sync.py
@@ -11,7 +11,7 @@ import sys
 
 from PIL import Image
 
-from pipecat.frames.frames import ImageRawFrame, Frame, SystemFrame, TextFrame
+from pipecat.frames.frames import Frame, OutputImageRawFrame, SystemFrame, TextFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
@@ -52,9 +52,16 @@ class ImageSyncAggregator(FrameProcessor):
         await super().process_frame(frame, direction)
 
         if not isinstance(frame, SystemFrame) and direction == FrameDirection.DOWNSTREAM:
-            await self.push_frame(ImageRawFrame(image=self._speaking_image_bytes, size=(1024, 1024), format=self._speaking_image_format))
+            await self.push_frame(OutputImageRawFrame(
+                image=self._speaking_image_bytes,
+                size=(1024, 1024),
+                format=self._speaking_image_format)
+            )
             await self.push_frame(frame)
-            await self.push_frame(ImageRawFrame(image=self._waiting_image_bytes, size=(1024, 1024), format=self._waiting_image_format))
+            await self.push_frame(OutputImageRawFrame(
+                image=self._waiting_image_bytes,
+                size=(1024, 1024),
+                format=self._waiting_image_format))
         else:
             await self.push_frame(frame)
 
diff --git a/examples/foundational/09-mirror.py b/examples/foundational/09-mirror.py
index 8f5f1073b..bb6253deb 100644
--- a/examples/foundational/09-mirror.py
+++ b/examples/foundational/09-mirror.py
@@ -8,9 +8,11 @@ import aiohttp
 import asyncio
 import sys
 
+from pipecat.frames.frames import Frame, InputAudioRawFrame, InputImageRawFrame, OutputAudioRawFrame, OutputImageRawFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
+from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.transports.services.daily import DailyTransport, DailyParams
 
 from runner import configure
@@ -24,6 +26,27 @@ logger.remove(0)
 logger.add(sys.stderr, level="DEBUG")
 
 
+class MirrorProcessor(FrameProcessor):
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        if isinstance(frame, InputAudioRawFrame):
+            await self.push_frame(OutputAudioRawFrame(
+                audio=frame.audio,
+                sample_rate=frame.sample_rate,
+                num_channels=frame.num_channels)
+            )
+        elif isinstance(frame, InputImageRawFrame):
+            await self.push_frame(OutputImageRawFrame(
+                image=frame.image,
+                size=frame.size,
+                format=frame.format)
+            )
+        else:
+            await self.push_frame(frame, direction)
+
+
 async def main():
     async with aiohttp.ClientSession() as session:
         (room_url, token) = await configure(session)
@@ -44,7 +67,7 @@ async def main():
         async def on_first_participant_joined(transport, participant):
             transport.capture_participant_video(participant["id"])
 
-        pipeline = Pipeline([transport.input(), transport.output()])
+        pipeline = Pipeline([transport.input(), MirrorProcessor(), transport.output()])
 
         runner = PipelineRunner()
 
diff --git a/examples/foundational/09a-local-mirror.py b/examples/foundational/09a-local-mirror.py
index d657a3631..afc77470d 100644
--- a/examples/foundational/09a-local-mirror.py
+++ b/examples/foundational/09a-local-mirror.py
@@ -10,9 +10,11 @@ import sys
 
 import tkinter as tk
 
+from pipecat.frames.frames import Frame, InputAudioRawFrame, InputImageRawFrame, OutputAudioRawFrame, OutputImageRawFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
+from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.transports.base_transport import TransportParams
 from pipecat.transports.local.tk import TkLocalTransport
 from pipecat.transports.services.daily import DailyParams, DailyTransport
@@ -27,6 +29,25 @@ load_dotenv(override=True)
 logger.remove(0)
 logger.add(sys.stderr, level="DEBUG")
 
+class MirrorProcessor(FrameProcessor):
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        if isinstance(frame, InputAudioRawFrame):
+            await self.push_frame(OutputAudioRawFrame(
+                audio=frame.audio,
+                sample_rate=frame.sample_rate,
+                num_channels=frame.num_channels)
+            )
+        elif isinstance(frame, InputImageRawFrame):
+            await self.push_frame(OutputImageRawFrame(
+                image=frame.image,
+                size=frame.size,
+                format=frame.format)
+            )
+        else:
+            await self.push_frame(frame, direction)
 
 async def main():
     async with aiohttp.ClientSession() as session:
@@ -52,7 +73,7 @@ async def main():
         async def on_first_participant_joined(transport, participant):
             transport.capture_participant_video(participant["id"])
 
-        pipeline = Pipeline([daily_transport.input(), tk_transport.output()])
+        pipeline = Pipeline([daily_transport.input(), MirrorProcessor(), tk_transport.output()])
 
         task = PipelineTask(pipeline)
 
diff --git a/examples/foundational/11-sound-effects.py b/examples/foundational/11-sound-effects.py
index 9dc4dc99b..21b03bedf 100644
--- a/examples/foundational/11-sound-effects.py
+++ b/examples/foundational/11-sound-effects.py
@@ -12,9 +12,9 @@ import wave
 
 from pipecat.frames.frames import (
     Frame,
-    AudioRawFrame,
     LLMFullResponseEndFrame,
     LLMMessagesFrame,
+    OutputAudioRawFrame,
 )
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
@@ -53,8 +53,8 @@ for file in sound_files:
     filename = os.path.splitext(os.path.basename(full_path))[0]
     # Open the image and convert it to bytes
     with wave.open(full_path) as audio_file:
-        sounds[file] = AudioRawFrame(audio_file.readframes(-1),
-                                     audio_file.getframerate(), audio_file.getnchannels())
+        sounds[file] = OutputAudioRawFrame(audio_file.readframes(-1),
+                                           audio_file.getframerate(), audio_file.getnchannels())
 
 
 class OutboundSoundEffectWrapper(FrameProcessor):
diff --git a/examples/moondream-chatbot/bot.py b/examples/moondream-chatbot/bot.py
index 32bbf7e6b..d14a5f016 100644
--- a/examples/moondream-chatbot/bot.py
+++ b/examples/moondream-chatbot/bot.py
@@ -13,10 +13,11 @@ from PIL import Image
 
 from pipecat.frames.frames import (
     ImageRawFrame,
+    OutputImageRawFrame,
     SpriteFrame,
     Frame,
     LLMMessagesFrame,
-    AudioRawFrame,
+    TTSAudioRawFrame,
     TTSStoppedFrame,
     TextFrame,
     UserImageRawFrame,
@@ -59,7 +60,11 @@ for i in range(1, 26):
     # Get the filename without the extension to use as the dictionary key
     # Open the image and convert it to bytes
     with Image.open(full_path) as img:
-        sprites.append(ImageRawFrame(image=img.tobytes(), size=img.size, format=img.format))
+        sprites.append(OutputImageRawFrame(
+            image=img.tobytes(),
+            size=img.size,
+            format=img.format)
+        )
 
 flipped = sprites[::-1]
 sprites.extend(flipped)
@@ -82,7 +87,7 @@ class TalkingAnimation(FrameProcessor):
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
-        if isinstance(frame, AudioRawFrame):
+        if isinstance(frame, TTSAudioRawFrame):
             if not self._is_talking:
                 await self.push_frame(talking_frame)
                 self._is_talking = True
diff --git a/examples/moondream-chatbot/requirements.txt b/examples/moondream-chatbot/requirements.txt
index 11132e136..08fd27cb7 100644
--- a/examples/moondream-chatbot/requirements.txt
+++ b/examples/moondream-chatbot/requirements.txt
@@ -1,4 +1,4 @@
 python-dotenv
 fastapi[all]
 uvicorn
-pipecat-ai[daily,moondream,openai,silero]
+pipecat-ai[daily,cartesia,moondream,openai,silero]
diff --git a/examples/patient-intake/bot.py b/examples/patient-intake/bot.py
index 7dc404c52..33ca9e26d 100644
--- a/examples/patient-intake/bot.py
+++ b/examples/patient-intake/bot.py
@@ -10,7 +10,7 @@ import os
 import sys
 import wave
 
-from pipecat.frames.frames import AudioRawFrame
+from pipecat.frames.frames import OutputAudioRawFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -49,8 +49,9 @@ for file in sound_files:
     filename = os.path.splitext(os.path.basename(full_path))[0]
     # Open the sound and convert it to bytes
     with wave.open(full_path) as audio_file:
-        sounds[file] = AudioRawFrame(audio_file.readframes(-1),
-                                     audio_file.getframerate(), audio_file.getnchannels())
+        sounds[file] = OutputAudioRawFrame(audio_file.readframes(-1),
+                                           audio_file.getframerate(),
+                                           audio_file.getnchannels())
 
 
 class IntakeProcessor:
diff --git a/examples/patient-intake/requirements.txt b/examples/patient-intake/requirements.txt
index a7a8729df..e8bfcd8e4 100644
--- a/examples/patient-intake/requirements.txt
+++ b/examples/patient-intake/requirements.txt
@@ -1,4 +1,4 @@
 python-dotenv
 fastapi[all]
 uvicorn
-pipecat-ai[daily,openai,silero]
+pipecat-ai[daily,cartesia,openai,silero]
diff --git a/examples/simple-chatbot/bot.py b/examples/simple-chatbot/bot.py
index 1664e47fb..f179dfeb5 100644
--- a/examples/simple-chatbot/bot.py
+++ b/examples/simple-chatbot/bot.py
@@ -16,11 +16,11 @@ from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_response import LLMAssistantResponseAggregator, LLMUserResponseAggregator
 from pipecat.frames.frames import (
-    AudioRawFrame,
-    ImageRawFrame,
+    OutputImageRawFrame,
     SpriteFrame,
     Frame,
     LLMMessagesFrame,
+    TTSAudioRawFrame,
     TTSStoppedFrame
 )
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
@@ -49,7 +49,11 @@ for i in range(1, 26):
     # Get the filename without the extension to use as the dictionary key
     # Open the image and convert it to bytes
     with Image.open(full_path) as img:
-        sprites.append(ImageRawFrame(image=img.tobytes(), size=img.size, format=img.format))
+        sprites.append(OutputImageRawFrame(
+            image=img.tobytes(),
+            size=img.size,
+            format=img.format)
+        )
 
 flipped = sprites[::-1]
 sprites.extend(flipped)
@@ -72,7 +76,7 @@ class TalkingAnimation(FrameProcessor):
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
-        if isinstance(frame, AudioRawFrame):
+        if isinstance(frame, TTSAudioRawFrame):
             if not self._is_talking:
                 await self.push_frame(talking_frame)
                 self._is_talking = True
diff --git a/examples/simple-chatbot/requirements.txt b/examples/simple-chatbot/requirements.txt
index a7a8729df..a4e6aa1db 100644
--- a/examples/simple-chatbot/requirements.txt
+++ b/examples/simple-chatbot/requirements.txt
@@ -1,4 +1,4 @@
 python-dotenv
 fastapi[all]
 uvicorn
-pipecat-ai[daily,openai,silero]
+pipecat-ai[daily,elevenlabs,openai,silero]
diff --git a/examples/storytelling-chatbot/requirements.txt b/examples/storytelling-chatbot/requirements.txt
index 663f78a76..0cebe6edb 100644
--- a/examples/storytelling-chatbot/requirements.txt
+++ b/examples/storytelling-chatbot/requirements.txt
@@ -2,4 +2,4 @@ async_timeout
 fastapi
 uvicorn
 python-dotenv
-pipecat-ai[daily,openai,fal]
+pipecat-ai[daily,elevenlabs,openai,fal]
diff --git a/examples/storytelling-chatbot/src/utils/helpers.py b/examples/storytelling-chatbot/src/utils/helpers.py
index 2c576fdff..743a04c97 100644
--- a/examples/storytelling-chatbot/src/utils/helpers.py
+++ b/examples/storytelling-chatbot/src/utils/helpers.py
@@ -2,7 +2,7 @@ import os
 import wave
 from PIL import Image
 
-from pipecat.frames.frames import AudioRawFrame, ImageRawFrame
+from pipecat.frames.frames import OutputAudioRawFrame, OutputImageRawFrame
 
 script_dir = os.path.dirname(__file__)
 
@@ -16,7 +16,8 @@ def load_images(image_files):
         filename = os.path.splitext(os.path.basename(full_path))[0]
         # Open the image and convert it to bytes
         with Image.open(full_path) as img:
-            images[filename] = ImageRawFrame(image=img.tobytes(), size=img.size, format=img.format)
+            images[filename] = OutputImageRawFrame(
+                image=img.tobytes(), size=img.size, format=img.format)
     return images
 
 
@@ -30,8 +31,8 @@ def load_sounds(sound_files):
         filename = os.path.splitext(os.path.basename(full_path))[0]
         # Open the sound and convert it to bytes
         with wave.open(full_path) as audio_file:
-            sounds[filename] = AudioRawFrame(audio=audio_file.readframes(-1),
-                                             sample_rate=audio_file.getframerate(),
-                                             num_channels=audio_file.getnchannels())
+            sounds[filename] = OutputAudioRawFrame(audio=audio_file.readframes(-1),
+                                                   sample_rate=audio_file.getframerate(),
+                                                   num_channels=audio_file.getnchannels())
 
     return sounds
diff --git a/examples/twilio-chatbot/README.md b/examples/twilio-chatbot/README.md
index 5d5d2385a..fdea359f9 100644
--- a/examples/twilio-chatbot/README.md
+++ b/examples/twilio-chatbot/README.md
@@ -55,7 +55,7 @@ This project is a FastAPI-based chatbot that integrates with Twilio to handle We
 2. **Update the Twilio Webhook**:
     Copy the ngrok URL and update your Twilio phone number webhook URL to `http://<ngrok_url>/start_call`.
 
-3. **Update the streams.xml**:
+3. **Update streams.xml**:
     Copy the ngrok URL and update templates/streams.xml with `wss://<ngrok_url>/ws`.
 
 ## Running the Application
diff --git a/examples/twilio-chatbot/bot.py b/examples/twilio-chatbot/bot.py
index b7376e084..5b83139f9 100644
--- a/examples/twilio-chatbot/bot.py
+++ b/examples/twilio-chatbot/bot.py
@@ -1,4 +1,3 @@
-import aiohttp
 import os
 import sys
 
@@ -27,63 +26,62 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 async def run_bot(websocket_client, stream_sid):
-    async with aiohttp.ClientSession() as session:
-        transport = FastAPIWebsocketTransport(
-            websocket=websocket_client,
-            params=FastAPIWebsocketParams(
-                audio_out_enabled=True,
-                add_wav_header=False,
-                vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer(),
-                vad_audio_passthrough=True,
-                serializer=TwilioFrameSerializer(stream_sid)
-            )
+    transport = FastAPIWebsocketTransport(
+        websocket=websocket_client,
+        params=FastAPIWebsocketParams(
+            audio_out_enabled=True,
+            add_wav_header=False,
+            vad_enabled=True,
+            vad_analyzer=SileroVADAnalyzer(),
+            vad_audio_passthrough=True,
+            serializer=TwilioFrameSerializer(stream_sid)
         )
+    )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
+    llm = OpenAILLMService(
+        api_key=os.getenv("OPENAI_API_KEY"),
+        model="gpt-4o")
 
-        stt = DeepgramSTTService(api_key=os.getenv('DEEPGRAM_API_KEY'))
+    stt = DeepgramSTTService(api_key=os.getenv('DEEPGRAM_API_KEY'))
 
-        tts = CartesiaTTSService(
-            api_key=os.getenv("CARTESIA_API_KEY"),
-            voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
-        )
+    tts = CartesiaTTSService(
+        api_key=os.getenv("CARTESIA_API_KEY"),
+        voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
+    )
 
-        messages = [
-            {
-                "role": "system",
-                "content": "You are a helpful LLM in an audio call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
-            },
-        ]
+    messages = [
+        {
+            "role": "system",
+            "content": "You are a helpful LLM in an audio call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+        },
+    ]
 
-        tma_in = LLMUserResponseAggregator(messages)
-        tma_out = LLMAssistantResponseAggregator(messages)
+    tma_in = LLMUserResponseAggregator(messages)
+    tma_out = LLMAssistantResponseAggregator(messages)
 
-        pipeline = Pipeline([
-            transport.input(),   # Websocket input from client
-            stt,                 # Speech-To-Text
-            tma_in,              # User responses
-            llm,                 # LLM
-            tts,                 # Text-To-Speech
-            transport.output(),  # Websocket output to client
-            tma_out              # LLM responses
-        ])
+    pipeline = Pipeline([
+        transport.input(),   # Websocket input from client
+        stt,                 # Speech-To-Text
+        tma_in,              # User responses
+        llm,                 # LLM
+        tts,                 # Text-To-Speech
+        transport.output(),  # Websocket output to client
+        tma_out              # LLM responses
+    ])
 
-        task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
+    task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
 
-        @transport.event_handler("on_client_connected")
-        async def on_client_connected(transport, client):
-            # Kick off the conversation.
-            messages.append(
-                {"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+    @transport.event_handler("on_client_connected")
+    async def on_client_connected(transport, client):
+        # Kick off the conversation.
+        messages.append(
+            {"role": "system", "content": "Please introduce yourself to the user."})
+        await task.queue_frames([LLMMessagesFrame(messages)])
 
-        @transport.event_handler("on_client_disconnected")
-        async def on_client_disconnected(transport, client):
-            await task.queue_frames([EndFrame()])
+    @transport.event_handler("on_client_disconnected")
+    async def on_client_disconnected(transport, client):
+        await task.queue_frames([EndFrame()])
 
-        runner = PipelineRunner(handle_sigint=False)
+    runner = PipelineRunner(handle_sigint=False)
 
-        await runner.run(task)
+    await runner.run(task)
diff --git a/examples/twilio-chatbot/requirements.txt b/examples/twilio-chatbot/requirements.txt
index f0456fcd5..eefaca888 100644
--- a/examples/twilio-chatbot/requirements.txt
+++ b/examples/twilio-chatbot/requirements.txt
@@ -1,4 +1,4 @@
-pipecat-ai[daily,openai,silero,deepgram]
+pipecat-ai[daily,cartesia,openai,silero,deepgram]
 fastapi
 uvicorn
 python-dotenv
diff --git a/examples/websocket-server/bot.py b/examples/websocket-server/bot.py
index 29a99614f..61d285fa8 100644
--- a/examples/websocket-server/bot.py
+++ b/examples/websocket-server/bot.py
@@ -4,7 +4,6 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-import aiohttp
 import asyncio
 import os
 import sys
@@ -33,60 +32,59 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 async def main():
-    async with aiohttp.ClientSession() as session:
-        transport = WebsocketServerTransport(
-            params=WebsocketServerParams(
-                audio_out_enabled=True,
-                add_wav_header=True,
-                vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer(),
-                vad_audio_passthrough=True
-            )
+    transport = WebsocketServerTransport(
+        params=WebsocketServerParams(
+            audio_out_enabled=True,
+            add_wav_header=True,
+            vad_enabled=True,
+            vad_analyzer=SileroVADAnalyzer(),
+            vad_audio_passthrough=True
         )
+    )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
+    llm = OpenAILLMService(
+        api_key=os.getenv("OPENAI_API_KEY"),
+        model="gpt-4o")
 
-        stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
+    stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
 
-        tts = CartesiaTTSService(
-            api_key=os.getenv("CARTESIA_API_KEY"),
-            voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
-        )
+    tts = CartesiaTTSService(
+        api_key=os.getenv("CARTESIA_API_KEY"),
+        voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
+    )
 
-        messages = [
-            {
-                "role": "system",
-                "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
-            },
-        ]
+    messages = [
+        {
+            "role": "system",
+            "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+        },
+    ]
 
-        tma_in = LLMUserResponseAggregator(messages)
-        tma_out = LLMAssistantResponseAggregator(messages)
+    tma_in = LLMUserResponseAggregator(messages)
+    tma_out = LLMAssistantResponseAggregator(messages)
 
-        pipeline = Pipeline([
-            transport.input(),   # Websocket input from client
-            stt,                 # Speech-To-Text
-            tma_in,              # User responses
-            llm,                 # LLM
-            tts,                 # Text-To-Speech
-            transport.output(),  # Websocket output to client
-            tma_out              # LLM responses
-        ])
+    pipeline = Pipeline([
+        transport.input(),   # Websocket input from client
+        stt,                 # Speech-To-Text
+        tma_in,              # User responses
+        llm,                 # LLM
+        tts,                 # Text-To-Speech
+        transport.output(),  # Websocket output to client
+        tma_out              # LLM responses
+    ])
 
-        task = PipelineTask(pipeline)
+    task = PipelineTask(pipeline)
 
-        @transport.event_handler("on_client_connected")
-        async def on_client_connected(transport, client):
-            # Kick off the conversation.
-            messages.append(
-                {"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+    @transport.event_handler("on_client_connected")
+    async def on_client_connected(transport, client):
+        # Kick off the conversation.
+        messages.append(
+            {"role": "system", "content": "Please introduce yourself to the user."})
+        await task.queue_frames([LLMMessagesFrame(messages)])
 
-        runner = PipelineRunner()
+    runner = PipelineRunner()
 
-        await runner.run(task)
+    await runner.run(task)
 
 if __name__ == "__main__":
     asyncio.run(main())
diff --git a/examples/websocket-server/frames.proto b/examples/websocket-server/frames.proto
index 5c5d81d4d..4c58d2a34 100644
--- a/examples/websocket-server/frames.proto
+++ b/examples/websocket-server/frames.proto
@@ -24,6 +24,7 @@ message AudioRawFrame {
   bytes audio = 3;
   uint32 sample_rate = 4;
   uint32 num_channels = 5;
+  optional uint64 pts = 6;
 }
 
 message TranscriptionFrame {
diff --git a/examples/websocket-server/requirements.txt b/examples/websocket-server/requirements.txt
index 77e5b9e91..0815c6b8a 100644
--- a/examples/websocket-server/requirements.txt
+++ b/examples/websocket-server/requirements.txt
@@ -1,2 +1,2 @@
 python-dotenv
-pipecat-ai[openai,silero,websocket,whisper]
+pipecat-ai[cartesia,openai,silero,websocket,whisper]
diff --git a/src/pipecat/frames/frames.proto b/src/pipecat/frames/frames.proto
index 5c5d81d4d..4c58d2a34 100644
--- a/src/pipecat/frames/frames.proto
+++ b/src/pipecat/frames/frames.proto
@@ -24,6 +24,7 @@ message AudioRawFrame {
   bytes audio = 3;
   uint32 sample_rate = 4;
   uint32 num_channels = 5;
+  optional uint64 pts = 6;
 }
 
 message TranscriptionFrame {
diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py
index 4d207fecd..d45487150 100644
--- a/src/pipecat/frames/frames.py
+++ b/src/pipecat/frames/frames.py
@@ -41,10 +41,7 @@ class DataFrame(Frame):
 
 @dataclass
 class AudioRawFrame(DataFrame):
-    """A chunk of audio. Will be played by the transport if the transport's
-    microphone has been enabled.
-
-    """
+    """A chunk of audio."""
     audio: bytes
     sample_rate: int
     num_channels: int
@@ -58,6 +55,31 @@ class AudioRawFrame(DataFrame):
         return f"{self.name}(pts: {pts}, size: {len(self.audio)}, frames: {self.num_frames}, sample_rate: {self.sample_rate}, channels: {self.num_channels})"
 
 
+@dataclass
+class InputAudioRawFrame(AudioRawFrame):
+    """A chunk of audio usually coming from an input transport.
+
+    """
+    pass
+
+
+@dataclass
+class OutputAudioRawFrame(AudioRawFrame):
+    """A chunk of audio. Will be played by the output transport if the
+    transport's microphone has been enabled.
+
+    """
+    pass
+
+
+@dataclass
+class TTSAudioRawFrame(OutputAudioRawFrame):
+    """A chunk of output audio generated by a TTS service.
+
+    """
+    pass
+
+
 @dataclass
 class ImageRawFrame(DataFrame):
     """An image. Will be shown by the transport if the transport's camera is
@@ -74,20 +96,30 @@ class ImageRawFrame(DataFrame):
 
 
 @dataclass
-class URLImageRawFrame(ImageRawFrame):
-    """An image with an associated URL. Will be shown by the transport if the
-    transport's camera is enabled.
-
-    """
-    url: str | None
-
-    def __str__(self):
-        pts = format_pts(self.pts)
-        return f"{self.name}(pts: {pts}, url: {self.url}, size: {self.size}, format: {self.format})"
+class InputImageRawFrame(ImageRawFrame):
+    pass
 
 
 @dataclass
-class VisionImageRawFrame(ImageRawFrame):
+class OutputImageRawFrame(ImageRawFrame):
+    pass
+
+
+@dataclass
+class UserImageRawFrame(InputImageRawFrame):
+    """An image associated to a user. Will be shown by the transport if the
+    transport's camera is enabled.
+
+    """
+    user_id: str
+
+    def __str__(self):
+        pts = format_pts(self.pts)
+        return f"{self.name}(pts: {pts}, user: {self.user_id}, size: {self.size}, format: {self.format})"
+
+
+@dataclass
+class VisionImageRawFrame(InputImageRawFrame):
     """An image with an associated text to ask for a description of it. Will be
     shown by the transport if the transport's camera is enabled.
 
@@ -100,16 +132,16 @@ class VisionImageRawFrame(ImageRawFrame):
 
 
 @dataclass
-class UserImageRawFrame(ImageRawFrame):
-    """An image associated to a user. Will be shown by the transport if the
+class URLImageRawFrame(OutputImageRawFrame):
+    """An image with an associated URL. Will be shown by the transport if the
     transport's camera is enabled.
 
     """
-    user_id: str
+    url: str | None
 
     def __str__(self):
         pts = format_pts(self.pts)
-        return f"{self.name}(pts: {pts}, user: {self.user_id}, size: {self.size}, format: {self.format})"
+        return f"{self.name}(pts: {pts}, url: {self.url}, size: {self.size}, format: {self.format})"
 
 
 @dataclass
@@ -420,10 +452,10 @@ class BotSpeakingFrame(ControlFrame):
 @dataclass
 class TTSStartedFrame(ControlFrame):
     """Used to indicate the beginning of a TTS response. Following
-    AudioRawFrames are part of the TTS response until an TTSStoppedFrame. These
-    frames can be used for aggregating audio frames in a transport to optimize
-    the size of frames sent to the session, without needing to control this in
-    the TTS service.
+    TTSAudioRawFrames are part of the TTS response until an
+    TTSStoppedFrame. These frames can be used for aggregating audio frames in a
+    transport to optimize the size of frames sent to the session, without
+    needing to control this in the TTS service.
 
     """
     pass
diff --git a/src/pipecat/frames/protobufs/frames_pb2.py b/src/pipecat/frames/protobufs/frames_pb2.py
index 5040efc97..d58bc8baa 100644
--- a/src/pipecat/frames/protobufs/frames_pb2.py
+++ b/src/pipecat/frames/protobufs/frames_pb2.py
@@ -14,7 +14,7 @@ _sym_db = _symbol_database.Default()
 
 
 
-DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\x0c\x66rames.proto\x12\x07pipecat\"3\n\tTextFrame\x12\n\n\x02id\x18\x01 \x01(\x04\x12\x0c\n\x04name\x18\x02 \x01(\t\x12\x0c\n\x04text\x18\x03 \x01(\t\"c\n\rAudioRawFrame\x12\n\n\x02id\x18\x01 \x01(\x04\x12\x0c\n\x04name\x18\x02 \x01(\t\x12\r\n\x05\x61udio\x18\x03 \x01(\x0c\x12\x13\n\x0bsample_rate\x18\x04 \x01(\r\x12\x14\n\x0cnum_channels\x18\x05 \x01(\r\"`\n\x12TranscriptionFrame\x12\n\n\x02id\x18\x01 \x01(\x04\x12\x0c\n\x04name\x18\x02 \x01(\t\x12\x0c\n\x04text\x18\x03 \x01(\t\x12\x0f\n\x07user_id\x18\x04 \x01(\t\x12\x11\n\ttimestamp\x18\x05 \x01(\t\"\x93\x01\n\x05\x46rame\x12\"\n\x04text\x18\x01 \x01(\x0b\x32\x12.pipecat.TextFrameH\x00\x12\'\n\x05\x61udio\x18\x02 \x01(\x0b\x32\x16.pipecat.AudioRawFrameH\x00\x12\x34\n\rtranscription\x18\x03 \x01(\x0b\x32\x1b.pipecat.TranscriptionFrameH\x00\x42\x07\n\x05\x66rameb\x06proto3')
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\x0c\x66rames.proto\x12\x07pipecat\"3\n\tTextFrame\x12\n\n\x02id\x18\x01 \x01(\x04\x12\x0c\n\x04name\x18\x02 \x01(\t\x12\x0c\n\x04text\x18\x03 \x01(\t\"}\n\rAudioRawFrame\x12\n\n\x02id\x18\x01 \x01(\x04\x12\x0c\n\x04name\x18\x02 \x01(\t\x12\r\n\x05\x61udio\x18\x03 \x01(\x0c\x12\x13\n\x0bsample_rate\x18\x04 \x01(\r\x12\x14\n\x0cnum_channels\x18\x05 \x01(\r\x12\x10\n\x03pts\x18\x06 \x01(\x04H\x00\x88\x01\x01\x42\x06\n\x04_pts\"`\n\x12TranscriptionFrame\x12\n\n\x02id\x18\x01 \x01(\x04\x12\x0c\n\x04name\x18\x02 \x01(\t\x12\x0c\n\x04text\x18\x03 \x01(\t\x12\x0f\n\x07user_id\x18\x04 \x01(\t\x12\x11\n\ttimestamp\x18\x05 \x01(\t\"\x93\x01\n\x05\x46rame\x12\"\n\x04text\x18\x01 \x01(\x0b\x32\x12.pipecat.TextFrameH\x00\x12\'\n\x05\x61udio\x18\x02 \x01(\x0b\x32\x16.pipecat.AudioRawFrameH\x00\x12\x34\n\rtranscription\x18\x03 \x01(\x0b\x32\x1b.pipecat.TranscriptionFrameH\x00\x42\x07\n\x05\x66rameb\x06proto3')
 
 _globals = globals()
 _builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
@@ -24,9 +24,9 @@ if _descriptor._USE_C_DESCRIPTORS == False:
   _globals['_TEXTFRAME']._serialized_start=25
   _globals['_TEXTFRAME']._serialized_end=76
   _globals['_AUDIORAWFRAME']._serialized_start=78
-  _globals['_AUDIORAWFRAME']._serialized_end=177
-  _globals['_TRANSCRIPTIONFRAME']._serialized_start=179
-  _globals['_TRANSCRIPTIONFRAME']._serialized_end=275
-  _globals['_FRAME']._serialized_start=278
-  _globals['_FRAME']._serialized_end=425
+  _globals['_AUDIORAWFRAME']._serialized_end=203
+  _globals['_TRANSCRIPTIONFRAME']._serialized_start=205
+  _globals['_TRANSCRIPTIONFRAME']._serialized_end=301
+  _globals['_FRAME']._serialized_start=304
+  _globals['_FRAME']._serialized_end=451
 # @@protoc_insertion_point(module_scope)
diff --git a/src/pipecat/processors/aggregators/llm_response.py b/src/pipecat/processors/aggregators/llm_response.py
index 379394120..13920c59b 100644
--- a/src/pipecat/processors/aggregators/llm_response.py
+++ b/src/pipecat/processors/aggregators/llm_response.py
@@ -4,7 +4,7 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-from typing import List
+from typing import List, Type
 
 from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContextFrame, OpenAILLMContext
 
@@ -34,8 +34,8 @@ class LLMResponseAggregator(FrameProcessor):
         role: str,
         start_frame,
         end_frame,
-        accumulator_frame: TextFrame,
-        interim_accumulator_frame: TextFrame | None = None,
+        accumulator_frame: Type[TextFrame],
+        interim_accumulator_frame: Type[TextFrame] | None = None,
         handle_interruptions: bool = False
     ):
         super().__init__()
diff --git a/src/pipecat/processors/aggregators/openai_llm_context.py b/src/pipecat/processors/aggregators/openai_llm_context.py
index 0d8b19a36..3d1acf32e 100644
--- a/src/pipecat/processors/aggregators/openai_llm_context.py
+++ b/src/pipecat/processors/aggregators/openai_llm_context.py
@@ -13,7 +13,11 @@ from typing import Any, Awaitable, Callable, List
 
 from PIL import Image
 
-from pipecat.frames.frames import Frame, VisionImageRawFrame, FunctionCallInProgressFrame, FunctionCallResultFrame
+from pipecat.frames.frames import (
+    Frame,
+    VisionImageRawFrame,
+    FunctionCallInProgressFrame,
+    FunctionCallResultFrame)
 from pipecat.processors.frame_processor import FrameProcessor
 
 from loguru import logger
diff --git a/src/pipecat/processors/aggregators/vision_image_frame.py b/src/pipecat/processors/aggregators/vision_image_frame.py
index 0bbb10841..97f6b5ec8 100644
--- a/src/pipecat/processors/aggregators/vision_image_frame.py
+++ b/src/pipecat/processors/aggregators/vision_image_frame.py
@@ -4,13 +4,19 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-from pipecat.frames.frames import Frame, ImageRawFrame, TextFrame, VisionImageRawFrame
+from pipecat.frames.frames import (
+    Frame,
+    InputImageRawFrame,
+    TextFrame,
+    VisionImageRawFrame
+)
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 
 
 class VisionImageFrameAggregator(FrameProcessor):
     """This aggregator waits for a consecutive TextFrame and an
-    ImageFrame. After the ImageFrame arrives it will output a VisionImageFrame.
+    InputImageRawFrame. After the InputImageRawFrame arrives it will output a
+    VisionImageRawFrame.
 
     >>> from pipecat.frames.frames import ImageFrame
 
@@ -34,7 +40,7 @@ class VisionImageFrameAggregator(FrameProcessor):
 
         if isinstance(frame, TextFrame):
             self._describe_text = frame.text
-        elif isinstance(frame, ImageRawFrame):
+        elif isinstance(frame, InputImageRawFrame):
             if self._describe_text:
                 frame = VisionImageRawFrame(
                     text=self._describe_text,
diff --git a/src/pipecat/processors/gstreamer/pipeline_source.py b/src/pipecat/processors/gstreamer/pipeline_source.py
index 8d46105a7..f852dd641 100644
--- a/src/pipecat/processors/gstreamer/pipeline_source.py
+++ b/src/pipecat/processors/gstreamer/pipeline_source.py
@@ -9,11 +9,11 @@ import asyncio
 from pydantic import BaseModel
 
 from pipecat.frames.frames import (
-    AudioRawFrame,
     CancelFrame,
     EndFrame,
     Frame,
-    ImageRawFrame,
+    OutputAudioRawFrame,
+    OutputImageRawFrame,
     StartFrame,
     SystemFrame)
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
@@ -182,9 +182,9 @@ class GStreamerPipelineSource(FrameProcessor):
     def _appsink_audio_new_sample(self, appsink: GstApp.AppSink):
         buffer = appsink.pull_sample().get_buffer()
         (_, info) = buffer.map(Gst.MapFlags.READ)
-        frame = AudioRawFrame(audio=info.data,
-                              sample_rate=self._out_params.audio_sample_rate,
-                              num_channels=self._out_params.audio_channels)
+        frame = OutputAudioRawFrame(audio=info.data,
+                                    sample_rate=self._out_params.audio_sample_rate,
+                                    num_channels=self._out_params.audio_channels)
         asyncio.run_coroutine_threadsafe(self.push_frame(frame), self.get_event_loop())
         buffer.unmap(info)
         return Gst.FlowReturn.OK
@@ -192,7 +192,7 @@ class GStreamerPipelineSource(FrameProcessor):
     def _appsink_video_new_sample(self, appsink: GstApp.AppSink):
         buffer = appsink.pull_sample().get_buffer()
         (_, info) = buffer.map(Gst.MapFlags.READ)
-        frame = ImageRawFrame(
+        frame = OutputImageRawFrame(
             image=info.data,
             size=(self._out_params.video_width, self._out_params.video_height),
             format="RGB")
diff --git a/src/pipecat/serializers/livekit.py b/src/pipecat/serializers/livekit.py
index 7a0e8afd1..fec5243f5 100644
--- a/src/pipecat/serializers/livekit.py
+++ b/src/pipecat/serializers/livekit.py
@@ -7,7 +7,10 @@
 import ctypes
 import pickle
 
-from pipecat.frames.frames import AudioRawFrame, Frame
+from pipecat.frames.frames import (
+    Frame,
+    InputAudioRawFrame,
+    OutputAudioRawFrame)
 from pipecat.serializers.base_serializer import FrameSerializer
 
 from loguru import logger
@@ -22,12 +25,8 @@ except ModuleNotFoundError as e:
 
 
 class LivekitFrameSerializer(FrameSerializer):
-    SERIALIZABLE_TYPES = {
-        AudioRawFrame: "audio",
-    }
-
     def serialize(self, frame: Frame) -> str | bytes | None:
-        if not isinstance(frame, AudioRawFrame):
+        if not isinstance(frame, OutputAudioRawFrame):
             return None
         audio_frame = AudioFrame(
             data=frame.audio,
@@ -39,7 +38,7 @@ class LivekitFrameSerializer(FrameSerializer):
 
     def deserialize(self, data: str | bytes) -> Frame | None:
         audio_frame: AudioFrame = pickle.loads(data)['frame']
-        return AudioRawFrame(
+        return InputAudioRawFrame(
             audio=bytes(audio_frame.data),
             sample_rate=audio_frame.sample_rate,
             num_channels=audio_frame.num_channels,
diff --git a/src/pipecat/serializers/protobuf.py b/src/pipecat/serializers/protobuf.py
index 0a6dee0b1..6ae1b0c03 100644
--- a/src/pipecat/serializers/protobuf.py
+++ b/src/pipecat/serializers/protobuf.py
@@ -8,7 +8,11 @@ import dataclasses
 
 import pipecat.frames.protobufs.frames_pb2 as frame_protos
 
-from pipecat.frames.frames import AudioRawFrame, Frame, TextFrame, TranscriptionFrame
+from pipecat.frames.frames import (
+    AudioRawFrame,
+    Frame,
+    TextFrame,
+    TranscriptionFrame)
 from pipecat.serializers.base_serializer import FrameSerializer
 
 from loguru import logger
@@ -29,14 +33,15 @@ class ProtobufFrameSerializer(FrameSerializer):
     def serialize(self, frame: Frame) -> str | bytes | None:
         proto_frame = frame_protos.Frame()
         if type(frame) not in self.SERIALIZABLE_TYPES:
-            raise ValueError(
-                f"Frame type {type(frame)} is not serializable. You may need to add it to ProtobufFrameSerializer.SERIALIZABLE_FIELDS.")
+            logger.warning(f"Frame type {type(frame)} is not serializable")
+            return None
 
         # ignoring linter errors; we check that type(frame) is in this dict above
         proto_optional_name = self.SERIALIZABLE_TYPES[type(frame)]  # type: ignore
         for field in dataclasses.fields(frame):  # type: ignore
-            setattr(getattr(proto_frame, proto_optional_name), field.name,
-                    getattr(frame, field.name))
+            value = getattr(frame, field.name)
+            if value:
+                setattr(getattr(proto_frame, proto_optional_name), field.name, value)
 
         result = proto_frame.SerializeToString()
         return result
@@ -48,8 +53,8 @@ class ProtobufFrameSerializer(FrameSerializer):
 
         >>> serializer = ProtobufFrameSerializer()
         >>> serializer.deserialize(
-        ...     serializer.serialize(AudioFrame(data=b'1234567890')))
-        AudioFrame(data=b'1234567890')
+        ...     serializer.serialize(OutputAudioFrame(data=b'1234567890')))
+        InputAudioFrame(data=b'1234567890')
 
         >>> serializer.deserialize(
         ...     serializer.serialize(TextFrame(text='hello world')))
@@ -75,10 +80,13 @@ class ProtobufFrameSerializer(FrameSerializer):
         # Remove special fields if needed
         id = getattr(args, "id")
         name = getattr(args, "name")
+        pts = getattr(args, "pts")
         if not id:
             del args_dict["id"]
         if not name:
             del args_dict["name"]
+        if not pts:
+            del args_dict["pts"]
 
         # Create the instance
         instance = class_name(**args_dict)
@@ -88,5 +96,7 @@ class ProtobufFrameSerializer(FrameSerializer):
             setattr(instance, "id", getattr(args, "id"))
         if name:
             setattr(instance, "name", getattr(args, "name"))
+        if pts:
+            setattr(instance, "pts", getattr(args, "pts"))
 
         return instance
diff --git a/src/pipecat/serializers/twilio.py b/src/pipecat/serializers/twilio.py
index 583234ae4..ed2905a40 100644
--- a/src/pipecat/serializers/twilio.py
+++ b/src/pipecat/serializers/twilio.py
@@ -9,7 +9,10 @@ import json
 
 from pydantic import BaseModel
 
-from pipecat.frames.frames import AudioRawFrame, Frame, StartInterruptionFrame
+from pipecat.frames.frames import (
+    AudioRawFrame,
+    Frame,
+    StartInterruptionFrame)
 from pipecat.serializers.base_serializer import FrameSerializer
 from pipecat.utils.audio import ulaw_to_pcm, pcm_to_ulaw
 
@@ -19,10 +22,6 @@ class TwilioFrameSerializer(FrameSerializer):
         twilio_sample_rate: int = 8000
         sample_rate: int = 16000
 
-    SERIALIZABLE_TYPES = {
-        AudioRawFrame: "audio",
-    }
-
     def __init__(self, stream_sid: str, params: InputParams = InputParams()):
         self._stream_sid = stream_sid
         self._params = params
diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index d91782e42..c00064e5d 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -22,6 +22,7 @@ from pipecat.frames.frames import (
     STTModelUpdateFrame,
     StartFrame,
     StartInterruptionFrame,
+    TTSAudioRawFrame,
     TTSLanguageUpdateFrame,
     TTSModelUpdateFrame,
     TTSSpeakFrame,
@@ -277,7 +278,7 @@ class AsyncTTSService(TTSService):
         if self._push_stop_frames and (
                 isinstance(frame, StartInterruptionFrame) or
                 isinstance(frame, TTSStartedFrame) or
-                isinstance(frame, AudioRawFrame) or
+                isinstance(frame, TTSAudioRawFrame) or
                 isinstance(frame, TTSStoppedFrame)):
             await self._stop_frame_queue.put(frame)
 
diff --git a/src/pipecat/services/azure.py b/src/pipecat/services/azure.py
index 90674fcc4..2c01fff3c 100644
--- a/src/pipecat/services/azure.py
+++ b/src/pipecat/services/azure.py
@@ -12,12 +12,12 @@ from PIL import Image
 from typing import AsyncGenerator
 
 from pipecat.frames.frames import (
-    AudioRawFrame,
     CancelFrame,
     EndFrame,
     ErrorFrame,
     Frame,
     StartFrame,
+    TTSAudioRawFrame,
     TTSStartedFrame,
     TTSStoppedFrame,
     TranscriptionFrame,
@@ -115,7 +115,7 @@ class AzureTTSService(TTSService):
             await self.stop_ttfb_metrics()
             await self.push_frame(TTSStartedFrame())
             # Azure always sends a 44-byte header. Strip it off.
-            yield AudioRawFrame(audio=result.audio_data[44:], sample_rate=self._sample_rate, num_channels=1)
+            yield TTSAudioRawFrame(audio=result.audio_data[44:], sample_rate=self._sample_rate, num_channels=1)
             await self.push_frame(TTSStoppedFrame())
         elif result.reason == ResultReason.Canceled:
             cancellation_details = result.cancellation_details
diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index 078926235..ac0a1b85b 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -15,10 +15,10 @@ from pipecat.frames.frames import (
     CancelFrame,
     ErrorFrame,
     Frame,
-    AudioRawFrame,
     StartInterruptionFrame,
     StartFrame,
     EndFrame,
+    TTSAudioRawFrame,
     TTSStartedFrame,
     TTSStoppedFrame,
     LLMFullResponseEndFrame
@@ -201,7 +201,7 @@ class CartesiaTTSService(AsyncWordTTSService):
                 elif msg["type"] == "chunk":
                     await self.stop_ttfb_metrics()
                     self.start_word_timestamps()
-                    frame = AudioRawFrame(
+                    frame = TTSAudioRawFrame(
                         audio=base64.b64decode(msg["data"]),
                         sample_rate=self._output_format["sample_rate"],
                         num_channels=1
@@ -326,7 +326,7 @@ class CartesiaHttpTTSService(TTSService):
 
             await self.stop_ttfb_metrics()
 
-            frame = AudioRawFrame(
+            frame = TTSAudioRawFrame(
                 audio=output["audio"],
                 sample_rate=self._output_format["sample_rate"],
                 num_channels=1
diff --git a/src/pipecat/services/deepgram.py b/src/pipecat/services/deepgram.py
index 708c3c511..5ce17d6ee 100644
--- a/src/pipecat/services/deepgram.py
+++ b/src/pipecat/services/deepgram.py
@@ -9,13 +9,13 @@ import aiohttp
 from typing import AsyncGenerator
 
 from pipecat.frames.frames import (
-    AudioRawFrame,
     CancelFrame,
     EndFrame,
     ErrorFrame,
     Frame,
     InterimTranscriptionFrame,
     StartFrame,
+    TTSAudioRawFrame,
     TTSStartedFrame,
     TTSStoppedFrame,
     TranscriptionFrame)
@@ -101,7 +101,8 @@ class DeepgramTTSService(TTSService):
                 await self.push_frame(TTSStartedFrame())
                 async for data in r.content:
                     await self.stop_ttfb_metrics()
-                    frame = AudioRawFrame(audio=data, sample_rate=self._sample_rate, num_channels=1)
+                    frame = TTSAudioRawFrame(
+                        audio=data, sample_rate=self._sample_rate, num_channels=1)
                     yield frame
                 await self.push_frame(TTSStoppedFrame())
         except Exception as e:
diff --git a/src/pipecat/services/elevenlabs.py b/src/pipecat/services/elevenlabs.py
index 081a6bf5d..f78eba266 100644
--- a/src/pipecat/services/elevenlabs.py
+++ b/src/pipecat/services/elevenlabs.py
@@ -12,12 +12,12 @@ from typing import Any, AsyncGenerator, List, Literal, Mapping, Tuple
 from pydantic import BaseModel
 
 from pipecat.frames.frames import (
-    AudioRawFrame,
     CancelFrame,
     EndFrame,
     Frame,
     StartFrame,
     StartInterruptionFrame,
+    TTSAudioRawFrame,
     TTSStartedFrame,
     TTSStoppedFrame)
 from pipecat.processors.frame_processor import FrameDirection
@@ -209,7 +209,7 @@ class ElevenLabsTTSService(AsyncWordTTSService):
                     self.start_word_timestamps()
 
                     audio = base64.b64decode(msg["audio"])
-                    frame = AudioRawFrame(audio, self.sample_rate, 1)
+                    frame = TTSAudioRawFrame(audio, self.sample_rate, 1)
                     await self.push_frame(frame)
 
                 if msg.get("alignment"):
diff --git a/src/pipecat/services/lmnt.py b/src/pipecat/services/lmnt.py
index 60f0cb7df..9285f1583 100644
--- a/src/pipecat/services/lmnt.py
+++ b/src/pipecat/services/lmnt.py
@@ -10,13 +10,13 @@ from typing import AsyncGenerator
 
 from pipecat.processors.frame_processor import FrameDirection
 from pipecat.frames.frames import (
-    AudioRawFrame,
     CancelFrame,
     EndFrame,
     ErrorFrame,
     Frame,
     StartFrame,
     StartInterruptionFrame,
+    TTSAudioRawFrame,
     TTSStartedFrame,
     TTSStoppedFrame,
 )
@@ -126,7 +126,7 @@ class LmntTTSService(AsyncTTSService):
                     await self.push_error(ErrorFrame(f'{self} error: {msg["error"]}'))
                 elif "audio" in msg:
                     await self.stop_ttfb_metrics()
-                    frame = AudioRawFrame(
+                    frame = TTSAudioRawFrame(
                         audio=msg["audio"],
                         sample_rate=self._output_format["sample_rate"],
                         num_channels=1
diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py
index 7483e2eb5..8a1355916 100644
--- a/src/pipecat/services/openai.py
+++ b/src/pipecat/services/openai.py
@@ -17,13 +17,13 @@ from loguru import logger
 from PIL import Image
 
 from pipecat.frames.frames import (
-    AudioRawFrame,
     ErrorFrame,
     Frame,
     LLMFullResponseEndFrame,
     LLMFullResponseStartFrame,
     LLMMessagesFrame,
     LLMModelUpdateFrame,
+    TTSAudioRawFrame,
     TTSStartedFrame,
     TTSStoppedFrame,
     TextFrame,
@@ -365,7 +365,7 @@ class OpenAITTSService(TTSService):
                 async for chunk in r.iter_bytes(8192):
                     if len(chunk) > 0:
                         await self.stop_ttfb_metrics()
-                        frame = AudioRawFrame(chunk, self.sample_rate, 1)
+                        frame = TTSAudioRawFrame(chunk, self.sample_rate, 1)
                         yield frame
                 await self.push_frame(TTSStoppedFrame())
         except BadRequestError as e:
diff --git a/src/pipecat/services/playht.py b/src/pipecat/services/playht.py
index c3200fee9..ae8606e91 100644
--- a/src/pipecat/services/playht.py
+++ b/src/pipecat/services/playht.py
@@ -9,7 +9,11 @@ import struct
 
 from typing import AsyncGenerator
 
-from pipecat.frames.frames import AudioRawFrame, Frame, TTSStartedFrame, TTSStoppedFrame
+from pipecat.frames.frames import (
+    Frame,
+    TTSAudioRawFrame,
+    TTSStartedFrame,
+    TTSStoppedFrame)
 from pipecat.services.ai_services import TTSService
 
 from loguru import logger
@@ -91,7 +95,7 @@ class PlayHTTTSService(TTSService):
                 else:
                     if len(chunk):
                         await self.stop_ttfb_metrics()
-                        frame = AudioRawFrame(chunk, 16000, 1)
+                        frame = TTSAudioRawFrame(chunk, 16000, 1)
                         yield frame
             await self.push_frame(TTSStoppedFrame())
         except Exception as e:
diff --git a/src/pipecat/services/together.py b/src/pipecat/services/together.py
index 49759cb01..dfd4c2966 100644
--- a/src/pipecat/services/together.py
+++ b/src/pipecat/services/together.py
@@ -4,23 +4,19 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-import base64
 import json
-import io
-import copy
-from typing import List, Optional
-from dataclasses import dataclass
-from asyncio import CancelledError
 import re
 import uuid
 
+from typing import List
+from dataclasses import dataclass
+from asyncio import CancelledError
+
 from pipecat.frames.frames import (
     Frame,
     LLMModelUpdateFrame,
     TextFrame,
-    VisionImageRawFrame,
     UserImageRequestFrame,
-    UserImageRawFrame,
     LLMMessagesFrame,
     LLMFullResponseStartFrame,
     LLMFullResponseEndFrame,
diff --git a/src/pipecat/services/xtts.py b/src/pipecat/services/xtts.py
index 38f0f9a64..69b754f55 100644
--- a/src/pipecat/services/xtts.py
+++ b/src/pipecat/services/xtts.py
@@ -9,10 +9,10 @@ import aiohttp
 from typing import Any, AsyncGenerator, Dict
 
 from pipecat.frames.frames import (
-    AudioRawFrame,
     ErrorFrame,
     Frame,
     StartFrame,
+    TTSAudioRawFrame,
     TTSStartedFrame,
     TTSStoppedFrame)
 from pipecat.services.ai_services import TTSService
@@ -128,7 +128,7 @@ class XTTSService(TTSService):
                         # Convert the numpy array back to bytes
                         resampled_audio_bytes = resampled_audio.astype(np.int16).tobytes()
                         # Create the frame with the resampled audio
-                        frame = AudioRawFrame(resampled_audio_bytes, 16000, 1)
+                        frame = TTSAudioRawFrame(resampled_audio_bytes, 16000, 1)
                         yield frame
 
             # Process any remaining data in the buffer
@@ -136,7 +136,7 @@ class XTTSService(TTSService):
                 audio_np = np.frombuffer(buffer, dtype=np.int16)
                 resampled_audio = resampy.resample(audio_np, 24000, 16000)
                 resampled_audio_bytes = resampled_audio.astype(np.int16).tobytes()
-                frame = AudioRawFrame(resampled_audio_bytes, 16000, 1)
+                frame = TTSAudioRawFrame(resampled_audio_bytes, 16000, 1)
                 yield frame
 
             await self.push_frame(TTSStoppedFrame())
diff --git a/src/pipecat/transports/base_input.py b/src/pipecat/transports/base_input.py
index de1ec8884..4e398e779 100644
--- a/src/pipecat/transports/base_input.py
+++ b/src/pipecat/transports/base_input.py
@@ -10,9 +10,9 @@ from concurrent.futures import ThreadPoolExecutor
 
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.frames.frames import (
-    AudioRawFrame,
     BotInterruptionFrame,
     CancelFrame,
+    InputAudioRawFrame,
     StartFrame,
     EndFrame,
     Frame,
@@ -59,7 +59,7 @@ class BaseInputTransport(FrameProcessor):
     def vad_analyzer(self) -> VADAnalyzer | None:
         return self._params.vad_analyzer
 
-    async def push_audio_frame(self, frame: AudioRawFrame):
+    async def push_audio_frame(self, frame: InputAudioRawFrame):
         if self._params.audio_in_enabled or self._params.vad_enabled:
             await self._audio_in_queue.put(frame)
 
@@ -151,7 +151,7 @@ class BaseInputTransport(FrameProcessor):
         vad_state: VADState = VADState.QUIET
         while True:
             try:
-                frame: AudioRawFrame = await self._audio_in_queue.get()
+                frame: InputAudioRawFrame = await self._audio_in_queue.get()
 
                 audio_passthrough = True
 
diff --git a/src/pipecat/transports/base_output.py b/src/pipecat/transports/base_output.py
index 9b1b9c29e..263bb64f4 100644
--- a/src/pipecat/transports/base_output.py
+++ b/src/pipecat/transports/base_output.py
@@ -15,17 +15,17 @@ from typing import List
 
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.frames.frames import (
-    AudioRawFrame,
     BotSpeakingFrame,
     BotStartedSpeakingFrame,
     BotStoppedSpeakingFrame,
     CancelFrame,
     MetricsFrame,
+    OutputAudioRawFrame,
+    OutputImageRawFrame,
     SpriteFrame,
     StartFrame,
     EndFrame,
     Frame,
-    ImageRawFrame,
     StartInterruptionFrame,
     StopInterruptionFrame,
     SystemFrame,
@@ -122,7 +122,7 @@ class BaseOutputTransport(FrameProcessor):
     async def send_metrics(self, frame: MetricsFrame):
         pass
 
-    async def write_frame_to_camera(self, frame: ImageRawFrame):
+    async def write_frame_to_camera(self, frame: OutputImageRawFrame):
         pass
 
     async def write_raw_audio_frames(self, frames: bytes):
@@ -162,9 +162,9 @@ class BaseOutputTransport(FrameProcessor):
             await self._sink_queue.put(frame)
             await self.stop(frame)
         # Other frames.
-        elif isinstance(frame, AudioRawFrame):
+        elif isinstance(frame, OutputAudioRawFrame):
             await self._handle_audio(frame)
-        elif isinstance(frame, ImageRawFrame) or isinstance(frame, SpriteFrame):
+        elif isinstance(frame, OutputImageRawFrame) or isinstance(frame, SpriteFrame):
             await self._handle_image(frame)
         elif isinstance(frame, TransportMessageFrame) and frame.urgent:
             await self.send_message(frame)
@@ -191,7 +191,7 @@ class BaseOutputTransport(FrameProcessor):
             if self._bot_speaking:
                 await self._bot_stopped_speaking()
 
-    async def _handle_audio(self, frame: AudioRawFrame):
+    async def _handle_audio(self, frame: OutputAudioRawFrame):
         if not self._params.audio_out_enabled:
             return
 
@@ -200,12 +200,14 @@ class BaseOutputTransport(FrameProcessor):
         else:
             self._audio_buffer.extend(frame.audio)
             while len(self._audio_buffer) >= self._audio_chunk_size:
-                chunk = AudioRawFrame(bytes(self._audio_buffer[:self._audio_chunk_size]),
-                                      sample_rate=frame.sample_rate, num_channels=frame.num_channels)
+                chunk = OutputAudioRawFrame(
+                    bytes(self._audio_buffer[:self._audio_chunk_size]),
+                    sample_rate=frame.sample_rate, num_channels=frame.num_channels
+                )
                 await self._sink_queue.put(chunk)
                 self._audio_buffer = self._audio_buffer[self._audio_chunk_size:]
 
-    async def _handle_image(self, frame: ImageRawFrame | SpriteFrame):
+    async def _handle_image(self, frame: OutputImageRawFrame | SpriteFrame):
         if not self._params.camera_out_enabled:
             return
 
@@ -226,11 +228,11 @@ class BaseOutputTransport(FrameProcessor):
         self._sink_clock_task = loop.create_task(self._sink_clock_task_handler())
 
     async def _sink_frame_handler(self, frame: Frame):
-        if isinstance(frame, AudioRawFrame):
+        if isinstance(frame, OutputAudioRawFrame):
             await self.write_raw_audio_frames(frame.audio)
             await self.push_frame(frame)
             await self.push_frame(BotSpeakingFrame(), FrameDirection.UPSTREAM)
-        elif isinstance(frame, ImageRawFrame):
+        elif isinstance(frame, OutputImageRawFrame):
             await self._set_camera_image(frame)
         elif isinstance(frame, SpriteFrame):
             await self._set_camera_images(frame.images)
@@ -305,10 +307,10 @@ class BaseOutputTransport(FrameProcessor):
     # Camera out
     #
 
-    async def send_image(self, frame: ImageRawFrame | SpriteFrame):
+    async def send_image(self, frame: OutputImageRawFrame | SpriteFrame):
         await self.process_frame(frame, FrameDirection.DOWNSTREAM)
 
-    async def _draw_image(self, frame: ImageRawFrame):
+    async def _draw_image(self, frame: OutputImageRawFrame):
         desired_size = (self._params.camera_out_width, self._params.camera_out_height)
 
         if frame.size != desired_size:
@@ -316,14 +318,17 @@ class BaseOutputTransport(FrameProcessor):
             resized_image = image.resize(desired_size)
             logger.warning(
                 f"{frame} does not have the expected size {desired_size}, resizing")
-            frame = ImageRawFrame(resized_image.tobytes(), resized_image.size, resized_image.format)
+            frame = OutputImageRawFrame(
+                resized_image.tobytes(),
+                resized_image.size,
+                resized_image.format)
 
         await self.write_frame_to_camera(frame)
 
-    async def _set_camera_image(self, image: ImageRawFrame):
+    async def _set_camera_image(self, image: OutputImageRawFrame):
         self._camera_images = itertools.cycle([image])
 
-    async def _set_camera_images(self, images: List[ImageRawFrame]):
+    async def _set_camera_images(self, images: List[OutputImageRawFrame]):
         self._camera_images = itertools.cycle(images)
 
     async def _camera_out_task_handler(self):
@@ -375,7 +380,7 @@ class BaseOutputTransport(FrameProcessor):
     # Audio out
     #
 
-    async def send_audio(self, frame: AudioRawFrame):
+    async def send_audio(self, frame: OutputAudioRawFrame):
         await self.process_frame(frame, FrameDirection.DOWNSTREAM)
 
     async def _audio_out_task_handler(self):
diff --git a/src/pipecat/transports/local/audio.py b/src/pipecat/transports/local/audio.py
index cd05550a9..45d18db52 100644
--- a/src/pipecat/transports/local/audio.py
+++ b/src/pipecat/transports/local/audio.py
@@ -8,7 +8,7 @@ import asyncio
 
 from concurrent.futures import ThreadPoolExecutor
 
-from pipecat.frames.frames import AudioRawFrame, StartFrame
+from pipecat.frames.frames import InputAudioRawFrame, StartFrame
 from pipecat.processors.frame_processor import FrameProcessor
 from pipecat.transports.base_input import BaseInputTransport
 from pipecat.transports.base_output import BaseOutputTransport
@@ -54,9 +54,9 @@ class LocalAudioInputTransport(BaseInputTransport):
         self._in_stream.close()
 
     def _audio_in_callback(self, in_data, frame_count, time_info, status):
-        frame = AudioRawFrame(audio=in_data,
-                              sample_rate=self._params.audio_in_sample_rate,
-                              num_channels=self._params.audio_in_channels)
+        frame = InputAudioRawFrame(audio=in_data,
+                                   sample_rate=self._params.audio_in_sample_rate,
+                                   num_channels=self._params.audio_in_channels)
 
         asyncio.run_coroutine_threadsafe(self.push_audio_frame(frame), self.get_event_loop())
 
diff --git a/src/pipecat/transports/local/tk.py b/src/pipecat/transports/local/tk.py
index e7dc04902..75dd30331 100644
--- a/src/pipecat/transports/local/tk.py
+++ b/src/pipecat/transports/local/tk.py
@@ -11,8 +11,7 @@ from concurrent.futures import ThreadPoolExecutor
 import numpy as np
 import tkinter as tk
 
-from pipecat.frames.frames import AudioRawFrame, ImageRawFrame, StartFrame
-from pipecat.processors.frame_processor import FrameProcessor
+from pipecat.frames.frames import InputAudioRawFrame, OutputImageRawFrame, StartFrame
 from pipecat.transports.base_input import BaseInputTransport
 from pipecat.transports.base_output import BaseOutputTransport
 from pipecat.transports.base_transport import BaseTransport, TransportParams
@@ -64,9 +63,9 @@ class TkInputTransport(BaseInputTransport):
         self._in_stream.close()
 
     def _audio_in_callback(self, in_data, frame_count, time_info, status):
-        frame = AudioRawFrame(audio=in_data,
-                              sample_rate=self._params.audio_in_sample_rate,
-                              num_channels=self._params.audio_in_channels)
+        frame = InputAudioRawFrame(audio=in_data,
+                                   sample_rate=self._params.audio_in_sample_rate,
+                                   num_channels=self._params.audio_in_channels)
 
         asyncio.run_coroutine_threadsafe(self.push_audio_frame(frame), self.get_event_loop())
 
@@ -108,10 +107,10 @@ class TkOutputTransport(BaseOutputTransport):
     async def write_raw_audio_frames(self, frames: bytes):
         await self.get_event_loop().run_in_executor(self._executor, self._out_stream.write, frames)
 
-    async def write_frame_to_camera(self, frame: ImageRawFrame):
+    async def write_frame_to_camera(self, frame: OutputImageRawFrame):
         self.get_event_loop().call_soon(self._write_frame_to_tk, frame)
 
-    def _write_frame_to_tk(self, frame: ImageRawFrame):
+    def _write_frame_to_tk(self, frame: OutputImageRawFrame):
         width = frame.size[0]
         height = frame.size[1]
         data = f"P6 {width} {height} 255 ".encode() + frame.image
diff --git a/src/pipecat/transports/network/fastapi_websocket.py b/src/pipecat/transports/network/fastapi_websocket.py
index 7169c73bd..815d7c2ef 100644
--- a/src/pipecat/transports/network/fastapi_websocket.py
+++ b/src/pipecat/transports/network/fastapi_websocket.py
@@ -12,8 +12,16 @@ import wave
 from typing import Awaitable, Callable
 from pydantic.main import BaseModel
 
-from pipecat.frames.frames import AudioRawFrame, CancelFrame, EndFrame, Frame, StartFrame, StartInterruptionFrame
-from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
+from pipecat.frames.frames import (
+    AudioRawFrame,
+    CancelFrame,
+    EndFrame,
+    Frame,
+    InputAudioRawFrame,
+    StartFrame,
+    StartInterruptionFrame
+)
+from pipecat.processors.frame_processor import FrameDirection
 from pipecat.serializers.base_serializer import FrameSerializer
 from pipecat.transports.base_input import BaseInputTransport
 from pipecat.transports.base_output import BaseOutputTransport
@@ -79,7 +87,11 @@ class FastAPIWebsocketInputTransport(BaseInputTransport):
                 continue
 
             if isinstance(frame, AudioRawFrame):
-                await self.push_audio_frame(frame)
+                await self.push_audio_frame(InputAudioRawFrame(
+                    audio=frame.audio,
+                    sample_rate=frame.sample_rate,
+                    num_channels=frame.num_channels)
+                )
 
         await self._callbacks.on_client_disconnected(self._websocket)
 
diff --git a/src/pipecat/transports/network/websocket_server.py b/src/pipecat/transports/network/websocket_server.py
index c17818898..329ae8994 100644
--- a/src/pipecat/transports/network/websocket_server.py
+++ b/src/pipecat/transports/network/websocket_server.py
@@ -11,8 +11,7 @@ import wave
 from typing import Awaitable, Callable
 from pydantic.main import BaseModel
 
-from pipecat.frames.frames import AudioRawFrame, CancelFrame, EndFrame, StartFrame
-from pipecat.processors.frame_processor import FrameProcessor
+from pipecat.frames.frames import AudioRawFrame, CancelFrame, EndFrame, InputAudioRawFrame, StartFrame
 from pipecat.serializers.base_serializer import FrameSerializer
 from pipecat.serializers.protobuf import ProtobufFrameSerializer
 from pipecat.transports.base_input import BaseInputTransport
@@ -98,7 +97,11 @@ class WebsocketServerInputTransport(BaseInputTransport):
                 continue
 
             if isinstance(frame, AudioRawFrame):
-                await self.queue_audio_frame(frame)
+                await self.push_audio_frame(InputAudioRawFrame(
+                    audio=frame.audio,
+                    sample_rate=frame.sample_rate,
+                    num_channels=frame.num_channels)
+                )
             else:
                 await self.push_frame(frame)
 
diff --git a/src/pipecat/transports/services/daily.py b/src/pipecat/transports/services/daily.py
index 2a45adf36..d595aaceb 100644
--- a/src/pipecat/transports/services/daily.py
+++ b/src/pipecat/transports/services/daily.py
@@ -22,13 +22,14 @@ from daily import (
 from pydantic.main import BaseModel
 
 from pipecat.frames.frames import (
-    AudioRawFrame,
     CancelFrame,
     EndFrame,
     Frame,
-    ImageRawFrame,
+    InputAudioRawFrame,
     InterimTranscriptionFrame,
     MetricsFrame,
+    OutputAudioRawFrame,
+    OutputImageRawFrame,
     SpriteFrame,
     StartFrame,
     TranscriptionFrame,
@@ -239,7 +240,7 @@ class DailyTransportClient(EventHandler):
             completion=completion_callback(future))
         await future
 
-    async def read_next_audio_frame(self) -> AudioRawFrame | None:
+    async def read_next_audio_frame(self) -> InputAudioRawFrame | None:
         if not self._speaker:
             return None
 
@@ -252,7 +253,10 @@ class DailyTransportClient(EventHandler):
         audio = await future
 
         if len(audio) > 0:
-            return AudioRawFrame(audio=audio, sample_rate=sample_rate, num_channels=num_channels)
+            return InputAudioRawFrame(
+                audio=audio,
+                sample_rate=sample_rate,
+                num_channels=num_channels)
         else:
             # If we don't read any audio it could be there's no participant
             # connected. daily-python will return immediately if that's the
@@ -268,7 +272,7 @@ class DailyTransportClient(EventHandler):
         self._mic.write_frames(frames, completion=completion_callback(future))
         await future
 
-    async def write_frame_to_camera(self, frame: ImageRawFrame):
+    async def write_frame_to_camera(self, frame: OutputImageRawFrame):
         if not self._camera:
             return None
 
@@ -749,7 +753,7 @@ class DailyOutputTransport(BaseOutputTransport):
     async def write_raw_audio_frames(self, frames: bytes):
         await self._client.write_raw_audio_frames(frames)
 
-    async def write_frame_to_camera(self, frame: ImageRawFrame):
+    async def write_frame_to_camera(self, frame: OutputImageRawFrame):
         await self._client.write_frame_to_camera(frame)
 
 
@@ -829,11 +833,11 @@ class DailyTransport(BaseTransport):
     def participant_id(self) -> str:
         return self._client.participant_id
 
-    async def send_image(self, frame: ImageRawFrame | SpriteFrame):
+    async def send_image(self, frame: OutputImageRawFrame | SpriteFrame):
         if self._output:
             await self._output.process_frame(frame, FrameDirection.DOWNSTREAM)
 
-    async def send_audio(self, frame: AudioRawFrame):
+    async def send_audio(self, frame: OutputAudioRawFrame):
         if self._output:
             await self._output.process_frame(frame, FrameDirection.DOWNSTREAM)
 

From 3b81cd462d36c83b5d741aed253b56932a9ae06c Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Fri, 20 Sep 2024 13:41:04 -0400
Subject: [PATCH 039/135] Input params to OpenAI LLM

---
 src/pipecat/services/openai.py | 63 ++++++++++++++++++++++++++++++----
 1 file changed, 57 insertions(+), 6 deletions(-)

diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py
index 6fe710b5e..440281c90 100644
--- a/src/pipecat/services/openai.py
+++ b/src/pipecat/services/openai.py
@@ -11,7 +11,8 @@ import json
 import httpx
 from dataclasses import dataclass
 
-from typing import AsyncGenerator, Dict, List, Literal
+from typing import AsyncGenerator, Dict, List, Literal, Optional
+from pydantic import BaseModel, Field
 
 from loguru import logger
 from PIL import Image
@@ -48,7 +49,7 @@ from pipecat.services.ai_services import (
 )
 
 try:
-    from openai import AsyncOpenAI, AsyncStream, DefaultAsyncHttpxClient, BadRequestError
+    from openai import AsyncOpenAI, AsyncStream, DefaultAsyncHttpxClient, BadRequestError, NOT_GIVEN
     from openai.types.chat import ChatCompletionChunk, ChatCompletionMessageParam
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
@@ -81,11 +82,31 @@ class BaseOpenAILLMService(LLMService):
     as well as tool choices and the tool, which is used if requesting function
     calls from the LLM.
     """
+    class InputParams(BaseModel):
+        frequency_penalty: Optional[float] = Field(
+            default_factory=lambda: NOT_GIVEN, ge=-2.0, le=2.0)
+        presence_penalty: Optional[float] = Field(
+            default_factory=lambda: NOT_GIVEN, ge=-2.0, le=2.0)
+        seed: Optional[int] = Field(default_factory=lambda: NOT_GIVEN, ge=0)
+        temperature: Optional[float] = Field(default_factory=lambda: NOT_GIVEN, ge=0.0, le=2.0)
+        top_p: Optional[float] = Field(default_factory=lambda: NOT_GIVEN, ge=0.0, le=1.0)
 
-    def __init__(self, *, model: str, api_key=None, base_url=None, **kwargs):
+    def __init__(
+            self,
+            *,
+            model: str,
+            api_key=None,
+            base_url=None,
+            params: InputParams = InputParams(),
+            **kwargs):
         super().__init__(**kwargs)
         self.set_model_name(model)
         self._client = self.create_client(api_key=api_key, base_url=base_url, **kwargs)
+        self._frequency_penalty = params.frequency_penalty
+        self._presence_penalty = params.presence_penalty
+        self._seed = params.seed
+        self._temperature = params.temperature
+        self._top_p = params.top_p
 
     def create_client(self, api_key=None, base_url=None, **kwargs):
         return AsyncOpenAI(
@@ -100,6 +121,26 @@ class BaseOpenAILLMService(LLMService):
     def can_generate_metrics(self) -> bool:
         return True
 
+    async def set_frequency_penalty(self, frequency_penalty: float):
+        logger.debug(f"Switching LLM frequency_penalty to: [{frequency_penalty}]")
+        self._frequency_penalty = frequency_penalty
+
+    async def set_presence_penalty(self, presence_penalty: float):
+        logger.debug(f"Switching LLM presence_penalty to: [{presence_penalty}]")
+        self._presence_penalty = presence_penalty
+
+    async def set_seed(self, seed: int):
+        logger.debug(f"Switching LLM seed to: [{seed}]")
+        self._seed = seed
+
+    async def set_temperature(self, temperature: float):
+        logger.debug(f"Switching LLM temperature to: [{temperature}]")
+        self._temperature = temperature
+
+    async def set_top_p(self, top_p: float):
+        logger.debug(f"Switching LLM top_p to: [{top_p}]")
+        self._top_p = top_p
+
     async def get_chat_completions(
             self,
             context: OpenAILLMContext,
@@ -110,7 +151,12 @@ class BaseOpenAILLMService(LLMService):
             messages=messages,
             tools=context.tools,
             tool_choice=context.tool_choice,
-            stream_options={"include_usage": True}
+            stream_options={"include_usage": True},
+            frequency_penalty=self._frequency_penalty,
+            presence_penalty=self._presence_penalty,
+            seed=self._seed,
+            temperature=self._temperature,
+            top_p=self._top_p
         )
         return chunks
 
@@ -248,8 +294,13 @@ class OpenAIContextAggregatorPair:
 
 class OpenAILLMService(BaseOpenAILLMService):
 
-    def __init__(self, *, model: str = "gpt-4o", **kwargs):
-        super().__init__(model=model, **kwargs)
+    def __init__(
+            self,
+            *,
+            model: str = "gpt-4o",
+            params: BaseOpenAILLMService.InputParams = BaseOpenAILLMService.InputParams(),
+            **kwargs):
+        super().__init__(model=model, params=params, **kwargs)
 
     @staticmethod
     def create_context_aggregator(context: OpenAILLMContext) -> OpenAIContextAggregatorPair:

From 4fa1ea8c4b7e2d5b156bc19c4f38e3f2ebc0c0ed Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Fri, 20 Sep 2024 15:29:20 -0400
Subject: [PATCH 040/135] Input params for Anthropic LLM

---
 src/pipecat/services/anthropic.py | 42 +++++++++++++++++++++++++++----
 1 file changed, 37 insertions(+), 5 deletions(-)

diff --git a/src/pipecat/services/anthropic.py b/src/pipecat/services/anthropic.py
index 7935691ce..ea1756f8c 100644
--- a/src/pipecat/services/anthropic.py
+++ b/src/pipecat/services/anthropic.py
@@ -13,6 +13,7 @@ from dataclasses import dataclass
 from PIL import Image
 from asyncio import CancelledError
 import re
+from pydantic import BaseModel, Field
 
 from pipecat.frames.frames import (
     Frame,
@@ -74,20 +75,28 @@ class AnthropicContextAggregatorPair:
 class AnthropicLLMService(LLMService):
     """This class implements inference with Anthropic's AI models
     """
+    class InputParams(BaseModel):
+        enable_prompt_caching_beta: Optional[bool] = False
+        max_tokens: Optional[int] = Field(default_factory=lambda: 4096, ge=1)
+        temperature: Optional[float] = Field(default_factory=lambda: NOT_GIVEN, ge=0.0, le=1.0)
+        top_k: Optional[int] = Field(default_factory=lambda: NOT_GIVEN, ge=0)
+        top_p: Optional[float] = Field(default_factory=lambda: NOT_GIVEN, ge=0.0, le=1.0)
 
     def __init__(
             self,
             *,
             api_key: str,
             model: str = "claude-3-5-sonnet-20240620",
-            max_tokens: int = 4096,
-            enable_prompt_caching_beta: bool = False,
+            params: InputParams = InputParams(),
             **kwargs):
         super().__init__(**kwargs)
         self._client = AsyncAnthropic(api_key=api_key)
         self.set_model_name(model)
-        self._max_tokens = max_tokens
-        self._enable_prompt_caching_beta = enable_prompt_caching_beta
+        self._max_tokens = params.max_tokens
+        self._enable_prompt_caching_beta: bool = params.enable_prompt_caching_beta or False
+        self._temperature = params.temperature
+        self._top_k = params.top_k
+        self._top_p = params.top_p
 
     def can_generate_metrics(self) -> bool:
         return True
@@ -105,6 +114,26 @@ class AnthropicLLMService(LLMService):
             _assistant=assistant
         )
 
+    async def set_enable_prompt_caching_beta(self, enable_prompt_caching_beta: bool):
+        logger.debug(f"Switching LLM enable_prompt_caching_beta to: [{enable_prompt_caching_beta}]")
+        self._enable_prompt_caching_beta = enable_prompt_caching_beta
+
+    async def set_max_tokens(self, max_tokens: int):
+        logger.debug(f"Switching LLM max_tokens to: [{max_tokens}]")
+        self._max_tokens = max_tokens
+
+    async def set_temperature(self, temperature: float):
+        logger.debug(f"Switching LLM temperature to: [{temperature}]")
+        self._temperature = temperature
+
+    async def set_top_k(self, top_k: float):
+        logger.debug(f"Switching LLM top_k to: [{top_k}]")
+        self._top_k = top_k
+
+    async def set_top_p(self, top_p: float):
+        logger.debug(f"Switching LLM top_p to: [{top_p}]")
+        self._top_p = top_p
+
     async def _process_context(self, context: OpenAILLMContext):
         # Usage tracking. We track the usage reported by Anthropic in prompt_tokens and
         # completion_tokens. We also estimate the completion tokens from output text
@@ -140,7 +169,10 @@ class AnthropicLLMService(LLMService):
                 messages=messages,
                 model=self.model_name,
                 max_tokens=self._max_tokens,
-                stream=True)
+                stream=True,
+                temperature=self._temperature,
+                top_k=self._top_k,
+                top_p=self._top_p)
 
             await self.stop_ttfb_metrics()
 

From 357e66d64da74a0fc66ce45f2f9fcc0f6fb3fc0d Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Fri, 20 Sep 2024 16:18:25 -0400
Subject: [PATCH 041/135] Input params for Together AI LLM

---
 src/pipecat/services/together.py | 46 ++++++++++++++++++++++++++++++--
 1 file changed, 44 insertions(+), 2 deletions(-)

diff --git a/src/pipecat/services/together.py b/src/pipecat/services/together.py
index 004236ac8..6bc3980ce 100644
--- a/src/pipecat/services/together.py
+++ b/src/pipecat/services/together.py
@@ -13,6 +13,7 @@ from dataclasses import dataclass
 from asyncio import CancelledError
 import re
 import uuid
+from pydantic import BaseModel, Field
 
 from pipecat.frames.frames import (
     Frame,
@@ -58,18 +59,30 @@ class TogetherContextAggregatorPair:
 class TogetherLLMService(LLMService):
     """This class implements inference with Together's Llama 3.1 models
     """
+    class InputParams(BaseModel):
+        frequency_penalty: Optional[float] = Field(default=None, ge=-2.0, le=2.0)
+        max_tokens: Optional[int] = Field(default=4096, ge=1)
+        presence_penalty: Optional[float] = Field(default=None, ge=-2.0, le=2.0)
+        temperature: Optional[float] = Field(default=None, ge=0.0, le=1.0)
+        top_k: Optional[int] = Field(default=None, ge=0)
+        top_p: Optional[float] = Field(default=None, ge=0.0, le=1.0)
 
     def __init__(
             self,
             *,
             api_key: str,
             model: str = "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo",
-            max_tokens: int = 4096,
+            params: InputParams = InputParams(),
             **kwargs):
         super().__init__(**kwargs)
         self._client = AsyncTogether(api_key=api_key)
         self.set_model_name(model)
-        self._max_tokens = max_tokens
+        self._max_tokens = params.max_tokens
+        self._frequency_penalty = params.frequency_penalty
+        self._presence_penalty = params.presence_penalty
+        self._temperature = params.temperature
+        self._top_k = params.top_k
+        self._top_p = params.top_p
 
     def can_generate_metrics(self) -> bool:
         return True
@@ -83,6 +96,30 @@ class TogetherLLMService(LLMService):
             _assistant=assistant
         )
 
+    async def set_frequency_penalty(self, frequency_penalty: float):
+        logger.debug(f"Switching LLM frequency_penalty to: [{frequency_penalty}]")
+        self._frequency_penalty = frequency_penalty
+
+    async def set_max_tokens(self, max_tokens: int):
+        logger.debug(f"Switching LLM max_tokens to: [{max_tokens}]")
+        self._max_tokens = max_tokens
+
+    async def set_presence_penalty(self, presence_penalty: float):
+        logger.debug(f"Switching LLM presence_penalty to: [{presence_penalty}]")
+        self._presence_penalty = presence_penalty
+
+    async def set_temperature(self, temperature: float):
+        logger.debug(f"Switching LLM temperature to: [{temperature}]")
+        self._temperature = temperature
+
+    async def set_top_k(self, top_k: float):
+        logger.debug(f"Switching LLM top_k to: [{top_k}]")
+        self._top_k = top_k
+
+    async def set_top_p(self, top_p: float):
+        logger.debug(f"Switching LLM top_p to: [{top_p}]")
+        self._top_p = top_p
+
     async def _process_context(self, context: OpenAILLMContext):
         try:
             await self.push_frame(LLMFullResponseStartFrame())
@@ -97,6 +134,11 @@ class TogetherLLMService(LLMService):
                 model=self.model_name,
                 max_tokens=self._max_tokens,
                 stream=True,
+                frequency_penalty=self._frequency_penalty,
+                presence_penalty=self._presence_penalty,
+                temperature=self._temperature,
+                top_k=self._top_k,
+                top_p=self._top_p
             )
 
             # Function calling

From f3fd312b8353bd9211fbe7c48bed0b0e8ad70c36 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Fri, 20 Sep 2024 17:42:58 -0400
Subject: [PATCH 042/135] Add Together AI interruptible example

---
 .../07l-interruptible-together.py             | 100 ++++++++++++++++++
 1 file changed, 100 insertions(+)
 create mode 100644 examples/foundational/07l-interruptible-together.py

diff --git a/examples/foundational/07l-interruptible-together.py b/examples/foundational/07l-interruptible-together.py
new file mode 100644
index 000000000..41befb67f
--- /dev/null
+++ b/examples/foundational/07l-interruptible-together.py
@@ -0,0 +1,100 @@
+#
+# Copyright (c) 2024, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import aiohttp
+import os
+import sys
+
+from pipecat.frames.frames import LLMMessagesFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.llm_response import (
+    LLMAssistantResponseAggregator, LLMUserResponseAggregator)
+from pipecat.services.cartesia import CartesiaTTSService
+from pipecat.services.together import TogetherLLMService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+from pipecat.vad.silero import SileroVADAnalyzer
+
+from runner import configure
+
+from loguru import logger
+
+from dotenv import load_dotenv
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, token) = await configure(session)
+
+        transport = DailyTransport(
+            room_url,
+            token,
+            "Respond bot",
+            DailyParams(
+                audio_out_enabled=True,
+                transcription_enabled=True,
+                vad_enabled=True,
+                vad_analyzer=SileroVADAnalyzer()
+            )
+        )
+
+        tts = CartesiaTTSService(
+            api_key=os.getenv("CARTESIA_API_KEY"),
+            voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
+        )
+
+        llm = TogetherLLMService(
+            api_key=os.getenv("TOGETHER_API_KEY"),
+            model=os.getenv("TOGETHER_MODEL"),
+            params=TogetherLLMService.InputParams(
+                temperature=1.0,
+                frequency_penalty=2.0,
+                presence_penalty=0.0,
+                top_p=0.9,
+                top_k=40
+            )
+        )
+
+        messages = [
+            {
+                "role": "system",
+                "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+            },
+        ]
+
+        tma_in = LLMUserResponseAggregator(messages)
+        tma_out = LLMAssistantResponseAggregator(messages)
+
+        pipeline = Pipeline([
+            transport.input(),   # Transport user input
+            tma_in,              # User responses
+            llm,                 # LLM
+            tts,                 # TTS
+            transport.output(),  # Transport bot output
+            tma_out              # Assistant spoken responses
+        ])
+
+        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            transport.capture_participant_transcription(participant["id"])
+            # Kick off the conversation.
+            await task.queue_frames([LLMMessagesFrame(messages)])
+
+        runner = PipelineRunner()
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

From 219304c5eeeeb36e773222bd46631119301027a8 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Fri, 20 Sep 2024 20:31:42 -0400
Subject: [PATCH 043/135] Added Changelog entries

---
 CHANGELOG.md | 14 ++++++++++----
 1 file changed, 10 insertions(+), 4 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 985834aba..ba20821cc 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,6 +9,12 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 
+- Added configurable LLM parameters (e.g., temperature, top_p, max_tokens, seed)
+  for OpenAI, Anthropic, and Together AI services along with corresponding
+  setter functions.
+
+- Added `sample_rate` as a constructor parameter for TTS services.
+
 - Pipecat has a pipeline-based architecture. The pipeline consists of frame
   processors linked to each other. The elements traveling across the pipeline
   are called frames.
@@ -334,7 +340,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - It is now possible to specify a Silero VAD version when using `SileroVADAnalyzer`
   or `SileroVAD`.
 
-- Added `AysncFrameProcessor` and `AsyncAIService`.  Some services like
+- Added `AysncFrameProcessor` and `AsyncAIService`. Some services like
   `DeepgramSTTService` need to process things asynchronously. For example, audio
   is sent to Deepgram but transcriptions are not returned immediately. In these
   cases we still require all frames (except system frames) to be pushed
@@ -351,7 +357,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 - `WhisperSTTService` model can now also be a string.
 
-- Added missing * keyword separators in services.
+- Added missing \* keyword separators in services.
 
 ### Fixed
 
@@ -428,7 +434,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Added new `TwilioFrameSerializer`. This is a new serializer that knows how to
   serialize and deserialize audio frames from Twilio.
 
-- Added Daily transport event: `on_dialout_answered`.  See
+- Added Daily transport event: `on_dialout_answered`. See
   https://reference-python.daily.co/api_reference.html#daily.EventHandler
 
 - Added new `AzureSTTService`. This allows you to use Azure Speech-To-Text.
@@ -668,7 +674,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Added Daily transport support for dial-in use cases.
 
 - Added Daily transport events: `on_dialout_connected`, `on_dialout_stopped`,
-  `on_dialout_error` and `on_dialout_warning`.  See
+  `on_dialout_error` and `on_dialout_warning`. See
   https://reference-python.daily.co/api_reference.html#daily.EventHandler
 
 ## [0.0.21] - 2024-05-22

From 78a3f081de561097346e72bed2e7313597bbf2a3 Mon Sep 17 00:00:00 2001
From: Kwindla Hultman Kramer <kwindla@gmail.com>
Date: Fri, 20 Sep 2024 18:21:06 -0700
Subject: [PATCH 044/135] fixup for serialization issue

---
 src/pipecat/transports/services/daily.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/src/pipecat/transports/services/daily.py b/src/pipecat/transports/services/daily.py
index e28fe6083..66d3b21d2 100644
--- a/src/pipecat/transports/services/daily.py
+++ b/src/pipecat/transports/services/daily.py
@@ -736,11 +736,11 @@ class DailyOutputTransport(BaseOutputTransport):
             if isinstance(d, TTFBMetricsData):
                 if "ttfb" not in metrics:
                     metrics["ttfb"] = []
-                metrics["ttfb"].append(d.model_dump())
+                metrics["ttfb"].append(d.model_dump(exclude_none=True))
             elif isinstance(d, ProcessingMetricsData):
                 if "processing" not in metrics:
                     metrics["processing"] = []
-                metrics["processing"].append(d.model_dump())
+                metrics["processing"].append(d.model_dump(exclude_none=True))
             elif isinstance(d, LLMUsageMetricsData):
                 if "tokens" not in metrics:
                     metrics["tokens"] = []
@@ -748,7 +748,7 @@ class DailyOutputTransport(BaseOutputTransport):
             elif isinstance(d, TTSUsageMetricsData):
                 if "characters" not in metrics:
                     metrics["characters"] = []
-                metrics["characters"].append(d.model_dump())
+                metrics["characters"].append(d.model_dump(exclude_none=True))
 
         message = DailyTransportMessageFrame(message={
             "type": "pipecat-metrics",

From c73111afea4aaa3fcf1e343a6c1ce700ec606543 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Fri, 20 Sep 2024 21:45:35 -0400
Subject: [PATCH 045/135] Add extra input param to LLMs

---
 .../07l-interruptible-together.py             |  8 ++--
 src/pipecat/services/anthropic.py             | 33 ++++++++++------
 src/pipecat/services/openai.py                | 39 ++++++++++++-------
 src/pipecat/services/together.py              | 34 ++++++++++------
 4 files changed, 74 insertions(+), 40 deletions(-)

diff --git a/examples/foundational/07l-interruptible-together.py b/examples/foundational/07l-interruptible-together.py
index 41befb67f..d5afa6d0d 100644
--- a/examples/foundational/07l-interruptible-together.py
+++ b/examples/foundational/07l-interruptible-together.py
@@ -57,10 +57,12 @@ async def main():
             model=os.getenv("TOGETHER_MODEL"),
             params=TogetherLLMService.InputParams(
                 temperature=1.0,
-                frequency_penalty=2.0,
-                presence_penalty=0.0,
                 top_p=0.9,
-                top_k=40
+                top_k=40,
+                extra={
+                    "frequency_penalty": 2.0,
+                    "presence_penalty": 0.0,
+                }
             )
         )
 
diff --git a/src/pipecat/services/anthropic.py b/src/pipecat/services/anthropic.py
index ea1756f8c..421196e2c 100644
--- a/src/pipecat/services/anthropic.py
+++ b/src/pipecat/services/anthropic.py
@@ -8,7 +8,7 @@ import base64
 import json
 import io
 import copy
-from typing import List, Optional
+from typing import Any, Dict, List, Optional
 from dataclasses import dataclass
 from PIL import Image
 from asyncio import CancelledError
@@ -81,6 +81,7 @@ class AnthropicLLMService(LLMService):
         temperature: Optional[float] = Field(default_factory=lambda: NOT_GIVEN, ge=0.0, le=1.0)
         top_k: Optional[int] = Field(default_factory=lambda: NOT_GIVEN, ge=0)
         top_p: Optional[float] = Field(default_factory=lambda: NOT_GIVEN, ge=0.0, le=1.0)
+        extra: Optional[Dict[str, Any]] = Field(default_factory=dict)
 
     def __init__(
             self,
@@ -97,6 +98,7 @@ class AnthropicLLMService(LLMService):
         self._temperature = params.temperature
         self._top_k = params.top_k
         self._top_p = params.top_p
+        self._extra = params.extra if isinstance(params.extra, dict) else {}
 
     def can_generate_metrics(self) -> bool:
         return True
@@ -134,6 +136,10 @@ class AnthropicLLMService(LLMService):
         logger.debug(f"Switching LLM top_p to: [{top_p}]")
         self._top_p = top_p
 
+    async def set_extra(self, extra: Dict[str, Any]):
+        logger.debug(f"Switching LLM extra to: [{extra}]")
+        self._extra = extra
+
     async def _process_context(self, context: OpenAILLMContext):
         # Usage tracking. We track the usage reported by Anthropic in prompt_tokens and
         # completion_tokens. We also estimate the completion tokens from output text
@@ -163,16 +169,21 @@ class AnthropicLLMService(LLMService):
 
             await self.start_ttfb_metrics()
 
-            response = await api_call(
-                tools=context.tools or [],
-                system=context.system,
-                messages=messages,
-                model=self.model_name,
-                max_tokens=self._max_tokens,
-                stream=True,
-                temperature=self._temperature,
-                top_k=self._top_k,
-                top_p=self._top_p)
+            params = {
+                "tools": context.tools or [],
+                "system": context.system,
+                "messages": messages,
+                "model": self.model_name,
+                "max_tokens": self._max_tokens,
+                "stream": True,
+                "temperature": self._temperature,
+                "top_k": self._top_k,
+                "top_p": self._top_p
+            }
+
+            params.update(self._extra)
+
+            response = await api_call(**params)
 
             await self.stop_ttfb_metrics()
 
diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py
index 274a14820..4203f8194 100644
--- a/src/pipecat/services/openai.py
+++ b/src/pipecat/services/openai.py
@@ -11,7 +11,7 @@ import json
 import httpx
 from dataclasses import dataclass
 
-from typing import AsyncGenerator, Dict, List, Literal, Optional
+from typing import Any, AsyncGenerator, Dict, List, Literal, Optional
 from pydantic import BaseModel, Field
 
 from loguru import logger
@@ -90,6 +90,7 @@ class BaseOpenAILLMService(LLMService):
         seed: Optional[int] = Field(default_factory=lambda: NOT_GIVEN, ge=0)
         temperature: Optional[float] = Field(default_factory=lambda: NOT_GIVEN, ge=0.0, le=2.0)
         top_p: Optional[float] = Field(default_factory=lambda: NOT_GIVEN, ge=0.0, le=1.0)
+        extra: Optional[Dict[str, Any]] = Field(default_factory=dict)
 
     def __init__(
             self,
@@ -107,6 +108,7 @@ class BaseOpenAILLMService(LLMService):
         self._seed = params.seed
         self._temperature = params.temperature
         self._top_p = params.top_p
+        self._extra = params.extra if isinstance(params.extra, dict) else {}
 
     def create_client(self, api_key=None, base_url=None, **kwargs):
         return AsyncOpenAI(
@@ -141,23 +143,32 @@ class BaseOpenAILLMService(LLMService):
         logger.debug(f"Switching LLM top_p to: [{top_p}]")
         self._top_p = top_p
 
+    async def set_extra(self, extra: Dict[str, Any]):
+        logger.debug(f"Switching LLM extra to: [{extra}]")
+        self._extra = extra
+
     async def get_chat_completions(
             self,
             context: OpenAILLMContext,
             messages: List[ChatCompletionMessageParam]) -> AsyncStream[ChatCompletionChunk]:
-        chunks = await self._client.chat.completions.create(
-            model=self.model_name,
-            stream=True,
-            messages=messages,
-            tools=context.tools,
-            tool_choice=context.tool_choice,
-            stream_options={"include_usage": True},
-            frequency_penalty=self._frequency_penalty,
-            presence_penalty=self._presence_penalty,
-            seed=self._seed,
-            temperature=self._temperature,
-            top_p=self._top_p
-        )
+
+        params = {
+            "model": self.model_name,
+            "stream": True,
+            "messages": messages,
+            "tools": context.tools,
+            "tool_choice": context.tool_choice,
+            "stream_options": {"include_usage": True},
+            "frequency_penalty": self._frequency_penalty,
+            "presence_penalty": self._presence_penalty,
+            "seed": self._seed,
+            "temperature": self._temperature,
+            "top_p": self._top_p,
+        }
+
+        params.update(self._extra)
+
+        chunks = await self._client.chat.completions.create(**params)
         return chunks
 
     async def _stream_chat_completions(
diff --git a/src/pipecat/services/together.py b/src/pipecat/services/together.py
index 4c8a5527d..ce8c62730 100644
--- a/src/pipecat/services/together.py
+++ b/src/pipecat/services/together.py
@@ -9,7 +9,7 @@ import re
 import uuid
 from pydantic import BaseModel, Field
 
-from typing import List
+from typing import Any, Dict, List, Optional
 from dataclasses import dataclass
 from asyncio import CancelledError
 
@@ -64,6 +64,7 @@ class TogetherLLMService(LLMService):
         temperature: Optional[float] = Field(default=None, ge=0.0, le=1.0)
         top_k: Optional[int] = Field(default=None, ge=0)
         top_p: Optional[float] = Field(default=None, ge=0.0, le=1.0)
+        extra: Optional[Dict[str, Any]] = Field(default_factory=dict)
 
     def __init__(
             self,
@@ -81,6 +82,7 @@ class TogetherLLMService(LLMService):
         self._temperature = params.temperature
         self._top_k = params.top_k
         self._top_p = params.top_p
+        self._extra = params.extra if isinstance(params.extra, dict) else {}
 
     def can_generate_metrics(self) -> bool:
         return True
@@ -118,6 +120,10 @@ class TogetherLLMService(LLMService):
         logger.debug(f"Switching LLM top_p to: [{top_p}]")
         self._top_p = top_p
 
+    async def set_extra(self, extra: Dict[str, Any]):
+        logger.debug(f"Switching LLM extra to: [{extra}]")
+        self._extra = extra
+
     async def _process_context(self, context: OpenAILLMContext):
         try:
             await self.push_frame(LLMFullResponseStartFrame())
@@ -127,17 +133,21 @@ class TogetherLLMService(LLMService):
 
             await self.start_ttfb_metrics()
 
-            stream = await self._client.chat.completions.create(
-                messages=context.messages,
-                model=self.model_name,
-                max_tokens=self._max_tokens,
-                stream=True,
-                frequency_penalty=self._frequency_penalty,
-                presence_penalty=self._presence_penalty,
-                temperature=self._temperature,
-                top_k=self._top_k,
-                top_p=self._top_p
-            )
+            params = {
+                "messages": context.messages,
+                "model": self.model_name,
+                "max_tokens": self._max_tokens,
+                "stream": True,
+                "frequency_penalty": self._frequency_penalty,
+                "presence_penalty": self._presence_penalty,
+                "temperature": self._temperature,
+                "top_k": self._top_k,
+                "top_p": self._top_p
+            }
+
+            params.update(self._extra)
+
+            stream = await self._client.chat.completions.create(**params)
 
             # Function calling
             got_first_chunk = False

From 9e27a8aad0da1495195f39ce387f75951e4b1ae1 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Fri, 20 Sep 2024 23:35:38 -0400
Subject: [PATCH 046/135] Add control frames for LLM param updates

---
 src/pipecat/frames/frames.py | 60 ++++++++++++++++++++++++++++++++++++
 1 file changed, 60 insertions(+)

diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py
index 8f1f52234..3211bd266 100644
--- a/src/pipecat/frames/frames.py
+++ b/src/pipecat/frames/frames.py
@@ -483,6 +483,66 @@ class LLMModelUpdateFrame(ControlFrame):
     model: str
 
 
+@dataclass
+class LLMTemperatureUpdateFrame(ControlFrame):
+    """A control frame containing a request to update to a new LLM temperature.
+    """
+    temperature: float
+
+
+@dataclass
+class LLMTopKUpdateFrame(ControlFrame):
+    """A control frame containing a request to update to a new LLM top_k.
+    """
+    top_k: int
+
+
+@dataclass
+class LLMTopPUpdateFrame(ControlFrame):
+    """A control frame containing a request to update to a new LLM top_p.
+    """
+    top_p: float
+
+
+@dataclass
+class LLMFrequencyPenaltyUpdateFrame(ControlFrame):
+    """A control frame containing a request to update to a new LLM frequency
+    penalty.
+
+    """
+    frequency_penalty: float
+
+
+@dataclass
+class LLMPresencePenaltyUpdateFrame(ControlFrame):
+    """A control frame containing a request to update to a new LLM presence
+    penalty.
+
+    """
+    presence_penalty: float
+
+
+@dataclass
+class LLMMaxTokensUpdateFrame(ControlFrame):
+    """A control frame containing a request to update to a new LLM max tokens.
+    """
+    max_tokens: int
+
+
+@dataclass
+class LLMSeedUpdateFrame(ControlFrame):
+    """A control frame containing a request to update to a new LLM seed.
+    """
+    seed: int
+
+
+@dataclass
+class LLMExtraUpdateFrame(ControlFrame):
+    """A control frame containing a request to update to a new LLM extra params.
+    """
+    extra: dict
+
+
 @dataclass
 class TTSModelUpdateFrame(ControlFrame):
     """A control frame containing a request to update the TTS model.

From 55c645c6141bd25554e3231f2fe9f80db3acf8d5 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Sun, 22 Sep 2024 09:49:35 -0400
Subject: [PATCH 047/135] Add voice_settings and optimize_streaming_latency to
 ElevenLabs

---
 .../07d-interruptible-elevenlabs.py           |  59 +++++-----
 src/pipecat/services/elevenlabs.py            | 103 +++++++++++++++---
 2 files changed, 116 insertions(+), 46 deletions(-)

diff --git a/examples/foundational/07d-interruptible-elevenlabs.py b/examples/foundational/07d-interruptible-elevenlabs.py
index 19bd4ad01..c8a32d872 100644
--- a/examples/foundational/07d-interruptible-elevenlabs.py
+++ b/examples/foundational/07d-interruptible-elevenlabs.py
@@ -5,26 +5,27 @@
 #
 
 import asyncio
-import aiohttp
 import os
 import sys
 
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+from runner import configure
+
 from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator, LLMUserResponseAggregator)
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
+)
 from pipecat.services.elevenlabs import ElevenLabsTTSService
 from pipecat.services.openai import OpenAILLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 from pipecat.vad.silero import SileroVADAnalyzer
 
-from runner import configure
-
-from loguru import logger
-
-from dotenv import load_dotenv
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -43,8 +44,8 @@ async def main():
                 audio_out_enabled=True,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
         tts = ElevenLabsTTSService(
@@ -52,9 +53,7 @@ async def main():
             voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""),
         )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
         messages = [
             {
@@ -66,28 +65,32 @@ async def main():
         tma_in = LLMUserResponseAggregator(messages)
         tma_out = LLMAssistantResponseAggregator(messages)
 
-        pipeline = Pipeline([
-            transport.input(),   # Transport user input
-            tma_in,              # User responses
-            llm,                 # LLM
-            tts,                 # TTS
-            transport.output(),  # Transport bot output
-            tma_out              # Assistant spoken responses
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                tma_in,  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                tma_out,  # Assistant spoken responses
+            ]
+        )
 
-        task = PipelineTask(pipeline, PipelineParams(
-            allow_interruptions=True,
-            enable_metrics=True,
-            enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
-        ))
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
             transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
-            messages.append(
-                {"role": "system", "content": "Please introduce yourself to the user."})
+            messages.append({"role": "system", "content": "Please introduce yourself to the user."})
             await task.queue_frames([LLMMessagesFrame(messages)])
 
         runner = PipelineRunner()
diff --git a/src/pipecat/services/elevenlabs.py b/src/pipecat/services/elevenlabs.py
index ac8dc4c3d..00a32cbfd 100644
--- a/src/pipecat/services/elevenlabs.py
+++ b/src/pipecat/services/elevenlabs.py
@@ -7,9 +7,10 @@
 import asyncio
 import base64
 import json
+from typing import Any, AsyncGenerator, Dict, List, Literal, Mapping, Optional, Tuple
 
-from typing import Any, AsyncGenerator, List, Literal, Mapping, Tuple
-from pydantic import BaseModel
+from loguru import logger
+from pydantic import BaseModel, model_validator
 
 from pipecat.frames.frames import (
     CancelFrame,
@@ -19,19 +20,19 @@ from pipecat.frames.frames import (
     StartInterruptionFrame,
     TTSAudioRawFrame,
     TTSStartedFrame,
-    TTSStoppedFrame)
+    TTSStoppedFrame,
+)
 from pipecat.processors.frame_processor import FrameDirection
 from pipecat.services.ai_services import AsyncWordTTSService
 
-from loguru import logger
-
 # See .env.example for ElevenLabs configuration needed
 try:
     import websockets
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
-        "In order to use ElevenLabs, you need to `pip install pipecat-ai[elevenlabs]`. Also, set `ELEVENLABS_API_KEY` environment variable.")
+        "In order to use ElevenLabs, you need to `pip install pipecat-ai[elevenlabs]`. Also, set `ELEVENLABS_API_KEY` environment variable."
+    )
     raise Exception(f"Missing module: {e}")
 
 
@@ -49,7 +50,7 @@ def sample_rate_from_output_format(output_format: str) -> int:
 
 
 def calculate_word_times(
-        alignment_info: Mapping[str, Any], cumulative_time: float
+    alignment_info: Mapping[str, Any], cumulative_time: float
 ) -> List[Tuple[str, float]]:
     zipped_times = list(zip(alignment_info["chars"], alignment_info["charStartTimesMs"]))
 
@@ -59,7 +60,7 @@ def calculate_word_times(
     # and using the previous word time, also taking into account there might not
     # be a space at the end.
     times = []
-    for (i, (a, b)) in enumerate(zipped_times):
+    for i, (a, b) in enumerate(zipped_times):
         if a == " " or i == len(zipped_times) - 1:
             t = cumulative_time + (zipped_times[i - 1][1] / 1000.0)
             times.append(t)
@@ -72,16 +73,32 @@ def calculate_word_times(
 class ElevenLabsTTSService(AsyncWordTTSService):
     class InputParams(BaseModel):
         output_format: Literal["pcm_16000", "pcm_22050", "pcm_24000", "pcm_44100"] = "pcm_16000"
+        optimize_streaming_latency: Optional[str] = None
+        stability: Optional[float] = None
+        similarity_boost: Optional[float] = None
+        style: Optional[float] = None
+        use_speaker_boost: Optional[bool] = None
+
+        @model_validator(mode="after")
+        def validate_voice_settings(self):
+            stability = self.stability
+            similarity_boost = self.similarity_boost
+            if (stability is None) != (similarity_boost is None):
+                raise ValueError(
+                    "Both 'stability' and 'similarity_boost' must be provided when using voice settings"
+                )
+            return self
 
     def __init__(
-            self,
-            *,
-            api_key: str,
-            voice_id: str,
-            model: str = "eleven_turbo_v2_5",
-            url: str = "wss://api.elevenlabs.io",
-            params: InputParams = InputParams(),
-            **kwargs):
+        self,
+        *,
+        api_key: str,
+        voice_id: str,
+        model: str = "eleven_turbo_v2_5",
+        url: str = "wss://api.elevenlabs.io",
+        params: InputParams = InputParams(),
+        **kwargs,
+    ):
         # Aggregating sentences still gives cleaner-sounding results and fewer
         # artifacts than streaming one word at a time. On average, waiting for a
         # full sentence should only "cost" us 15ms or so with GPT-4o or a Llama
@@ -102,7 +119,7 @@ class ElevenLabsTTSService(AsyncWordTTSService):
             push_stop_frames=True,
             stop_frame_timeout_s=2.0,
             sample_rate=sample_rate_from_output_format(params.output_format),
-            **kwargs
+            **kwargs,
         )
 
         self._api_key = api_key
@@ -110,6 +127,7 @@ class ElevenLabsTTSService(AsyncWordTTSService):
         self.set_model_name(model)
         self._url = url
         self._params = params
+        self._voice_settings = self._set_voice_settings()
 
         # Websocket connection to ElevenLabs.
         self._websocket = None
@@ -121,6 +139,27 @@ class ElevenLabsTTSService(AsyncWordTTSService):
     def can_generate_metrics(self) -> bool:
         return True
 
+    def _set_voice_settings(self):
+        voice_settings = {}
+        if self._params.stability is not None and self._params.similarity_boost is not None:
+            voice_settings["stability"] = self._params.stability
+            voice_settings["similarity_boost"] = self._params.similarity_boost
+            if self._params.style is not None:
+                voice_settings["style"] = self._params.style
+            if self._params.use_speaker_boost is not None:
+                voice_settings["use_speaker_boost"] = self._params.use_speaker_boost
+        else:
+            if self._params.style is not None:
+                logger.warning(
+                    "'style' is set but will not be applied because 'stability' and 'similarity_boost' are not both set."
+                )
+            if self._params.use_speaker_boost is not None:
+                logger.warning(
+                    "'use_speaker_boost' is set but will not be applied because 'stability' and 'similarity_boost' are not both set."
+                )
+
+        return voice_settings or None
+
     async def set_model(self, model: str):
         await super().set_model(model)
         logger.debug(f"Switching TTS model to: [{model}]")
@@ -133,6 +172,28 @@ class ElevenLabsTTSService(AsyncWordTTSService):
         await self._disconnect()
         await self._connect()
 
+    async def set_voice_settings(
+        self,
+        stability: Optional[float] = None,
+        similarity_boost: Optional[float] = None,
+        style: Optional[float] = None,
+        use_speaker_boost: Optional[bool] = None,
+    ):
+        self._params.stability = stability if stability is not None else self._params.stability
+        self._params.similarity_boost = (
+            similarity_boost if similarity_boost is not None else self._params.similarity_boost
+        )
+        self._params.style = style if style is not None else self._params.style
+        self._params.use_speaker_boost = (
+            use_speaker_boost if use_speaker_boost is not None else self._params.use_speaker_boost
+        )
+
+        self._set_voice_settings()
+
+        if self._websocket:
+            msg = {"voice_settings": self._voice_settings}
+            await self._websocket.send(json.dumps(msg))
+
     async def start(self, frame: StartFrame):
         await super().start(frame)
         await self._connect()
@@ -163,15 +224,21 @@ class ElevenLabsTTSService(AsyncWordTTSService):
             model = self.model_name
             output_format = self._params.output_format
             url = f"{self._url}/v1/text-to-speech/{voice_id}/stream-input?model_id={model}&output_format={output_format}"
+
+            if self._params.optimize_streaming_latency:
+                url += f"&optimize_streaming_latency={self._params.optimize_streaming_latency}"
+
             self._websocket = await websockets.connect(url)
             self._receive_task = self.get_event_loop().create_task(self._receive_task_handler())
             self._keepalive_task = self.get_event_loop().create_task(self._keepalive_task_handler())
 
             # According to ElevenLabs, we should always start with a single space.
-            msg = {
+            msg: Dict[str, Any] = {
                 "text": " ",
                 "xi_api_key": self._api_key,
             }
+            if self._voice_settings:
+                msg["voice_settings"] = self._voice_settings
             await self._websocket.send(json.dumps(msg))
         except Exception as e:
             logger.error(f"{self} initialization error: {e}")

From 4533ed014fc4a22d3f7123c8f2ab3425ff7afb2f Mon Sep 17 00:00:00 2001
From: duyalei <>
Date: Mon, 23 Sep 2024 16:34:31 +0800
Subject: [PATCH 048/135] add full-width punctuations as end of the sentence

---
 src/pipecat/utils/string.py |  3 ++-
 tests/test_ai_services.py   | 13 +++++++++++++
 2 files changed, 15 insertions(+), 1 deletion(-)

diff --git a/src/pipecat/utils/string.py b/src/pipecat/utils/string.py
index a47db6c5c..cf9a22ad8 100644
--- a/src/pipecat/utils/string.py
+++ b/src/pipecat/utils/string.py
@@ -14,7 +14,8 @@ ENDOFSENTENCE_PATTERN_STR = r"""
     (?<!Mr|Ms|Dr)    # Negative lookbehind: not preceded by Mr, Ms, Dr (combined bc. length is the same)
     (?<!Mrs)         # Negative lookbehind: not preceded by "Mrs"
     (?<!Prof)        # Negative lookbehind: not preceded by "Prof"
-    [\.\?\!:]        # Match a period, question mark, exclamation point, or colon
+    [\.\?\!:;]|      # Match a period, question mark, exclamation point, colon, or semicolon
+    [。？！：；]       # the full-width version (mainly used in East Asian languages such as Chinese)
     $                # End of string
 """
 ENDOFSENTENCE_PATTERN = re.compile(ENDOFSENTENCE_PATTERN_STR, re.VERBOSE)
diff --git a/tests/test_ai_services.py b/tests/test_ai_services.py
index fb00fc893..f539a44ce 100644
--- a/tests/test_ai_services.py
+++ b/tests/test_ai_services.py
@@ -32,6 +32,7 @@ class TestBaseAIService(unittest.IsolatedAsyncioTestCase):
         assert match_endofsentence("This is a sentence! ")
         assert match_endofsentence("This is a sentence?")
         assert match_endofsentence("This is a sentence:")
+        assert match_endofsentence("This is a sentence;")
         assert not match_endofsentence("This is not a sentence")
         assert not match_endofsentence("This is not a sentence,")
         assert not match_endofsentence("This is not a sentence, ")
@@ -43,6 +44,18 @@ class TestBaseAIService(unittest.IsolatedAsyncioTestCase):
         assert not match_endofsentence("America, or the U.")  # U.S.A.
         assert not match_endofsentence("It still early, it's 3:00 a.")  # 3:00 a.m.
 
+    async def test_endofsentence_zh(self):
+        chinese_sentences = [
+            "你好。",
+            "你好！",
+            "吃了吗？",
+            "安全第一；",
+            "他说：",
+        ]
+        for i in chinese_sentences:
+            assert match_endofsentence(i)
+        assert not match_endofsentence("你好，")
+
 
 if __name__ == "__main__":
     unittest.main()

From 306632b29a0ee2e4ea2a38cf10c804b8d0545107 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Mon, 23 Sep 2024 08:37:29 -0400
Subject: [PATCH 049/135] Add language_code support for ElevenLabs TTS

---
 src/pipecat/services/elevenlabs.py | 10 ++++++++++
 1 file changed, 10 insertions(+)

diff --git a/src/pipecat/services/elevenlabs.py b/src/pipecat/services/elevenlabs.py
index 00a32cbfd..79d90bc58 100644
--- a/src/pipecat/services/elevenlabs.py
+++ b/src/pipecat/services/elevenlabs.py
@@ -72,6 +72,7 @@ def calculate_word_times(
 
 class ElevenLabsTTSService(AsyncWordTTSService):
     class InputParams(BaseModel):
+        language_code: Optional[str] = None
         output_format: Literal["pcm_16000", "pcm_22050", "pcm_24000", "pcm_44100"] = "pcm_16000"
         optimize_streaming_latency: Optional[str] = None
         stability: Optional[float] = None
@@ -228,6 +229,15 @@ class ElevenLabsTTSService(AsyncWordTTSService):
             if self._params.optimize_streaming_latency:
                 url += f"&optimize_streaming_latency={self._params.optimize_streaming_latency}"
 
+            # language_code can only be used with the 'eleven_turbo_v2_5' model
+            if self._params.language_code:
+                if model == "eleven_turbo_v2_5":
+                    url += f"&language_code={self._params.language_code}"
+                else:
+                    logger.debug(
+                        f"Language code [{self._params.language_code}] not applied. Language codes can only be used with the 'eleven_turbo_v2_5' model."
+                    )
+
             self._websocket = await websockets.connect(url)
             self._receive_task = self.get_event_loop().create_task(self._receive_task_handler())
             self._keepalive_task = self.get_event_loop().create_task(self._keepalive_task_handler())

From dfa4ac81fdcefc823e801c6ba102de5924362d6f Mon Sep 17 00:00:00 2001
From: "Cyril S." <98121174+cyrilS-dev@users.noreply.github.com>
Date: Mon, 23 Sep 2024 17:44:14 +0200
Subject: [PATCH 050/135] Implement Sentry instrumentation for performance and
 error tracking (#470)

* feat: Add Sentry support in FrameProcessor

This update add optional Sentry integration for performance tracking and error monitoring.

Key changes include:

- Add conditional Sentry import and initialization check
- Implement Sentry spans in FrameProcessorMetrics to measure TTFB (Time To First Byte) and processing time when Sentry is available
- Maintain existing metrics functionality with MetricsFrame regardless of Sentry availability

* feat: Enable metrics in DeepgramSTTService for Sentry

This commit enhances the DeepgramSTTService class to enable metrics generation for use with Sentry.

Key changes include:

1. Enable general metrics generation:
   - Implement `can_generate_metrics` method, returning True when VAD is enabled
   - This allows metrics to be collected and used by both Sentry and the metrics system in frame_processor.py

2. Integrate Sentry-compatible performance tracking:
   - Add start_ttfb_metrics and start_processing_metrics calls in the VAD speech detection handler
   - Implement stop_ttfb_metrics call when receiving transcripts
   - Add stop_processing_metrics for final transcripts

3. Enhance VAD support for metrics:
   - Add `vad_enabled` property to check VAD event availability
   - Implement VAD-based speech detection handler for precise metric timing

These changes enable detailed performance tracking via both Sentry and the general metrics system when VAD is active. This allows for better monitoring and analysis of the speech-to-text process, providing valuable insights through Sentry and any other metrics consumers in the pipeline.

* Update frame_processor.py

* Refactor to support flexible metrics implementation

- Modified the __init__ method to accept a metrics parameter that is either FrameProcessorMetrics or one of its subclasses
- Updated the metrics initialization to create an instance with the processor's name
- Moved all FrameProcessorMetrics-related logic to a new processors\metrics\base.py file

* Implement flexible metrics system with Sentry integration

1. Created a new metrics module in processors/metrics/

2. Implemented FrameProcessorMetrics base class in base.py:

3. Implemented SentryMetrics class in sentry.py:
   - Inherits from FrameProcessorMetrics
   - Integrates with Sentry SDK for advanced metrics tracking
   - Implements Sentry-specific span creation and management for TTFB and processing metrics
   - Handles cases where Sentry is not available or initialized
---
 src/pipecat/processors/frame_processor.py     | 84 ++-----------------
 .../metrics/frame_processor_metrics.py        | 81 ++++++++++++++++++
 src/pipecat/processors/metrics/sentry.py      | 56 +++++++++++++
 src/pipecat/services/deepgram.py              | 28 +++++--
 4 files changed, 169 insertions(+), 80 deletions(-)
 create mode 100644 src/pipecat/processors/metrics/frame_processor_metrics.py
 create mode 100644 src/pipecat/processors/metrics/sentry.py

diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py
index e44b8b0ff..69c957c97 100644
--- a/src/pipecat/processors/frame_processor.py
+++ b/src/pipecat/processors/frame_processor.py
@@ -14,18 +14,14 @@ from pipecat.frames.frames import (
     EndFrame,
     ErrorFrame,
     Frame,
-    MetricsFrame,
     StartFrame,
     StartInterruptionFrame,
     StopInterruptionFrame,
     SystemFrame)
 from pipecat.metrics.metrics import (
     LLMTokenUsage,
-    LLMUsageMetricsData,
-    MetricsData,
-    ProcessingMetricsData,
-    TTFBMetricsData,
-    TTSUsageMetricsData)
+    MetricsData)
+from pipecat.processors.metrics.frame_processor_metrics import FrameProcessorMetrics
 from pipecat.utils.utils import obj_count, obj_id
 
 from loguru import logger
@@ -36,78 +32,13 @@ class FrameDirection(Enum):
     UPSTREAM = 2
 
 
-class FrameProcessorMetrics:
-    def __init__(self, name: str):
-        self._core_metrics_data = MetricsData(processor=name)
-        self._start_ttfb_time = 0
-        self._start_processing_time = 0
-        self._should_report_ttfb = True
-
-    def _processor_name(self):
-        return self._core_metrics_data.processor
-
-    def _model_name(self):
-        return self._core_metrics_data.model
-
-    def set_core_metrics_data(self, data: MetricsData):
-        self._core_metrics_data = data
-
-    async def start_ttfb_metrics(self, report_only_initial_ttfb):
-        if self._should_report_ttfb:
-            self._start_ttfb_time = time.time()
-            self._should_report_ttfb = not report_only_initial_ttfb
-
-    async def stop_ttfb_metrics(self):
-        if self._start_ttfb_time == 0:
-            return None
-
-        value = time.time() - self._start_ttfb_time
-        logger.debug(f"{self._processor_name()} TTFB: {value}")
-        ttfb = TTFBMetricsData(
-            processor=self._processor_name(),
-            value=value,
-            model=self._model_name())
-        self._start_ttfb_time = 0
-        return MetricsFrame(data=[ttfb])
-
-    async def start_processing_metrics(self):
-        self._start_processing_time = time.time()
-
-    async def stop_processing_metrics(self):
-        if self._start_processing_time == 0:
-            return None
-
-        value = time.time() - self._start_processing_time
-        logger.debug(f"{self._processor_name()} processing time: {value}")
-        processing = ProcessingMetricsData(
-            processor=self._processor_name(), value=value, model=self._model_name())
-        self._start_processing_time = 0
-        return MetricsFrame(data=[processing])
-
-    async def start_llm_usage_metrics(self, tokens: LLMTokenUsage):
-        logger.debug(
-            f"{self._processor_name()} prompt tokens: {tokens.prompt_tokens}, completion tokens: {tokens.completion_tokens}")
-        value = LLMUsageMetricsData(
-            processor=self._processor_name(),
-            model=self._model_name(),
-            value=tokens)
-        return MetricsFrame(data=[value])
-
-    async def start_tts_usage_metrics(self, text: str):
-        characters = TTSUsageMetricsData(
-            processor=self._processor_name(),
-            model=self._model_name(),
-            value=len(text))
-        logger.debug(f"{self._processor_name()} usage characters: {characters.value}")
-        return MetricsFrame(data=[characters])
-
-
 class FrameProcessor:
 
     def __init__(
             self,
             *,
             name: str | None = None,
+            metrics: FrameProcessorMetrics | None = None,
             sync: bool = True,
             loop: asyncio.AbstractEventLoop | None = None,
             **kwargs):
@@ -129,7 +60,8 @@ class FrameProcessor:
         self._report_only_initial_ttfb = False
 
         # Metrics
-        self._metrics = FrameProcessorMetrics(name=self.name)
+        self._metrics = metrics or FrameProcessorMetrics()
+        self._metrics.set_processor_name(self.name)
 
         # Every processor in Pipecat should only output frames from a single
         # task. This avoid problems like audio overlapping. System frames are
@@ -262,14 +194,16 @@ class FrameProcessor:
                 logger.trace(f"Pushing {frame} from {self} to {self._next}")
                 await self._next.process_frame(frame, direction)
             elif direction == FrameDirection.UPSTREAM and self._prev:
-                logger.trace(f"Pushing {frame} upstream from {self} to {self._prev}")
+                logger.trace(f"Pushing {frame} upstream from {
+                             self} to {self._prev}")
                 await self._prev.process_frame(frame, direction)
         except Exception as e:
             logger.exception(f"Uncaught exception in {self}: {e}")
 
     def __create_push_task(self):
         self.__push_queue = asyncio.Queue()
-        self.__push_frame_task = self.get_event_loop().create_task(self.__push_frame_task_handler())
+        self.__push_frame_task = self.get_event_loop(
+        ).create_task(self.__push_frame_task_handler())
 
     async def __push_frame_task_handler(self):
         running = True
diff --git a/src/pipecat/processors/metrics/frame_processor_metrics.py b/src/pipecat/processors/metrics/frame_processor_metrics.py
new file mode 100644
index 000000000..b9de3c2b4
--- /dev/null
+++ b/src/pipecat/processors/metrics/frame_processor_metrics.py
@@ -0,0 +1,81 @@
+import time
+
+from pipecat.frames.frames import MetricsFrame
+from pipecat.metrics.metrics import (
+    LLMTokenUsage,
+    LLMUsageMetricsData,
+    MetricsData,
+    ProcessingMetricsData,
+    TTFBMetricsData,
+    TTSUsageMetricsData)
+
+from loguru import logger
+
+
+class FrameProcessorMetrics:
+    def __init__(self):
+        self._start_ttfb_time = 0
+        self._start_processing_time = 0
+        self._should_report_ttfb = True
+
+    def _processor_name(self):
+        return self._core_metrics_data.processor
+
+    def _model_name(self):
+        return self._core_metrics_data.model
+
+    def set_core_metrics_data(self, data: MetricsData):
+        self._core_metrics_data = data
+
+    def set_processor_name(self, name: str):
+        self._core_metrics_data = MetricsData(processor=name)
+
+    async def start_ttfb_metrics(self, report_only_initial_ttfb):
+        if self._should_report_ttfb:
+            self._start_ttfb_time = time.time()
+            self._should_report_ttfb = not report_only_initial_ttfb
+
+    async def stop_ttfb_metrics(self):
+        if self._start_ttfb_time == 0:
+            return None
+
+        value = time.time() - self._start_ttfb_time
+        logger.debug(f"{self._processor_name()} TTFB: {value}")
+        ttfb = TTFBMetricsData(
+            processor=self._processor_name(),
+            value=value,
+            model=self._model_name())
+        self._start_ttfb_time = 0
+        return MetricsFrame(data=[ttfb])
+
+    async def start_processing_metrics(self):
+        self._start_processing_time = time.time()
+
+    async def stop_processing_metrics(self):
+        if self._start_processing_time == 0:
+            return None
+
+        value = time.time() - self._start_processing_time
+        logger.debug(f"{self._processor_name()} processing time: {value}")
+        processing = ProcessingMetricsData(
+            processor=self._processor_name(), value=value, model=self._model_name())
+        self._start_processing_time = 0
+        return MetricsFrame(data=[processing])
+
+    async def start_llm_usage_metrics(self, tokens: LLMTokenUsage):
+        logger.debug(
+            f"{self._processor_name()} prompt tokens: {tokens.prompt_tokens}, completion tokens: {tokens.completion_tokens}")
+        value = LLMUsageMetricsData(
+            processor=self._processor_name(),
+            model=self._model_name(),
+            value=tokens)
+        return MetricsFrame(data=[value])
+
+    async def start_tts_usage_metrics(self, text: str):
+        characters = TTSUsageMetricsData(
+            processor=self._processor_name(),
+            model=self._model_name(),
+            value=len(text))
+        logger.debug(f"{self._processor_name()} usage characters: {
+                     characters.value}")
+        return MetricsFrame(data=[characters])
diff --git a/src/pipecat/processors/metrics/sentry.py b/src/pipecat/processors/metrics/sentry.py
new file mode 100644
index 000000000..da3057e76
--- /dev/null
+++ b/src/pipecat/processors/metrics/sentry.py
@@ -0,0 +1,56 @@
+import time
+from loguru import logger
+
+try:
+    import sentry_sdk
+    sentry_available = sentry_sdk.is_initialized()
+    if not sentry_available:
+        logger.warning(
+            "Sentry SDK not initialized. Sentry features will be disabled.")
+except ImportError:
+    sentry_available = False
+    logger.warning(
+        "Sentry SDK not installed. Sentry features will be disabled.")
+
+from pipecat.processors.metrics.frame_processor_metrics import FrameProcessorMetrics
+
+
+class SentryMetrics(FrameProcessorMetrics):
+    def __init__(self):
+        super().__init__()
+        self._ttfb_metrics_span = None
+        self._processing_metrics_span = None
+
+    async def start_ttfb_metrics(self, report_only_initial_ttfb):
+        if self._should_report_ttfb:
+            self._start_ttfb_time = time.time()
+            if sentry_available:
+                self._ttfb_metrics_span = sentry_sdk.start_span(
+                    op="ttfb",
+                    description=f"TTFB for {self._processor_name()}",
+                    start_timestamp=self._start_ttfb_time
+                )
+                logger.debug(f"Sentry Span ID: {self._ttfb_metrics_span.span_id} Description: {
+                             self._ttfb_metrics_span.description} started.")
+            self._should_report_ttfb = not report_only_initial_ttfb
+
+    async def stop_ttfb_metrics(self):
+        stop_time = time.time()
+        if sentry_available:
+            self._ttfb_metrics_span.finish(end_timestamp=stop_time)
+
+    async def start_processing_metrics(self):
+        self._start_processing_time = time.time()
+        if sentry_available:
+            self._processing_metrics_span = sentry_sdk.start_span(
+                op="processing",
+                description=f"Processing for {self._processor_name()}",
+                start_timestamp=self._start_processing_time
+            )
+            logger.debug(f"Sentry Span ID: {self._processing_metrics_span.span_id} Description: {
+                         self._processing_metrics_span.description} started.")
+
+    async def stop_processing_metrics(self):
+        stop_time = time.time()
+        if sentry_available:
+            self._processing_metrics_span.finish(end_timestamp=stop_time)
diff --git a/src/pipecat/services/deepgram.py b/src/pipecat/services/deepgram.py
index e3089dd0c..25f7b7a56 100644
--- a/src/pipecat/services/deepgram.py
+++ b/src/pipecat/services/deepgram.py
@@ -75,7 +75,8 @@ class DeepgramTTSService(TTSService):
         logger.debug(f"Generating TTS: [{text}]")
 
         base_url = self._base_url
-        request_url = f"{base_url}?model={self._voice}&encoding={self._encoding}&container=none&sample_rate={self._sample_rate}"
+        request_url = f"{base_url}?model={self._voice}&encoding={
+            self._encoding}&container=none&sample_rate={self._sample_rate}"
         headers = {"authorization": f"token {self._api_key}"}
         body = {"text": text}
 
@@ -124,6 +125,7 @@ class DeepgramSTTService(STTService):
                      smart_format=True,
                      punctuate=True,
                      profanity_filter=True,
+                     vad_events=False,
                  ),
                  **kwargs):
         super().__init__(**kwargs)
@@ -132,8 +134,20 @@ class DeepgramSTTService(STTService):
 
         self._client = DeepgramClient(
             api_key, config=DeepgramClientOptions(url=url, options={"keepalive": "true"}))
-        self._connection: AsyncListenWebSocketClient = self._client.listen.asyncwebsocket.v("1")
-        self._connection.on(LiveTranscriptionEvents.Transcript, self._on_message)
+        self._connection: AsyncListenWebSocketClient = self._client.listen.asyncwebsocket.v(
+            "1")
+        self._connection.on(
+            LiveTranscriptionEvents.Transcript, self._on_message)
+        if self.vad_enabled:
+            self._connection.on(
+                LiveTranscriptionEvents.SpeechStarted, self._on_speech_started)
+
+    @property
+    def vad_enabled(self):
+        return self._live_options.vad_events
+
+    def can_generate_metrics(self) -> bool:
+        return self.vad_enabled
 
     async def set_model(self, model: str):
         await super().set_model(model)
@@ -161,9 +175,7 @@ class DeepgramSTTService(STTService):
         await self._disconnect()
 
     async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]:
-        await self.start_processing_metrics()
         await self._connection.send(audio)
-        await self.stop_processing_metrics()
         yield None
 
     async def _connect(self):
@@ -177,6 +189,10 @@ class DeepgramSTTService(STTService):
             await self._connection.finish()
             logger.debug(f"{self}: Disconnected from Deepgram")
 
+    async def _on_speech_started(self, *args, **kwargs):
+        await self.start_ttfb_metrics()
+        await self.start_processing_metrics()
+
     async def _on_message(self, *args, **kwargs):
         result: LiveResultResponse = kwargs["result"]
         if len(result.channel.alternatives) == 0:
@@ -188,7 +204,9 @@ class DeepgramSTTService(STTService):
             language = result.channel.alternatives[0].languages[0]
             language = Language(language)
         if len(transcript) > 0:
+            await self.stop_ttfb_metrics()
             if is_final:
                 await self.push_frame(TranscriptionFrame(transcript, "", time_now_iso8601(), language))
+                await self.stop_processing_metrics()
             else:
                 await self.push_frame(InterimTranscriptionFrame(transcript, "", time_now_iso8601(), language))

From eeb8338dce52d8539985ff5d5107d76b51badcdd Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Mon, 23 Sep 2024 09:11:37 -0700
Subject: [PATCH 051/135] introduce Ruff formatting

---
 .github/workflows/{lint.yaml => format.yaml}  |  19 +-
 dev-requirements.txt                          |   2 +-
 examples/deployment/flyio-example/bot.py      |  30 ++-
 .../deployment/flyio-example/bot_runner.py    | 118 ++++-----
 examples/dialin-chatbot/bot_daily.py          |  39 ++-
 examples/dialin-chatbot/bot_runner.py         |  70 ++---
 examples/dialin-chatbot/bot_twilio.py         |  40 +--
 examples/foundational/01-say-one-thing.py     |   7 +-
 examples/foundational/01a-local-audio.py      |   1 +
 examples/foundational/02-llm-say-one-thing.py |  14 +-
 examples/foundational/03-still-frame.py       |  11 +-
 .../foundational/03a-local-still-frame.py     |  11 +-
 .../foundational/04-utterance-and-speech.py   |   7 +-
 .../foundational/05-sync-speech-and-image.py  |  35 ++-
 .../05a-local-sync-speech-and-image.py        |  48 ++--
 .../foundational/06-listen-and-respond.py     |  43 +--
 examples/foundational/06a-image-sync.py       |  50 ++--
 examples/foundational/07-interruptible.py     |  49 ++--
 .../07a-interruptible-anthropic.py            |  31 ++-
 .../07b-interruptible-langchain.py            |  38 +--
 .../07c-interruptible-deepgram.py             |  40 +--
 .../foundational/07e-interruptible-playht.py  |  34 +--
 .../foundational/07f-interruptible-azure.py   |  30 ++-
 .../07g-interruptible-openai-tts.py           |  39 ++-
 .../07h-interruptible-openpipe.py             |  30 +--
 .../foundational/07i-interruptible-xtts.py    |  34 +--
 .../foundational/07j-interruptible-gladia.py  |  34 +--
 .../foundational/07k-interruptible-lmnt.py    |  39 ++-
 .../07l-interruptible-together.py             |  31 ++-
 examples/foundational/08-bots-arguing.py      |  11 +-
 examples/foundational/09-mirror.py            |  34 ++-
 examples/foundational/09a-local-mirror.py     |  36 ++-
 examples/foundational/10-wake-phrase.py       |  33 +--
 examples/foundational/11-sound-effects.py     |  42 +--
 examples/foundational/12-describe-video.py    |  31 ++-
 .../12a-describe-video-gemini-flash.py        |  35 +--
 .../foundational/12b-describe-video-gpt-4o.py |  36 +--
 .../12c-describe-video-anthropic.py           |  35 +--
 .../foundational/13-whisper-transcription.py  |   7 +-
 examples/foundational/13a-whisper-local.py    |   2 +-
 .../13b-deepgram-transcription.py             |   7 +-
 examples/foundational/14-function-calling.py  |  49 ++--
 examples/foundational/15-switch-voices.py     |  49 ++--
 examples/foundational/15a-switch-languages.py |  43 +--
 .../16-gpu-container-local-bot.py             |  52 ++--
 examples/foundational/17-detect-user-idle.py  |  55 ++--
 examples/foundational/18-gstreamer-filesrc.py |  22 +-
 .../18a-gstreamer-videotestsrc.py             |  21 +-
 examples/foundational/19a-tools-anthropic.py  |  28 +-
 .../foundational/19b-tools-video-anthropic.py |  37 +--
 examples/foundational/19c-tools-togetherai.py |  41 ++-
 examples/foundational/runner.py               |  21 +-
 examples/moondream-chatbot/bot.py             |  41 ++-
 examples/moondream-chatbot/runner.py          |  16 +-
 examples/moondream-chatbot/server.py          |  41 ++-
 examples/patient-intake/bot.py                | 173 +++++++-----
 examples/patient-intake/runner.py             |  17 +-
 examples/patient-intake/server.py             |  41 ++-
 examples/simple-chatbot/bot.py                |  42 ++-
 examples/simple-chatbot/runner.py             |  16 +-
 examples/simple-chatbot/server.py             |  41 ++-
 examples/storytelling-chatbot/src/bot.py      |  54 ++--
 .../storytelling-chatbot/src/bot_runner.py    | 110 ++++----
 .../storytelling-chatbot/src/processors.py    |   9 +-
 examples/storytelling-chatbot/src/prompts.py  |   4 +-
 .../storytelling-chatbot/src/utils/helpers.py |  11 +-
 examples/studypal/runner.py                   |  21 +-
 examples/studypal/studypal.py                 |  64 +++--
 examples/translation-chatbot/bot.py           |  32 +--
 examples/translation-chatbot/runner.py        |  16 +-
 examples/translation-chatbot/server.py        |  41 ++-
 examples/twilio-chatbot/bot.py                |  41 +--
 examples/twilio-chatbot/server.py             |   4 +-
 examples/websocket-server/bot.py              |  38 +--
 src/pipecat/clocks/base_clock.py              |   1 -
 src/pipecat/clocks/system_clock.py            |   1 -
 src/pipecat/frames/frames.py                  | 111 +++++---
 src/pipecat/pipeline/base_pipeline.py         |   1 -
 src/pipecat/pipeline/parallel_pipeline.py     |   2 -
 src/pipecat/pipeline/pipeline.py              |   3 -
 src/pipecat/pipeline/runner.py                |   7 +-
 .../pipeline/sync_parallel_pipeline.py        |   2 -
 src/pipecat/pipeline/task.py                  |  20 +-
 .../pipeline/to_be_updated/merge_pipeline.py  |   4 +-
 src/pipecat/processors/aggregators/gated.py   |  11 +-
 .../processors/aggregators/llm_response.py    |  19 +-
 .../aggregators/openai_llm_context.py         |  91 +++----
 .../processors/aggregators/user_response.py   |   5 +-
 .../aggregators/vision_image_frame.py         |  10 +-
 .../processors/filters/frame_filter.py        |   9 +-
 .../processors/filters/function_filter.py     |   1 -
 .../processors/filters/wake_check_filter.py   |  11 +-
 src/pipecat/processors/frame_processor.py     |  26 +-
 .../processors/frameworks/langchain.py        |   7 +-
 src/pipecat/processors/frameworks/rtvi.py     |  87 +++---
 .../processors/gstreamer/pipeline_source.py   |  28 +-
 .../processors/idle_frame_processor.py        |  13 +-
 src/pipecat/processors/logger.py              |   5 +-
 .../metrics/frame_processor_metrics.py        |  24 +-
 src/pipecat/processors/metrics/sentry.py      |  11 +-
 src/pipecat/processors/user_idle_processor.py |  14 +-
 src/pipecat/serializers/base_serializer.py    |   1 -
 src/pipecat/serializers/livekit.py            |  10 +-
 src/pipecat/serializers/protobuf.py           |   8 +-
 src/pipecat/serializers/twilio.py             |  22 +-
 src/pipecat/services/ai_services.py           |  92 +++----
 src/pipecat/services/anthropic.py             | 250 ++++++++++--------
 src/pipecat/services/azure.py                 |  67 +++--
 src/pipecat/services/cartesia.py              |  71 +++--
 src/pipecat/services/deepgram.py              |  94 ++++---
 src/pipecat/services/fal.py                   |  13 +-
 src/pipecat/services/fireworks.py             |  13 +-
 src/pipecat/services/gladia.py                |  36 +--
 src/pipecat/services/google.py                |  26 +-
 src/pipecat/services/lmnt.py                  |  24 +-
 src/pipecat/services/moondream.py             |  13 +-
 src/pipecat/services/ollama.py                |   1 -
 src/pipecat/services/openai.py                | 189 ++++++-------
 src/pipecat/services/openpipe.py              |  43 ++-
 src/pipecat/services/playht.py                |  36 +--
 .../to_be_updated/cloudflare_ai_service.py    |  27 +-
 .../to_be_updated/google_ai_service.py        |   8 +-
 .../to_be_updated/huggingface_ai_service.py   |   4 +-
 src/pipecat/services/together.py              |  87 +++---
 src/pipecat/services/whisper.py               |  26 +-
 src/pipecat/services/xtts.py                  |  33 ++-
 src/pipecat/transcriptions/language.py        |  87 +++---
 src/pipecat/transports/base_input.py          |  13 +-
 src/pipecat/transports/base_output.py         |  28 +-
 src/pipecat/transports/base_transport.py      |  12 +-
 src/pipecat/transports/local/audio.py         |  20 +-
 src/pipecat/transports/local/tk.py            |  26 +-
 .../transports/network/fastapi_websocket.py   |  63 ++---
 .../transports/network/websocket_server.py    |  67 +++--
 src/pipecat/transports/services/daily.py      | 194 +++++++-------
 .../transports/services/helpers/daily_rest.py |  49 ++--
 src/pipecat/utils/test_frame_processor.py     |   4 +-
 src/pipecat/vad/silero.py                     |  64 +++--
 src/pipecat/vad/vad_analyzer.py               |   1 -
 tests/integration/integration_azure_llm.py    |   6 +-
 tests/integration/integration_ollama_llm.py   |   6 +-
 tests/integration/integration_openai_llm.py   |  49 ++--
 tests/test_aggregators.py                     |  35 +--
 tests/test_ai_services.py                     |   5 +-
 tests/test_daily_transport_service.py         |   1 -
 tests/test_langchain.py                       |  20 +-
 tests/test_openai_tts.py                      |   7 +-
 tests/test_pipeline.py                        |  47 ++--
 tests/test_protobuf_serializer.py             |  18 +-
 149 files changed, 2653 insertions(+), 2461 deletions(-)
 rename .github/workflows/{lint.yaml => format.yaml} (63%)

diff --git a/.github/workflows/lint.yaml b/.github/workflows/format.yaml
similarity index 63%
rename from .github/workflows/lint.yaml
rename to .github/workflows/format.yaml
index ad5b160f1..1100ea394 100644
--- a/.github/workflows/lint.yaml
+++ b/.github/workflows/format.yaml
@@ -1,4 +1,4 @@
-name: lint
+name: format
 
 on:
   workflow_dispatch:
@@ -12,12 +12,12 @@ on:
       - "docs/**"
 
 concurrency:
-  group: build-lint-${{ github.event.pull_request.number || github.ref }}
+  group: build-format-${{ github.event.pull_request.number || github.ref }}
   cancel-in-progress: true
 
 jobs:
-  autopep8:
-    name: "Formatting lints"
+  ruff-format:
+    name: "Formatting checker"
     runs-on: ubuntu-latest
     steps:
       - name: Checkout repo
@@ -25,7 +25,7 @@ jobs:
       - name: Set up Python
         uses: actions/setup-python@v4
         with:
-          python-version: '3.10'
+          python-version: "3.10"
       - name: Setup virtual environment
         run: |
           python -m venv .venv
@@ -34,11 +34,8 @@ jobs:
           source .venv/bin/activate
           python -m pip install --upgrade pip
           pip install -r dev-requirements.txt
-      - name: autopep8
-        id: autopep8
+      - name: Ruff formatter
+        id: ruff
         run: |
           source .venv/bin/activate
-          autopep8 --max-line-length 100 --exit-code -r -d --exclude "*_pb2.py" -a -a src/
-      - name: Fail if autopep8 requires changes
-        if: steps.autopep8.outputs.exit-code == 2
-        run: exit 1
+          ruff format --config line-length=100 --diff --exclude "*_pb2.py"
diff --git a/dev-requirements.txt b/dev-requirements.txt
index 6ce9ffcb4..cce356b14 100644
--- a/dev-requirements.txt
+++ b/dev-requirements.txt
@@ -1,8 +1,8 @@
-autopep8~=2.3.1
 build~=1.2.1
 grpcio-tools~=1.62.2
 pip-tools~=7.4.1
 pyright~=1.1.376
 pytest~=8.3.2
+ruff~=0.6.6
 setuptools~=72.2.0
 setuptools_scm~=8.1.0
diff --git a/examples/deployment/flyio-example/bot.py b/examples/deployment/flyio-example/bot.py
index c6380f6f3..b7378c0ff 100644
--- a/examples/deployment/flyio-example/bot.py
+++ b/examples/deployment/flyio-example/bot.py
@@ -6,7 +6,10 @@ import argparse
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_response import LLMAssistantResponseAggregator, LLMUserResponseAggregator
+from pipecat.processors.aggregators.llm_response import (
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
+)
 from pipecat.frames.frames import LLMMessagesFrame, EndFrame
 from pipecat.services.openai import OpenAILLMService
 from pipecat.services.elevenlabs import ElevenLabsTTSService
@@ -16,6 +19,7 @@ from pipecat.vad.silero import SileroVADAnalyzer
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -39,7 +43,7 @@ async def main(room_url: str, token: str):
             vad_enabled=True,
             vad_analyzer=SileroVADAnalyzer(),
             transcription_enabled=True,
-        )
+        ),
     )
 
     tts = ElevenLabsTTSService(
@@ -47,9 +51,7 @@ async def main(room_url: str, token: str):
         voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""),
     )
 
-    llm = OpenAILLMService(
-        api_key=os.getenv("OPENAI_API_KEY"),
-        model="gpt-4o")
+    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
     messages = [
         {
@@ -61,14 +63,16 @@ async def main(room_url: str, token: str):
     tma_in = LLMUserResponseAggregator(messages)
     tma_out = LLMAssistantResponseAggregator(messages)
 
-    pipeline = Pipeline([
-        transport.input(),
-        tma_in,
-        llm,
-        tts,
-        transport.output(),
-        tma_out,
-    ])
+    pipeline = Pipeline(
+        [
+            transport.input(),
+            tma_in,
+            llm,
+            tts,
+            transport.output(),
+            tma_out,
+        ]
+    )
 
     task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
 
diff --git a/examples/deployment/flyio-example/bot_runner.py b/examples/deployment/flyio-example/bot_runner.py
index 2c2ee43cc..7c76d26f4 100644
--- a/examples/deployment/flyio-example/bot_runner.py
+++ b/examples/deployment/flyio-example/bot_runner.py
@@ -16,9 +16,14 @@ from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import JSONResponse
 
 from pipecat.transports.services.helpers.daily_rest import (
-    DailyRESTHelper, DailyRoomObject, DailyRoomProperties, DailyRoomParams)
+    DailyRESTHelper,
+    DailyRoomObject,
+    DailyRoomProperties,
+    DailyRoomParams,
+)
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 
@@ -26,37 +31,37 @@ load_dotenv(override=True)
 
 MAX_SESSION_TIME = 5 * 60  # 5 minutes
 REQUIRED_ENV_VARS = [
-    'DAILY_API_KEY',
-    'OPENAI_API_KEY',
-    'ELEVENLABS_API_KEY',
-    'ELEVENLABS_VOICE_ID',
-    'FLY_API_KEY',
-    'FLY_APP_NAME',]
+    "DAILY_API_KEY",
+    "OPENAI_API_KEY",
+    "ELEVENLABS_API_KEY",
+    "ELEVENLABS_VOICE_ID",
+    "FLY_API_KEY",
+    "FLY_APP_NAME",
+]
 
 FLY_API_HOST = os.getenv("FLY_API_HOST", "https://api.machines.dev/v1")
 FLY_APP_NAME = os.getenv("FLY_APP_NAME", "pipecat-fly-example")
 FLY_API_KEY = os.getenv("FLY_API_KEY", "")
-FLY_HEADERS = {
-    'Authorization': f"Bearer {FLY_API_KEY}",
-    'Content-Type': 'application/json'
-}
+FLY_HEADERS = {"Authorization": f"Bearer {FLY_API_KEY}", "Content-Type": "application/json"}
 
 daily_helpers = {}
 
 
 # ----------------- API ----------------- #
 
+
 @asynccontextmanager
 async def lifespan(app: FastAPI):
     aiohttp_session = aiohttp.ClientSession()
     daily_helpers["rest"] = DailyRESTHelper(
         daily_api_key=os.getenv("DAILY_API_KEY", ""),
-        daily_api_url=os.getenv("DAILY_API_URL", 'https://api.daily.co/v1'),
-        aiohttp_session=aiohttp_session
+        daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
+        aiohttp_session=aiohttp_session,
     )
     yield
     await aiohttp_session.close()
 
+
 app = FastAPI(lifespan=lifespan)
 
 app.add_middleware(
@@ -64,7 +69,7 @@ app.add_middleware(
     allow_origins=["*"],
     allow_credentials=True,
     allow_methods=["*"],
-    allow_headers=["*"]
+    allow_headers=["*"],
 )
 
 # ----------------- Main ----------------- #
@@ -73,13 +78,15 @@ app.add_middleware(
 async def spawn_fly_machine(room_url: str, token: str):
     async with aiohttp.ClientSession() as session:
         # Use the same image as the bot runner
-        async with session.get(f"{FLY_API_HOST}/apps/{FLY_APP_NAME}/machines", headers=FLY_HEADERS) as r:
+        async with session.get(
+            f"{FLY_API_HOST}/apps/{FLY_APP_NAME}/machines", headers=FLY_HEADERS
+        ) as r:
             if r.status != 200:
                 text = await r.text()
                 raise Exception(f"Unable to get machine info from Fly: {text}")
 
             data = await r.json()
-            image = data[0]['config']['image']
+            image = data[0]["config"]["image"]
 
         # Machine configuration
         cmd = f"python3 bot.py -u {room_url} -t {token}"
@@ -88,31 +95,28 @@ async def spawn_fly_machine(room_url: str, token: str):
             "config": {
                 "image": image,
                 "auto_destroy": True,
-                "init": {
-                    "cmd": cmd
-                },
-                "restart": {
-                    "policy": "no"
-                },
-                "guest": {
-                    "cpu_kind": "shared",
-                    "cpus": 1,
-                    "memory_mb": 1024
-                }
+                "init": {"cmd": cmd},
+                "restart": {"policy": "no"},
+                "guest": {"cpu_kind": "shared", "cpus": 1, "memory_mb": 1024},
             },
         }
 
         # Spawn a new machine instance
-        async with session.post(f"{FLY_API_HOST}/apps/{FLY_APP_NAME}/machines", headers=FLY_HEADERS, json=worker_props) as r:
+        async with session.post(
+            f"{FLY_API_HOST}/apps/{FLY_APP_NAME}/machines", headers=FLY_HEADERS, json=worker_props
+        ) as r:
             if r.status != 200:
                 text = await r.text()
                 raise Exception(f"Problem starting a bot worker: {text}")
 
             data = await r.json()
             # Wait for the machine to enter the started state
-            vm_id = data['id']
+            vm_id = data["id"]
 
-        async with session.get(f"{FLY_API_HOST}/apps/{FLY_APP_NAME}/machines/{vm_id}/wait?state=started", headers=FLY_HEADERS) as r:
+        async with session.get(
+            f"{FLY_API_HOST}/apps/{FLY_APP_NAME}/machines/{vm_id}/wait?state=started",
+            headers=FLY_HEADERS,
+        ) as r:
             if r.status != 200:
                 text = await r.text()
                 raise Exception(f"Bot was unable to enter started state: {text}")
@@ -134,29 +138,23 @@ async def start_bot(request: Request) -> JSONResponse:
     room_url = os.getenv("DAILY_SAMPLE_ROOM_URL", "")
 
     if not room_url:
-        params = DailyRoomParams(
-            properties=DailyRoomProperties()
-        )
+        params = DailyRoomParams(properties=DailyRoomProperties())
         try:
             room: DailyRoomObject = await daily_helpers["rest"].create_room(params=params)
         except Exception as e:
-            raise HTTPException(
-                status_code=500,
-                detail=f"Unable to provision room {e}")
+            raise HTTPException(status_code=500, detail=f"Unable to provision room {e}")
     else:
         # Check passed room URL exists, we should assume that it already has a sip set up
         try:
             room: DailyRoomObject = await daily_helpers["rest"].get_room_from_url(room_url)
         except Exception:
-            raise HTTPException(
-                status_code=500, detail=f"Room not found: {room_url}")
+            raise HTTPException(status_code=500, detail=f"Room not found: {room_url}")
 
     # Give the agent a token to join the session
     token = await daily_helpers["rest"].get_token(room.url, MAX_SESSION_TIME)
 
     if not room or not token:
-        raise HTTPException(
-            status_code=500, detail=f"Failed to get token for room: {room_url}")
+        raise HTTPException(status_code=500, detail=f"Failed to get token for room: {room_url}")
 
     # Launch a new fly.io machine, or run as a shell process (not recommended)
     run_as_process = os.getenv("RUN_AS_PROCESS", False)
@@ -167,24 +165,26 @@ async def start_bot(request: Request) -> JSONResponse:
                 [f"python3 -m bot -u {room.url} -t {token}"],
                 shell=True,
                 bufsize=1,
-                cwd=os.path.dirname(os.path.abspath(__file__)))
+                cwd=os.path.dirname(os.path.abspath(__file__)),
+            )
         except Exception as e:
-            raise HTTPException(
-                status_code=500, detail=f"Failed to start subprocess: {e}")
+            raise HTTPException(status_code=500, detail=f"Failed to start subprocess: {e}")
     else:
         try:
             await spawn_fly_machine(room.url, token)
         except Exception as e:
-            raise HTTPException(
-                status_code=500, detail=f"Failed to spawn VM: {e}")
+            raise HTTPException(status_code=500, detail=f"Failed to spawn VM: {e}")
 
     # Grab a token for the user to join with
     user_token = await daily_helpers["rest"].get_token(room.url, MAX_SESSION_TIME)
 
-    return JSONResponse({
-        "room_url": room.url,
-        "token": user_token,
-    })
+    return JSONResponse(
+        {
+            "room_url": room.url,
+            "token": user_token,
+        }
+    )
+
 
 if __name__ == "__main__":
     # Check environment variables
@@ -193,23 +193,19 @@ if __name__ == "__main__":
             raise Exception(f"Missing environment variable: {env_var}.")
 
     parser = argparse.ArgumentParser(description="Pipecat Bot Runner")
-    parser.add_argument("--host", type=str,
-                        default=os.getenv("HOST", "0.0.0.0"), help="Host address")
-    parser.add_argument("--port", type=int,
-                        default=os.getenv("PORT", 7860), help="Port number")
-    parser.add_argument("--reload", action="store_true",
-                        default=False, help="Reload code on change")
+    parser.add_argument(
+        "--host", type=str, default=os.getenv("HOST", "0.0.0.0"), help="Host address"
+    )
+    parser.add_argument("--port", type=int, default=os.getenv("PORT", 7860), help="Port number")
+    parser.add_argument(
+        "--reload", action="store_true", default=False, help="Reload code on change"
+    )
 
     config = parser.parse_args()
 
     try:
         import uvicorn
 
-        uvicorn.run(
-            "bot_runner:app",
-            host=config.host,
-            port=config.port,
-            reload=config.reload
-        )
+        uvicorn.run("bot_runner:app", host=config.host, port=config.port, reload=config.reload)
     except KeyboardInterrupt:
         print("Pipecat runner shutting down...")
diff --git a/examples/dialin-chatbot/bot_daily.py b/examples/dialin-chatbot/bot_daily.py
index cd6afdad0..2645c65a0 100644
--- a/examples/dialin-chatbot/bot_daily.py
+++ b/examples/dialin-chatbot/bot_daily.py
@@ -6,11 +6,11 @@ import argparse
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_response import LLMAssistantResponseAggregator, LLMUserResponseAggregator
-from pipecat.frames.frames import (
-    LLMMessagesFrame,
-    EndFrame
+from pipecat.processors.aggregators.llm_response import (
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
 )
+from pipecat.frames.frames import LLMMessagesFrame, EndFrame
 from pipecat.services.elevenlabs import ElevenLabsTTSService
 from pipecat.services.openai import OpenAILLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport, DailyDialinSettings
@@ -18,6 +18,7 @@ from pipecat.vad.silero import SileroVADAnalyzer
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -31,10 +32,7 @@ async def main(room_url: str, token: str, callId: str, callDomain: str):
     # diallin_settings are only needed if Daily's SIP URI is used
     # If you are handling this via Twilio, Telnyx, set this to None
     # and handle call-forwarding when on_dialin_ready fires.
-    diallin_settings = DailyDialinSettings(
-        call_id=callId,
-        call_domain=callDomain
-    )
+    diallin_settings = DailyDialinSettings(call_id=callId, call_domain=callDomain)
 
     transport = DailyTransport(
         room_url,
@@ -50,7 +48,7 @@ async def main(room_url: str, token: str, callId: str, callDomain: str):
             vad_enabled=True,
             vad_analyzer=SileroVADAnalyzer(),
             transcription_enabled=True,
-        )
+        ),
     )
 
     tts = ElevenLabsTTSService(
@@ -58,10 +56,7 @@ async def main(room_url: str, token: str, callId: str, callDomain: str):
         voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""),
     )
 
-    llm = OpenAILLMService(
-        api_key=os.getenv("OPENAI_API_KEY"),
-        model="gpt-4o"
-    )
+    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
     messages = [
         {
@@ -73,14 +68,16 @@ async def main(room_url: str, token: str, callId: str, callDomain: str):
     tma_in = LLMUserResponseAggregator(messages)
     tma_out = LLMAssistantResponseAggregator(messages)
 
-    pipeline = Pipeline([
-        transport.input(),
-        tma_in,
-        llm,
-        tts,
-        transport.output(),
-        tma_out,
-    ])
+    pipeline = Pipeline(
+        [
+            transport.input(),
+            tma_in,
+            llm,
+            tts,
+            transport.output(),
+            tma_out,
+        ]
+    )
 
     task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
 
diff --git a/examples/dialin-chatbot/bot_runner.py b/examples/dialin-chatbot/bot_runner.py
index 3b6e12eec..d29adc34e 100644
--- a/examples/dialin-chatbot/bot_runner.py
+++ b/examples/dialin-chatbot/bot_runner.py
@@ -7,7 +7,6 @@ provisioning a room and starting a Pipecat bot in response.
 Refer to README for more information.
 """
 
-
 import aiohttp
 import os
 import argparse
@@ -25,17 +24,18 @@ from pipecat.transports.services.helpers.daily_rest import (
     DailyRoomObject,
     DailyRoomProperties,
     DailyRoomSipParams,
-    DailyRoomParams)
+    DailyRoomParams,
+)
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 
 # ------------ Configuration ------------ #
 
 MAX_SESSION_TIME = 5 * 60  # 5 minutes
-REQUIRED_ENV_VARS = ['OPENAI_API_KEY', 'DAILY_API_KEY',
-                     'ELEVENLABS_API_KEY', 'ELEVENLABS_VOICE_ID']
+REQUIRED_ENV_VARS = ["OPENAI_API_KEY", "DAILY_API_KEY", "ELEVENLABS_API_KEY", "ELEVENLABS_VOICE_ID"]
 
 daily_helpers = {}
 
@@ -47,12 +47,13 @@ async def lifespan(app: FastAPI):
     aiohttp_session = aiohttp.ClientSession()
     daily_helpers["rest"] = DailyRESTHelper(
         daily_api_key=os.getenv("DAILY_API_KEY", ""),
-        daily_api_url=os.getenv("DAILY_API_URL", 'https://api.daily.co/v1'),
-        aiohttp_session=aiohttp_session
+        daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
+        aiohttp_session=aiohttp_session,
     )
     yield
     await aiohttp_session.close()
 
+
 app = FastAPI(lifespan=lifespan)
 
 app.add_middleware(
@@ -60,7 +61,7 @@ app.add_middleware(
     allow_origins=["*"],
     allow_credentials=True,
     allow_methods=["*"],
-    allow_headers=["*"]
+    allow_headers=["*"],
 )
 
 """
@@ -80,10 +81,7 @@ async def _create_daily_room(room_url, callId, callDomain=None, vendor="daily"):
             properties=DailyRoomProperties(
                 # Note: these are the default values, except for the display name
                 sip=DailyRoomSipParams(
-                    display_name="dialin-user",
-                    video=False,
-                    sip_mode="dial-in",
-                    num_endpoints=1
+                    display_name="dialin-user", video=False, sip_mode="dial-in", num_endpoints=1
                 )
             )
         )
@@ -97,8 +95,7 @@ async def _create_daily_room(room_url, callId, callDomain=None, vendor="daily"):
             print(f"Joining existing room: {room_url}")
             room: DailyRoomObject = await daily_helpers["rest"].get_room_from_url(room_url)
         except Exception:
-            raise HTTPException(
-                status_code=500, detail=f"Room not found: {room_url}")
+            raise HTTPException(status_code=500, detail=f"Room not found: {room_url}")
 
     print(f"Daily room: {room.url} {room.config.sip_endpoint}")
 
@@ -106,8 +103,7 @@ async def _create_daily_room(room_url, callId, callDomain=None, vendor="daily"):
     token = await daily_helpers["rest"].get_token(room.url, MAX_SESSION_TIME)
 
     if not room or not token:
-        raise HTTPException(
-            status_code=500, detail=f"Failed to get room or token token")
+        raise HTTPException(status_code=500, detail=f"Failed to get room or token token")
 
     # Spawn a new agent, and join the user session
     # Note: this is mostly for demonstration purposes (refer to 'deployment' in docs)
@@ -120,14 +116,10 @@ async def _create_daily_room(room_url, callId, callDomain=None, vendor="daily"):
 
     try:
         subprocess.Popen(
-            [bot_proc],
-            shell=True,
-            bufsize=1,
-            cwd=os.path.dirname(os.path.abspath(__file__))
+            [bot_proc], shell=True, bufsize=1, cwd=os.path.dirname(os.path.abspath(__file__))
         )
     except Exception as e:
-        raise HTTPException(
-            status_code=500, detail=f"Failed to start subprocess: {e}")
+        raise HTTPException(status_code=500, detail=f"Failed to start subprocess: {e}")
 
     return room
 
@@ -150,11 +142,10 @@ async def twilio_start_bot(request: Request):
         pass
 
     room_url = os.getenv("DAILY_SAMPLE_ROOM_URL", None)
-    callId = data.get('CallSid')
+    callId = data.get("CallSid")
 
     if not callId:
-        raise HTTPException(
-            status_code=500, detail="Missing 'CallSid' in request")
+        raise HTTPException(status_code=500, detail="Missing 'CallSid' in request")
 
     print("CallId: %s" % callId)
 
@@ -170,7 +161,8 @@ async def twilio_start_bot(request: Request):
     # http://com.twilio.music.classical.s3.amazonaws.com/BusyStrings.mp3
     resp = VoiceResponse()
     resp.play(
-        url="http://com.twilio.sounds.music.s3.amazonaws.com/MARKOVICHAMP-Borghestral.mp3", loop=10)
+        url="http://com.twilio.sounds.music.s3.amazonaws.com/MARKOVICHAMP-Borghestral.mp3", loop=10
+    )
     return str(resp)
 
 
@@ -192,18 +184,14 @@ async def daily_start_bot(request: Request) -> JSONResponse:
         callId = data.get("callId", None)
         callDomain = data.get("callDomain", None)
     except Exception:
-        raise HTTPException(
-            status_code=500,
-            detail="Missing properties 'callId' or 'callDomain'")
+        raise HTTPException(status_code=500, detail="Missing properties 'callId' or 'callDomain'")
 
     print(f"CallId: {callId}, CallDomain: {callDomain}")
     room: DailyRoomObject = await _create_daily_room(room_url, callId, callDomain, "daily")
 
     # Grab a token for the user to join with
-    return JSONResponse({
-        "room_url": room.url,
-        "sipUri": room.config.sip_endpoint
-    })
+    return JSONResponse({"room_url": room.url, "sipUri": room.config.sip_endpoint})
+
 
 # ----------------- Main ----------------- #
 
@@ -215,24 +203,18 @@ if __name__ == "__main__":
             raise Exception(f"Missing environment variable: {env_var}.")
 
     parser = argparse.ArgumentParser(description="Pipecat Bot Runner")
-    parser.add_argument("--host", type=str,
-                        default=os.getenv("HOST", "0.0.0.0"), help="Host address")
-    parser.add_argument("--port", type=int,
-                        default=os.getenv("PORT", 7860), help="Port number")
-    parser.add_argument("--reload", action="store_true",
-                        default=True, help="Reload code on change")
+    parser.add_argument(
+        "--host", type=str, default=os.getenv("HOST", "0.0.0.0"), help="Host address"
+    )
+    parser.add_argument("--port", type=int, default=os.getenv("PORT", 7860), help="Port number")
+    parser.add_argument("--reload", action="store_true", default=True, help="Reload code on change")
 
     config = parser.parse_args()
 
     try:
         import uvicorn
 
-        uvicorn.run(
-            "bot_runner:app",
-            host=config.host,
-            port=config.port,
-            reload=config.reload
-        )
+        uvicorn.run("bot_runner:app", host=config.host, port=config.port, reload=config.reload)
 
     except KeyboardInterrupt:
         print("Pipecat runner shutting down...")
diff --git a/examples/dialin-chatbot/bot_twilio.py b/examples/dialin-chatbot/bot_twilio.py
index e6653babd..c2fe144a6 100644
--- a/examples/dialin-chatbot/bot_twilio.py
+++ b/examples/dialin-chatbot/bot_twilio.py
@@ -6,11 +6,11 @@ import argparse
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_response import LLMAssistantResponseAggregator, LLMUserResponseAggregator
-from pipecat.frames.frames import (
-    LLMMessagesFrame,
-    EndFrame
+from pipecat.processors.aggregators.llm_response import (
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
 )
+from pipecat.frames.frames import LLMMessagesFrame, EndFrame
 from pipecat.services.elevenlabs import ElevenLabsTTSService
 from pipecat.services.openai import OpenAILLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
@@ -21,14 +21,15 @@ from twilio.rest import Client
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
 logger.add(sys.stderr, level="DEBUG")
 
 
-twilio_account_sid = os.getenv('TWILIO_ACCOUNT_SID')
-twilio_auth_token = os.getenv('TWILIO_AUTH_TOKEN')
+twilio_account_sid = os.getenv("TWILIO_ACCOUNT_SID")
+twilio_auth_token = os.getenv("TWILIO_AUTH_TOKEN")
 twilioclient = Client(twilio_account_sid, twilio_auth_token)
 
 daily_api_key = os.getenv("DAILY_API_KEY", "")
@@ -51,7 +52,7 @@ async def main(room_url: str, token: str, callId: str, sipUri: str):
             vad_enabled=True,
             vad_analyzer=SileroVADAnalyzer(),
             transcription_enabled=True,
-        )
+        ),
     )
 
     tts = ElevenLabsTTSService(
@@ -59,10 +60,7 @@ async def main(room_url: str, token: str, callId: str, sipUri: str):
         voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""),
     )
 
-    llm = OpenAILLMService(
-        api_key=os.getenv("OPENAI_API_KEY"),
-        model="gpt-4o"
-    )
+    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
     messages = [
         {
@@ -74,14 +72,16 @@ async def main(room_url: str, token: str, callId: str, sipUri: str):
     tma_in = LLMUserResponseAggregator(messages)
     tma_out = LLMAssistantResponseAggregator(messages)
 
-    pipeline = Pipeline([
-        transport.input(),
-        tma_in,
-        llm,
-        tts,
-        transport.output(),
-        tma_out,
-    ])
+    pipeline = Pipeline(
+        [
+            transport.input(),
+            tma_in,
+            llm,
+            tts,
+            transport.output(),
+            tma_out,
+        ]
+    )
 
     task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
 
@@ -103,7 +103,7 @@ async def main(room_url: str, token: str, callId: str, sipUri: str):
         try:
             # The TwiML is updated using Twilio's client library
             call = twilioclient.calls(callId).update(
-                twiml=f'<Response><Dial><Sip>{sipUri}</Sip></Dial></Response>'
+                twiml=f"<Response><Dial><Sip>{sipUri}</Sip></Dial></Response>"
             )
         except Exception as e:
             raise Exception(f"Failed to forward call: {str(e)}")
diff --git a/examples/foundational/01-say-one-thing.py b/examples/foundational/01-say-one-thing.py
index fce774822..288fcefc3 100644
--- a/examples/foundational/01-say-one-thing.py
+++ b/examples/foundational/01-say-one-thing.py
@@ -21,6 +21,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -32,7 +33,8 @@ async def main():
         (room_url, _) = await configure(session)
 
         transport = DailyTransport(
-            room_url, None, "Say One Thing", DailyParams(audio_out_enabled=True))
+            room_url, None, "Say One Thing", DailyParams(audio_out_enabled=True)
+        )
 
         tts = CartesiaHttpTTSService(
             api_key=os.getenv("CARTESIA_API_KEY"),
@@ -47,10 +49,11 @@ async def main():
         # participant joins.
         @transport.event_handler("on_participant_joined")
         async def on_new_participant_joined(transport, participant):
-            participant_name = participant["info"]["userName"] or ''
+            participant_name = participant["info"]["userName"] or ""
             await task.queue_frames([TextFrame(f"Hello there, {participant_name}!"), EndFrame()])
 
         await runner.run(task)
 
+
 if __name__ == "__main__":
     asyncio.run(main())
diff --git a/examples/foundational/01a-local-audio.py b/examples/foundational/01a-local-audio.py
index df63bca99..d39e922d7 100644
--- a/examples/foundational/01a-local-audio.py
+++ b/examples/foundational/01a-local-audio.py
@@ -20,6 +20,7 @@ from pipecat.transports.local.audio import LocalAudioTransport
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
diff --git a/examples/foundational/02-llm-say-one-thing.py b/examples/foundational/02-llm-say-one-thing.py
index 00a1e9e51..8cce7a017 100644
--- a/examples/foundational/02-llm-say-one-thing.py
+++ b/examples/foundational/02-llm-say-one-thing.py
@@ -22,6 +22,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -33,25 +34,22 @@ async def main():
         (room_url, _) = await configure(session)
 
         transport = DailyTransport(
-            room_url,
-            None,
-            "Say One Thing From an LLM",
-            DailyParams(audio_out_enabled=True))
+            room_url, None, "Say One Thing From an LLM", DailyParams(audio_out_enabled=True)
+        )
 
         tts = CartesiaHttpTTSService(
             api_key=os.getenv("CARTESIA_API_KEY"),
             voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
         )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
         messages = [
             {
                 "role": "system",
                 "content": "You are an LLM in a WebRTC session, and this is a 'hello world' demo. Say hello to the world.",
-            }]
+            }
+        ]
 
         runner = PipelineRunner()
 
diff --git a/examples/foundational/03-still-frame.py b/examples/foundational/03-still-frame.py
index 1ad36dfcc..46e333ba4 100644
--- a/examples/foundational/03-still-frame.py
+++ b/examples/foundational/03-still-frame.py
@@ -21,6 +21,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -35,17 +36,11 @@ async def main():
             room_url,
             None,
             "Show a still frame image",
-            DailyParams(
-                camera_out_enabled=True,
-                camera_out_width=1024,
-                camera_out_height=1024
-            )
+            DailyParams(camera_out_enabled=True, camera_out_width=1024, camera_out_height=1024),
         )
 
         imagegen = FalImageGenService(
-            params=FalImageGenService.InputParams(
-                image_size="square_hd"
-            ),
+            params=FalImageGenService.InputParams(image_size="square_hd"),
             aiohttp_session=session,
             key=os.getenv("FAL_KEY"),
         )
diff --git a/examples/foundational/03a-local-still-frame.py b/examples/foundational/03a-local-still-frame.py
index 14e092508..c06834d90 100644
--- a/examples/foundational/03a-local-still-frame.py
+++ b/examples/foundational/03a-local-still-frame.py
@@ -22,6 +22,7 @@ from pipecat.transports.local.tk import TkLocalTransport
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -35,15 +36,11 @@ async def main():
 
         transport = TkLocalTransport(
             tk_root,
-            TransportParams(
-                camera_out_enabled=True,
-                camera_out_width=1024,
-                camera_out_height=1024))
+            TransportParams(camera_out_enabled=True, camera_out_width=1024, camera_out_height=1024),
+        )
 
         imagegen = FalImageGenService(
-            params=FalImageGenService.InputParams(
-                image_size="square_hd"
-            ),
+            params=FalImageGenService.InputParams(image_size="square_hd"),
             aiohttp_session=session,
             key=os.getenv("FAL_KEY"),
         )
diff --git a/examples/foundational/04-utterance-and-speech.py b/examples/foundational/04-utterance-and-speech.py
index 10a1dcf1c..7f63757d6 100644
--- a/examples/foundational/04-utterance-and-speech.py
+++ b/examples/foundational/04-utterance-and-speech.py
@@ -28,6 +28,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -58,8 +59,7 @@ async def main():
             voice_id=os.getenv("ELEVENLABS_VOICE_ID"),
         )
 
-        messages = [{"role": "system",
-                     "content": "tell the user a joke about llamas"}]
+        messages = [{"role": "system", "content": "tell the user a joke about llamas"}]
 
         # Start a task to run the LLM to create a joke, and convert the LLM
         # output to audio frames. This task will run in parallel with generating
@@ -77,8 +77,7 @@ async def main():
             ]
         )
 
-        merge_pipeline = SequentialMergePipeline(
-            [simple_tts_pipeline, llm_pipeline])
+        merge_pipeline = SequentialMergePipeline([simple_tts_pipeline, llm_pipeline])
 
         await asyncio.gather(
             transport.run(merge_pipeline),
diff --git a/examples/foundational/05-sync-speech-and-image.py b/examples/foundational/05-sync-speech-and-image.py
index 07e54ab8a..dae860a92 100644
--- a/examples/foundational/05-sync-speech-and-image.py
+++ b/examples/foundational/05-sync-speech-and-image.py
@@ -16,7 +16,7 @@ from pipecat.frames.frames import (
     Frame,
     LLMFullResponseStartFrame,
     LLMMessagesFrame,
-    TextFrame
+    TextFrame,
 )
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
@@ -34,6 +34,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -81,8 +82,8 @@ async def main():
                 audio_out_enabled=True,
                 camera_out_enabled=True,
                 camera_out_width=1024,
-                camera_out_height=1024
-            )
+                camera_out_height=1024,
+            ),
         )
 
         tts = CartesiaHttpTTSService(
@@ -90,14 +91,10 @@ async def main():
             voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
         )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
         imagegen = FalImageGenService(
-            params=FalImageGenService.InputParams(
-                image_size="square_hd"
-            ),
+            params=FalImageGenService.InputParams(image_size="square_hd"),
             aiohttp_session=session,
             key=os.getenv("FAL_KEY"),
         )
@@ -112,15 +109,17 @@ async def main():
         #
         # Note that `SyncParallelPipeline` requires all processors in it to be
         # synchronous (which is the default for most processors).
-        pipeline = Pipeline([
-            llm,                     # LLM
-            sentence_aggregator,     # Aggregates LLM output into full sentences
-            SyncParallelPipeline(    # Run pipelines in parallel aggregating the result
-                [month_prepender, tts],  # Create "Month: sentence" and output audio
-                [imagegen]               # Generate image
-            ),
-            transport.output()       # Transport output
-        ])
+        pipeline = Pipeline(
+            [
+                llm,  # LLM
+                sentence_aggregator,  # Aggregates LLM output into full sentences
+                SyncParallelPipeline(  # Run pipelines in parallel aggregating the result
+                    [month_prepender, tts],  # Create "Month: sentence" and output audio
+                    [imagegen],  # Generate image
+                ),
+                transport.output(),  # Transport output
+            ]
+        )
 
         frames = []
         for month in [
diff --git a/examples/foundational/05a-local-sync-speech-and-image.py b/examples/foundational/05a-local-sync-speech-and-image.py
index d9a0e792e..27c36f6ce 100644
--- a/examples/foundational/05a-local-sync-speech-and-image.py
+++ b/examples/foundational/05a-local-sync-speech-and-image.py
@@ -17,7 +17,8 @@ from pipecat.frames.frames import (
     TTSAudioRawFrame,
     URLImageRawFrame,
     LLMMessagesFrame,
-    TextFrame)
+    TextFrame,
+)
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.sync_parallel_pipeline import SyncParallelPipeline
@@ -48,7 +49,12 @@ async def main():
         runner = PipelineRunner()
 
         async def get_month_data(month):
-            messages = [{"role": "system", "content": f"Describe a nature photograph suitable for use in a calendar, for the month of {month}. Include only the image description with no preamble. Limit the description to one sentence, please.", }]
+            messages = [
+                {
+                    "role": "system",
+                    "content": f"Describe a nature photograph suitable for use in a calendar, for the month of {month}. Include only the image description with no preamble. Limit the description to one sentence, please.",
+                }
+            ]
 
             class ImageDescription(FrameProcessor):
                 def __init__(self):
@@ -74,7 +80,8 @@ async def main():
                     if isinstance(frame, TTSAudioRawFrame):
                         self.audio.extend(frame.audio)
                         self.frame = OutputAudioRawFrame(
-                            bytes(self.audio), frame.sample_rate, frame.num_channels)
+                            bytes(self.audio), frame.sample_rate, frame.num_channels
+                        )
 
             class ImageGrabber(FrameProcessor):
                 def __init__(self):
@@ -87,9 +94,7 @@ async def main():
                     if isinstance(frame, URLImageRawFrame):
                         self.frame = frame
 
-            llm = OpenAILLMService(
-                api_key=os.getenv("OPENAI_API_KEY"),
-                model="gpt-4o")
+            llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
             tts = CartesiaHttpTTSService(
                 api_key=os.getenv("CARTESIA_API_KEY"),
@@ -97,11 +102,10 @@ async def main():
             )
 
             imagegen = FalImageGenService(
-                params=FalImageGenService.InputParams(
-                    image_size="square_hd"
-                ),
+                params=FalImageGenService.InputParams(image_size="square_hd"),
                 aiohttp_session=session,
-                key=os.getenv("FAL_KEY"))
+                key=os.getenv("FAL_KEY"),
+            )
 
             sentence_aggregator = SentenceAggregator()
 
@@ -119,15 +123,17 @@ async def main():
             #
             # Note that `SyncParallelPipeline` requires all processors in it to
             # be synchronous (which is the default for most processors).
-            pipeline = Pipeline([
-                llm,                     # LLM
-                sentence_aggregator,     # Aggregates LLM output into full sentences
-                description,             # Store sentence
-                SyncParallelPipeline(
-                    [tts, audio_grabber],      # Generate and store audio for the given sentence
-                    [imagegen, image_grabber]  # Generate and storeimage for the given sentence
-                )
-            ])
+            pipeline = Pipeline(
+                [
+                    llm,  # LLM
+                    sentence_aggregator,  # Aggregates LLM output into full sentences
+                    description,  # Store sentence
+                    SyncParallelPipeline(
+                        [tts, audio_grabber],  # Generate and store audio for the given sentence
+                        [imagegen, image_grabber],  # Generate and storeimage for the given sentence
+                    ),
+                ]
+            )
 
             task = PipelineTask(pipeline)
             await task.queue_frame(LLMMessagesFrame(messages))
@@ -148,7 +154,9 @@ async def main():
                 audio_out_enabled=True,
                 camera_out_enabled=True,
                 camera_out_width=1024,
-                camera_out_height=1024))
+                camera_out_height=1024,
+            ),
+        )
 
         pipeline = Pipeline([transport.output()])
 
diff --git a/examples/foundational/06-listen-and-respond.py b/examples/foundational/06-listen-and-respond.py
index 6a10f927c..ce9e235f5 100644
--- a/examples/foundational/06-listen-and-respond.py
+++ b/examples/foundational/06-listen-and-respond.py
@@ -10,7 +10,12 @@ import os
 import sys
 
 from pipecat.frames.frames import Frame, LLMMessagesFrame, MetricsFrame
-from pipecat.metrics.metrics import TTFBMetricsData, ProcessingMetricsData, LLMUsageMetricsData, TTSUsageMetricsData
+from pipecat.metrics.metrics import (
+    TTFBMetricsData,
+    ProcessingMetricsData,
+    LLMUsageMetricsData,
+    TTSUsageMetricsData,
+)
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -29,6 +34,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -48,7 +54,8 @@ class MetricsLogger(FrameProcessor):
                     print(
                         f"!!! MetricsFrame: {frame}, tokens: {
                             tokens.prompt_tokens}, characters: {
-                            tokens.completion_tokens}")
+                            tokens.completion_tokens}"
+                    )
                 elif isinstance(d, TTSUsageMetricsData):
                     print(f"!!! MetricsFrame: {frame}, characters: {d.value}")
         await self.push_frame(frame, direction)
@@ -66,8 +73,8 @@ async def main():
                 audio_out_enabled=True,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
         tts = CartesiaTTSService(
@@ -75,10 +82,7 @@ async def main():
             voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
         )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o"
-        )
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
         ml = MetricsLogger()
 
@@ -91,15 +95,17 @@ async def main():
         tma_in = LLMUserResponseAggregator(messages)
         tma_out = LLMAssistantResponseAggregator(messages)
 
-        pipeline = Pipeline([
-            transport.input(),
-            tma_in,
-            llm,
-            tts,
-            ml,
-            transport.output(),
-            tma_out,
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),
+                tma_in,
+                llm,
+                tts,
+                ml,
+                transport.output(),
+                tma_out,
+            ]
+        )
 
         task = PipelineTask(pipeline)
 
@@ -107,8 +113,7 @@ async def main():
         async def on_first_participant_joined(transport, participant):
             transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
-            messages.append(
-                {"role": "system", "content": "Please introduce yourself to the user."})
+            messages.append({"role": "system", "content": "Please introduce yourself to the user."})
             await task.queue_frames([LLMMessagesFrame(messages)])
 
         runner = PipelineRunner()
diff --git a/examples/foundational/06a-image-sync.py b/examples/foundational/06a-image-sync.py
index db48b709e..30bd8dc64 100644
--- a/examples/foundational/06a-image-sync.py
+++ b/examples/foundational/06a-image-sync.py
@@ -31,6 +31,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -52,16 +53,21 @@ class ImageSyncAggregator(FrameProcessor):
         await super().process_frame(frame, direction)
 
         if not isinstance(frame, SystemFrame) and direction == FrameDirection.DOWNSTREAM:
-            await self.push_frame(OutputImageRawFrame(
-                image=self._speaking_image_bytes,
-                size=(1024, 1024),
-                format=self._speaking_image_format)
+            await self.push_frame(
+                OutputImageRawFrame(
+                    image=self._speaking_image_bytes,
+                    size=(1024, 1024),
+                    format=self._speaking_image_format,
+                )
             )
             await self.push_frame(frame)
-            await self.push_frame(OutputImageRawFrame(
-                image=self._waiting_image_bytes,
-                size=(1024, 1024),
-                format=self._waiting_image_format))
+            await self.push_frame(
+                OutputImageRawFrame(
+                    image=self._waiting_image_bytes,
+                    size=(1024, 1024),
+                    format=self._waiting_image_format,
+                )
+            )
         else:
             await self.push_frame(frame)
 
@@ -82,7 +88,7 @@ async def main():
                 transcription_enabled=True,
                 vad_enabled=True,
                 vad_analyzer=SileroVADAnalyzer(),
-            )
+            ),
         )
 
         tts = CartesiaHttpTTSService(
@@ -90,9 +96,7 @@ async def main():
             voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
         )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
         messages = [
             {
@@ -109,21 +113,23 @@ async def main():
             os.path.join(os.path.dirname(__file__), "assets", "waiting.png"),
         )
 
-        pipeline = Pipeline([
-            transport.input(),
-            image_sync_aggregator,
-            tma_in,
-            llm,
-            tts,
-            transport.output(),
-            tma_out
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),
+                image_sync_aggregator,
+                tma_in,
+                llm,
+                tts,
+                transport.output(),
+                tma_out,
+            ]
+        )
 
         task = PipelineTask(pipeline)
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
-            participant_name = participant["info"]["userName"] or ''
+            participant_name = participant["info"]["userName"] or ""
             transport.capture_participant_transcription(participant["id"])
             await task.queue_frames([TextFrame(f"Hi there {participant_name}!")])
 
diff --git a/examples/foundational/07-interruptible.py b/examples/foundational/07-interruptible.py
index 90c10c76d..8026940f8 100644
--- a/examples/foundational/07-interruptible.py
+++ b/examples/foundational/07-interruptible.py
@@ -14,7 +14,9 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator, LLMUserResponseAggregator)
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
+)
 from pipecat.services.cartesia import CartesiaTTSService
 from pipecat.services.openai import OpenAILLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
@@ -25,6 +27,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -43,8 +46,8 @@ async def main():
                 audio_out_enabled=True,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
         tts = CartesiaTTSService(
@@ -52,9 +55,7 @@ async def main():
             voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
         )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
         messages = [
             {
@@ -66,28 +67,32 @@ async def main():
         tma_in = LLMUserResponseAggregator(messages)
         tma_out = LLMAssistantResponseAggregator(messages)
 
-        pipeline = Pipeline([
-            transport.input(),   # Transport user input
-            tma_in,              # User responses
-            llm,                 # LLM
-            tts,                 # TTS
-            transport.output(),  # Transport bot output
-            tma_out              # Assistant spoken responses
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                tma_in,  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                tma_out,  # Assistant spoken responses
+            ]
+        )
 
-        task = PipelineTask(pipeline, PipelineParams(
-            allow_interruptions=True,
-            enable_metrics=True,
-            enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
-        ))
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
             transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
-            messages.append(
-                {"role": "system", "content": "Please introduce yourself to the user."})
+            messages.append({"role": "system", "content": "Please introduce yourself to the user."})
             await task.queue_frames([LLMMessagesFrame(messages)])
 
         runner = PipelineRunner()
diff --git a/examples/foundational/07a-interruptible-anthropic.py b/examples/foundational/07a-interruptible-anthropic.py
index a8d90f087..2bded2480 100644
--- a/examples/foundational/07a-interruptible-anthropic.py
+++ b/examples/foundational/07a-interruptible-anthropic.py
@@ -14,7 +14,9 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator, LLMUserResponseAggregator)
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
+)
 from pipecat.services.cartesia import CartesiaTTSService
 from pipecat.services.anthropic import AnthropicLLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
@@ -25,6 +27,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -43,8 +46,8 @@ async def main():
                 audio_out_enabled=True,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
         tts = CartesiaTTSService(
@@ -53,8 +56,8 @@ async def main():
         )
 
         llm = AnthropicLLMService(
-            api_key=os.getenv("ANTHROPIC_API_KEY"),
-            model="claude-3-opus-20240229")
+            api_key=os.getenv("ANTHROPIC_API_KEY"), model="claude-3-opus-20240229"
+        )
 
         # todo: think more about how to handle system prompts in a more general way. OpenAI,
         # Google, and Anthropic all have slightly different approaches to providing a system
@@ -69,14 +72,16 @@ async def main():
         tma_in = LLMUserResponseAggregator(messages)
         tma_out = LLMAssistantResponseAggregator(messages)
 
-        pipeline = Pipeline([
-            transport.input(),   # Transport user input
-            tma_in,              # User responses
-            llm,                 # LLM
-            tts,                 # TTS
-            transport.output(),  # Transport bot output
-            tma_out              # Assistant spoken responses
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                tma_in,  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                tma_out,  # Assistant spoken responses
+            ]
+        )
 
         task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
 
diff --git a/examples/foundational/07b-interruptible-langchain.py b/examples/foundational/07b-interruptible-langchain.py
index 872dbf9bb..5ebfd3388 100644
--- a/examples/foundational/07b-interruptible-langchain.py
+++ b/examples/foundational/07b-interruptible-langchain.py
@@ -15,7 +15,9 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator, LLMUserResponseAggregator)
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
+)
 from pipecat.processors.frameworks.langchain import LangchainProcessor
 from pipecat.services.cartesia import CartesiaTTSService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
@@ -32,6 +34,7 @@ from loguru import logger
 from runner import configure
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 
@@ -70,19 +73,22 @@ async def main():
 
         prompt = ChatPromptTemplate.from_messages(
             [
-                ("system",
-                 "Be nice and helpful. Answer very briefly and without special characters like `#` or `*`. "
-                 "Your response will be synthesized to voice and those characters will create unnatural sounds.",
-                 ),
+                (
+                    "system",
+                    "Be nice and helpful. Answer very briefly and without special characters like `#` or `*`. "
+                    "Your response will be synthesized to voice and those characters will create unnatural sounds.",
+                ),
                 MessagesPlaceholder("chat_history"),
                 ("human", "{input}"),
-            ])
+            ]
+        )
         chain = prompt | ChatOpenAI(model="gpt-4o", temperature=0.7)
         history_chain = RunnableWithMessageHistory(
             chain,
             get_session_history,
             history_messages_key="chat_history",
-            input_messages_key="input")
+            input_messages_key="input",
+        )
         lc = LangchainProcessor(history_chain)
 
         tma_in = LLMUserResponseAggregator()
@@ -90,12 +96,12 @@ async def main():
 
         pipeline = Pipeline(
             [
-                transport.input(),      # Transport user input
-                tma_in,                 # User responses
-                lc,                     # Langchain
-                tts,                    # TTS
-                transport.output(),     # Transport bot output
-                tma_out,                # Assistant spoken responses
+                transport.input(),  # Transport user input
+                tma_in,  # User responses
+                lc,  # Langchain
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                tma_out,  # Assistant spoken responses
             ]
         )
 
@@ -109,11 +115,7 @@ async def main():
             # the `LLMMessagesFrame` will be picked up by the LangchainProcessor using
             # only the content of the last message to inject it in the prompt defined
             # above. So no role is required here.
-            messages = [(
-                {
-                    "content": "Please briefly introduce yourself to the user."
-                }
-            )]
+            messages = [({"content": "Please briefly introduce yourself to the user."})]
             await task.queue_frames([LLMMessagesFrame(messages)])
 
         runner = PipelineRunner()
diff --git a/examples/foundational/07c-interruptible-deepgram.py b/examples/foundational/07c-interruptible-deepgram.py
index dad6834ec..41bef8a47 100644
--- a/examples/foundational/07c-interruptible-deepgram.py
+++ b/examples/foundational/07c-interruptible-deepgram.py
@@ -14,7 +14,9 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator, LLMUserResponseAggregator)
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
+)
 from pipecat.services.deepgram import DeepgramSTTService, DeepgramTTSService
 from pipecat.services.openai import OpenAILLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
@@ -25,6 +27,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -43,21 +46,17 @@ async def main():
                 audio_out_enabled=True,
                 vad_enabled=True,
                 vad_analyzer=SileroVADAnalyzer(),
-                vad_audio_passthrough=True
-            )
+                vad_audio_passthrough=True,
+            ),
         )
 
         stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
 
         tts = DeepgramTTSService(
-            aiohttp_session=session,
-            api_key=os.getenv("DEEPGRAM_API_KEY"),
-            voice="aura-helios-en"
+            aiohttp_session=session, api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-helios-en"
         )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
         messages = [
             {
@@ -69,15 +68,17 @@ async def main():
         tma_in = LLMUserResponseAggregator(messages)
         tma_out = LLMAssistantResponseAggregator(messages)
 
-        pipeline = Pipeline([
-            transport.input(),   # Transport user input
-            stt,                 # STT
-            tma_in,              # User responses
-            llm,                 # LLM
-            tts,                 # TTS
-            transport.output(),  # Transport bot output
-            tma_out              # Assistant spoken responses
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                stt,  # STT
+                tma_in,  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                tma_out,  # Assistant spoken responses
+            ]
+        )
 
         task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
 
@@ -85,8 +86,7 @@ async def main():
         async def on_first_participant_joined(transport, participant):
             transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
-            messages.append(
-                {"role": "system", "content": "Please introduce yourself to the user."})
+            messages.append({"role": "system", "content": "Please introduce yourself to the user."})
             await task.queue_frames([LLMMessagesFrame(messages)])
 
         runner = PipelineRunner()
diff --git a/examples/foundational/07e-interruptible-playht.py b/examples/foundational/07e-interruptible-playht.py
index 1ad61dc5e..9c48df93a 100644
--- a/examples/foundational/07e-interruptible-playht.py
+++ b/examples/foundational/07e-interruptible-playht.py
@@ -14,7 +14,9 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator, LLMUserResponseAggregator)
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
+)
 from pipecat.services.playht import PlayHTTTSService
 from pipecat.services.openai import OpenAILLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
@@ -25,6 +27,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -44,8 +47,8 @@ async def main():
                 audio_out_sample_rate=16000,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
         tts = PlayHTTTSService(
@@ -54,9 +57,7 @@ async def main():
             voice_url="s3://voice-cloning-zero-shot/801a663f-efd0-4254-98d0-5c175514c3e8/jennifer/manifest.json",
         )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
         messages = [
             {
@@ -68,14 +69,16 @@ async def main():
         tma_in = LLMUserResponseAggregator(messages)
         tma_out = LLMAssistantResponseAggregator(messages)
 
-        pipeline = Pipeline([
-            transport.input(),   # Transport user input
-            tma_in,              # User responses
-            llm,                 # LLM
-            tts,                 # TTS
-            transport.output(),  # Transport bot output
-            tma_out              # Assistant spoken responses
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                tma_in,  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                tma_out,  # Assistant spoken responses
+            ]
+        )
 
         task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
 
@@ -83,8 +86,7 @@ async def main():
         async def on_first_participant_joined(transport, participant):
             transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
-            messages.append(
-                {"role": "system", "content": "Please introduce yourself to the user."})
+            messages.append({"role": "system", "content": "Please introduce yourself to the user."})
             await task.queue_frames([LLMMessagesFrame(messages)])
 
         runner = PipelineRunner()
diff --git a/examples/foundational/07f-interruptible-azure.py b/examples/foundational/07f-interruptible-azure.py
index 50f67f94c..11bfebe53 100644
--- a/examples/foundational/07f-interruptible-azure.py
+++ b/examples/foundational/07f-interruptible-azure.py
@@ -14,7 +14,9 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator, LLMUserResponseAggregator)
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
+)
 from pipecat.services.azure import AzureLLMService, AzureSTTService, AzureTTSService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 from pipecat.vad.silero import SileroVADAnalyzer
@@ -25,6 +27,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -45,7 +48,7 @@ async def main():
                 vad_enabled=True,
                 vad_analyzer=SileroVADAnalyzer(),
                 vad_audio_passthrough=True,
-            )
+            ),
         )
 
         stt = AzureSTTService(
@@ -74,15 +77,17 @@ async def main():
         tma_in = LLMUserResponseAggregator(messages)
         tma_out = LLMAssistantResponseAggregator(messages)
 
-        pipeline = Pipeline([
-            transport.input(),   # Transport user input
-            stt,                 # STT
-            tma_in,              # User responses
-            llm,                 # LLM
-            tts,                 # TTS
-            transport.output(),  # Transport bot output
-            tma_out              # Assistant spoken responses
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                stt,  # STT
+                tma_in,  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                tma_out,  # Assistant spoken responses
+            ]
+        )
 
         task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
 
@@ -90,8 +95,7 @@ async def main():
         async def on_first_participant_joined(transport, participant):
             transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
-            messages.append(
-                {"role": "system", "content": "Please introduce yourself to the user."})
+            messages.append({"role": "system", "content": "Please introduce yourself to the user."})
             await task.queue_frames([LLMMessagesFrame(messages)])
 
         runner = PipelineRunner()
diff --git a/examples/foundational/07g-interruptible-openai-tts.py b/examples/foundational/07g-interruptible-openai-tts.py
index 2b27f7c0b..70576c97a 100644
--- a/examples/foundational/07g-interruptible-openai-tts.py
+++ b/examples/foundational/07g-interruptible-openai-tts.py
@@ -14,7 +14,9 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator, LLMUserResponseAggregator)
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
+)
 from pipecat.services.openai import OpenAITTSService
 from pipecat.services.openai import OpenAILLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
@@ -25,6 +27,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -44,18 +47,13 @@ async def main():
                 audio_out_sample_rate=24000,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
-        tts = OpenAITTSService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            voice="alloy"
-        )
+        tts = OpenAITTSService(api_key=os.getenv("OPENAI_API_KEY"), voice="alloy")
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
         messages = [
             {
@@ -67,14 +65,16 @@ async def main():
         tma_in = LLMUserResponseAggregator(messages)
         tma_out = LLMAssistantResponseAggregator(messages)
 
-        pipeline = Pipeline([
-            transport.input(),   # Transport user input
-            tma_in,              # User responses
-            llm,                 # LLM
-            tts,                 # TTS
-            transport.output(),  # Transport bot output
-            tma_out              # Assistant spoken responses
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                tma_in,  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                tma_out,  # Assistant spoken responses
+            ]
+        )
 
         task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
 
@@ -82,8 +82,7 @@ async def main():
         async def on_first_participant_joined(transport, participant):
             transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
-            messages.append(
-                {"role": "system", "content": "Please introduce yourself to the user."})
+            messages.append({"role": "system", "content": "Please introduce yourself to the user."})
             await task.queue_frames([LLMMessagesFrame(messages)])
 
         runner = PipelineRunner()
diff --git a/examples/foundational/07h-interruptible-openpipe.py b/examples/foundational/07h-interruptible-openpipe.py
index 489015f21..b87563bd3 100644
--- a/examples/foundational/07h-interruptible-openpipe.py
+++ b/examples/foundational/07h-interruptible-openpipe.py
@@ -28,6 +28,7 @@ from loguru import logger
 import time
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -46,8 +47,8 @@ async def main():
                 audio_out_enabled=True,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
         tts = CartesiaTTSService(
@@ -60,9 +61,7 @@ async def main():
             api_key=os.getenv("OPENAI_API_KEY"),
             openpipe_api_key=os.getenv("OPENPIPE_API_KEY"),
             model="gpt-4o",
-            tags={
-                "conversation_id": f"pipecat-{timestamp}"
-            }
+            tags={"conversation_id": f"pipecat-{timestamp}"},
         )
 
         messages = [
@@ -74,14 +73,16 @@ async def main():
         tma_in = LLMUserResponseAggregator(messages)
         tma_out = LLMAssistantResponseAggregator(messages)
 
-        pipeline = Pipeline([
-            transport.input(),   # Transport user input
-            tma_in,              # User responses
-            llm,                 # LLM
-            tts,                 # TTS
-            transport.output(),  # Transport bot output
-            tma_out              # Assistant spoken responses
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                tma_in,  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                tma_out,  # Assistant spoken responses
+            ]
+        )
 
         task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
 
@@ -89,8 +90,7 @@ async def main():
         async def on_first_participant_joined(transport, participant):
             transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
-            messages.append(
-                {"role": "system", "content": "Please introduce yourself to the user."})
+            messages.append({"role": "system", "content": "Please introduce yourself to the user."})
             await task.queue_frames([LLMMessagesFrame(messages)])
 
         runner = PipelineRunner()
diff --git a/examples/foundational/07i-interruptible-xtts.py b/examples/foundational/07i-interruptible-xtts.py
index e892651e0..2e6f95433 100644
--- a/examples/foundational/07i-interruptible-xtts.py
+++ b/examples/foundational/07i-interruptible-xtts.py
@@ -14,7 +14,9 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator, LLMUserResponseAggregator)
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
+)
 from pipecat.services.deepgram import DeepgramSTTService, DeepgramTTSService
 from pipecat.services.openai import OpenAILLMService
 from pipecat.services.xtts import XTTSService
@@ -26,6 +28,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -45,19 +48,17 @@ async def main():
                 transcription_enabled=True,
                 vad_enabled=True,
                 vad_analyzer=SileroVADAnalyzer(),
-            )
+            ),
         )
 
         tts = XTTSService(
             aiohttp_session=session,
             voice_id="Claribel Dervla",
             language="en",
-            base_url="http://localhost:8000"
+            base_url="http://localhost:8000",
         )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
         messages = [
             {
@@ -69,14 +70,16 @@ async def main():
         tma_in = LLMUserResponseAggregator(messages)
         tma_out = LLMAssistantResponseAggregator(messages)
 
-        pipeline = Pipeline([
-            transport.input(),   # Transport user input
-            tma_in,              # User responses
-            llm,                 # LLM
-            tts,                 # TTS
-            transport.output(),  # Transport bot output
-            tma_out              # Assistant spoken responses
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                tma_in,  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                tma_out,  # Assistant spoken responses
+            ]
+        )
 
         task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
 
@@ -84,8 +87,7 @@ async def main():
         async def on_first_participant_joined(transport, participant):
             transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
-            messages.append(
-                {"role": "system", "content": "Please introduce yourself to the user."})
+            messages.append({"role": "system", "content": "Please introduce yourself to the user."})
             await task.queue_frames([LLMMessagesFrame(messages)])
 
         runner = PipelineRunner()
diff --git a/examples/foundational/07j-interruptible-gladia.py b/examples/foundational/07j-interruptible-gladia.py
index aff975e29..dc07ec7ba 100644
--- a/examples/foundational/07j-interruptible-gladia.py
+++ b/examples/foundational/07j-interruptible-gladia.py
@@ -14,7 +14,9 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator, LLMUserResponseAggregator)
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
+)
 from pipecat.services.cartesia import CartesiaTTSService
 from pipecat.services.gladia import GladiaSTTService
 from pipecat.services.openai import OpenAILLMService
@@ -26,6 +28,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -45,7 +48,7 @@ async def main():
                 vad_enabled=True,
                 vad_analyzer=SileroVADAnalyzer(),
                 vad_audio_passthrough=True,
-            )
+            ),
         )
 
         stt = GladiaSTTService(
@@ -57,9 +60,7 @@ async def main():
             voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
         )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
         messages = [
             {
@@ -71,15 +72,17 @@ async def main():
         tma_in = LLMUserResponseAggregator(messages)
         tma_out = LLMAssistantResponseAggregator(messages)
 
-        pipeline = Pipeline([
-            transport.input(),   # Transport user input
-            stt,                 # STT
-            tma_in,              # User responses
-            llm,                 # LLM
-            tts,                 # TTS
-            transport.output(),  # Transport bot output
-            tma_out              # Assistant spoken responses
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                stt,  # STT
+                tma_in,  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                tma_out,  # Assistant spoken responses
+            ]
+        )
 
         task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
 
@@ -87,8 +90,7 @@ async def main():
         async def on_first_participant_joined(transport, participant):
             transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
-            messages.append(
-                {"role": "system", "content": "Please introduce yourself to the user."})
+            messages.append({"role": "system", "content": "Please introduce yourself to the user."})
             await task.queue_frames([LLMMessagesFrame(messages)])
 
         runner = PipelineRunner()
diff --git a/examples/foundational/07k-interruptible-lmnt.py b/examples/foundational/07k-interruptible-lmnt.py
index 6e68564ea..fb231c7bc 100644
--- a/examples/foundational/07k-interruptible-lmnt.py
+++ b/examples/foundational/07k-interruptible-lmnt.py
@@ -14,7 +14,9 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator, LLMUserResponseAggregator)
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
+)
 from pipecat.services.lmnt import LmntTTSService
 from pipecat.services.openai import OpenAILLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
@@ -25,6 +27,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -44,18 +47,13 @@ async def main():
                 audio_out_sample_rate=24000,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
-        tts = LmntTTSService(
-            api_key=os.getenv("LMNT_API_KEY"),
-            voice_id="morgan"
-        )
+        tts = LmntTTSService(api_key=os.getenv("LMNT_API_KEY"), voice_id="morgan")
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
         messages = [
             {
@@ -67,14 +65,16 @@ async def main():
         tma_in = LLMUserResponseAggregator(messages)
         tma_out = LLMAssistantResponseAggregator(messages)
 
-        pipeline = Pipeline([
-            transport.input(),   # Transport user input
-            tma_in,              # User responses
-            llm,                 # LLM
-            tts,                 # TTS
-            transport.output(),  # Transport bot output
-            tma_out              # Assistant spoken responses
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                tma_in,  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                tma_out,  # Assistant spoken responses
+            ]
+        )
 
         task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
 
@@ -82,8 +82,7 @@ async def main():
         async def on_first_participant_joined(transport, participant):
             transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
-            messages.append(
-                {"role": "system", "content": "Please introduce yourself to the user."})
+            messages.append({"role": "system", "content": "Please introduce yourself to the user."})
             await task.queue_frames([LLMMessagesFrame(messages)])
 
         runner = PipelineRunner()
diff --git a/examples/foundational/07l-interruptible-together.py b/examples/foundational/07l-interruptible-together.py
index d5afa6d0d..e2cb55fed 100644
--- a/examples/foundational/07l-interruptible-together.py
+++ b/examples/foundational/07l-interruptible-together.py
@@ -14,7 +14,9 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator, LLMUserResponseAggregator)
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
+)
 from pipecat.services.cartesia import CartesiaTTSService
 from pipecat.services.together import TogetherLLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
@@ -25,6 +27,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -43,8 +46,8 @@ async def main():
                 audio_out_enabled=True,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
         tts = CartesiaTTSService(
@@ -62,8 +65,8 @@ async def main():
                 extra={
                     "frequency_penalty": 2.0,
                     "presence_penalty": 0.0,
-                }
-            )
+                },
+            ),
         )
 
         messages = [
@@ -76,14 +79,16 @@ async def main():
         tma_in = LLMUserResponseAggregator(messages)
         tma_out = LLMAssistantResponseAggregator(messages)
 
-        pipeline = Pipeline([
-            transport.input(),   # Transport user input
-            tma_in,              # User responses
-            llm,                 # LLM
-            tts,                 # TTS
-            transport.output(),  # Transport bot output
-            tma_out              # Assistant spoken responses
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                tma_in,  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                tma_out,  # Assistant spoken responses
+            ]
+        )
 
         task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
 
diff --git a/examples/foundational/08-bots-arguing.py b/examples/foundational/08-bots-arguing.py
index abf5a1d54..150fbfc0a 100644
--- a/examples/foundational/08-bots-arguing.py
+++ b/examples/foundational/08-bots-arguing.py
@@ -15,6 +15,7 @@ from pipecat.frames.frames import AudioFrame, EndFrame, ImageFrame, LLMMessagesF
 from runner import configure
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logging.basicConfig(format=f"%(levelno)s %(asctime)s %(message)s")
@@ -53,9 +54,7 @@ async def main():
             voice_id="jBpfuIE2acCO8z3wKNLl",
         )
         dalle = FalImageGenService(
-            params=FalImageGenService.InputParams(
-                image_size="1024x1024"
-            ),
+            params=FalImageGenService.InputParams(image_size="1024x1024"),
             aiohttp_session=session,
             key=os.getenv("FAL_KEY"),
         )
@@ -75,13 +74,11 @@ async def main():
 
         async def get_text_and_audio(messages) -> Tuple[str, bytearray]:
             """This function streams text from the LLM and uses the TTS service to convert
-             that text to speech as it's received. """
+            that text to speech as it's received."""
             source_queue = asyncio.Queue()
             sink_queue = asyncio.Queue()
             sentence_aggregator = SentenceAggregator()
-            pipeline = Pipeline(
-                [llm, sentence_aggregator, tts1], source_queue, sink_queue
-            )
+            pipeline = Pipeline([llm, sentence_aggregator, tts1], source_queue, sink_queue)
 
             await source_queue.put(LLMMessagesFrame(messages))
             await source_queue.put(EndFrame())
diff --git a/examples/foundational/09-mirror.py b/examples/foundational/09-mirror.py
index bb6253deb..ff71c60d6 100644
--- a/examples/foundational/09-mirror.py
+++ b/examples/foundational/09-mirror.py
@@ -8,7 +8,13 @@ import aiohttp
 import asyncio
 import sys
 
-from pipecat.frames.frames import Frame, InputAudioRawFrame, InputImageRawFrame, OutputAudioRawFrame, OutputImageRawFrame
+from pipecat.frames.frames import (
+    Frame,
+    InputAudioRawFrame,
+    InputImageRawFrame,
+    OutputAudioRawFrame,
+    OutputImageRawFrame,
+)
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
@@ -20,6 +26,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -27,21 +34,20 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 class MirrorProcessor(FrameProcessor):
-
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
         if isinstance(frame, InputAudioRawFrame):
-            await self.push_frame(OutputAudioRawFrame(
-                audio=frame.audio,
-                sample_rate=frame.sample_rate,
-                num_channels=frame.num_channels)
+            await self.push_frame(
+                OutputAudioRawFrame(
+                    audio=frame.audio,
+                    sample_rate=frame.sample_rate,
+                    num_channels=frame.num_channels,
+                )
             )
         elif isinstance(frame, InputImageRawFrame):
-            await self.push_frame(OutputImageRawFrame(
-                image=frame.image,
-                size=frame.size,
-                format=frame.format)
+            await self.push_frame(
+                OutputImageRawFrame(image=frame.image, size=frame.size, format=frame.format)
             )
         else:
             await self.push_frame(frame, direction)
@@ -52,15 +58,17 @@ async def main():
         (room_url, token) = await configure(session)
 
         transport = DailyTransport(
-            room_url, token, "Test",
+            room_url,
+            token,
+            "Test",
             DailyParams(
                 audio_in_enabled=True,
                 audio_out_enabled=True,
                 camera_out_enabled=True,
                 camera_out_is_live=True,
                 camera_out_width=1280,
-                camera_out_height=720
-            )
+                camera_out_height=720,
+            ),
         )
 
         @transport.event_handler("on_first_participant_joined")
diff --git a/examples/foundational/09a-local-mirror.py b/examples/foundational/09a-local-mirror.py
index afc77470d..c3c66569b 100644
--- a/examples/foundational/09a-local-mirror.py
+++ b/examples/foundational/09a-local-mirror.py
@@ -10,7 +10,13 @@ import sys
 
 import tkinter as tk
 
-from pipecat.frames.frames import Frame, InputAudioRawFrame, InputImageRawFrame, OutputAudioRawFrame, OutputImageRawFrame
+from pipecat.frames.frames import (
+    Frame,
+    InputAudioRawFrame,
+    InputImageRawFrame,
+    OutputAudioRawFrame,
+    OutputImageRawFrame,
+)
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
@@ -24,31 +30,33 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
 logger.add(sys.stderr, level="DEBUG")
 
-class MirrorProcessor(FrameProcessor):
 
+class MirrorProcessor(FrameProcessor):
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
         if isinstance(frame, InputAudioRawFrame):
-            await self.push_frame(OutputAudioRawFrame(
-                audio=frame.audio,
-                sample_rate=frame.sample_rate,
-                num_channels=frame.num_channels)
+            await self.push_frame(
+                OutputAudioRawFrame(
+                    audio=frame.audio,
+                    sample_rate=frame.sample_rate,
+                    num_channels=frame.num_channels,
+                )
             )
         elif isinstance(frame, InputImageRawFrame):
-            await self.push_frame(OutputImageRawFrame(
-                image=frame.image,
-                size=frame.size,
-                format=frame.format)
+            await self.push_frame(
+                OutputImageRawFrame(image=frame.image, size=frame.size, format=frame.format)
             )
         else:
             await self.push_frame(frame, direction)
 
+
 async def main():
     async with aiohttp.ClientSession() as session:
         (room_url, token) = await configure(session)
@@ -57,8 +65,8 @@ async def main():
         tk_root.title("Local Mirror")
 
         daily_transport = DailyTransport(
-            room_url, token, "Test", DailyParams(
-                audio_in_enabled=True))
+            room_url, token, "Test", DailyParams(audio_in_enabled=True)
+        )
 
         tk_transport = TkLocalTransport(
             tk_root,
@@ -67,7 +75,9 @@ async def main():
                 camera_out_enabled=True,
                 camera_out_is_live=True,
                 camera_out_width=1280,
-                camera_out_height=720))
+                camera_out_height=720,
+            ),
+        )
 
         @daily_transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
diff --git a/examples/foundational/10-wake-phrase.py b/examples/foundational/10-wake-phrase.py
index 6e9e106b8..860cda7d0 100644
--- a/examples/foundational/10-wake-phrase.py
+++ b/examples/foundational/10-wake-phrase.py
@@ -14,7 +14,9 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator, LLMUserResponseAggregator)
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
+)
 from pipecat.services.cartesia import CartesiaTTSService
 from pipecat.services.openai import OpenAILLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
@@ -25,6 +27,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -43,8 +46,8 @@ async def main():
                 audio_out_enabled=True,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
         tts = CartesiaTTSService(
@@ -52,9 +55,7 @@ async def main():
             voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
         )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
         messages = [
             {
@@ -67,15 +68,17 @@ async def main():
         tma_in = LLMUserResponseAggregator(messages)
         tma_out = LLMAssistantResponseAggregator(messages)
 
-        pipeline = Pipeline([
-            transport.input(),   # Transport user input
-            hey_robot_filter,    # Filter out speech not directed at the robot
-            tma_in,              # User responses
-            llm,                 # LLM
-            tts,                 # TTS
-            transport.output(),  # Transport bot output
-            tma_out              # Assistant spoken responses
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                hey_robot_filter,  # Filter out speech not directed at the robot
+                tma_in,  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                tma_out,  # Assistant spoken responses
+            ]
+        )
 
         task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
 
diff --git a/examples/foundational/11-sound-effects.py b/examples/foundational/11-sound-effects.py
index 21b03bedf..89b7ea93c 100644
--- a/examples/foundational/11-sound-effects.py
+++ b/examples/foundational/11-sound-effects.py
@@ -35,6 +35,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -53,12 +54,12 @@ for file in sound_files:
     filename = os.path.splitext(os.path.basename(full_path))[0]
     # Open the image and convert it to bytes
     with wave.open(full_path) as audio_file:
-        sounds[file] = OutputAudioRawFrame(audio_file.readframes(-1),
-                                           audio_file.getframerate(), audio_file.getnchannels())
+        sounds[file] = OutputAudioRawFrame(
+            audio_file.readframes(-1), audio_file.getframerate(), audio_file.getnchannels()
+        )
 
 
 class OutboundSoundEffectWrapper(FrameProcessor):
-
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
@@ -71,7 +72,6 @@ class OutboundSoundEffectWrapper(FrameProcessor):
 
 
 class InboundSoundEffectWrapper(FrameProcessor):
-
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
@@ -95,13 +95,11 @@ async def main():
                 audio_out_enabled=True,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
         tts = CartesiaHttpTTSService(
             api_key=os.getenv("CARTESIA_API_KEY"),
@@ -122,18 +120,20 @@ async def main():
         fl = FrameLogger("LLM Out")
         fl2 = FrameLogger("Transcription In")
 
-        pipeline = Pipeline([
-            transport.input(),
-            tma_in,
-            in_sound,
-            fl2,
-            llm,
-            fl,
-            tts,
-            out_sound,
-            transport.output(),
-            tma_out
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),
+                tma_in,
+                in_sound,
+                fl2,
+                llm,
+                fl,
+                tts,
+                out_sound,
+                transport.output(),
+                tma_out,
+            ]
+        )
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
diff --git a/examples/foundational/12-describe-video.py b/examples/foundational/12-describe-video.py
index 11240e8de..6b24190d0 100644
--- a/examples/foundational/12-describe-video.py
+++ b/examples/foundational/12-describe-video.py
@@ -26,6 +26,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -33,7 +34,6 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 class UserImageRequester(FrameProcessor):
-
     def __init__(self, participant_id: str | None = None):
         super().__init__()
         self._participant_id = participant_id
@@ -45,7 +45,9 @@ class UserImageRequester(FrameProcessor):
         await super().process_frame(frame, direction)
 
         if self._participant_id and isinstance(frame, TextFrame):
-            await self.push_frame(UserImageRequestFrame(self._participant_id), FrameDirection.UPSTREAM)
+            await self.push_frame(
+                UserImageRequestFrame(self._participant_id), FrameDirection.UPSTREAM
+            )
         await self.push_frame(frame, direction)
 
 
@@ -61,8 +63,8 @@ async def main():
                 audio_out_enabled=True,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
         user_response = UserResponseAggregator()
@@ -86,15 +88,17 @@ async def main():
             transport.capture_participant_transcription(participant["id"])
             image_requester.set_participant_id(participant["id"])
 
-        pipeline = Pipeline([
-            transport.input(),
-            user_response,
-            image_requester,
-            vision_aggregator,
-            moondream,
-            tts,
-            transport.output()
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),
+                user_response,
+                image_requester,
+                vision_aggregator,
+                moondream,
+                tts,
+                transport.output(),
+            ]
+        )
 
         task = PipelineTask(pipeline)
 
@@ -102,5 +106,6 @@ async def main():
 
         await runner.run(task)
 
+
 if __name__ == "__main__":
     asyncio.run(main())
diff --git a/examples/foundational/12a-describe-video-gemini-flash.py b/examples/foundational/12a-describe-video-gemini-flash.py
index 395abdbdc..440564d23 100644
--- a/examples/foundational/12a-describe-video-gemini-flash.py
+++ b/examples/foundational/12a-describe-video-gemini-flash.py
@@ -26,6 +26,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -33,7 +34,6 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 class UserImageRequester(FrameProcessor):
-
     def __init__(self, participant_id: str | None = None):
         super().__init__()
         self._participant_id = participant_id
@@ -45,7 +45,9 @@ class UserImageRequester(FrameProcessor):
         await super().process_frame(frame, direction)
 
         if self._participant_id and isinstance(frame, TextFrame):
-            await self.push_frame(UserImageRequestFrame(self._participant_id), FrameDirection.UPSTREAM)
+            await self.push_frame(
+                UserImageRequestFrame(self._participant_id), FrameDirection.UPSTREAM
+            )
         await self.push_frame(frame, direction)
 
 
@@ -62,8 +64,8 @@ async def main():
                 audio_out_enabled=True,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
         user_response = UserResponseAggregator()
@@ -73,8 +75,8 @@ async def main():
         vision_aggregator = VisionImageFrameAggregator()
 
         google = GoogleLLMService(
-            model="gemini-1.5-flash-latest",
-            api_key=os.getenv("GOOGLE_API_KEY"))
+            model="gemini-1.5-flash-latest", api_key=os.getenv("GOOGLE_API_KEY")
+        )
 
         tts = CartesiaTTSService(
             api_key=os.getenv("CARTESIA_API_KEY"),
@@ -88,15 +90,17 @@ async def main():
             transport.capture_participant_transcription(participant["id"])
             image_requester.set_participant_id(participant["id"])
 
-        pipeline = Pipeline([
-            transport.input(),
-            user_response,
-            image_requester,
-            vision_aggregator,
-            google,
-            tts,
-            transport.output()
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),
+                user_response,
+                image_requester,
+                vision_aggregator,
+                google,
+                tts,
+                transport.output(),
+            ]
+        )
 
         task = PipelineTask(pipeline)
 
@@ -104,5 +108,6 @@ async def main():
 
         await runner.run(task)
 
+
 if __name__ == "__main__":
     asyncio.run(main())
diff --git a/examples/foundational/12b-describe-video-gpt-4o.py b/examples/foundational/12b-describe-video-gpt-4o.py
index 384c9aa0c..1d2865004 100644
--- a/examples/foundational/12b-describe-video-gpt-4o.py
+++ b/examples/foundational/12b-describe-video-gpt-4o.py
@@ -26,6 +26,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -33,7 +34,6 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 class UserImageRequester(FrameProcessor):
-
     def __init__(self, participant_id: str | None = None):
         super().__init__()
         self._participant_id = participant_id
@@ -45,7 +45,9 @@ class UserImageRequester(FrameProcessor):
         await super().process_frame(frame, direction)
 
         if self._participant_id and isinstance(frame, TextFrame):
-            await self.push_frame(UserImageRequestFrame(self._participant_id), FrameDirection.UPSTREAM)
+            await self.push_frame(
+                UserImageRequestFrame(self._participant_id), FrameDirection.UPSTREAM
+            )
         await self.push_frame(frame, direction)
 
 
@@ -61,8 +63,8 @@ async def main():
                 audio_out_enabled=True,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
         user_response = UserResponseAggregator()
@@ -71,10 +73,7 @@ async def main():
 
         vision_aggregator = VisionImageFrameAggregator()
 
-        openai = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o"
-        )
+        openai = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
         tts = CartesiaTTSService(
             api_key=os.getenv("CARTESIA_API_KEY"),
@@ -88,15 +87,17 @@ async def main():
             transport.capture_participant_transcription(participant["id"])
             image_requester.set_participant_id(participant["id"])
 
-        pipeline = Pipeline([
-            transport.input(),
-            user_response,
-            image_requester,
-            vision_aggregator,
-            openai,
-            tts,
-            transport.output()
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),
+                user_response,
+                image_requester,
+                vision_aggregator,
+                openai,
+                tts,
+                transport.output(),
+            ]
+        )
 
         task = PipelineTask(pipeline)
 
@@ -104,5 +105,6 @@ async def main():
 
         await runner.run(task)
 
+
 if __name__ == "__main__":
     asyncio.run(main())
diff --git a/examples/foundational/12c-describe-video-anthropic.py b/examples/foundational/12c-describe-video-anthropic.py
index cc1f14c92..7458adf69 100644
--- a/examples/foundational/12c-describe-video-anthropic.py
+++ b/examples/foundational/12c-describe-video-anthropic.py
@@ -26,6 +26,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -33,7 +34,6 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 class UserImageRequester(FrameProcessor):
-
     def __init__(self, participant_id: str | None = None):
         super().__init__()
         self._participant_id = participant_id
@@ -45,7 +45,9 @@ class UserImageRequester(FrameProcessor):
         await super().process_frame(frame, direction)
 
         if self._participant_id and isinstance(frame, TextFrame):
-            await self.push_frame(UserImageRequestFrame(self._participant_id), FrameDirection.UPSTREAM)
+            await self.push_frame(
+                UserImageRequestFrame(self._participant_id), FrameDirection.UPSTREAM
+            )
         await self.push_frame(frame, direction)
 
 
@@ -61,8 +63,8 @@ async def main():
                 audio_out_enabled=True,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
         user_response = UserResponseAggregator()
@@ -71,9 +73,7 @@ async def main():
 
         vision_aggregator = VisionImageFrameAggregator()
 
-        anthropic = AnthropicLLMService(
-            api_key=os.getenv("ANTHROPIC_API_KEY")
-        )
+        anthropic = AnthropicLLMService(api_key=os.getenv("ANTHROPIC_API_KEY"))
 
         tts = CartesiaTTSService(
             api_key=os.getenv("CARTESIA_API_KEY"),
@@ -88,15 +88,17 @@ async def main():
             transport.capture_participant_transcription(participant["id"])
             image_requester.set_participant_id(participant["id"])
 
-        pipeline = Pipeline([
-            transport.input(),
-            user_response,
-            image_requester,
-            vision_aggregator,
-            anthropic,
-            tts,
-            transport.output()
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),
+                user_response,
+                image_requester,
+                vision_aggregator,
+                anthropic,
+                tts,
+                transport.output(),
+            ]
+        )
 
         task = PipelineTask(pipeline)
 
@@ -104,5 +106,6 @@ async def main():
 
         await runner.run(task)
 
+
 if __name__ == "__main__":
     asyncio.run(main())
diff --git a/examples/foundational/13-whisper-transcription.py b/examples/foundational/13-whisper-transcription.py
index bb24a80bb..c895cb944 100644
--- a/examples/foundational/13-whisper-transcription.py
+++ b/examples/foundational/13-whisper-transcription.py
@@ -21,6 +21,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -28,7 +29,6 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 class TranscriptionLogger(FrameProcessor):
-
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
@@ -40,8 +40,9 @@ async def main():
     async with aiohttp.ClientSession() as session:
         (room_url, _) = await configure(session)
 
-        transport = DailyTransport(room_url, None, "Transcription bot",
-                                   DailyParams(audio_in_enabled=True))
+        transport = DailyTransport(
+            room_url, None, "Transcription bot", DailyParams(audio_in_enabled=True)
+        )
 
         stt = WhisperSTTService()
 
diff --git a/examples/foundational/13a-whisper-local.py b/examples/foundational/13a-whisper-local.py
index 6bf27aa0a..c1ba37ca9 100644
--- a/examples/foundational/13a-whisper-local.py
+++ b/examples/foundational/13a-whisper-local.py
@@ -19,6 +19,7 @@ from pipecat.transports.local.audio import LocalAudioTransport
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -26,7 +27,6 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 class TranscriptionLogger(FrameProcessor):
-
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
diff --git a/examples/foundational/13b-deepgram-transcription.py b/examples/foundational/13b-deepgram-transcription.py
index c5961109b..6af3237db 100644
--- a/examples/foundational/13b-deepgram-transcription.py
+++ b/examples/foundational/13b-deepgram-transcription.py
@@ -22,6 +22,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -29,7 +30,6 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 class TranscriptionLogger(FrameProcessor):
-
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
@@ -41,8 +41,9 @@ async def main():
     async with aiohttp.ClientSession() as session:
         (room_url, _) = await configure(session)
 
-        transport = DailyTransport(room_url, None, "Transcription bot",
-                                   DailyParams(audio_in_enabled=True))
+        transport = DailyTransport(
+            room_url, None, "Transcription bot", DailyParams(audio_in_enabled=True)
+        )
 
         stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
 
diff --git a/examples/foundational/14-function-calling.py b/examples/foundational/14-function-calling.py
index e4bdd5797..b5aba449c 100644
--- a/examples/foundational/14-function-calling.py
+++ b/examples/foundational/14-function-calling.py
@@ -26,6 +26,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -52,8 +53,8 @@ async def main():
                 audio_out_enabled=True,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
         tts = CartesiaTTSService(
@@ -61,15 +62,10 @@ async def main():
             voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
         )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
         # Register a function_name of None to get all functions
         # sent to the same callback with an additional function_name parameter.
-        llm.register_function(
-            None,
-            fetch_weather_from_api,
-            start_callback=start_fetch_weather)
+        llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
 
         fl_in = FrameLogger("Inner")
         fl_out = FrameLogger("Outer")
@@ -89,17 +85,15 @@ async def main():
                             },
                             "format": {
                                 "type": "string",
-                                "enum": [
-                                    "celsius",
-                                    "fahrenheit"],
+                                "enum": ["celsius", "fahrenheit"],
                                 "description": "The temperature unit to use. Infer this from the users location.",
                             },
                         },
-                        "required": [
-                            "location",
-                            "format"],
+                        "required": ["location", "format"],
                     },
-                })]
+                },
+            )
+        ]
         messages = [
             {
                 "role": "system",
@@ -110,16 +104,18 @@ async def main():
         context = OpenAILLMContext(messages, tools)
         context_aggregator = llm.create_context_aggregator(context)
 
-        pipeline = Pipeline([
-            fl_in,
-            transport.input(),
-            context_aggregator.user(),
-            llm,
-            fl_out,
-            tts,
-            transport.output(),
-            context_aggregator.assistant(),
-        ])
+        pipeline = Pipeline(
+            [
+                fl_in,
+                transport.input(),
+                context_aggregator.user(),
+                llm,
+                fl_out,
+                tts,
+                transport.output(),
+                context_aggregator.assistant(),
+            ]
+        )
 
         task = PipelineTask(pipeline)
 
@@ -133,5 +129,6 @@ async def main():
 
         await runner.run(task)
 
+
 if __name__ == "__main__":
     asyncio.run(main())
diff --git a/examples/foundational/15-switch-voices.py b/examples/foundational/15-switch-voices.py
index a55dedc83..4feaa4bbf 100644
--- a/examples/foundational/15-switch-voices.py
+++ b/examples/foundational/15-switch-voices.py
@@ -28,6 +28,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -39,7 +40,11 @@ current_voice = "News Lady"
 async def switch_voice(function_name, tool_call_id, args, llm, context, result_callback):
     global current_voice
     current_voice = args["voice"]
-    await result_callback({"voice": f"You are now using your {current_voice} voice. Your responses should now be as if you were a {current_voice}."})
+    await result_callback(
+        {
+            "voice": f"You are now using your {current_voice} voice. Your responses should now be as if you were a {current_voice}."
+        }
+    )
 
 
 async def news_lady_filter(frame) -> bool:
@@ -66,8 +71,8 @@ async def main():
                 audio_out_enabled=True,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
         news_lady = CartesiaTTSService(
@@ -85,9 +90,7 @@ async def main():
             voice_id="a0e99841-438c-4a64-b679-ae501e7d6091",  # Barbershop Man
         )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
         llm.register_function("switch_voice", switch_voice)
 
         tools = [
@@ -106,7 +109,9 @@ async def main():
                         },
                         "required": ["voice"],
                     },
-                })]
+                },
+            )
+        ]
         messages = [
             {
                 "role": "system",
@@ -117,18 +122,20 @@ async def main():
         context = OpenAILLMContext(messages, tools)
         context_aggregator = llm.create_context_aggregator(context)
 
-        pipeline = Pipeline([
-            transport.input(),   # Transport user input
-            context_aggregator.user(),  # User responses
-            llm,                 # LLM
-            ParallelPipeline(    # TTS (one of the following vocies)
-                [FunctionFilter(news_lady_filter), news_lady],            # News Lady voice
-                [FunctionFilter(british_lady_filter), british_lady],      # British Lady voice
-                [FunctionFilter(barbershop_man_filter), barbershop_man],  # Barbershop Man voice
-            ),
-            transport.output(),  # Transport bot output
-            context_aggregator.assistant(),  # Assistant spoken responses
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                context_aggregator.user(),  # User responses
+                llm,  # LLM
+                ParallelPipeline(  # TTS (one of the following vocies)
+                    [FunctionFilter(news_lady_filter), news_lady],  # News Lady voice
+                    [FunctionFilter(british_lady_filter), british_lady],  # British Lady voice
+                    [FunctionFilter(barbershop_man_filter), barbershop_man],  # Barbershop Man voice
+                ),
+                transport.output(),  # Transport bot output
+                context_aggregator.assistant(),  # Assistant spoken responses
+            ]
+        )
 
         task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
 
@@ -139,7 +146,9 @@ async def main():
             messages.append(
                 {
                     "role": "system",
-                    "content": f"Please introduce yourself to the user and let them know the voices you can do. Your initial responses should be as if you were a {current_voice}."})
+                    "content": f"Please introduce yourself to the user and let them know the voices you can do. Your initial responses should be as if you were a {current_voice}.",
+                }
+            )
             await task.queue_frames([LLMMessagesFrame(messages)])
 
         runner = PipelineRunner()
diff --git a/examples/foundational/15a-switch-languages.py b/examples/foundational/15a-switch-languages.py
index 0dde985ef..8c47ad963 100644
--- a/examples/foundational/15a-switch-languages.py
+++ b/examples/foundational/15a-switch-languages.py
@@ -29,6 +29,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -64,8 +65,8 @@ async def main():
                 audio_out_enabled=True,
                 vad_enabled=True,
                 vad_analyzer=SileroVADAnalyzer(),
-                vad_audio_passthrough=True
-            )
+                vad_audio_passthrough=True,
+            ),
         )
 
         stt = WhisperSTTService(model=Model.LARGE)
@@ -80,9 +81,7 @@ async def main():
             voice_id="846d6cb0-2301-48b6-9683-48f5618ea2f6",  # Spanish-speaking Lady
         )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
         llm.register_function("switch_language", switch_language)
 
         tools = [
@@ -101,7 +100,9 @@ async def main():
                         },
                         "required": ["language"],
                     },
-                })]
+                },
+            )
+        ]
         messages = [
             {
                 "role": "system",
@@ -112,18 +113,20 @@ async def main():
         context = OpenAILLMContext(messages, tools)
         context_aggregator = llm.create_context_aggregator(context)
 
-        pipeline = Pipeline([
-            transport.input(),   # Transport user input
-            stt,                 # STT
-            context_aggregator.user(),  # User responses
-            llm,                 # LLM
-            ParallelPipeline(    # TTS (bot will speak the chosen language)
-                [FunctionFilter(english_filter), english_tts],  # English
-                [FunctionFilter(spanish_filter), spanish_tts],  # Spanish
-            ),
-            transport.output(),  # Transport bot output
-            context_aggregator.assistant()  # Assistant spoken responses
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                stt,  # STT
+                context_aggregator.user(),  # User responses
+                llm,  # LLM
+                ParallelPipeline(  # TTS (bot will speak the chosen language)
+                    [FunctionFilter(english_filter), english_tts],  # English
+                    [FunctionFilter(spanish_filter), spanish_tts],  # Spanish
+                ),
+                transport.output(),  # Transport bot output
+                context_aggregator.assistant(),  # Assistant spoken responses
+            ]
+        )
 
         task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
 
@@ -134,7 +137,9 @@ async def main():
             messages.append(
                 {
                     "role": "system",
-                    "content": f"Please introduce yourself to the user and let them know the languages you speak. Your initial responses should be in {current_language}."})
+                    "content": f"Please introduce yourself to the user and let them know the languages you speak. Your initial responses should be in {current_language}.",
+                }
+            )
             await task.queue_frames([LLMMessagesFrame(messages)])
 
         runner = PipelineRunner()
diff --git a/examples/foundational/16-gpu-container-local-bot.py b/examples/foundational/16-gpu-container-local-bot.py
index 7c0af45f7..06bf45195 100644
--- a/examples/foundational/16-gpu-container-local-bot.py
+++ b/examples/foundational/16-gpu-container-local-bot.py
@@ -14,10 +14,16 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator, LLMUserResponseAggregator)
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
+)
 from pipecat.services.deepgram import DeepgramTTSService
 from pipecat.services.openai import OpenAILLMService
-from pipecat.transports.services.daily import DailyParams, DailyTransport, DailyTransportMessageFrame
+from pipecat.transports.services.daily import (
+    DailyParams,
+    DailyTransport,
+    DailyTransportMessageFrame,
+)
 from pipecat.vad.silero import SileroVADAnalyzer
 
 from runner import configure
@@ -25,6 +31,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -43,15 +50,15 @@ async def main():
                 audio_out_enabled=True,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
         tts = DeepgramTTSService(
             aiohttp_session=session,
             api_key=os.getenv("DEEPGRAM_API_KEY"),
             voice="aura-asteria-en",
-            base_url="http://0.0.0.0:8080/v1/speak"
+            base_url="http://0.0.0.0:8080/v1/speak",
         )
 
         llm = OpenAILLMService(
@@ -60,7 +67,7 @@ async def main():
             # model="gpt-4o"
             # Or, to use a local vLLM (or similar) api server
             model="meta-llama/Meta-Llama-3-8B-Instruct",
-            base_url="http://0.0.0.0:8000/v1"
+            base_url="http://0.0.0.0:8000/v1",
         )
 
         messages = [
@@ -73,14 +80,16 @@ async def main():
         tma_in = LLMUserResponseAggregator(messages)
         tma_out = LLMAssistantResponseAggregator(messages)
 
-        pipeline = Pipeline([
-            transport.input(),   # Transport user input
-            tma_in,              # User responses
-            llm,                 # LLM
-            tts,                 # TTS
-            transport.output(),  # Transport bot output
-            tma_out              # Assistant spoken responses
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                tma_in,  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                tma_out,  # Assistant spoken responses
+            ]
+        )
 
         task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True, enable_metrics=True))
 
@@ -93,8 +102,7 @@ async def main():
         # When the first participant joins, the bot should introduce itself.
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
-            messages.append(
-                {"role": "system", "content": "Please introduce yourself to the user."})
+            messages.append({"role": "system", "content": "Please introduce yourself to the user."})
             await task.queue_frames([LLMMessagesFrame(messages)])
 
         # Handle "latency-ping" messages. The client will send app messages that look like
@@ -111,14 +119,18 @@ async def main():
                     logger.debug(f"Received latency ping app message: {message}")
                     ts = message["latency-ping"]["ts"]
                     # Send immediately
-                    transport.output().send_message(DailyTransportMessageFrame(
-                        message={"latency-pong-msg-handler": {"ts": ts}},
-                        participant_id=sender))
+                    transport.output().send_message(
+                        DailyTransportMessageFrame(
+                            message={"latency-pong-msg-handler": {"ts": ts}}, participant_id=sender
+                        )
+                    )
                     # And push to the pipeline for the Daily transport.output to send
                     await tma_in.push_frame(
                         DailyTransportMessageFrame(
                             message={"latency-pong-pipeline-delivery": {"ts": ts}},
-                            participant_id=sender))
+                            participant_id=sender,
+                        )
+                    )
             except Exception as e:
                 logger.debug(f"message handling error: {e} - {message}")
 
diff --git a/examples/foundational/17-detect-user-idle.py b/examples/foundational/17-detect-user-idle.py
index 66fcfb200..91835f8b3 100644
--- a/examples/foundational/17-detect-user-idle.py
+++ b/examples/foundational/17-detect-user-idle.py
@@ -14,7 +14,9 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator, LLMUserResponseAggregator)
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
+)
 from pipecat.processors.user_idle_processor import UserIdleProcessor
 from pipecat.services.cartesia import CartesiaTTSService
 from pipecat.services.openai import OpenAILLMService
@@ -26,6 +28,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -44,8 +47,8 @@ async def main():
                 audio_out_enabled=True,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
         tts = CartesiaTTSService(
@@ -53,9 +56,7 @@ async def main():
             voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
         )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
         messages = [
             {
@@ -69,33 +70,41 @@ async def main():
 
         async def user_idle_callback(user_idle: UserIdleProcessor):
             messages.append(
-                {"role": "system", "content": "Ask the user if they are still there and try to prompt for some input, but be short."})
+                {
+                    "role": "system",
+                    "content": "Ask the user if they are still there and try to prompt for some input, but be short.",
+                }
+            )
             await user_idle.push_frame(LLMMessagesFrame(messages))
 
         user_idle = UserIdleProcessor(callback=user_idle_callback, timeout=5.0)
 
-        pipeline = Pipeline([
-            transport.input(),   # Transport user input
-            user_idle,           # Idle user check-in
-            tma_in,              # User responses
-            llm,                 # LLM
-            tts,                 # TTS
-            transport.output(),  # Transport bot output
-            tma_out              # Assistant spoken responses
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                user_idle,  # Idle user check-in
+                tma_in,  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                tma_out,  # Assistant spoken responses
+            ]
+        )
 
-        task = PipelineTask(pipeline, PipelineParams(
-            allow_interruptions=True,
-            enable_metrics=True,
-            report_only_initial_ttfb=True,
-        ))
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
             transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
-            messages.append(
-                {"role": "system", "content": "Please introduce yourself to the user."})
+            messages.append({"role": "system", "content": "Please introduce yourself to the user."})
             await task.queue_frames([LLMMessagesFrame(messages)])
 
         runner = PipelineRunner()
diff --git a/examples/foundational/18-gstreamer-filesrc.py b/examples/foundational/18-gstreamer-filesrc.py
index 4b04dcf92..cdb187f66 100644
--- a/examples/foundational/18-gstreamer-filesrc.py
+++ b/examples/foundational/18-gstreamer-filesrc.py
@@ -20,6 +20,7 @@ from runner import configure_with_args
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -29,12 +30,7 @@ logger.add(sys.stderr, level="DEBUG")
 async def main():
     async with aiohttp.ClientSession() as session:
         parser = argparse.ArgumentParser(description="Daily AI SDK Bot Sample")
-        parser.add_argument(
-            "-i",
-            "--input",
-            type=str,
-            required=True,
-            help="Input video file")
+        parser.add_argument("-i", "--input", type=str, required=True, help="Input video file")
 
         (room_url, _, args) = await configure_with_args(session, parser)
 
@@ -49,7 +45,7 @@ async def main():
                 camera_out_width=1280,
                 camera_out_height=720,
                 camera_out_is_live=True,
-            )
+            ),
         )
 
         gst = GStreamerPipelineSource(
@@ -59,13 +55,15 @@ async def main():
                 video_height=720,
                 audio_sample_rate=16000,
                 audio_channels=1,
-            )
+            ),
         )
 
-        pipeline = Pipeline([
-            gst,                 # GStreamer file source
-            transport.output(),  # Transport bot output
-        ])
+        pipeline = Pipeline(
+            [
+                gst,  # GStreamer file source
+                transport.output(),  # Transport bot output
+            ]
+        )
 
         task = PipelineTask(pipeline)
 
diff --git a/examples/foundational/18a-gstreamer-videotestsrc.py b/examples/foundational/18a-gstreamer-videotestsrc.py
index 7c71e06ce..9e5977348 100644
--- a/examples/foundational/18a-gstreamer-videotestsrc.py
+++ b/examples/foundational/18a-gstreamer-videotestsrc.py
@@ -19,6 +19,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -38,20 +39,22 @@ async def main():
                 camera_out_width=1280,
                 camera_out_height=720,
                 camera_out_is_live=True,
-            )
+            ),
         )
 
         gst = GStreamerPipelineSource(
-            pipeline="videotestsrc ! capsfilter caps=\"video/x-raw,width=1280,height=720,framerate=30/1\"",
+            pipeline='videotestsrc ! capsfilter caps="video/x-raw,width=1280,height=720,framerate=30/1"',
             out_params=GStreamerPipelineSource.OutputParams(
-                video_width=1280,
-                video_height=720,
-                clock_sync=False))
+                video_width=1280, video_height=720, clock_sync=False
+            ),
+        )
 
-        pipeline = Pipeline([
-            gst,                 # GStreamer file source
-            transport.output(),  # Transport bot output
-        ])
+        pipeline = Pipeline(
+            [
+                gst,  # GStreamer file source
+                transport.output(),  # Transport bot output
+            ]
+        )
 
         task = PipelineTask(pipeline)
 
diff --git a/examples/foundational/19a-tools-anthropic.py b/examples/foundational/19a-tools-anthropic.py
index 4cf42c2a2..05042c65b 100644
--- a/examples/foundational/19a-tools-anthropic.py
+++ b/examples/foundational/19a-tools-anthropic.py
@@ -23,6 +23,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -46,8 +47,8 @@ async def main():
                 audio_out_enabled=True,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
         tts = CartesiaTTSService(
@@ -56,8 +57,7 @@ async def main():
         )
 
         llm = AnthropicLLMService(
-            api_key=os.getenv("ANTHROPIC_API_KEY"),
-            model="claude-3-5-sonnet-20240620"
+            api_key=os.getenv("ANTHROPIC_API_KEY"), model="claude-3-5-sonnet-20240620"
         )
         llm.register_function("get_weather", get_weather)
 
@@ -90,18 +90,20 @@ async def main():
         context = OpenAILLMContext(messages, tools)
         context_aggregator = llm.create_context_aggregator(context)
 
-        pipeline = Pipeline([
-            transport.input(),               # Transport user input
-            context_aggregator.user(),       # User spoken responses
-            llm,                             # LLM
-            tts,                             # TTS
-            transport.output(),              # Transport bot output
-            context_aggregator.assistant(),  # Assistant spoken responses and tool context
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                context_aggregator.user(),  # User spoken responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                context_aggregator.assistant(),  # Assistant spoken responses and tool context
+            ]
+        )
 
         task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True, enable_metrics=True))
 
-        @ transport.event_handler("on_first_participant_joined")
+        @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
             transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
diff --git a/examples/foundational/19b-tools-video-anthropic.py b/examples/foundational/19b-tools-video-anthropic.py
index d9446d8e2..8a8110487 100644
--- a/examples/foundational/19b-tools-video-anthropic.py
+++ b/examples/foundational/19b-tools-video-anthropic.py
@@ -23,6 +23,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -55,8 +56,8 @@ async def main():
                 audio_out_enabled=True,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
         tts = CartesiaTTSService(
@@ -67,7 +68,7 @@ async def main():
         llm = AnthropicLLMService(
             api_key=os.getenv("ANTHROPIC_API_KEY"),
             model="claude-3-5-sonnet-20240620",
-            enable_prompt_caching_beta=True
+            enable_prompt_caching_beta=True,
         )
         llm.register_function("get_weather", get_weather)
         llm.register_function("get_image", get_image)
@@ -100,7 +101,7 @@ async def main():
                     },
                     "required": ["question"],
                 },
-            }
+            },
         ]
 
         # todo: test with very short initial user message
@@ -134,28 +135,28 @@ If you need to use a tool, simply use the tool. Do not tell the user the tool yo
                         "type": "text",
                         "text": system_prompt,
                     }
-                ]
+                ],
             },
-            {
-                "role": "user",
-                "content": "Start the conversation by introducing yourself."
-            }]
+            {"role": "user", "content": "Start the conversation by introducing yourself."},
+        ]
 
         context = OpenAILLMContext(messages, tools)
         context_aggregator = llm.create_context_aggregator(context)
 
-        pipeline = Pipeline([
-            transport.input(),               # Transport user input
-            context_aggregator.user(),       # User speech to text
-            llm,                             # LLM
-            tts,                             # TTS
-            transport.output(),              # Transport bot output
-            context_aggregator.assistant(),  # Assistant spoken responses and tool context
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                context_aggregator.user(),  # User speech to text
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                context_aggregator.assistant(),  # Assistant spoken responses and tool context
+            ]
+        )
 
         task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True, enable_metrics=True))
 
-        @ transport.event_handler("on_first_participant_joined")
+        @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
             global video_participant_id
             video_participant_id = participant["id"]
diff --git a/examples/foundational/19c-tools-togetherai.py b/examples/foundational/19c-tools-togetherai.py
index 329ecce68..f8e63ef75 100644
--- a/examples/foundational/19c-tools-togetherai.py
+++ b/examples/foundational/19c-tools-togetherai.py
@@ -25,6 +25,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -32,12 +33,8 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 async def get_current_weather(
-        function_name,
-        tool_call_id,
-        arguments,
-        llm,
-        context,
-        result_callback):
+    function_name, tool_call_id, arguments, llm, context, result_callback
+):
     logger.debug("IN get_current_weather")
     location = arguments["location"]
     await result_callback(f"The weather in {location} is currently 72 degrees and sunny.")
@@ -55,8 +52,8 @@ async def main():
                 audio_out_enabled=True,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
         tts = CartesiaTTSService(
@@ -104,26 +101,28 @@ Reminder:
 
 """
 
-        messages = [{"role": "system",
-                     "content": system_prompt},
-                    {"role": "user",
-                     "content": "Wait for the user to say something."}]
+        messages = [
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": "Wait for the user to say something."},
+        ]
 
         context = OpenAILLMContext(messages)
         context_aggregator = llm.create_context_aggregator(context)
 
-        pipeline = Pipeline([
-            transport.input(),               # Transport user input
-            context_aggregator.user(),       # User speech to text
-            llm,                             # LLM
-            tts,                             # TTS
-            transport.output(),              # Transport bot output
-            context_aggregator.assistant(),  # Assistant spoken responses and tool context
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                context_aggregator.user(),  # User speech to text
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                context_aggregator.assistant(),  # Assistant spoken responses and tool context
+            ]
+        )
 
         task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True, enable_metrics=True))
 
-        @ transport.event_handler("on_first_participant_joined")
+        @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
             transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
diff --git a/examples/foundational/runner.py b/examples/foundational/runner.py
index 068174eec..13c4ff076 100644
--- a/examples/foundational/runner.py
+++ b/examples/foundational/runner.py
@@ -17,16 +17,13 @@ async def configure(aiohttp_session: aiohttp.ClientSession):
 
 
 async def configure_with_args(
-        aiohttp_session: aiohttp.ClientSession,
-        parser: argparse.ArgumentParser | None = None):
+    aiohttp_session: aiohttp.ClientSession, parser: argparse.ArgumentParser | None = None
+):
     if not parser:
         parser = argparse.ArgumentParser(description="Daily AI SDK Bot Sample")
     parser.add_argument(
-        "-u",
-        "--url",
-        type=str,
-        required=False,
-        help="URL of the Daily room to join")
+        "-u", "--url", type=str, required=False, help="URL of the Daily room to join"
+    )
     parser.add_argument(
         "-k",
         "--apikey",
@@ -42,15 +39,19 @@ async def configure_with_args(
 
     if not url:
         raise Exception(
-            "No Daily room specified. use the -u/--url option from the command line, or set DAILY_SAMPLE_ROOM_URL in your environment to specify a Daily room URL.")
+            "No Daily room specified. use the -u/--url option from the command line, or set DAILY_SAMPLE_ROOM_URL in your environment to specify a Daily room URL."
+        )
 
     if not key:
-        raise Exception("No Daily API key specified. use the -k/--apikey option from the command line, or set DAILY_API_KEY in your environment to specify a Daily API key, available from https://dashboard.daily.co/developers.")
+        raise Exception(
+            "No Daily API key specified. use the -k/--apikey option from the command line, or set DAILY_API_KEY in your environment to specify a Daily API key, available from https://dashboard.daily.co/developers."
+        )
 
     daily_rest_helper = DailyRESTHelper(
         daily_api_key=key,
         daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
-        aiohttp_session=aiohttp_session)
+        aiohttp_session=aiohttp_session,
+    )
 
     # Create a meeting token for the given room with an expiration 1 hour in
     # the future.
diff --git a/examples/moondream-chatbot/bot.py b/examples/moondream-chatbot/bot.py
index d14a5f016..86456d40f 100644
--- a/examples/moondream-chatbot/bot.py
+++ b/examples/moondream-chatbot/bot.py
@@ -43,6 +43,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -60,11 +61,7 @@ for i in range(1, 26):
     # Get the filename without the extension to use as the dictionary key
     # Open the image and convert it to bytes
     with Image.open(full_path) as img:
-        sprites.append(OutputImageRawFrame(
-            image=img.tobytes(),
-            size=img.size,
-            format=img.format)
-        )
+        sprites.append(OutputImageRawFrame(image=img.tobytes(), size=img.size, format=img.format))
 
 flipped = sprites[::-1]
 sprites.extend(flipped)
@@ -110,7 +107,9 @@ class UserImageRequester(FrameProcessor):
 
         if self.participant_id and isinstance(frame, TextFrame):
             if frame.text == user_request_answer:
-                await self.push_frame(UserImageRequestFrame(self.participant_id), FrameDirection.UPSTREAM)
+                await self.push_frame(
+                    UserImageRequestFrame(self.participant_id), FrameDirection.UPSTREAM
+                )
                 await self.push_frame(TextFrame("Describe the image in a short sentence."))
         elif isinstance(frame, UserImageRawFrame):
             await self.push_frame(frame)
@@ -154,8 +153,8 @@ async def main():
                 camera_out_height=576,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
         tts = CartesiaTTSService(
@@ -163,9 +162,7 @@ async def main():
             voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
         )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
         ta = TalkingAnimation()
 
@@ -188,17 +185,17 @@ async def main():
 
         ura = LLMUserResponseAggregator(messages)
 
-        pipeline = Pipeline([
-            transport.input(),
-            ura,
-            llm,
-            ParallelPipeline(
-                [sa, ir, va, moondream],
-                [tf, imgf]),
-            tts,
-            ta,
-            transport.output()
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),
+                ura,
+                llm,
+                ParallelPipeline([sa, ir, va, moondream], [tf, imgf]),
+                tts,
+                ta,
+                transport.output(),
+            ]
+        )
 
         task = PipelineTask(pipeline)
         await task.queue_frame(quiet_frame)
diff --git a/examples/moondream-chatbot/runner.py b/examples/moondream-chatbot/runner.py
index 7507d28d6..3df3ee81f 100644
--- a/examples/moondream-chatbot/runner.py
+++ b/examples/moondream-chatbot/runner.py
@@ -14,11 +14,8 @@ from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper
 async def configure(aiohttp_session: aiohttp.ClientSession):
     parser = argparse.ArgumentParser(description="Daily AI SDK Bot Sample")
     parser.add_argument(
-        "-u",
-        "--url",
-        type=str,
-        required=False,
-        help="URL of the Daily room to join")
+        "-u", "--url", type=str, required=False, help="URL of the Daily room to join"
+    )
     parser.add_argument(
         "-k",
         "--apikey",
@@ -34,15 +31,18 @@ async def configure(aiohttp_session: aiohttp.ClientSession):
 
     if not url:
         raise Exception(
-            "No Daily room specified. use the -u/--url option from the command line, or set DAILY_SAMPLE_ROOM_URL in your environment to specify a Daily room URL.")
+            "No Daily room specified. use the -u/--url option from the command line, or set DAILY_SAMPLE_ROOM_URL in your environment to specify a Daily room URL."
+        )
 
     if not key:
-        raise Exception("No Daily API key specified. use the -k/--apikey option from the command line, or set DAILY_API_KEY in your environment to specify a Daily API key, available from https://dashboard.daily.co/developers.")
+        raise Exception(
+            "No Daily API key specified. use the -k/--apikey option from the command line, or set DAILY_API_KEY in your environment to specify a Daily API key, available from https://dashboard.daily.co/developers."
+        )
 
     daily_rest_helper = DailyRESTHelper(
         daily_api_key=key,
         daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
-        aiohttp_session=aiohttp_session
+        aiohttp_session=aiohttp_session,
     )
 
     # Create a meeting token for the given room with an expiration 1 hour in
diff --git a/examples/moondream-chatbot/server.py b/examples/moondream-chatbot/server.py
index d758e67f9..e3523851e 100644
--- a/examples/moondream-chatbot/server.py
+++ b/examples/moondream-chatbot/server.py
@@ -38,13 +38,14 @@ async def lifespan(app: FastAPI):
     aiohttp_session = aiohttp.ClientSession()
     daily_helpers["rest"] = DailyRESTHelper(
         daily_api_key=os.getenv("DAILY_API_KEY", ""),
-        daily_api_url=os.getenv("DAILY_API_URL", 'https://api.daily.co/v1'),
-        aiohttp_session=aiohttp_session
+        daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
+        aiohttp_session=aiohttp_session,
     )
     yield
     await aiohttp_session.close()
     cleanup()
 
+
 app = FastAPI(lifespan=lifespan)
 
 app.add_middleware(
@@ -65,37 +66,34 @@ async def start_agent(request: Request):
     if not room.url:
         raise HTTPException(
             status_code=500,
-            detail="Missing 'room' property in request data. Cannot start agent without a target room!")
+            detail="Missing 'room' property in request data. Cannot start agent without a target room!",
+        )
 
     # Check if there is already an existing process running in this room
     num_bots_in_room = sum(
-        1 for proc in bot_procs.values() if proc[1] == room.url and proc[0].poll() is None)
+        1 for proc in bot_procs.values() if proc[1] == room.url and proc[0].poll() is None
+    )
     if num_bots_in_room >= MAX_BOTS_PER_ROOM:
-        raise HTTPException(
-            status_code=500, detail=f"Max bot limited reach for room: {room.url}")
+        raise HTTPException(status_code=500, detail=f"Max bot limited reach for room: {room.url}")
 
     # Get the token for the room
     token = await daily_helpers["rest"].get_token(room.url)
 
     if not token:
-        raise HTTPException(
-            status_code=500, detail=f"Failed to get token for room: {room.url}")
+        raise HTTPException(status_code=500, detail=f"Failed to get token for room: {room.url}")
 
     # Spawn a new agent, and join the user session
     # Note: this is mostly for demonstration purposes (refer to 'deployment' in README)
     try:
         proc = subprocess.Popen(
-            [
-                f"python3 -m bot -u {room.url} -t {token}"
-            ],
+            [f"python3 -m bot -u {room.url} -t {token}"],
             shell=True,
             bufsize=1,
-            cwd=os.path.dirname(os.path.abspath(__file__))
+            cwd=os.path.dirname(os.path.abspath(__file__)),
         )
         bot_procs[proc.pid] = (proc, room.url)
     except Exception as e:
-        raise HTTPException(
-            status_code=500, detail=f"Failed to start subprocess: {e}")
+        raise HTTPException(status_code=500, detail=f"Failed to start subprocess: {e}")
 
     return RedirectResponse(room.url)
 
@@ -107,8 +105,7 @@ def get_status(pid: int):
 
     # If the subprocess doesn't exist, return an error
     if not proc:
-        raise HTTPException(
-            status_code=404, detail=f"Bot with process id: {pid} not found")
+        raise HTTPException(status_code=404, detail=f"Bot with process id: {pid} not found")
 
     # Check the status of the subprocess
     if proc[0].poll() is None:
@@ -125,14 +122,10 @@ if __name__ == "__main__":
     default_host = os.getenv("HOST", "0.0.0.0")
     default_port = int(os.getenv("FAST_API_PORT", "7860"))
 
-    parser = argparse.ArgumentParser(
-        description="Daily Moondream FastAPI server")
-    parser.add_argument("--host", type=str,
-                        default=default_host, help="Host address")
-    parser.add_argument("--port", type=int,
-                        default=default_port, help="Port number")
-    parser.add_argument("--reload", action="store_true",
-                        help="Reload code on change")
+    parser = argparse.ArgumentParser(description="Daily Moondream FastAPI server")
+    parser.add_argument("--host", type=str, default=default_host, help="Host address")
+    parser.add_argument("--port", type=int, default=default_port, help="Port number")
+    parser.add_argument("--reload", action="store_true", help="Reload code on change")
 
     config = parser.parse_args()
 
diff --git a/examples/patient-intake/bot.py b/examples/patient-intake/bot.py
index 33ca9e26d..52f45f75e 100644
--- a/examples/patient-intake/bot.py
+++ b/examples/patient-intake/bot.py
@@ -26,6 +26,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -49,41 +50,44 @@ for file in sound_files:
     filename = os.path.splitext(os.path.basename(full_path))[0]
     # Open the sound and convert it to bytes
     with wave.open(full_path) as audio_file:
-        sounds[file] = OutputAudioRawFrame(audio_file.readframes(-1),
-                                           audio_file.getframerate(),
-                                           audio_file.getnchannels())
+        sounds[file] = OutputAudioRawFrame(
+            audio_file.readframes(-1), audio_file.getframerate(), audio_file.getnchannels()
+        )
 
 
 class IntakeProcessor:
-
     def __init__(self, context: OpenAILLMContext):
         print(f"Initializing context from IntakeProcessor")
-        context.add_message({"role": "system", "content": "You are Jessica, an agent for a company called Tri-County Health Services. Your job is to collect important information from the user before their doctor visit. You're talking to Chad Bailey. You should address the user by their first name and be polite and professional. You're not a medical professional, so you shouldn't provide any advice. Keep your responses short. Your job is to collect information to give to a doctor. Don't make assumptions about what values to plug into functions. Ask for clarification if a user response is ambiguous. Start by introducing yourself. Then, ask the user to confirm their identity by telling you their birthday, including the year. When they answer with their birthday, call the verify_birthday function."})
-        context.set_tools([
+        context.add_message(
             {
-                "type": "function",
-                "function": {
-                    "name": "verify_birthday",
-                    "description": "Use this function to verify the user has provided their correct birthday.",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "birthday": {
-                                "type": "string",
-                                "description": "The user's birthdate, including the year. The user can provide it in any format, but convert it to YYYY-MM-DD format to call this function.",
-                            }},
+                "role": "system",
+                "content": "You are Jessica, an agent for a company called Tri-County Health Services. Your job is to collect important information from the user before their doctor visit. You're talking to Chad Bailey. You should address the user by their first name and be polite and professional. You're not a medical professional, so you shouldn't provide any advice. Keep your responses short. Your job is to collect information to give to a doctor. Don't make assumptions about what values to plug into functions. Ask for clarification if a user response is ambiguous. Start by introducing yourself. Then, ask the user to confirm their identity by telling you their birthday, including the year. When they answer with their birthday, call the verify_birthday function.",
+            }
+        )
+        context.set_tools(
+            [
+                {
+                    "type": "function",
+                    "function": {
+                        "name": "verify_birthday",
+                        "description": "Use this function to verify the user has provided their correct birthday.",
+                        "parameters": {
+                            "type": "object",
+                            "properties": {
+                                "birthday": {
+                                    "type": "string",
+                                    "description": "The user's birthdate, including the year. The user can provide it in any format, but convert it to YYYY-MM-DD format to call this function.",
+                                }
+                            },
+                        },
                     },
-                },
-            }])
+                }
+            ]
+        )
 
     async def verify_birthday(
-            self,
-            function_name,
-            tool_call_id,
-            args,
-            llm,
-            context,
-            result_callback):
+        self, function_name, tool_call_id, args, llm, context, result_callback
+    ):
         if args["birthday"] == "1983-01-01":
             context.set_tools(
                 [
@@ -110,18 +114,35 @@ class IntakeProcessor:
                                                 },
                                             },
                                         },
-                                    }},
+                                    }
+                                },
                             },
                         },
-                    }])
+                    }
+                ]
+            )
             # It's a bit weird to push this to the LLM, but it gets it into the pipeline
             # await llm.push_frame(sounds["ding2.wav"], FrameDirection.DOWNSTREAM)
             # We don't need the function call in the context, so just return a new
             # system message and let the framework re-prompt
-            await result_callback([{"role": "system", "content": "Next, thank the user for confirming their identity, then ask the user to list their current prescriptions. Each prescription needs to have a medication name and a dosage. Do not call the list_prescriptions function with any unknown dosages."}])
+            await result_callback(
+                [
+                    {
+                        "role": "system",
+                        "content": "Next, thank the user for confirming their identity, then ask the user to list their current prescriptions. Each prescription needs to have a medication name and a dosage. Do not call the list_prescriptions function with any unknown dosages.",
+                    }
+                ]
+            )
         else:
             # The user provided an incorrect birthday; ask them to try again
-            await result_callback([{"role": "system", "content": "The user provided an incorrect birthday. Ask them for their birthday again. When they answer, call the verify_birthday function."}])
+            await result_callback(
+                [
+                    {
+                        "role": "system",
+                        "content": "The user provided an incorrect birthday. Ask them for their birthday again. When they answer, call the verify_birthday function.",
+                    }
+                ]
+            )
 
     async def start_prescriptions(self, function_name, llm, context):
         print(f"!!! doing start prescriptions")
@@ -144,16 +165,22 @@ class IntakeProcessor:
                                             "name": {
                                                 "type": "string",
                                                 "description": "What the user is allergic to",
-                                            }},
+                                            }
+                                        },
                                     },
-                                }},
+                                }
+                            },
                         },
                     },
-                }])
+                }
+            ]
+        )
         context.add_message(
             {
                 "role": "system",
-                "content": "Next, ask the user if they have any allergies. Once they have listed their allergies or confirmed they don't have any, call the list_allergies function."})
+                "content": "Next, ask the user if they have any allergies. Once they have listed their allergies or confirmed they don't have any, call the list_allergies function.",
+            }
+        )
         print(f"!!! about to await llm process frame in start prescrpitions")
         await llm.process_frame(OpenAILLMContextFrame(context), FrameDirection.DOWNSTREAM)
         print(f"!!! past await process frame in start prescriptions")
@@ -179,17 +206,22 @@ class IntakeProcessor:
                                             "name": {
                                                 "type": "string",
                                                 "description": "The user's medical condition",
-                                            }},
+                                            }
+                                        },
                                     },
-                                }},
+                                }
+                            },
                         },
                     },
                 },
-            ])
+            ]
+        )
         context.add_message(
             {
                 "role": "system",
-                "content": "Now ask the user if they have any medical conditions the doctor should know about. Once they've answered the question, call the list_conditions function."})
+                "content": "Now ask the user if they have any medical conditions the doctor should know about. Once they've answered the question, call the list_conditions function.",
+            }
+        )
         await llm.process_frame(OpenAILLMContextFrame(context), FrameDirection.DOWNSTREAM)
 
     async def start_conditions(self, function_name, llm, context):
@@ -213,24 +245,31 @@ class IntakeProcessor:
                                             "name": {
                                                 "type": "string",
                                                 "description": "The user's reason for visiting the doctor",
-                                            }},
+                                            }
+                                        },
                                     },
-                                }},
+                                }
+                            },
                         },
                     },
-                }])
+                }
+            ]
+        )
         context.add_message(
             {
                 "role": "system",
-                "content": "Finally, ask the user the reason for their doctor visit today. Once they answer, call the list_visit_reasons function."})
+                "content": "Finally, ask the user the reason for their doctor visit today. Once they answer, call the list_visit_reasons function.",
+            }
+        )
         await llm.process_frame(OpenAILLMContextFrame(context), FrameDirection.DOWNSTREAM)
 
     async def start_visit_reasons(self, function_name, llm, context):
         print("!!! doing start visit reasons")
         # move to finish call
         context.set_tools([])
-        context.add_message({"role": "system",
-                             "content": "Now, thank the user and end the conversation."})
+        context.add_message(
+            {"role": "system", "content": "Now, thank the user and end the conversation."}
+        )
         await llm.process_frame(OpenAILLMContextFrame(context), FrameDirection.DOWNSTREAM)
 
     async def save_data(self, function_name, tool_call_id, args, llm, context, result_callback):
@@ -261,7 +300,7 @@ async def main():
                 #     tier="nova",
                 #     model="2-general"
                 # )
-            )
+            ),
         )
 
         tts = CartesiaTTSService(
@@ -274,9 +313,7 @@ async def main():
         #     voice_id="846d6cb0-2301-48b6-9683-48f5618ea2f6",  # Spanish-speaking Lady
         # )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
         messages = []
         context = OpenAILLMContext(messages=messages)
@@ -285,33 +322,31 @@ async def main():
         intake = IntakeProcessor(context)
         llm.register_function("verify_birthday", intake.verify_birthday)
         llm.register_function(
-            "list_prescriptions",
-            intake.save_data,
-            start_callback=intake.start_prescriptions)
+            "list_prescriptions", intake.save_data, start_callback=intake.start_prescriptions
+        )
         llm.register_function(
-            "list_allergies",
-            intake.save_data,
-            start_callback=intake.start_allergies)
+            "list_allergies", intake.save_data, start_callback=intake.start_allergies
+        )
         llm.register_function(
-            "list_conditions",
-            intake.save_data,
-            start_callback=intake.start_conditions)
+            "list_conditions", intake.save_data, start_callback=intake.start_conditions
+        )
         llm.register_function(
-            "list_visit_reasons",
-            intake.save_data,
-            start_callback=intake.start_visit_reasons)
+            "list_visit_reasons", intake.save_data, start_callback=intake.start_visit_reasons
+        )
 
         fl = FrameLogger("LLM Output")
 
-        pipeline = Pipeline([
-            transport.input(),   # Transport input
-            context_aggregator.user(),  # User responses
-            llm,                 # LLM
-            fl,                  # Frame logger
-            tts,                 # TTS
-            transport.output(),  # Transport output
-            context_aggregator.assistant(),  # Assistant responses
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport input
+                context_aggregator.user(),  # User responses
+                llm,  # LLM
+                fl,  # Frame logger
+                tts,  # TTS
+                transport.output(),  # Transport output
+                context_aggregator.assistant(),  # Assistant responses
+            ]
+        )
 
         task = PipelineTask(pipeline, PipelineParams(allow_interruptions=False))
 
diff --git a/examples/patient-intake/runner.py b/examples/patient-intake/runner.py
index 7242c4f27..3df3ee81f 100644
--- a/examples/patient-intake/runner.py
+++ b/examples/patient-intake/runner.py
@@ -14,11 +14,8 @@ from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper
 async def configure(aiohttp_session: aiohttp.ClientSession):
     parser = argparse.ArgumentParser(description="Daily AI SDK Bot Sample")
     parser.add_argument(
-        "-u",
-        "--url",
-        type=str,
-        required=False,
-        help="URL of the Daily room to join")
+        "-u", "--url", type=str, required=False, help="URL of the Daily room to join"
+    )
     parser.add_argument(
         "-k",
         "--apikey",
@@ -34,15 +31,19 @@ async def configure(aiohttp_session: aiohttp.ClientSession):
 
     if not url:
         raise Exception(
-            "No Daily room specified. use the -u/--url option from the command line, or set DAILY_SAMPLE_ROOM_URL in your environment to specify a Daily room URL.")
+            "No Daily room specified. use the -u/--url option from the command line, or set DAILY_SAMPLE_ROOM_URL in your environment to specify a Daily room URL."
+        )
 
     if not key:
-        raise Exception("No Daily API key specified. use the -k/--apikey option from the command line, or set DAILY_API_KEY in your environment to specify a Daily API key, available from https://dashboard.daily.co/developers.")
+        raise Exception(
+            "No Daily API key specified. use the -k/--apikey option from the command line, or set DAILY_API_KEY in your environment to specify a Daily API key, available from https://dashboard.daily.co/developers."
+        )
 
     daily_rest_helper = DailyRESTHelper(
         daily_api_key=key,
         daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
-        aiohttp_session=aiohttp_session)
+        aiohttp_session=aiohttp_session,
+    )
 
     # Create a meeting token for the given room with an expiration 1 hour in
     # the future.
diff --git a/examples/patient-intake/server.py b/examples/patient-intake/server.py
index 639587894..c0fc9c97f 100644
--- a/examples/patient-intake/server.py
+++ b/examples/patient-intake/server.py
@@ -38,13 +38,14 @@ async def lifespan(app: FastAPI):
     aiohttp_session = aiohttp.ClientSession()
     daily_helpers["rest"] = DailyRESTHelper(
         daily_api_key=os.getenv("DAILY_API_KEY", ""),
-        daily_api_url=os.getenv("DAILY_API_URL", 'https://api.daily.co/v1'),
-        aiohttp_session=aiohttp_session
+        daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
+        aiohttp_session=aiohttp_session,
     )
     yield
     await aiohttp_session.close()
     cleanup()
 
+
 app = FastAPI(lifespan=lifespan)
 
 app.add_middleware(
@@ -65,37 +66,34 @@ async def start_agent(request: Request):
     if not room.url:
         raise HTTPException(
             status_code=500,
-            detail="Missing 'room' property in request data. Cannot start agent without a target room!")
+            detail="Missing 'room' property in request data. Cannot start agent without a target room!",
+        )
 
     # Check if there is already an existing process running in this room
     num_bots_in_room = sum(
-        1 for proc in bot_procs.values() if proc[1] == room.url and proc[0].poll() is None)
+        1 for proc in bot_procs.values() if proc[1] == room.url and proc[0].poll() is None
+    )
     if num_bots_in_room >= MAX_BOTS_PER_ROOM:
-        raise HTTPException(
-            status_code=500, detail=f"Max bot limited reach for room: {room.url}")
+        raise HTTPException(status_code=500, detail=f"Max bot limited reach for room: {room.url}")
 
     # Get the token for the room
     token = await daily_helpers["rest"].get_token(room.url)
 
     if not token:
-        raise HTTPException(
-            status_code=500, detail=f"Failed to get token for room: {room.url}")
+        raise HTTPException(status_code=500, detail=f"Failed to get token for room: {room.url}")
 
     # Spawn a new agent, and join the user session
     # Note: this is mostly for demonstration purposes (refer to 'deployment' in README)
     try:
         proc = subprocess.Popen(
-            [
-                f"python3 -m bot -u {room.url} -t {token}"
-            ],
+            [f"python3 -m bot -u {room.url} -t {token}"],
             shell=True,
             bufsize=1,
-            cwd=os.path.dirname(os.path.abspath(__file__))
+            cwd=os.path.dirname(os.path.abspath(__file__)),
         )
         bot_procs[proc.pid] = (proc, room.url)
     except Exception as e:
-        raise HTTPException(
-            status_code=500, detail=f"Failed to start subprocess: {e}")
+        raise HTTPException(status_code=500, detail=f"Failed to start subprocess: {e}")
 
     return RedirectResponse(room.url)
 
@@ -107,8 +105,7 @@ def get_status(pid: int):
 
     # If the subprocess doesn't exist, return an error
     if not proc:
-        raise HTTPException(
-            status_code=404, detail=f"Bot with process id: {pid} not found")
+        raise HTTPException(status_code=404, detail=f"Bot with process id: {pid} not found")
 
     # Check the status of the subprocess
     if proc[0].poll() is None:
@@ -125,14 +122,10 @@ if __name__ == "__main__":
     default_host = os.getenv("HOST", "0.0.0.0")
     default_port = int(os.getenv("FAST_API_PORT", "7860"))
 
-    parser = argparse.ArgumentParser(
-        description="Daily Storyteller FastAPI server")
-    parser.add_argument("--host", type=str,
-                        default=default_host, help="Host address")
-    parser.add_argument("--port", type=int,
-                        default=default_port, help="Port number")
-    parser.add_argument("--reload", action="store_true",
-                        help="Reload code on change")
+    parser = argparse.ArgumentParser(description="Daily Storyteller FastAPI server")
+    parser.add_argument("--host", type=str, default=default_host, help="Host address")
+    parser.add_argument("--port", type=int, default=default_port, help="Port number")
+    parser.add_argument("--reload", action="store_true", help="Reload code on change")
 
     config = parser.parse_args()
     print(f"to join a test room, visit http://localhost:{config.port}/start")
diff --git a/examples/simple-chatbot/bot.py b/examples/simple-chatbot/bot.py
index f179dfeb5..b06721d4c 100644
--- a/examples/simple-chatbot/bot.py
+++ b/examples/simple-chatbot/bot.py
@@ -14,14 +14,17 @@ from PIL import Image
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_response import LLMAssistantResponseAggregator, LLMUserResponseAggregator
+from pipecat.processors.aggregators.llm_response import (
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
+)
 from pipecat.frames.frames import (
     OutputImageRawFrame,
     SpriteFrame,
     Frame,
     LLMMessagesFrame,
     TTSAudioRawFrame,
-    TTSStoppedFrame
+    TTSStoppedFrame,
 )
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.services.elevenlabs import ElevenLabsTTSService
@@ -34,6 +37,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -49,11 +53,7 @@ for i in range(1, 26):
     # Get the filename without the extension to use as the dictionary key
     # Open the image and convert it to bytes
     with Image.open(full_path) as img:
-        sprites.append(OutputImageRawFrame(
-            image=img.tobytes(),
-            size=img.size,
-            format=img.format)
-        )
+        sprites.append(OutputImageRawFrame(image=img.tobytes(), size=img.size, format=img.format))
 
 flipped = sprites[::-1]
 sprites.extend(flipped)
@@ -111,7 +111,7 @@ async def main():
                 #     tier="nova",
                 #     model="2-general"
                 # )
-            )
+            ),
         )
 
         tts = ElevenLabsTTSService(
@@ -120,7 +120,6 @@ async def main():
             # English
             #
             voice_id="pNInz6obpgDQGcFmaJgB",
-
             #
             # Spanish
             #
@@ -128,9 +127,7 @@ async def main():
             # voice_id="gD1IexrzCvsXPHUuT0s3",
         )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o")
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
         messages = [
             {
@@ -139,7 +136,6 @@ async def main():
                 # English
                 #
                 "content": "You are Chatbot, a friendly, helpful robot. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way, but keep your responses brief. Start by introducing yourself.",
-
                 #
                 # Spanish
                 #
@@ -152,15 +148,17 @@ async def main():
 
         ta = TalkingAnimation()
 
-        pipeline = Pipeline([
-            transport.input(),
-            user_response,
-            llm,
-            tts,
-            ta,
-            transport.output(),
-            assistant_response,
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),
+                user_response,
+                llm,
+                tts,
+                ta,
+                transport.output(),
+                assistant_response,
+            ]
+        )
 
         task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
         await task.queue_frame(quiet_frame)
diff --git a/examples/simple-chatbot/runner.py b/examples/simple-chatbot/runner.py
index 7507d28d6..3df3ee81f 100644
--- a/examples/simple-chatbot/runner.py
+++ b/examples/simple-chatbot/runner.py
@@ -14,11 +14,8 @@ from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper
 async def configure(aiohttp_session: aiohttp.ClientSession):
     parser = argparse.ArgumentParser(description="Daily AI SDK Bot Sample")
     parser.add_argument(
-        "-u",
-        "--url",
-        type=str,
-        required=False,
-        help="URL of the Daily room to join")
+        "-u", "--url", type=str, required=False, help="URL of the Daily room to join"
+    )
     parser.add_argument(
         "-k",
         "--apikey",
@@ -34,15 +31,18 @@ async def configure(aiohttp_session: aiohttp.ClientSession):
 
     if not url:
         raise Exception(
-            "No Daily room specified. use the -u/--url option from the command line, or set DAILY_SAMPLE_ROOM_URL in your environment to specify a Daily room URL.")
+            "No Daily room specified. use the -u/--url option from the command line, or set DAILY_SAMPLE_ROOM_URL in your environment to specify a Daily room URL."
+        )
 
     if not key:
-        raise Exception("No Daily API key specified. use the -k/--apikey option from the command line, or set DAILY_API_KEY in your environment to specify a Daily API key, available from https://dashboard.daily.co/developers.")
+        raise Exception(
+            "No Daily API key specified. use the -k/--apikey option from the command line, or set DAILY_API_KEY in your environment to specify a Daily API key, available from https://dashboard.daily.co/developers."
+        )
 
     daily_rest_helper = DailyRESTHelper(
         daily_api_key=key,
         daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
-        aiohttp_session=aiohttp_session
+        aiohttp_session=aiohttp_session,
     )
 
     # Create a meeting token for the given room with an expiration 1 hour in
diff --git a/examples/simple-chatbot/server.py b/examples/simple-chatbot/server.py
index d54452d10..5240c254f 100644
--- a/examples/simple-chatbot/server.py
+++ b/examples/simple-chatbot/server.py
@@ -38,13 +38,14 @@ async def lifespan(app: FastAPI):
     aiohttp_session = aiohttp.ClientSession()
     daily_helpers["rest"] = DailyRESTHelper(
         daily_api_key=os.getenv("DAILY_API_KEY", ""),
-        daily_api_url=os.getenv("DAILY_API_URL", 'https://api.daily.co/v1'),
-        aiohttp_session=aiohttp_session
+        daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
+        aiohttp_session=aiohttp_session,
     )
     yield
     await aiohttp_session.close()
     cleanup()
 
+
 app = FastAPI(lifespan=lifespan)
 
 app.add_middleware(
@@ -65,37 +66,34 @@ async def start_agent(request: Request):
     if not room.url:
         raise HTTPException(
             status_code=500,
-            detail="Missing 'room' property in request data. Cannot start agent without a target room!")
+            detail="Missing 'room' property in request data. Cannot start agent without a target room!",
+        )
 
     # Check if there is already an existing process running in this room
     num_bots_in_room = sum(
-        1 for proc in bot_procs.values() if proc[1] == room.url and proc[0].poll() is None)
+        1 for proc in bot_procs.values() if proc[1] == room.url and proc[0].poll() is None
+    )
     if num_bots_in_room >= MAX_BOTS_PER_ROOM:
-        raise HTTPException(
-            status_code=500, detail=f"Max bot limited reach for room: {room.url}")
+        raise HTTPException(status_code=500, detail=f"Max bot limited reach for room: {room.url}")
 
     # Get the token for the room
     token = await daily_helpers["rest"].get_token(room.url)
 
     if not token:
-        raise HTTPException(
-            status_code=500, detail=f"Failed to get token for room: {room.url}")
+        raise HTTPException(status_code=500, detail=f"Failed to get token for room: {room.url}")
 
     # Spawn a new agent, and join the user session
     # Note: this is mostly for demonstration purposes (refer to 'deployment' in README)
     try:
         proc = subprocess.Popen(
-            [
-                f"python3 -m bot -u {room.url} -t {token}"
-            ],
+            [f"python3 -m bot -u {room.url} -t {token}"],
             shell=True,
             bufsize=1,
-            cwd=os.path.dirname(os.path.abspath(__file__))
+            cwd=os.path.dirname(os.path.abspath(__file__)),
         )
         bot_procs[proc.pid] = (proc, room.url)
     except Exception as e:
-        raise HTTPException(
-            status_code=500, detail=f"Failed to start subprocess: {e}")
+        raise HTTPException(status_code=500, detail=f"Failed to start subprocess: {e}")
 
     return RedirectResponse(room.url)
 
@@ -107,8 +105,7 @@ def get_status(pid: int):
 
     # If the subprocess doesn't exist, return an error
     if not proc:
-        raise HTTPException(
-            status_code=404, detail=f"Bot with process id: {pid} not found")
+        raise HTTPException(status_code=404, detail=f"Bot with process id: {pid} not found")
 
     # Check the status of the subprocess
     if proc[0].poll() is None:
@@ -125,14 +122,10 @@ if __name__ == "__main__":
     default_host = os.getenv("HOST", "0.0.0.0")
     default_port = int(os.getenv("FAST_API_PORT", "7860"))
 
-    parser = argparse.ArgumentParser(
-        description="Daily Storyteller FastAPI server")
-    parser.add_argument("--host", type=str,
-                        default=default_host, help="Host address")
-    parser.add_argument("--port", type=int,
-                        default=default_port, help="Port number")
-    parser.add_argument("--reload", action="store_true",
-                        help="Reload code on change")
+    parser = argparse.ArgumentParser(description="Daily Storyteller FastAPI server")
+    parser.add_argument("--host", type=str, default=default_host, help="Host address")
+    parser.add_argument("--port", type=int, default=default_port, help="Port number")
+    parser.add_argument("--reload", action="store_true", help="Reload code on change")
 
     config = parser.parse_args()
 
diff --git a/examples/storytelling-chatbot/src/bot.py b/examples/storytelling-chatbot/src/bot.py
index 91452dd75..e67af8d7d 100644
--- a/examples/storytelling-chatbot/src/bot.py
+++ b/examples/storytelling-chatbot/src/bot.py
@@ -9,11 +9,18 @@ from pipecat.frames.frames import LLMMessagesFrame, StopTaskFrame, EndFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
-from pipecat.processors.aggregators.llm_response import LLMAssistantResponseAggregator, LLMUserResponseAggregator
+from pipecat.processors.aggregators.llm_response import (
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
+)
 from pipecat.services.elevenlabs import ElevenLabsTTSService
 from pipecat.services.fal import FalImageGenService
 from pipecat.services.openai import OpenAILLMService
-from pipecat.transports.services.daily import DailyParams, DailyTransport, DailyTransportMessageFrame
+from pipecat.transports.services.daily import (
+    DailyParams,
+    DailyTransport,
+    DailyTransportMessageFrame,
+)
 
 from processors import StoryProcessor, StoryImageProcessor
 from prompts import LLM_BASE_PROMPT, LLM_INTRO_PROMPT, CUE_USER_TURN
@@ -22,6 +29,7 @@ from utils.helpers import load_sounds, load_images
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -33,7 +41,6 @@ images = load_images(["book1.png", "book2.png"])
 
 async def main(room_url, token=None):
     async with aiohttp.ClientSession() as session:
-
         # -------------- Transport --------------- #
 
         transport = DailyTransport(
@@ -47,17 +54,14 @@ async def main(room_url, token=None):
                 camera_out_height=768,
                 transcription_enabled=True,
                 vad_enabled=True,
-            )
+            ),
         )
 
         logger.debug("Transport created for room:" + room_url)
 
         # -------------- Services --------------- #
 
-        llm_service = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o"
-        )
+        llm_service = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
         tts_service = ElevenLabsTTSService(
             api_key=os.getenv("ELEVENLABS_API_KEY"),
@@ -65,10 +69,7 @@ async def main(room_url, token=None):
         )
 
         fal_service_params = FalImageGenService.InputParams(
-            image_size={
-                "width": 768,
-                "height": 768
-            }
+            image_size={"width": 768, "height": 768}
         )
 
         fal_service = FalImageGenService(
@@ -110,12 +111,12 @@ async def main(room_url, token=None):
             transport.capture_participant_transcription(participant["id"])
             await intro_task.queue_frames(
                 [
-                    images['book1'],
+                    images["book1"],
                     LLMMessagesFrame([LLM_INTRO_PROMPT]),
                     DailyTransportMessageFrame(CUE_USER_TURN),
                     sounds["listening"],
-                    images['book2'],
-                    StopTaskFrame()
+                    images["book2"],
+                    StopTaskFrame(),
                 ]
             )
 
@@ -125,16 +126,18 @@ async def main(room_url, token=None):
 
         # The main story pipeline is used to continue the story based on user
         # input.
-        main_pipeline = Pipeline([
-            transport.input(),
-            user_responses,
-            llm_service,
-            story_processor,
-            image_processor,
-            tts_service,
-            transport.output(),
-            llm_responses
-        ])
+        main_pipeline = Pipeline(
+            [
+                transport.input(),
+                user_responses,
+                llm_service,
+                story_processor,
+                image_processor,
+                tts_service,
+                transport.output(),
+                llm_responses,
+            ]
+        )
 
         main_task = PipelineTask(main_pipeline)
 
@@ -150,6 +153,7 @@ async def main(room_url, token=None):
 
         await runner.run(main_task)
 
+
 if __name__ == "__main__":
     parser = argparse.ArgumentParser(description="Daily Storyteller Bot")
     parser.add_argument("-u", type=str, help="Room URL")
diff --git a/examples/storytelling-chatbot/src/bot_runner.py b/examples/storytelling-chatbot/src/bot_runner.py
index 97e933c25..13ce49834 100644
--- a/examples/storytelling-chatbot/src/bot_runner.py
+++ b/examples/storytelling-chatbot/src/bot_runner.py
@@ -20,10 +20,15 @@ from fastapi.staticfiles import StaticFiles
 from fastapi.responses import FileResponse, JSONResponse
 
 from pipecat.transports.services.helpers.daily_rest import (
-    DailyRESTHelper, DailyRoomObject, DailyRoomProperties, DailyRoomParams)
+    DailyRESTHelper,
+    DailyRoomObject,
+    DailyRoomProperties,
+    DailyRoomParams,
+)
 
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 # ------------ Fast API Config ------------ #
@@ -38,12 +43,13 @@ async def lifespan(app: FastAPI):
     aiohttp_session = aiohttp.ClientSession()
     daily_helpers["rest"] = DailyRESTHelper(
         daily_api_key=os.getenv("DAILY_API_KEY", ""),
-        daily_api_url=os.getenv("DAILY_API_URL", 'https://api.daily.co/v1'),
-        aiohttp_session=aiohttp_session
+        daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
+        aiohttp_session=aiohttp_session,
     )
     yield
     await aiohttp_session.close()
 
+
 app = FastAPI(lifespan=lifespan)
 
 app.add_middleware(
@@ -85,55 +91,50 @@ async def start_bot(request: Request) -> JSONResponse:
     room_url = os.getenv("DAILY_SAMPLE_ROOM_URL", "")
 
     if not room_url:
-        params = DailyRoomParams(
-            properties=DailyRoomProperties()
-        )
+        params = DailyRoomParams(properties=DailyRoomProperties())
         try:
             room: DailyRoomObject = await daily_helpers["rest"].create_room(params=params)
         except Exception as e:
-            raise HTTPException(
-                status_code=500,
-                detail=f"Unable to provision room {e}")
+            raise HTTPException(status_code=500, detail=f"Unable to provision room {e}")
     else:
         # Check passed room URL exists, we should assume that it already has a sip set up
         try:
             room: DailyRoomObject = await daily_helpers["rest"].get_room_from_url(room_url)
         except Exception:
-            raise HTTPException(
-                status_code=500, detail=f"Room not found: {room_url}")
+            raise HTTPException(status_code=500, detail=f"Room not found: {room_url}")
 
     # Give the agent a token to join the session
     token = await daily_helpers["rest"].get_token(room.url, MAX_SESSION_TIME)
 
     if not room or not token:
-        raise HTTPException(
-            status_code=500, detail=f"Failed to get token for room: {room_url}")
+        raise HTTPException(status_code=500, detail=f"Failed to get token for room: {room_url}")
 
     # Launch a new VM, or run as a shell process (not recommended)
     if os.getenv("RUN_AS_VM", False):
         try:
             await virtualize_bot(room.url, token)
         except Exception as e:
-            raise HTTPException(
-                status_code=500, detail=f"Failed to spawn VM: {e}")
+            raise HTTPException(status_code=500, detail=f"Failed to spawn VM: {e}")
     else:
         try:
             subprocess.Popen(
                 [f"python3 -m bot -u {room.url} -t {token}"],
                 shell=True,
                 bufsize=1,
-                cwd=os.path.dirname(os.path.abspath(__file__)))
+                cwd=os.path.dirname(os.path.abspath(__file__)),
+            )
         except Exception as e:
-            raise HTTPException(
-                status_code=500, detail=f"Failed to start subprocess: {e}")
+            raise HTTPException(status_code=500, detail=f"Failed to start subprocess: {e}")
 
     # Grab a token for the user to join with
     user_token = await daily_helpers["rest"].get_token(room.url, MAX_SESSION_TIME)
 
-    return JSONResponse({
-        "room_url": room.url,
-        "token": user_token,
-    })
+    return JSONResponse(
+        {
+            "room_url": room.url,
+            "token": user_token,
+        }
+    )
 
 
 @app.get("/{path_name:path}", response_class=FileResponse)
@@ -155,6 +156,7 @@ async def catch_all(path_name: Optional[str] = ""):
 
 # ------------ Virtualization ------------ #
 
+
 async def virtualize_bot(room_url: str, token: str):
     """
     This is an example of how to virtualize the bot using Fly.io
@@ -163,20 +165,19 @@ async def virtualize_bot(room_url: str, token: str):
     FLY_API_HOST = os.getenv("FLY_API_HOST", "https://api.machines.dev/v1")
     FLY_APP_NAME = os.getenv("FLY_APP_NAME", "storytelling-chatbot")
     FLY_API_KEY = os.getenv("FLY_API_KEY", "")
-    FLY_HEADERS = {
-        'Authorization': f"Bearer {FLY_API_KEY}",
-        'Content-Type': 'application/json'
-    }
+    FLY_HEADERS = {"Authorization": f"Bearer {FLY_API_KEY}", "Content-Type": "application/json"}
 
     async with aiohttp.ClientSession() as session:
         # Use the same image as the bot runner
-        async with session.get(f"{FLY_API_HOST}/apps/{FLY_APP_NAME}/machines", headers=FLY_HEADERS) as r:
+        async with session.get(
+            f"{FLY_API_HOST}/apps/{FLY_APP_NAME}/machines", headers=FLY_HEADERS
+        ) as r:
             if r.status != 200:
                 text = await r.text()
                 raise Exception(f"Unable to get machine info from Fly: {text}")
 
             data = await r.json()
-            image = data[0]['config']['image']
+            image = data[0]["config"]["image"]
 
         # Machine configuration
         cmd = f"python3 src/bot.py -u {room_url} -t {token}"
@@ -185,31 +186,28 @@ async def virtualize_bot(room_url: str, token: str):
             "config": {
                 "image": image,
                 "auto_destroy": True,
-                "init": {
-                    "cmd": cmd
-                },
-                "restart": {
-                    "policy": "no"
-                },
-                "guest": {
-                    "cpu_kind": "shared",
-                    "cpus": 1,
-                    "memory_mb": 512
-                }
+                "init": {"cmd": cmd},
+                "restart": {"policy": "no"},
+                "guest": {"cpu_kind": "shared", "cpus": 1, "memory_mb": 512},
             },
         }
 
         # Spawn a new machine instance
-        async with session.post(f"{FLY_API_HOST}/apps/{FLY_APP_NAME}/machines", headers=FLY_HEADERS, json=worker_props) as r:
+        async with session.post(
+            f"{FLY_API_HOST}/apps/{FLY_APP_NAME}/machines", headers=FLY_HEADERS, json=worker_props
+        ) as r:
             if r.status != 200:
                 text = await r.text()
                 raise Exception(f"Problem starting a bot worker: {text}")
 
             data = await r.json()
             # Wait for the machine to enter the started state
-            vm_id = data['id']
+            vm_id = data["id"]
 
-        async with session.get(f"{FLY_API_HOST}/apps/{FLY_APP_NAME}/machines/{vm_id}/wait?state=started", headers=FLY_HEADERS) as r:
+        async with session.get(
+            f"{FLY_API_HOST}/apps/{FLY_APP_NAME}/machines/{vm_id}/wait?state=started",
+            headers=FLY_HEADERS,
+        ) as r:
             if r.status != 200:
                 text = await r.text()
                 raise Exception(f"Bot was unable to enter started state: {text}")
@@ -221,8 +219,13 @@ async def virtualize_bot(room_url: str, token: str):
 
 if __name__ == "__main__":
     # Check environment variables
-    required_env_vars = ['OPENAI_API_KEY', 'DAILY_API_KEY',
-                         'FAL_KEY', 'ELEVENLABS_VOICE_ID', 'ELEVENLABS_API_KEY']
+    required_env_vars = [
+        "OPENAI_API_KEY",
+        "DAILY_API_KEY",
+        "FAL_KEY",
+        "ELEVENLABS_VOICE_ID",
+        "ELEVENLABS_API_KEY",
+    ]
     for env_var in required_env_vars:
         if env_var not in os.environ:
             raise Exception(f"Missing environment variable: {env_var}.")
@@ -232,20 +235,11 @@ if __name__ == "__main__":
     default_host = os.getenv("HOST", "0.0.0.0")
     default_port = int(os.getenv("FAST_API_PORT", "7860"))
 
-    parser = argparse.ArgumentParser(
-        description="Daily Storyteller FastAPI server")
-    parser.add_argument("--host", type=str,
-                        default=default_host, help="Host address")
-    parser.add_argument("--port", type=int,
-                        default=default_port, help="Port number")
-    parser.add_argument("--reload", action="store_true",
-                        help="Reload code on change")
+    parser = argparse.ArgumentParser(description="Daily Storyteller FastAPI server")
+    parser.add_argument("--host", type=str, default=default_host, help="Host address")
+    parser.add_argument("--port", type=int, default=default_port, help="Port number")
+    parser.add_argument("--reload", action="store_true", help="Reload code on change")
 
     config = parser.parse_args()
 
-    uvicorn.run(
-        "bot_runner:app",
-        host=config.host,
-        port=config.port,
-        reload=config.reload
-    )
+    uvicorn.run("bot_runner:app", host=config.host, port=config.port, reload=config.reload)
diff --git a/examples/storytelling-chatbot/src/processors.py b/examples/storytelling-chatbot/src/processors.py
index a8b2a0980..6aa9ad7ab 100644
--- a/examples/storytelling-chatbot/src/processors.py
+++ b/examples/storytelling-chatbot/src/processors.py
@@ -6,7 +6,8 @@ from pipecat.frames.frames import (
     Frame,
     LLMFullResponseEndFrame,
     TextFrame,
-    UserStoppedSpeakingFrame)
+    UserStoppedSpeakingFrame,
+)
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.transports.services.daily import DailyTransportMessageFrame
 
@@ -35,6 +36,7 @@ class StoryPromptFrame(TextFrame):
 
 # ------------ Frame Processors ----------- #
 
+
 class StoryImageProcessor(FrameProcessor):
     """
     Processor for image prompt frames that will be sent to the FAL service.
@@ -113,7 +115,7 @@ class StoryProcessor(FrameProcessor):
                 # Extract the image prompt from the text using regex
                 image_prompt = re.search(r"<(.*?)>", self._text).group(1)
                 # Remove the image prompt from the text
-                self._text = re.sub(r"<.*?>", '', self._text, count=1)
+                self._text = re.sub(r"<.*?>", "", self._text, count=1)
                 # Process the image prompt frame
                 await self.push_frame(StoryImageFrame(image_prompt))
 
@@ -124,8 +126,7 @@ class StoryProcessor(FrameProcessor):
             if re.search(r".*\[[bB]reak\].*", self._text):
                 # Remove the [break] token from the text
                 # so it isn't spoken out loud by the TTS
-                self._text = re.sub(r'\[[bB]reak\]', '',
-                                    self._text, flags=re.IGNORECASE)
+                self._text = re.sub(r"\[[bB]reak\]", "", self._text, flags=re.IGNORECASE)
                 self._text = self._text.replace("\n", " ")
                 if len(self._text) > 2:
                     # Append the sentence to the story
diff --git a/examples/storytelling-chatbot/src/prompts.py b/examples/storytelling-chatbot/src/prompts.py
index 551a7c4f2..08abbc93c 100644
--- a/examples/storytelling-chatbot/src/prompts.py
+++ b/examples/storytelling-chatbot/src/prompts.py
@@ -3,7 +3,7 @@ LLM_INTRO_PROMPT = {
     "content": "You are a creative storyteller who loves to tell whimsical, fantastical stories. \
         Your goal is to craft an engaging and fun story. \
         Start by asking the user what kind of story they'd like to hear. Don't provide any examples. \
-        Keep your response to only a few sentences."
+        Keep your response to only a few sentences.",
 }
 
 
@@ -25,7 +25,7 @@ LLM_BASE_PROMPT = {
         Responses should use the format: <...> story sentence [break] <...> story sentence [break] ... \
         After each response, ask me how I'd like the story to continue and wait for my input. \
         Please ensure your responses are less than 3-4 sentences long. \
-        Please refrain from using any explicit language or content. Do not tell scary stories."
+        Please refrain from using any explicit language or content. Do not tell scary stories.",
 }
 
 
diff --git a/examples/storytelling-chatbot/src/utils/helpers.py b/examples/storytelling-chatbot/src/utils/helpers.py
index 743a04c97..36ba3e609 100644
--- a/examples/storytelling-chatbot/src/utils/helpers.py
+++ b/examples/storytelling-chatbot/src/utils/helpers.py
@@ -17,7 +17,8 @@ def load_images(image_files):
         # Open the image and convert it to bytes
         with Image.open(full_path) as img:
             images[filename] = OutputImageRawFrame(
-                image=img.tobytes(), size=img.size, format=img.format)
+                image=img.tobytes(), size=img.size, format=img.format
+            )
     return images
 
 
@@ -31,8 +32,10 @@ def load_sounds(sound_files):
         filename = os.path.splitext(os.path.basename(full_path))[0]
         # Open the sound and convert it to bytes
         with wave.open(full_path) as audio_file:
-            sounds[filename] = OutputAudioRawFrame(audio=audio_file.readframes(-1),
-                                                   sample_rate=audio_file.getframerate(),
-                                                   num_channels=audio_file.getnchannels())
+            sounds[filename] = OutputAudioRawFrame(
+                audio=audio_file.readframes(-1),
+                sample_rate=audio_file.getframerate(),
+                num_channels=audio_file.getnchannels(),
+            )
 
     return sounds
diff --git a/examples/studypal/runner.py b/examples/studypal/runner.py
index 068174eec..13c4ff076 100644
--- a/examples/studypal/runner.py
+++ b/examples/studypal/runner.py
@@ -17,16 +17,13 @@ async def configure(aiohttp_session: aiohttp.ClientSession):
 
 
 async def configure_with_args(
-        aiohttp_session: aiohttp.ClientSession,
-        parser: argparse.ArgumentParser | None = None):
+    aiohttp_session: aiohttp.ClientSession, parser: argparse.ArgumentParser | None = None
+):
     if not parser:
         parser = argparse.ArgumentParser(description="Daily AI SDK Bot Sample")
     parser.add_argument(
-        "-u",
-        "--url",
-        type=str,
-        required=False,
-        help="URL of the Daily room to join")
+        "-u", "--url", type=str, required=False, help="URL of the Daily room to join"
+    )
     parser.add_argument(
         "-k",
         "--apikey",
@@ -42,15 +39,19 @@ async def configure_with_args(
 
     if not url:
         raise Exception(
-            "No Daily room specified. use the -u/--url option from the command line, or set DAILY_SAMPLE_ROOM_URL in your environment to specify a Daily room URL.")
+            "No Daily room specified. use the -u/--url option from the command line, or set DAILY_SAMPLE_ROOM_URL in your environment to specify a Daily room URL."
+        )
 
     if not key:
-        raise Exception("No Daily API key specified. use the -k/--apikey option from the command line, or set DAILY_API_KEY in your environment to specify a Daily API key, available from https://dashboard.daily.co/developers.")
+        raise Exception(
+            "No Daily API key specified. use the -k/--apikey option from the command line, or set DAILY_API_KEY in your environment to specify a Daily API key, available from https://dashboard.daily.co/developers."
+        )
 
     daily_rest_helper = DailyRESTHelper(
         daily_api_key=key,
         daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
-        aiohttp_session=aiohttp_session)
+        aiohttp_session=aiohttp_session,
+    )
 
     # Create a meeting token for the given room with an expiration 1 hour in
     # the future.
diff --git a/examples/studypal/studypal.py b/examples/studypal/studypal.py
index 368a9b072..2364c65cf 100644
--- a/examples/studypal/studypal.py
+++ b/examples/studypal/studypal.py
@@ -13,7 +13,9 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator, LLMUserResponseAggregator)
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
+)
 from pipecat.services.cartesia import CartesiaTTSService
 from pipecat.services.openai import OpenAILLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
@@ -24,6 +26,7 @@ from runner import configure
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 # Run this script directly from your command line.
@@ -45,15 +48,17 @@ def truncate_content(content, model_name):
         return encoding.decode(truncated_tokens)
     return content
 
+
 # Main function to extract content from url
 
 
 async def get_article_content(url: str, aiohttp_session: aiohttp.ClientSession):
-    if 'arxiv.org' in url:
+    if "arxiv.org" in url:
         return await get_arxiv_content(url, aiohttp_session)
     else:
         return await get_wikipedia_content(url, aiohttp_session)
 
+
 # Helper function to extract content from Wikipedia url (this is
 # technically agnostic to URL type but will work best with Wikipedia
 # articles)
@@ -65,23 +70,24 @@ async def get_wikipedia_content(url: str, aiohttp_session: aiohttp.ClientSession
             return "Failed to download Wikipedia article."
 
         text = await response.text()
-        soup = BeautifulSoup(text, 'html.parser')
+        soup = BeautifulSoup(text, "html.parser")
 
-        content = soup.find('div', {'class': 'mw-parser-output'})
+        content = soup.find("div", {"class": "mw-parser-output"})
 
         if content:
             return content.get_text()
         else:
             return "Failed to extract Wikipedia article content."
 
+
 # Helper function to extract content from arXiv url
 
 
 async def get_arxiv_content(url: str, aiohttp_session: aiohttp.ClientSession):
-    if '/abs/' in url:
-        url = url.replace('/abs/', '/pdf/')
-    if not url.endswith('.pdf'):
-        url += '.pdf'
+    if "/abs/" in url:
+        url = url.replace("/abs/", "/pdf/")
+    if not url.endswith(".pdf"):
+        url += ".pdf"
 
     async with aiohttp_session.get(url) as response:
         if response.status != 200:
@@ -95,6 +101,7 @@ async def get_arxiv_content(url: str, aiohttp_session: aiohttp.ClientSession):
             text += page.extract_text()
         return text
 
+
 # This is the main function that handles STT -> LLM -> TTS
 
 
@@ -116,8 +123,8 @@ async def main():
                 audio_out_enabled=True,
                 transcription_enabled=True,
                 vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer()
-            )
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
         )
 
         tts = CartesiaTTSService(
@@ -127,29 +134,33 @@ async def main():
             sample_rate=44100,
         )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o-mini")
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o-mini")
 
-        messages = [{
-            "role": "system", "content": f"""You are an AI study partner. You have been given the following article content:
+        messages = [
+            {
+                "role": "system",
+                "content": f"""You are an AI study partner. You have been given the following article content:
 
 {article_content}
 
 Your task is to help the user understand and learn from this article in 2 sentences. THESE RESPONSES SHOULD BE ONLY MAX 2 SENTENCES. THIS INSTRUCTION IS VERY IMPORTANT. RESPONSES SHOULDN'T BE LONG.
-""", }, ]
+""",
+            },
+        ]
 
         tma_in = LLMUserResponseAggregator(messages)
         tma_out = LLMAssistantResponseAggregator(messages)
 
-        pipeline = Pipeline([
-            transport.input(),
-            tma_in,
-            llm,
-            tts,
-            transport.output(),
-            tma_out,
-        ])
+        pipeline = Pipeline(
+            [
+                transport.input(),
+                tma_in,
+                llm,
+                tts,
+                transport.output(),
+                tma_out,
+            ]
+        )
 
         task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True, enable_metrics=True))
 
@@ -159,12 +170,15 @@ Your task is to help the user understand and learn from this article in 2 senten
             messages.append(
                 {
                     "role": "system",
-                    "content": "Hello! I'm ready to discuss the article with you. What would you like to learn about?"})
+                    "content": "Hello! I'm ready to discuss the article with you. What would you like to learn about?",
+                }
+            )
             await task.queue_frames([LLMMessagesFrame(messages)])
 
         runner = PipelineRunner()
 
         await runner.run(task)
 
+
 if __name__ == "__main__":
     asyncio.run(main())
diff --git a/examples/translation-chatbot/bot.py b/examples/translation-chatbot/bot.py
index 1dbe802b9..55302b392 100644
--- a/examples/translation-chatbot/bot.py
+++ b/examples/translation-chatbot/bot.py
@@ -22,13 +22,15 @@ from pipecat.transports.services.daily import (
     DailyParams,
     DailyTranscriptionSettings,
     DailyTransport,
-    DailyTransportMessageFrame)
+    DailyTransportMessageFrame,
+)
 
 from runner import configure
 
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -44,7 +46,6 @@ It also isn't saving what the user or bot says into the context object for use i
 # We need to use a custom service here to yield LLM frames without saving
 # any context
 class TranslationProcessor(FrameProcessor):
-
     def __init__(self, language):
         super().__init__()
         self._language = language
@@ -80,10 +81,7 @@ class TranslationSubtitles(FrameProcessor):
         await super().process_frame(frame, direction)
 
         if isinstance(frame, TextFrame):
-            message = {
-                "language": self._language,
-                "text": frame.text
-            }
+            message = {"language": self._language, "text": frame.text}
             await self.push_frame(DailyTransportMessageFrame(message))
 
         await self.push_frame(frame)
@@ -100,10 +98,8 @@ async def main():
             DailyParams(
                 audio_out_enabled=True,
                 transcription_enabled=True,
-                transcription_settings=DailyTranscriptionSettings(extra={
-                    "interim_results": False
-                })
-            )
+                transcription_settings=DailyTranscriptionSettings(extra={"interim_results": False}),
+            ),
         )
 
         tts = AzureTTSService(
@@ -112,26 +108,14 @@ async def main():
             voice="es-ES-AlvaroNeural",
         )
 
-        llm = OpenAILLMService(
-            api_key=os.getenv("OPENAI_API_KEY"),
-            model="gpt-4o"
-        )
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
         sa = SentenceAggregator()
         tp = TranslationProcessor("Spanish")
         lfra = LLMFullResponseAggregator()
         ts = TranslationSubtitles("spanish")
 
-        pipeline = Pipeline([
-            transport.input(),
-            sa,
-            tp,
-            llm,
-            lfra,
-            ts,
-            tts,
-            transport.output()
-        ])
+        pipeline = Pipeline([transport.input(), sa, tp, llm, lfra, ts, tts, transport.output()])
 
         task = PipelineTask(pipeline)
 
diff --git a/examples/translation-chatbot/runner.py b/examples/translation-chatbot/runner.py
index 5f0e41795..f19fcf211 100644
--- a/examples/translation-chatbot/runner.py
+++ b/examples/translation-chatbot/runner.py
@@ -15,11 +15,8 @@ from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper
 async def configure(aiohttp_session: aiohttp.ClientSession):
     parser = argparse.ArgumentParser(description="Daily AI SDK Bot Sample")
     parser.add_argument(
-        "-u",
-        "--url",
-        type=str,
-        required=False,
-        help="URL of the Daily room to join")
+        "-u", "--url", type=str, required=False, help="URL of the Daily room to join"
+    )
     parser.add_argument(
         "-k",
         "--apikey",
@@ -35,15 +32,18 @@ async def configure(aiohttp_session: aiohttp.ClientSession):
 
     if not url:
         raise Exception(
-            "No Daily room specified. use the -u/--url option from the command line, or set DAILY_SAMPLE_ROOM_URL in your environment to specify a Daily room URL.")
+            "No Daily room specified. use the -u/--url option from the command line, or set DAILY_SAMPLE_ROOM_URL in your environment to specify a Daily room URL."
+        )
 
     if not key:
-        raise Exception("No Daily API key specified. use the -k/--apikey option from the command line, or set DAILY_API_KEY in your environment to specify a Daily API key, available from https://dashboard.daily.co/developers.")
+        raise Exception(
+            "No Daily API key specified. use the -k/--apikey option from the command line, or set DAILY_API_KEY in your environment to specify a Daily API key, available from https://dashboard.daily.co/developers."
+        )
 
     daily_rest_helper = DailyRESTHelper(
         daily_api_key=key,
         daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
-        aiohttp_session=aiohttp_session
+        aiohttp_session=aiohttp_session,
     )
 
     # Create a meeting token for the given room with an expiration 1 hour in
diff --git a/examples/translation-chatbot/server.py b/examples/translation-chatbot/server.py
index d54452d10..5240c254f 100644
--- a/examples/translation-chatbot/server.py
+++ b/examples/translation-chatbot/server.py
@@ -38,13 +38,14 @@ async def lifespan(app: FastAPI):
     aiohttp_session = aiohttp.ClientSession()
     daily_helpers["rest"] = DailyRESTHelper(
         daily_api_key=os.getenv("DAILY_API_KEY", ""),
-        daily_api_url=os.getenv("DAILY_API_URL", 'https://api.daily.co/v1'),
-        aiohttp_session=aiohttp_session
+        daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
+        aiohttp_session=aiohttp_session,
     )
     yield
     await aiohttp_session.close()
     cleanup()
 
+
 app = FastAPI(lifespan=lifespan)
 
 app.add_middleware(
@@ -65,37 +66,34 @@ async def start_agent(request: Request):
     if not room.url:
         raise HTTPException(
             status_code=500,
-            detail="Missing 'room' property in request data. Cannot start agent without a target room!")
+            detail="Missing 'room' property in request data. Cannot start agent without a target room!",
+        )
 
     # Check if there is already an existing process running in this room
     num_bots_in_room = sum(
-        1 for proc in bot_procs.values() if proc[1] == room.url and proc[0].poll() is None)
+        1 for proc in bot_procs.values() if proc[1] == room.url and proc[0].poll() is None
+    )
     if num_bots_in_room >= MAX_BOTS_PER_ROOM:
-        raise HTTPException(
-            status_code=500, detail=f"Max bot limited reach for room: {room.url}")
+        raise HTTPException(status_code=500, detail=f"Max bot limited reach for room: {room.url}")
 
     # Get the token for the room
     token = await daily_helpers["rest"].get_token(room.url)
 
     if not token:
-        raise HTTPException(
-            status_code=500, detail=f"Failed to get token for room: {room.url}")
+        raise HTTPException(status_code=500, detail=f"Failed to get token for room: {room.url}")
 
     # Spawn a new agent, and join the user session
     # Note: this is mostly for demonstration purposes (refer to 'deployment' in README)
     try:
         proc = subprocess.Popen(
-            [
-                f"python3 -m bot -u {room.url} -t {token}"
-            ],
+            [f"python3 -m bot -u {room.url} -t {token}"],
             shell=True,
             bufsize=1,
-            cwd=os.path.dirname(os.path.abspath(__file__))
+            cwd=os.path.dirname(os.path.abspath(__file__)),
         )
         bot_procs[proc.pid] = (proc, room.url)
     except Exception as e:
-        raise HTTPException(
-            status_code=500, detail=f"Failed to start subprocess: {e}")
+        raise HTTPException(status_code=500, detail=f"Failed to start subprocess: {e}")
 
     return RedirectResponse(room.url)
 
@@ -107,8 +105,7 @@ def get_status(pid: int):
 
     # If the subprocess doesn't exist, return an error
     if not proc:
-        raise HTTPException(
-            status_code=404, detail=f"Bot with process id: {pid} not found")
+        raise HTTPException(status_code=404, detail=f"Bot with process id: {pid} not found")
 
     # Check the status of the subprocess
     if proc[0].poll() is None:
@@ -125,14 +122,10 @@ if __name__ == "__main__":
     default_host = os.getenv("HOST", "0.0.0.0")
     default_port = int(os.getenv("FAST_API_PORT", "7860"))
 
-    parser = argparse.ArgumentParser(
-        description="Daily Storyteller FastAPI server")
-    parser.add_argument("--host", type=str,
-                        default=default_host, help="Host address")
-    parser.add_argument("--port", type=int,
-                        default=default_port, help="Port number")
-    parser.add_argument("--reload", action="store_true",
-                        help="Reload code on change")
+    parser = argparse.ArgumentParser(description="Daily Storyteller FastAPI server")
+    parser.add_argument("--host", type=str, default=default_host, help="Host address")
+    parser.add_argument("--port", type=int, default=default_port, help="Port number")
+    parser.add_argument("--reload", action="store_true", help="Reload code on change")
 
     config = parser.parse_args()
 
diff --git a/examples/twilio-chatbot/bot.py b/examples/twilio-chatbot/bot.py
index 5b83139f9..de9e395c4 100644
--- a/examples/twilio-chatbot/bot.py
+++ b/examples/twilio-chatbot/bot.py
@@ -7,18 +7,22 @@ from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_response import (
     LLMAssistantResponseAggregator,
-    LLMUserResponseAggregator
+    LLMUserResponseAggregator,
 )
 from pipecat.services.cartesia import CartesiaTTSService
 from pipecat.services.openai import OpenAILLMService
 from pipecat.services.deepgram import DeepgramSTTService
-from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketTransport, FastAPIWebsocketParams
+from pipecat.transports.network.fastapi_websocket import (
+    FastAPIWebsocketTransport,
+    FastAPIWebsocketParams,
+)
 from pipecat.vad.silero import SileroVADAnalyzer
 from pipecat.serializers.twilio import TwilioFrameSerializer
 
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -34,15 +38,13 @@ async def run_bot(websocket_client, stream_sid):
             vad_enabled=True,
             vad_analyzer=SileroVADAnalyzer(),
             vad_audio_passthrough=True,
-            serializer=TwilioFrameSerializer(stream_sid)
-        )
+            serializer=TwilioFrameSerializer(stream_sid),
+        ),
     )
 
-    llm = OpenAILLMService(
-        api_key=os.getenv("OPENAI_API_KEY"),
-        model="gpt-4o")
+    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
-    stt = DeepgramSTTService(api_key=os.getenv('DEEPGRAM_API_KEY'))
+    stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
 
     tts = CartesiaTTSService(
         api_key=os.getenv("CARTESIA_API_KEY"),
@@ -59,23 +61,24 @@ async def run_bot(websocket_client, stream_sid):
     tma_in = LLMUserResponseAggregator(messages)
     tma_out = LLMAssistantResponseAggregator(messages)
 
-    pipeline = Pipeline([
-        transport.input(),   # Websocket input from client
-        stt,                 # Speech-To-Text
-        tma_in,              # User responses
-        llm,                 # LLM
-        tts,                 # Text-To-Speech
-        transport.output(),  # Websocket output to client
-        tma_out              # LLM responses
-    ])
+    pipeline = Pipeline(
+        [
+            transport.input(),  # Websocket input from client
+            stt,  # Speech-To-Text
+            tma_in,  # User responses
+            llm,  # LLM
+            tts,  # Text-To-Speech
+            transport.output(),  # Websocket output to client
+            tma_out,  # LLM responses
+        ]
+    )
 
     task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
 
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):
         # Kick off the conversation.
-        messages.append(
-            {"role": "system", "content": "Please introduce yourself to the user."})
+        messages.append({"role": "system", "content": "Please introduce yourself to the user."})
         await task.queue_frames([LLMMessagesFrame(messages)])
 
     @transport.event_handler("on_client_disconnected")
diff --git a/examples/twilio-chatbot/server.py b/examples/twilio-chatbot/server.py
index f64e7f309..9656875ec 100644
--- a/examples/twilio-chatbot/server.py
+++ b/examples/twilio-chatbot/server.py
@@ -19,7 +19,7 @@ app.add_middleware(
 )
 
 
-@app.post('/start_call')
+@app.post("/start_call")
 async def start_call():
     print("POST TwiML")
     return HTMLResponse(content=open("templates/streams.xml").read(), media_type="application/xml")
@@ -32,7 +32,7 @@ async def websocket_endpoint(websocket: WebSocket):
     await start_data.__anext__()
     call_data = json.loads(await start_data.__anext__())
     print(call_data, flush=True)
-    stream_sid = call_data['start']['streamSid']
+    stream_sid = call_data["start"]["streamSid"]
     print("WebSocket connection accepted")
     await run_bot(websocket, stream_sid)
 
diff --git a/examples/websocket-server/bot.py b/examples/websocket-server/bot.py
index 61d285fa8..e223d4e3f 100644
--- a/examples/websocket-server/bot.py
+++ b/examples/websocket-server/bot.py
@@ -14,17 +14,21 @@ from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
 from pipecat.processors.aggregators.llm_response import (
     LLMAssistantResponseAggregator,
-    LLMUserResponseAggregator
+    LLMUserResponseAggregator,
 )
 from pipecat.services.cartesia import CartesiaTTSService
 from pipecat.services.deepgram import DeepgramSTTService
 from pipecat.services.openai import OpenAILLMService
-from pipecat.transports.network.websocket_server import WebsocketServerParams, WebsocketServerTransport
+from pipecat.transports.network.websocket_server import (
+    WebsocketServerParams,
+    WebsocketServerTransport,
+)
 from pipecat.vad.silero import SileroVADAnalyzer
 
 from loguru import logger
 
 from dotenv import load_dotenv
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -38,13 +42,11 @@ async def main():
             add_wav_header=True,
             vad_enabled=True,
             vad_analyzer=SileroVADAnalyzer(),
-            vad_audio_passthrough=True
+            vad_audio_passthrough=True,
         )
     )
 
-    llm = OpenAILLMService(
-        api_key=os.getenv("OPENAI_API_KEY"),
-        model="gpt-4o")
+    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
     stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
 
@@ -63,28 +65,30 @@ async def main():
     tma_in = LLMUserResponseAggregator(messages)
     tma_out = LLMAssistantResponseAggregator(messages)
 
-    pipeline = Pipeline([
-        transport.input(),   # Websocket input from client
-        stt,                 # Speech-To-Text
-        tma_in,              # User responses
-        llm,                 # LLM
-        tts,                 # Text-To-Speech
-        transport.output(),  # Websocket output to client
-        tma_out              # LLM responses
-    ])
+    pipeline = Pipeline(
+        [
+            transport.input(),  # Websocket input from client
+            stt,  # Speech-To-Text
+            tma_in,  # User responses
+            llm,  # LLM
+            tts,  # Text-To-Speech
+            transport.output(),  # Websocket output to client
+            tma_out,  # LLM responses
+        ]
+    )
 
     task = PipelineTask(pipeline)
 
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):
         # Kick off the conversation.
-        messages.append(
-            {"role": "system", "content": "Please introduce yourself to the user."})
+        messages.append({"role": "system", "content": "Please introduce yourself to the user."})
         await task.queue_frames([LLMMessagesFrame(messages)])
 
     runner = PipelineRunner()
 
     await runner.run(task)
 
+
 if __name__ == "__main__":
     asyncio.run(main())
diff --git a/src/pipecat/clocks/base_clock.py b/src/pipecat/clocks/base_clock.py
index aa7b7b806..79e17d5ba 100644
--- a/src/pipecat/clocks/base_clock.py
+++ b/src/pipecat/clocks/base_clock.py
@@ -8,7 +8,6 @@ from abc import ABC, abstractmethod
 
 
 class BaseClock(ABC):
-
     @abstractmethod
     def get_time(self) -> int:
         pass
diff --git a/src/pipecat/clocks/system_clock.py b/src/pipecat/clocks/system_clock.py
index 20319cff6..d919b6acd 100644
--- a/src/pipecat/clocks/system_clock.py
+++ b/src/pipecat/clocks/system_clock.py
@@ -10,7 +10,6 @@ from pipecat.clocks.base_clock import BaseClock
 
 
 class SystemClock(BaseClock):
-
     def __init__(self):
         self._time = 0
 
diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py
index 3211bd266..e4495098b 100644
--- a/src/pipecat/frames/frames.py
+++ b/src/pipecat/frames/frames.py
@@ -43,6 +43,7 @@ class DataFrame(Frame):
 @dataclass
 class AudioRawFrame(DataFrame):
     """A chunk of audio."""
+
     audio: bytes
     sample_rate: int
     num_channels: int
@@ -58,9 +59,8 @@ class AudioRawFrame(DataFrame):
 
 @dataclass
 class InputAudioRawFrame(AudioRawFrame):
-    """A chunk of audio usually coming from an input transport.
+    """A chunk of audio usually coming from an input transport."""
 
-    """
     pass
 
 
@@ -70,14 +70,14 @@ class OutputAudioRawFrame(AudioRawFrame):
     transport's microphone has been enabled.
 
     """
+
     pass
 
 
 @dataclass
 class TTSAudioRawFrame(OutputAudioRawFrame):
-    """A chunk of output audio generated by a TTS service.
+    """A chunk of output audio generated by a TTS service."""
 
-    """
     pass
 
 
@@ -87,6 +87,7 @@ class ImageRawFrame(DataFrame):
     enabled.
 
     """
+
     image: bytes
     size: Tuple[int, int]
     format: str | None
@@ -112,6 +113,7 @@ class UserImageRawFrame(InputImageRawFrame):
     transport's camera is enabled.
 
     """
+
     user_id: str
 
     def __str__(self):
@@ -125,11 +127,14 @@ class VisionImageRawFrame(InputImageRawFrame):
     shown by the transport if the transport's camera is enabled.
 
     """
+
     text: str | None
 
     def __str__(self):
         pts = format_pts(self.pts)
-        return f"{self.name}(pts: {pts}, text: {self.text}, size: {self.size}, format: {self.format})"
+        return (
+            f"{self.name}(pts: {pts}, text: {self.text}, size: {self.size}, format: {self.format})"
+        )
 
 
 @dataclass
@@ -138,6 +143,7 @@ class URLImageRawFrame(OutputImageRawFrame):
     transport's camera is enabled.
 
     """
+
     url: str | None
 
     def __str__(self):
@@ -152,6 +158,7 @@ class SpriteFrame(Frame):
     `camera_out_framerate` constructor parameter.
 
     """
+
     images: List[ImageRawFrame]
 
     def __str__(self):
@@ -165,6 +172,7 @@ class TextFrame(DataFrame):
     be used to send text through pipelines.
 
     """
+
     text: str
 
     def __str__(self):
@@ -178,6 +186,7 @@ class TranscriptionFrame(TextFrame):
     transport's receive queue when a participant speaks.
 
     """
+
     user_id: str
     timestamp: str
     language: Language | None = None
@@ -190,6 +199,7 @@ class TranscriptionFrame(TextFrame):
 class InterimTranscriptionFrame(TextFrame):
     """A text frame with interim transcription-specific data. Will be placed in
     the transport's receive queue when a participant speaks."""
+
     user_id: str
     timestamp: str
     language: Language | None = None
@@ -207,6 +217,7 @@ class LLMMessagesFrame(DataFrame):
     processors.
 
     """
+
     messages: List[dict]
 
 
@@ -216,6 +227,7 @@ class LLMMessagesAppendFrame(DataFrame):
     current context.
 
     """
+
     messages: List[dict]
 
 
@@ -226,6 +238,7 @@ class LLMMessagesUpdateFrame(DataFrame):
     LLMMessagesFrame.
 
     """
+
     messages: List[dict]
 
 
@@ -235,13 +248,14 @@ class LLMSetToolsFrame(DataFrame):
     The specific format depends on the LLM being used, but it should typically
     contain JSON Schema objects.
     """
+
     tools: List[dict]
 
 
 @dataclass
 class LLMEnablePromptCachingFrame(DataFrame):
-    """A frame to enable/disable prompt caching in certain LLMs.
-    """
+    """A frame to enable/disable prompt caching in certain LLMs."""
+
     enable: bool
 
 
@@ -251,6 +265,7 @@ class TTSSpeakFrame(DataFrame):
     pipeline (if any).
 
     """
+
     text: str
 
 
@@ -262,6 +277,7 @@ class TransportMessageFrame(DataFrame):
     def __str__(self):
         return f"{self.name}(message: {self.message})"
 
+
 #
 # App frames. Application user-defined frames.
 #
@@ -271,6 +287,7 @@ class TransportMessageFrame(DataFrame):
 class AppFrame(Frame):
     pass
 
+
 #
 # System frames
 #
@@ -284,6 +301,7 @@ class SystemFrame(Frame):
 @dataclass
 class StartFrame(SystemFrame):
     """This is the first frame that should be pushed down a pipeline."""
+
     clock: BaseClock
     allow_interruptions: bool = False
     enable_metrics: bool = False
@@ -294,6 +312,7 @@ class StartFrame(SystemFrame):
 @dataclass
 class CancelFrame(SystemFrame):
     """Indicates that a pipeline needs to stop right away."""
+
     pass
 
 
@@ -304,6 +323,7 @@ class ErrorFrame(SystemFrame):
     bot should exit.
 
     """
+
     error: str
     fatal: bool = False
 
@@ -317,6 +337,7 @@ class FatalErrorFrame(ErrorFrame):
     that the bot should exit.
 
     """
+
     fatal: bool = field(default=True, init=False)
 
 
@@ -327,6 +348,7 @@ class StopTaskFrame(SystemFrame):
     the pipeline task.
 
     """
+
     pass
 
 
@@ -338,6 +360,7 @@ class StartInterruptionFrame(SystemFrame):
     guaranteed).
 
     """
+
     pass
 
 
@@ -349,6 +372,7 @@ class StopInterruptionFrame(SystemFrame):
     guaranteed).
 
     """
+
     pass
 
 
@@ -359,13 +383,14 @@ class BotInterruptionFrame(SystemFrame):
     UserStartedSpeakingFrame and UserStoppedSpeakingFrame won't be generated.
 
     """
+
     pass
 
 
 @dataclass
 class MetricsFrame(SystemFrame):
-    """Emitted by processor that can compute metrics like latencies.
-    """
+    """Emitted by processor that can compute metrics like latencies."""
+
     data: List[MetricsData]
 
 
@@ -388,6 +413,7 @@ class EndFrame(ControlFrame):
     was sent (unline system frames).
 
     """
+
     pass
 
 
@@ -395,12 +421,14 @@ class EndFrame(ControlFrame):
 class LLMFullResponseStartFrame(ControlFrame):
     """Used to indicate the beginning of an LLM response. Following by one or
     more TextFrame and a final LLMFullResponseEndFrame."""
+
     pass
 
 
 @dataclass
 class LLMFullResponseEndFrame(ControlFrame):
     """Indicates the end of an LLM response."""
+
     pass
 
 
@@ -412,28 +440,28 @@ class UserStartedSpeakingFrame(ControlFrame):
     with a TranscriptionFrame)
 
     """
+
     pass
 
 
 @dataclass
 class UserStoppedSpeakingFrame(ControlFrame):
     """Emitted by the VAD to indicate that a user stopped speaking."""
+
     pass
 
 
 @dataclass
 class BotStartedSpeakingFrame(ControlFrame):
-    """Emitted upstream by transport outputs to indicate the bot started speaking.
+    """Emitted upstream by transport outputs to indicate the bot started speaking."""
 
-    """
     pass
 
 
 @dataclass
 class BotStoppedSpeakingFrame(ControlFrame):
-    """Emitted upstream by transport outputs to indicate the bot stopped speaking.
+    """Emitted upstream by transport outputs to indicate the bot stopped speaking."""
 
-    """
     pass
 
 
@@ -445,6 +473,7 @@ class BotSpeakingFrame(ControlFrame):
     since the user might be listening.
 
     """
+
     pass
 
 
@@ -457,18 +486,21 @@ class TTSStartedFrame(ControlFrame):
     needing to control this in the TTS service.
 
     """
+
     pass
 
 
 @dataclass
 class TTSStoppedFrame(ControlFrame):
     """Indicates the end of a TTS response."""
+
     pass
 
 
 @dataclass
 class UserImageRequestFrame(ControlFrame):
     """A frame user to request an image from the given user."""
+
     user_id: str
     context: Optional[Any] = None
 
@@ -478,29 +510,29 @@ class UserImageRequestFrame(ControlFrame):
 
 @dataclass
 class LLMModelUpdateFrame(ControlFrame):
-    """A control frame containing a request to update to a new LLM model.
-    """
+    """A control frame containing a request to update to a new LLM model."""
+
     model: str
 
 
 @dataclass
 class LLMTemperatureUpdateFrame(ControlFrame):
-    """A control frame containing a request to update to a new LLM temperature.
-    """
+    """A control frame containing a request to update to a new LLM temperature."""
+
     temperature: float
 
 
 @dataclass
 class LLMTopKUpdateFrame(ControlFrame):
-    """A control frame containing a request to update to a new LLM top_k.
-    """
+    """A control frame containing a request to update to a new LLM top_k."""
+
     top_k: int
 
 
 @dataclass
 class LLMTopPUpdateFrame(ControlFrame):
-    """A control frame containing a request to update to a new LLM top_p.
-    """
+    """A control frame containing a request to update to a new LLM top_p."""
+
     top_p: float
 
 
@@ -510,6 +542,7 @@ class LLMFrequencyPenaltyUpdateFrame(ControlFrame):
     penalty.
 
     """
+
     frequency_penalty: float
 
 
@@ -519,41 +552,42 @@ class LLMPresencePenaltyUpdateFrame(ControlFrame):
     penalty.
 
     """
+
     presence_penalty: float
 
 
 @dataclass
 class LLMMaxTokensUpdateFrame(ControlFrame):
-    """A control frame containing a request to update to a new LLM max tokens.
-    """
+    """A control frame containing a request to update to a new LLM max tokens."""
+
     max_tokens: int
 
 
 @dataclass
 class LLMSeedUpdateFrame(ControlFrame):
-    """A control frame containing a request to update to a new LLM seed.
-    """
+    """A control frame containing a request to update to a new LLM seed."""
+
     seed: int
 
 
 @dataclass
 class LLMExtraUpdateFrame(ControlFrame):
-    """A control frame containing a request to update to a new LLM extra params.
-    """
+    """A control frame containing a request to update to a new LLM extra params."""
+
     extra: dict
 
 
 @dataclass
 class TTSModelUpdateFrame(ControlFrame):
-    """A control frame containing a request to update the TTS model.
-    """
+    """A control frame containing a request to update the TTS model."""
+
     model: str
 
 
 @dataclass
 class TTSVoiceUpdateFrame(ControlFrame):
-    """A control frame containing a request to update to a new TTS voice.
-    """
+    """A control frame containing a request to update to a new TTS voice."""
+
     voice: str
 
 
@@ -563,6 +597,7 @@ class TTSLanguageUpdateFrame(ControlFrame):
     optional voice.
 
     """
+
     language: Language
 
 
@@ -572,20 +607,21 @@ class STTModelUpdateFrame(ControlFrame):
     language.
 
     """
+
     model: str
 
 
 @dataclass
 class STTLanguageUpdateFrame(ControlFrame):
-    """A control frame containing a request to update to STT language.
-    """
+    """A control frame containing a request to update to STT language."""
+
     language: Language
 
 
 @dataclass
 class FunctionCallInProgressFrame(SystemFrame):
-    """A frame signaling that a function call is in progress.
-    """
+    """A frame signaling that a function call is in progress."""
+
     function_name: str
     tool_call_id: str
     arguments: str
@@ -593,8 +629,8 @@ class FunctionCallInProgressFrame(SystemFrame):
 
 @dataclass
 class FunctionCallResultFrame(DataFrame):
-    """A frame containing the result of an LLM function (tool) call.
-    """
+    """A frame containing the result of an LLM function (tool) call."""
+
     function_name: str
     tool_call_id: str
     arguments: str
@@ -606,4 +642,5 @@ class VADParamsUpdateFrame(ControlFrame):
     """A control frame containing a request to update VAD params. Intended
     to be pushed upstream from RTVI processor.
     """
+
     params: VADParams
diff --git a/src/pipecat/pipeline/base_pipeline.py b/src/pipecat/pipeline/base_pipeline.py
index 54f6499a9..393914684 100644
--- a/src/pipecat/pipeline/base_pipeline.py
+++ b/src/pipecat/pipeline/base_pipeline.py
@@ -12,7 +12,6 @@ from pipecat.processors.frame_processor import FrameProcessor
 
 
 class BasePipeline(FrameProcessor):
-
     def __init__(self):
         super().__init__()
 
diff --git a/src/pipecat/pipeline/parallel_pipeline.py b/src/pipecat/pipeline/parallel_pipeline.py
index d045c3493..1c2eeabde 100644
--- a/src/pipecat/pipeline/parallel_pipeline.py
+++ b/src/pipecat/pipeline/parallel_pipeline.py
@@ -18,7 +18,6 @@ from loguru import logger
 
 
 class Source(FrameProcessor):
-
     def __init__(self, upstream_queue: asyncio.Queue):
         super().__init__()
         self._up_queue = upstream_queue
@@ -34,7 +33,6 @@ class Source(FrameProcessor):
 
 
 class Sink(FrameProcessor):
-
     def __init__(self, downstream_queue: asyncio.Queue):
         super().__init__()
         self._down_queue = downstream_queue
diff --git a/src/pipecat/pipeline/pipeline.py b/src/pipecat/pipeline/pipeline.py
index 6805cfad0..a1715570e 100644
--- a/src/pipecat/pipeline/pipeline.py
+++ b/src/pipecat/pipeline/pipeline.py
@@ -12,7 +12,6 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 
 
 class PipelineSource(FrameProcessor):
-
     def __init__(self, upstream_push_frame: Callable[[Frame, FrameDirection], Coroutine]):
         super().__init__()
         self._upstream_push_frame = upstream_push_frame
@@ -28,7 +27,6 @@ class PipelineSource(FrameProcessor):
 
 
 class PipelineSink(FrameProcessor):
-
     def __init__(self, downstream_push_frame: Callable[[Frame, FrameDirection], Coroutine]):
         super().__init__()
         self._downstream_push_frame = downstream_push_frame
@@ -44,7 +42,6 @@ class PipelineSink(FrameProcessor):
 
 
 class Pipeline(BasePipeline):
-
     def __init__(self, processors: List[FrameProcessor]):
         super().__init__()
 
diff --git a/src/pipecat/pipeline/runner.py b/src/pipecat/pipeline/runner.py
index 3237c3904..57b818487 100644
--- a/src/pipecat/pipeline/runner.py
+++ b/src/pipecat/pipeline/runner.py
@@ -14,7 +14,6 @@ from loguru import logger
 
 
 class PipelineRunner:
-
     def __init__(self, *, name: str | None = None, handle_sigint: bool = True):
         self.id: int = obj_id()
         self.name: str = name or f"{self.__class__.__name__}#{obj_count(self)}"
@@ -42,12 +41,10 @@ class PipelineRunner:
     def _setup_sigint(self):
         loop = asyncio.get_running_loop()
         loop.add_signal_handler(
-            signal.SIGINT,
-            lambda *args: asyncio.create_task(self._sig_handler())
+            signal.SIGINT, lambda *args: asyncio.create_task(self._sig_handler())
         )
         loop.add_signal_handler(
-            signal.SIGTERM,
-            lambda *args: asyncio.create_task(self._sig_handler())
+            signal.SIGTERM, lambda *args: asyncio.create_task(self._sig_handler())
         )
 
     async def _sig_handler(self):
diff --git a/src/pipecat/pipeline/sync_parallel_pipeline.py b/src/pipecat/pipeline/sync_parallel_pipeline.py
index d922134f4..854cea89d 100644
--- a/src/pipecat/pipeline/sync_parallel_pipeline.py
+++ b/src/pipecat/pipeline/sync_parallel_pipeline.py
@@ -18,7 +18,6 @@ from loguru import logger
 
 
 class Source(FrameProcessor):
-
     def __init__(self, upstream_queue: asyncio.Queue):
         super().__init__()
         self._up_queue = upstream_queue
@@ -34,7 +33,6 @@ class Source(FrameProcessor):
 
 
 class Sink(FrameProcessor):
-
     def __init__(self, downstream_queue: asyncio.Queue):
         super().__init__()
         self._down_queue = downstream_queue
diff --git a/src/pipecat/pipeline/task.py b/src/pipecat/pipeline/task.py
index 26e6e9f4f..2b46c47c2 100644
--- a/src/pipecat/pipeline/task.py
+++ b/src/pipecat/pipeline/task.py
@@ -19,7 +19,8 @@ from pipecat.frames.frames import (
     Frame,
     MetricsFrame,
     StartFrame,
-    StopTaskFrame)
+    StopTaskFrame,
+)
 from pipecat.metrics.metrics import TTFBMetricsData, ProcessingMetricsData
 from pipecat.pipeline.base_pipeline import BasePipeline
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
@@ -37,7 +38,6 @@ class PipelineParams(BaseModel):
 
 
 class Source(FrameProcessor):
-
     def __init__(self, up_queue: asyncio.Queue):
         super().__init__()
         self._up_queue = up_queue
@@ -62,12 +62,12 @@ class Source(FrameProcessor):
 
 
 class PipelineTask:
-
     def __init__(
-            self,
-            pipeline: BasePipeline,
-            params: PipelineParams = PipelineParams(),
-            clock: BaseClock = SystemClock()):
+        self,
+        pipeline: BasePipeline,
+        params: PipelineParams = PipelineParams(),
+        clock: BaseClock = SystemClock(),
+    ):
         self.id: int = obj_id()
         self.name: str = f"{self.__class__.__name__}#{obj_count(self)}"
 
@@ -133,12 +133,14 @@ class PipelineTask:
             enable_metrics=self._params.enable_metrics,
             enable_usage_metrics=self._params.enable_metrics,
             report_only_initial_ttfb=self._params.report_only_initial_ttfb,
-            clock=self._clock
+            clock=self._clock,
         )
         await self._source.process_frame(start_frame, FrameDirection.DOWNSTREAM)
 
         if self._params.enable_metrics and self._params.send_initial_empty_metrics:
-            await self._source.process_frame(self._initial_metrics_frame(), FrameDirection.DOWNSTREAM)
+            await self._source.process_frame(
+                self._initial_metrics_frame(), FrameDirection.DOWNSTREAM
+            )
 
         running = True
         should_cleanup = True
diff --git a/src/pipecat/pipeline/to_be_updated/merge_pipeline.py b/src/pipecat/pipeline/to_be_updated/merge_pipeline.py
index f6f9a5ebd..6142a55ea 100644
--- a/src/pipecat/pipeline/to_be_updated/merge_pipeline.py
+++ b/src/pipecat/pipeline/to_be_updated/merge_pipeline.py
@@ -15,9 +15,7 @@ class SequentialMergePipeline(Pipeline):
         for idx, pipeline in enumerate(self.pipelines):
             while True:
                 frame = await pipeline.sink.get()
-                if isinstance(
-                        frame, EndFrame) or isinstance(
-                        frame, EndPipeFrame):
+                if isinstance(frame, EndFrame) or isinstance(frame, EndPipeFrame):
                     break
                 await self.sink.put(frame)
 
diff --git a/src/pipecat/processors/aggregators/gated.py b/src/pipecat/processors/aggregators/gated.py
index 7d784b14c..c39a35c82 100644
--- a/src/pipecat/processors/aggregators/gated.py
+++ b/src/pipecat/processors/aggregators/gated.py
@@ -41,8 +41,13 @@ class GatedAggregator(FrameProcessor):
     Goodbye.
     """
 
-    def __init__(self, gate_open_fn, gate_close_fn, start_open,
-                 direction: FrameDirection = FrameDirection.DOWNSTREAM):
+    def __init__(
+        self,
+        gate_open_fn,
+        gate_close_fn,
+        start_open,
+        direction: FrameDirection = FrameDirection.DOWNSTREAM,
+    ):
         super().__init__()
         self._gate_open_fn = gate_open_fn
         self._gate_close_fn = gate_close_fn
@@ -75,7 +80,7 @@ class GatedAggregator(FrameProcessor):
 
         if self._gate_open:
             await self.push_frame(frame, direction)
-            for (f, d) in self._accumulator:
+            for f, d in self._accumulator:
                 await self.push_frame(f, d)
             self._accumulator = []
         else:
diff --git a/src/pipecat/processors/aggregators/llm_response.py b/src/pipecat/processors/aggregators/llm_response.py
index 13920c59b..036f5fe47 100644
--- a/src/pipecat/processors/aggregators/llm_response.py
+++ b/src/pipecat/processors/aggregators/llm_response.py
@@ -6,7 +6,10 @@
 
 from typing import List, Type
 
-from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContextFrame, OpenAILLMContext
+from pipecat.processors.aggregators.openai_llm_context import (
+    OpenAILLMContextFrame,
+    OpenAILLMContext,
+)
 
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.frames.frames import (
@@ -22,11 +25,11 @@ from pipecat.frames.frames import (
     TranscriptionFrame,
     TextFrame,
     UserStartedSpeakingFrame,
-    UserStoppedSpeakingFrame)
+    UserStoppedSpeakingFrame,
+)
 
 
 class LLMResponseAggregator(FrameProcessor):
-
     def __init__(
         self,
         *,
@@ -36,7 +39,7 @@ class LLMResponseAggregator(FrameProcessor):
         end_frame,
         accumulator_frame: Type[TextFrame],
         interim_accumulator_frame: Type[TextFrame] | None = None,
-        handle_interruptions: bool = False
+        handle_interruptions: bool = False,
     ):
         super().__init__()
 
@@ -175,7 +178,7 @@ class LLMAssistantResponseAggregator(LLMResponseAggregator):
             start_frame=LLMFullResponseStartFrame,
             end_frame=LLMFullResponseEndFrame,
             accumulator_frame=TextFrame,
-            handle_interruptions=True
+            handle_interruptions=True,
         )
 
 
@@ -187,7 +190,7 @@ class LLMUserResponseAggregator(LLMResponseAggregator):
             start_frame=UserStartedSpeakingFrame,
             end_frame=UserStoppedSpeakingFrame,
             accumulator_frame=TranscriptionFrame,
-            interim_accumulator_frame=InterimTranscriptionFrame
+            interim_accumulator_frame=InterimTranscriptionFrame,
         )
 
 
@@ -295,7 +298,7 @@ class LLMAssistantContextAggregator(LLMContextAggregator):
             start_frame=LLMFullResponseStartFrame,
             end_frame=LLMFullResponseEndFrame,
             accumulator_frame=TextFrame,
-            handle_interruptions=True
+            handle_interruptions=True,
         )
 
 
@@ -308,5 +311,5 @@ class LLMUserContextAggregator(LLMContextAggregator):
             start_frame=UserStartedSpeakingFrame,
             end_frame=UserStoppedSpeakingFrame,
             accumulator_frame=TranscriptionFrame,
-            interim_accumulator_frame=InterimTranscriptionFrame
+            interim_accumulator_frame=InterimTranscriptionFrame,
         )
diff --git a/src/pipecat/processors/aggregators/openai_llm_context.py b/src/pipecat/processors/aggregators/openai_llm_context.py
index 3d1acf32e..83ec3e57f 100644
--- a/src/pipecat/processors/aggregators/openai_llm_context.py
+++ b/src/pipecat/processors/aggregators/openai_llm_context.py
@@ -17,7 +17,8 @@ from pipecat.frames.frames import (
     Frame,
     VisionImageRawFrame,
     FunctionCallInProgressFrame,
-    FunctionCallResultFrame)
+    FunctionCallResultFrame,
+)
 from pipecat.processors.frame_processor import FrameProcessor
 
 from loguru import logger
@@ -28,12 +29,13 @@ try:
     from openai.types.chat import (
         ChatCompletionToolParam,
         ChatCompletionToolChoiceOptionParam,
-        ChatCompletionMessageParam
+        ChatCompletionMessageParam,
     )
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
-        "In order to use OpenAI, you need to `pip install pipecat-ai[openai]`. Also, set `OPENAI_API_KEY` environment variable.")
+        "In order to use OpenAI, you need to `pip install pipecat-ai[openai]`. Also, set `OPENAI_API_KEY` environment variable."
+    )
     raise Exception(f"Missing module: {e}")
 
 # JSON custom encoder to handle bytes arrays so that we can log contexts
@@ -44,20 +46,18 @@ class CustomEncoder(json.JSONEncoder):
     def default(self, obj):
         if isinstance(obj, io.BytesIO):
             # Convert the first 8 bytes to an ASCII hex string
-            return (f"{obj.getbuffer()[0:8].hex()}...")
+            return f"{obj.getbuffer()[0:8].hex()}..."
         return super().default(obj)
 
 
 class OpenAILLMContext:
-
     def __init__(
         self,
         messages: List[ChatCompletionMessageParam] | None = None,
         tools: List[ChatCompletionToolParam] | NotGiven = NOT_GIVEN,
-        tool_choice: ChatCompletionToolChoiceOptionParam | NotGiven = NOT_GIVEN
+        tool_choice: ChatCompletionToolChoiceOptionParam | NotGiven = NOT_GIVEN,
     ):
-        self._messages: List[ChatCompletionMessageParam] = messages if messages else [
-        ]
+        self._messages: List[ChatCompletionMessageParam] = messages if messages else []
         self._tool_choice: ChatCompletionToolChoiceOptionParam | NotGiven = tool_choice
         self._tools: List[ChatCompletionToolParam] | NotGiven = tools
 
@@ -81,19 +81,10 @@ class OpenAILLMContext:
         """
         context = OpenAILLMContext()
         buffer = io.BytesIO()
-        Image.frombytes(
-            frame.format,
-            frame.size,
-            frame.image
-        ).save(
-            buffer,
-            format="JPEG")
-        context.add_message({
-            "content": frame.text,
-            "role": "user",
-            "data": buffer,
-            "mime_type": "image/jpeg"
-        })
+        Image.frombytes(frame.format, frame.size, frame.image).save(buffer, format="JPEG")
+        context.add_message(
+            {"content": frame.text, "role": "user", "data": buffer, "mime_type": "image/jpeg"}
+        )
         return context
 
     @property
@@ -123,9 +114,7 @@ class OpenAILLMContext:
     def get_messages_json(self) -> str:
         return json.dumps(self._messages, cls=CustomEncoder)
 
-    def set_tool_choice(
-        self, tool_choice: ChatCompletionToolChoiceOptionParam | NotGiven
-    ):
+    def set_tool_choice(self, tool_choice: ChatCompletionToolChoiceOptionParam | NotGiven):
         self._tool_choice = tool_choice
 
     def set_tools(self, tools: List[ChatCompletionToolParam] | NotGiven = NOT_GIVEN):
@@ -133,37 +122,40 @@ class OpenAILLMContext:
             tools = NOT_GIVEN
         self._tools = tools
 
-    async def call_function(self,
-                            f: Callable[[str,
-                                         str,
-                                         Any,
-                                         FrameProcessor,
-                                         'OpenAILLMContext',
-                                         Callable[[Any],
-                                                  Awaitable[None]]],
-                                        Awaitable[None]],
-                            *,
-                            function_name: str,
-                            tool_call_id: str,
-                            arguments: str,
-                            llm: FrameProcessor) -> None:
-
+    async def call_function(
+        self,
+        f: Callable[
+            [str, str, Any, FrameProcessor, "OpenAILLMContext", Callable[[Any], Awaitable[None]]],
+            Awaitable[None],
+        ],
+        *,
+        function_name: str,
+        tool_call_id: str,
+        arguments: str,
+        llm: FrameProcessor,
+    ) -> None:
         # Push a SystemFrame downstream. This frame will let our assistant context aggregator
         # know that we are in the middle of a function call. Some contexts/aggregators may
         # not need this. But some definitely do (Anthropic, for example).
-        await llm.push_frame(FunctionCallInProgressFrame(
-            function_name=function_name,
-            tool_call_id=tool_call_id,
-            arguments=arguments,
-        ))
-
-        # Define a callback function that pushes a FunctionCallResultFrame downstream.
-        async def function_call_result_callback(result):
-            await llm.push_frame(FunctionCallResultFrame(
+        await llm.push_frame(
+            FunctionCallInProgressFrame(
                 function_name=function_name,
                 tool_call_id=tool_call_id,
                 arguments=arguments,
-                result=result))
+            )
+        )
+
+        # Define a callback function that pushes a FunctionCallResultFrame downstream.
+        async def function_call_result_callback(result):
+            await llm.push_frame(
+                FunctionCallResultFrame(
+                    function_name=function_name,
+                    tool_call_id=tool_call_id,
+                    arguments=arguments,
+                    result=result,
+                )
+            )
+
         await f(function_name, tool_call_id, arguments, llm, self, function_call_result_callback)
 
 
@@ -174,4 +166,5 @@ class OpenAILLMContextFrame(Frame):
     OpenAIContextAggregator frame processor.
 
     """
+
     context: OpenAILLMContext
diff --git a/src/pipecat/processors/aggregators/user_response.py b/src/pipecat/processors/aggregators/user_response.py
index 002b6dd95..903019059 100644
--- a/src/pipecat/processors/aggregators/user_response.py
+++ b/src/pipecat/processors/aggregators/user_response.py
@@ -12,7 +12,8 @@ from pipecat.frames.frames import (
     TextFrame,
     TranscriptionFrame,
     UserStartedSpeakingFrame,
-    UserStoppedSpeakingFrame)
+    UserStoppedSpeakingFrame,
+)
 
 
 class ResponseAggregator(FrameProcessor):
@@ -49,7 +50,7 @@ class ResponseAggregator(FrameProcessor):
         start_frame,
         end_frame,
         accumulator_frame: TextFrame,
-        interim_accumulator_frame: TextFrame | None = None
+        interim_accumulator_frame: TextFrame | None = None,
     ):
         super().__init__()
 
diff --git a/src/pipecat/processors/aggregators/vision_image_frame.py b/src/pipecat/processors/aggregators/vision_image_frame.py
index 97f6b5ec8..d07337f06 100644
--- a/src/pipecat/processors/aggregators/vision_image_frame.py
+++ b/src/pipecat/processors/aggregators/vision_image_frame.py
@@ -4,12 +4,7 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-from pipecat.frames.frames import (
-    Frame,
-    InputImageRawFrame,
-    TextFrame,
-    VisionImageRawFrame
-)
+from pipecat.frames.frames import Frame, InputImageRawFrame, TextFrame, VisionImageRawFrame
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 
 
@@ -46,7 +41,8 @@ class VisionImageFrameAggregator(FrameProcessor):
                     text=self._describe_text,
                     image=frame.image,
                     size=frame.size,
-                    format=frame.format)
+                    format=frame.format,
+                )
                 await self.push_frame(frame)
                 self._describe_text = None
         else:
diff --git a/src/pipecat/processors/filters/frame_filter.py b/src/pipecat/processors/filters/frame_filter.py
index 9f2eb98c4..45927a604 100644
--- a/src/pipecat/processors/filters/frame_filter.py
+++ b/src/pipecat/processors/filters/frame_filter.py
@@ -11,7 +11,6 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 
 
 class FrameFilter(FrameProcessor):
-
     def __init__(self, types: List[type]):
         super().__init__()
         self._types = types
@@ -25,9 +24,11 @@ class FrameFilter(FrameProcessor):
             if isinstance(frame, t):
                 return True
 
-        return (isinstance(frame, AppFrame)
-                or isinstance(frame, ControlFrame)
-                or isinstance(frame, SystemFrame))
+        return (
+            isinstance(frame, AppFrame)
+            or isinstance(frame, ControlFrame)
+            or isinstance(frame, SystemFrame)
+        )
 
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
diff --git a/src/pipecat/processors/filters/function_filter.py b/src/pipecat/processors/filters/function_filter.py
index 421fcc80c..ba1f706a7 100644
--- a/src/pipecat/processors/filters/function_filter.py
+++ b/src/pipecat/processors/filters/function_filter.py
@@ -11,7 +11,6 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 
 
 class FunctionFilter(FrameProcessor):
-
     def __init__(self, filter: Callable[[Frame], Awaitable[bool]]):
         super().__init__()
         self._filter = filter
diff --git a/src/pipecat/processors/filters/wake_check_filter.py b/src/pipecat/processors/filters/wake_check_filter.py
index c3e0942ea..f1a7afbef 100644
--- a/src/pipecat/processors/filters/wake_check_filter.py
+++ b/src/pipecat/processors/filters/wake_check_filter.py
@@ -21,6 +21,7 @@ class WakeCheckFilter(FrameProcessor):
     after a wake phrase has been detected. It also has a keepalive timeout to allow for a brief
     period of continued conversation after a wake phrase has been detected.
     """
+
     class WakeState(Enum):
         IDLE = 1
         AWAKE = 2
@@ -38,8 +39,9 @@ class WakeCheckFilter(FrameProcessor):
         self._keepalive_timeout = keepalive_timeout
         self._wake_patterns = []
         for name in wake_phrases:
-            pattern = re.compile(r'\b' + r'\s*'.join(re.escape(word)
-                                 for word in name.split()) + r'\b', re.IGNORECASE)
+            pattern = re.compile(
+                r"\b" + r"\s*".join(re.escape(word) for word in name.split()) + r"\b", re.IGNORECASE
+            )
             self._wake_patterns.append(pattern)
 
     async def process_frame(self, frame: Frame, direction: FrameDirection):
@@ -57,7 +59,8 @@ class WakeCheckFilter(FrameProcessor):
                 if p.state == WakeCheckFilter.WakeState.AWAKE:
                     if time.time() - p.wake_timer < self._keepalive_timeout:
                         logger.debug(
-                            f"Wake phrase keepalive timeout has not expired. Pushing {frame}")
+                            f"Wake phrase keepalive timeout has not expired. Pushing {frame}"
+                        )
                         p.wake_timer = time.time()
                         await self.push_frame(frame)
                         return
@@ -73,7 +76,7 @@ class WakeCheckFilter(FrameProcessor):
                         # and modify the frame in place.
                         p.state = WakeCheckFilter.WakeState.AWAKE
                         p.wake_timer = time.time()
-                        frame.text = p.accumulator[match.start():]
+                        frame.text = p.accumulator[match.start() :]
                         p.accumulator = ""
                         await self.push_frame(frame)
                     else:
diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py
index 69c957c97..9dd92599e 100644
--- a/src/pipecat/processors/frame_processor.py
+++ b/src/pipecat/processors/frame_processor.py
@@ -17,10 +17,9 @@ from pipecat.frames.frames import (
     StartFrame,
     StartInterruptionFrame,
     StopInterruptionFrame,
-    SystemFrame)
-from pipecat.metrics.metrics import (
-    LLMTokenUsage,
-    MetricsData)
+    SystemFrame,
+)
+from pipecat.metrics.metrics import LLMTokenUsage, MetricsData
 from pipecat.processors.metrics.frame_processor_metrics import FrameProcessorMetrics
 from pipecat.utils.utils import obj_count, obj_id
 
@@ -33,15 +32,15 @@ class FrameDirection(Enum):
 
 
 class FrameProcessor:
-
     def __init__(
-            self,
-            *,
-            name: str | None = None,
-            metrics: FrameProcessorMetrics | None = None,
-            sync: bool = True,
-            loop: asyncio.AbstractEventLoop | None = None,
-            **kwargs):
+        self,
+        *,
+        name: str | None = None,
+        metrics: FrameProcessorMetrics | None = None,
+        sync: bool = True,
+        loop: asyncio.AbstractEventLoop | None = None,
+        **kwargs,
+    ):
         self.id: int = obj_id()
         self.name = name or f"{self.__class__.__name__}#{obj_count(self)}"
         self._parent: "FrameProcessor" | None = None
@@ -202,8 +201,7 @@ class FrameProcessor:
 
     def __create_push_task(self):
         self.__push_queue = asyncio.Queue()
-        self.__push_frame_task = self.get_event_loop(
-        ).create_task(self.__push_frame_task_handler())
+        self.__push_frame_task = self.get_event_loop().create_task(self.__push_frame_task_handler())
 
     async def __push_frame_task_handler(self):
         running = True
diff --git a/src/pipecat/processors/frameworks/langchain.py b/src/pipecat/processors/frameworks/langchain.py
index b6a24cfd2..c49dbaa76 100644
--- a/src/pipecat/processors/frameworks/langchain.py
+++ b/src/pipecat/processors/frameworks/langchain.py
@@ -11,7 +11,8 @@ from pipecat.frames.frames import (
     LLMFullResponseEndFrame,
     LLMFullResponseStartFrame,
     LLMMessagesFrame,
-    TextFrame)
+    TextFrame,
+)
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 
 from loguru import logger
@@ -20,9 +21,7 @@ try:
     from langchain_core.messages import AIMessageChunk
     from langchain_core.runnables import Runnable
 except ModuleNotFoundError as e:
-    logger.exception(
-        "In order to use Langchain, you need to `pip install pipecat-ai[langchain]`. "
-    )
+    logger.exception("In order to use Langchain, you need to `pip install pipecat-ai[langchain]`. ")
     raise Exception(f"Missing module: {e}")
 
 
diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py
index 66adb9ad0..0450102a7 100644
--- a/src/pipecat/processors/frameworks/rtvi.py
+++ b/src/pipecat/processors/frameworks/rtvi.py
@@ -24,7 +24,8 @@ from pipecat.frames.frames import (
     TransportMessageFrame,
     UserStartedSpeakingFrame,
     FunctionCallResultFrame,
-    UserStoppedSpeakingFrame)
+    UserStoppedSpeakingFrame,
+)
 from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 
@@ -39,8 +40,9 @@ ActionResult = Union[bool, int, float, str, list, dict]
 class RTVIServiceOption(BaseModel):
     name: str
     type: Literal["bool", "number", "string", "array", "object"]
-    handler: Callable[["RTVIProcessor", str, "RTVIServiceOptionConfig"],
-                      Awaitable[None]] = Field(exclude=True)
+    handler: Callable[["RTVIProcessor", str, "RTVIServiceOptionConfig"], Awaitable[None]] = Field(
+        exclude=True
+    )
 
 
 class RTVIService(BaseModel):
@@ -70,8 +72,9 @@ class RTVIAction(BaseModel):
     action: str
     arguments: List[RTVIActionArgument] = []
     result: Literal["bool", "number", "string", "array", "object"]
-    handler: Callable[["RTVIProcessor", str, Dict[str, Any]],
-                      Awaitable[ActionResult]] = Field(exclude=True)
+    handler: Callable[["RTVIProcessor", str, Dict[str, Any]], Awaitable[ActionResult]] = Field(
+        exclude=True
+    )
     _arguments_dict: Dict[str, RTVIActionArgument] = PrivateAttr(default={})
 
     def model_post_init(self, __context: Any) -> None:
@@ -122,6 +125,7 @@ class RTVIMessage(BaseModel):
     id: str
     data: Optional[Dict[str, Any]] = None
 
+
 #
 # Pipecat -> Client responses and messages.
 #
@@ -268,12 +272,13 @@ class RTVIProcessorParams(BaseModel):
 
 
 class RTVIProcessor(FrameProcessor):
-
-    def __init__(self,
-                 *,
-                 config: RTVIConfig = RTVIConfig(config=[]),
-                 params: RTVIProcessorParams = RTVIProcessorParams(),
-                 **kwargs):
+    def __init__(
+        self,
+        *,
+        config: RTVIConfig = RTVIConfig(config=[]),
+        params: RTVIProcessorParams = RTVIProcessorParams(),
+        **kwargs,
+    ):
         super().__init__(sync=False, **kwargs)
         self._config = config
         self._params = params
@@ -310,25 +315,23 @@ class RTVIProcessor(FrameProcessor):
             await self._maybe_send_bot_ready()
 
     async def handle_function_call(
-            self,
-            function_name: str,
-            tool_call_id: str,
-            arguments: dict,
-            llm: FrameProcessor,
-            context: OpenAILLMContext,
-            result_callback):
+        self,
+        function_name: str,
+        tool_call_id: str,
+        arguments: dict,
+        llm: FrameProcessor,
+        context: OpenAILLMContext,
+        result_callback,
+    ):
         fn = RTVILLMFunctionCallMessageData(
-            function_name=function_name,
-            tool_call_id=tool_call_id,
-            args=arguments)
+            function_name=function_name, tool_call_id=tool_call_id, args=arguments
+        )
         message = RTVILLMFunctionCallMessage(data=fn)
         await self._push_transport_message(message, exclude_none=False)
 
     async def handle_function_call_start(
-            self,
-            function_name: str,
-            llm: FrameProcessor,
-            context: OpenAILLMContext):
+        self, function_name: str, llm: FrameProcessor, context: OpenAILLMContext
+    ):
         fn = RTVILLMFunctionCallStartMessageData(function_name=function_name)
         message = RTVILLMFunctionCallStartMessage(data=fn)
         await self._push_transport_message(message, exclude_none=False)
@@ -357,10 +360,14 @@ class RTVIProcessor(FrameProcessor):
             # finish and the task finishes when EndFrame is processed.
             await self.push_frame(frame, direction)
             await self._stop(frame)
-        elif isinstance(frame, UserStartedSpeakingFrame) or isinstance(frame, UserStoppedSpeakingFrame):
+        elif isinstance(frame, UserStartedSpeakingFrame) or isinstance(
+            frame, UserStoppedSpeakingFrame
+        ):
             await self._handle_interruptions(frame)
             await self.push_frame(frame, direction)
-        elif isinstance(frame, BotStartedSpeakingFrame) or isinstance(frame, BotStoppedSpeakingFrame):
+        elif isinstance(frame, BotStartedSpeakingFrame) or isinstance(
+            frame, BotStoppedSpeakingFrame
+        ):
             await self._handle_bot_speaking(frame)
             await self.push_frame(frame, direction)
         # Data frames
@@ -393,8 +400,8 @@ class RTVIProcessor(FrameProcessor):
 
     async def _push_transport_message(self, model: BaseModel, exclude_none: bool = True):
         frame = TransportMessageFrame(
-            message=model.model_dump(exclude_none=exclude_none),
-            urgent=True)
+            message=model.model_dump(exclude_none=exclude_none), urgent=True
+        )
         await self.push_frame(frame)
 
     async def _handle_transcriptions(self, frame: Frame):
@@ -405,17 +412,15 @@ class RTVIProcessor(FrameProcessor):
         if isinstance(frame, TranscriptionFrame):
             message = RTVITranscriptionMessage(
                 data=RTVITranscriptionMessageData(
-                    text=frame.text,
-                    user_id=frame.user_id,
-                    timestamp=frame.timestamp,
-                    final=True))
+                    text=frame.text, user_id=frame.user_id, timestamp=frame.timestamp, final=True
+                )
+            )
         elif isinstance(frame, InterimTranscriptionFrame):
             message = RTVITranscriptionMessage(
                 data=RTVITranscriptionMessageData(
-                    text=frame.text,
-                    user_id=frame.user_id,
-                    timestamp=frame.timestamp,
-                    final=False))
+                    text=frame.text, user_id=frame.user_id, timestamp=frame.timestamp, final=False
+                )
+            )
 
         if message:
             await self._push_transport_message(message)
@@ -539,7 +544,8 @@ class RTVIProcessor(FrameProcessor):
             function_name=data.function_name,
             tool_call_id=data.tool_call_id,
             arguments=data.arguments,
-            result=data.result)
+            result=data.result,
+        )
         await self.push_frame(frame)
 
     async def _handle_action(self, request_id: str, data: RTVIActionRun):
@@ -567,9 +573,8 @@ class RTVIProcessor(FrameProcessor):
 
         message = RTVIBotReady(
             id=self._client_ready_id,
-            data=RTVIBotReadyData(
-                version=RTVI_PROTOCOL_VERSION,
-                config=self._config.config))
+            data=RTVIBotReadyData(version=RTVI_PROTOCOL_VERSION, config=self._config.config),
+        )
         await self._push_transport_message(message)
 
     async def _send_error_frame(self, frame: ErrorFrame):
diff --git a/src/pipecat/processors/gstreamer/pipeline_source.py b/src/pipecat/processors/gstreamer/pipeline_source.py
index f852dd641..9f8471153 100644
--- a/src/pipecat/processors/gstreamer/pipeline_source.py
+++ b/src/pipecat/processors/gstreamer/pipeline_source.py
@@ -15,20 +15,23 @@ from pipecat.frames.frames import (
     OutputAudioRawFrame,
     OutputImageRawFrame,
     StartFrame,
-    SystemFrame)
+    SystemFrame,
+)
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 
 from loguru import logger
 
 try:
     import gi
-    gi.require_version('Gst', '1.0')
-    gi.require_version('GstApp', '1.0')
+
+    gi.require_version("Gst", "1.0")
+    gi.require_version("GstApp", "1.0")
     from gi.repository import Gst, GstApp
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
-        "In order to use GStreamer, you need to `pip install pipecat-ai[gstreamer]`. Also, you need to install GStreamer in your system.")
+        "In order to use GStreamer, you need to `pip install pipecat-ai[gstreamer]`. Also, you need to install GStreamer in your system."
+    )
     raise Exception(f"Missing module: {e}")
 
 
@@ -120,7 +123,8 @@ class GStreamerPipelineSource(FrameProcessor):
         audioresample = Gst.ElementFactory.make("audioresample", None)
         audiocapsfilter = Gst.ElementFactory.make("capsfilter", None)
         audiocaps = Gst.Caps.from_string(
-            f"audio/x-raw,format=S16LE,rate={self._out_params.audio_sample_rate},channels={self._out_params.audio_channels},layout=interleaved")
+            f"audio/x-raw,format=S16LE,rate={self._out_params.audio_sample_rate},channels={self._out_params.audio_channels},layout=interleaved"
+        )
         audiocapsfilter.set_property("caps", audiocaps)
         appsink_audio = Gst.ElementFactory.make("appsink", None)
         appsink_audio.set_property("emit-signals", True)
@@ -152,7 +156,8 @@ class GStreamerPipelineSource(FrameProcessor):
         videoscale = Gst.ElementFactory.make("videoscale", None)
         videocapsfilter = Gst.ElementFactory.make("capsfilter", None)
         videocaps = Gst.Caps.from_string(
-            f"video/x-raw,format=RGB,width={self._out_params.video_width},height={self._out_params.video_height}")
+            f"video/x-raw,format=RGB,width={self._out_params.video_width},height={self._out_params.video_height}"
+        )
         videocapsfilter.set_property("caps", videocaps)
 
         appsink_video = Gst.ElementFactory.make("appsink", None)
@@ -182,9 +187,11 @@ class GStreamerPipelineSource(FrameProcessor):
     def _appsink_audio_new_sample(self, appsink: GstApp.AppSink):
         buffer = appsink.pull_sample().get_buffer()
         (_, info) = buffer.map(Gst.MapFlags.READ)
-        frame = OutputAudioRawFrame(audio=info.data,
-                                    sample_rate=self._out_params.audio_sample_rate,
-                                    num_channels=self._out_params.audio_channels)
+        frame = OutputAudioRawFrame(
+            audio=info.data,
+            sample_rate=self._out_params.audio_sample_rate,
+            num_channels=self._out_params.audio_channels,
+        )
         asyncio.run_coroutine_threadsafe(self.push_frame(frame), self.get_event_loop())
         buffer.unmap(info)
         return Gst.FlowReturn.OK
@@ -195,7 +202,8 @@ class GStreamerPipelineSource(FrameProcessor):
         frame = OutputImageRawFrame(
             image=info.data,
             size=(self._out_params.video_width, self._out_params.video_height),
-            format="RGB")
+            format="RGB",
+        )
         asyncio.run_coroutine_threadsafe(self.push_frame(frame), self.get_event_loop())
         buffer.unmap(info)
         return Gst.FlowReturn.OK
diff --git a/src/pipecat/processors/idle_frame_processor.py b/src/pipecat/processors/idle_frame_processor.py
index 42b81517e..576cb9087 100644
--- a/src/pipecat/processors/idle_frame_processor.py
+++ b/src/pipecat/processors/idle_frame_processor.py
@@ -19,12 +19,13 @@ class IdleFrameProcessor(FrameProcessor):
     """
 
     def __init__(
-            self,
-            *,
-            callback: Callable[["IdleFrameProcessor"], Awaitable[None]],
-            timeout: float,
-            types: List[type] = [],
-            **kwargs):
+        self,
+        *,
+        callback: Callable[["IdleFrameProcessor"], Awaitable[None]],
+        timeout: float,
+        types: List[type] = [],
+        **kwargs,
+    ):
         super().__init__(sync=False, **kwargs)
 
         self._callback = callback
diff --git a/src/pipecat/processors/logger.py b/src/pipecat/processors/logger.py
index 79334ba73..a26c67014 100644
--- a/src/pipecat/processors/logger.py
+++ b/src/pipecat/processors/logger.py
@@ -8,6 +8,7 @@ from pipecat.frames.frames import BotSpeakingFrame, Frame, AudioRawFrame, Transp
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from loguru import logger
 from typing import Optional
+
 logger = logger.opt(ansi=True)
 
 
@@ -19,7 +20,9 @@ class FrameLogger(FrameProcessor):
         ignored_frame_types: Optional[list] = [
             BotSpeakingFrame,
             AudioRawFrame,
-            TransportMessageFrame]):
+            TransportMessageFrame,
+        ],
+    ):
         super().__init__()
         self._prefix = prefix
         self._color = color
diff --git a/src/pipecat/processors/metrics/frame_processor_metrics.py b/src/pipecat/processors/metrics/frame_processor_metrics.py
index b9de3c2b4..52ea7e34c 100644
--- a/src/pipecat/processors/metrics/frame_processor_metrics.py
+++ b/src/pipecat/processors/metrics/frame_processor_metrics.py
@@ -7,7 +7,8 @@ from pipecat.metrics.metrics import (
     MetricsData,
     ProcessingMetricsData,
     TTFBMetricsData,
-    TTSUsageMetricsData)
+    TTSUsageMetricsData,
+)
 
 from loguru import logger
 
@@ -42,9 +43,8 @@ class FrameProcessorMetrics:
         value = time.time() - self._start_ttfb_time
         logger.debug(f"{self._processor_name()} TTFB: {value}")
         ttfb = TTFBMetricsData(
-            processor=self._processor_name(),
-            value=value,
-            model=self._model_name())
+            processor=self._processor_name(), value=value, model=self._model_name()
+        )
         self._start_ttfb_time = 0
         return MetricsFrame(data=[ttfb])
 
@@ -58,24 +58,24 @@ class FrameProcessorMetrics:
         value = time.time() - self._start_processing_time
         logger.debug(f"{self._processor_name()} processing time: {value}")
         processing = ProcessingMetricsData(
-            processor=self._processor_name(), value=value, model=self._model_name())
+            processor=self._processor_name(), value=value, model=self._model_name()
+        )
         self._start_processing_time = 0
         return MetricsFrame(data=[processing])
 
     async def start_llm_usage_metrics(self, tokens: LLMTokenUsage):
         logger.debug(
-            f"{self._processor_name()} prompt tokens: {tokens.prompt_tokens}, completion tokens: {tokens.completion_tokens}")
+            f"{self._processor_name()} prompt tokens: {tokens.prompt_tokens}, completion tokens: {tokens.completion_tokens}"
+        )
         value = LLMUsageMetricsData(
-            processor=self._processor_name(),
-            model=self._model_name(),
-            value=tokens)
+            processor=self._processor_name(), model=self._model_name(), value=tokens
+        )
         return MetricsFrame(data=[value])
 
     async def start_tts_usage_metrics(self, text: str):
         characters = TTSUsageMetricsData(
-            processor=self._processor_name(),
-            model=self._model_name(),
-            value=len(text))
+            processor=self._processor_name(), model=self._model_name(), value=len(text)
+        )
         logger.debug(f"{self._processor_name()} usage characters: {
                      characters.value}")
         return MetricsFrame(data=[characters])
diff --git a/src/pipecat/processors/metrics/sentry.py b/src/pipecat/processors/metrics/sentry.py
index da3057e76..e37dd9d44 100644
--- a/src/pipecat/processors/metrics/sentry.py
+++ b/src/pipecat/processors/metrics/sentry.py
@@ -3,14 +3,13 @@ from loguru import logger
 
 try:
     import sentry_sdk
+
     sentry_available = sentry_sdk.is_initialized()
     if not sentry_available:
-        logger.warning(
-            "Sentry SDK not initialized. Sentry features will be disabled.")
+        logger.warning("Sentry SDK not initialized. Sentry features will be disabled.")
 except ImportError:
     sentry_available = False
-    logger.warning(
-        "Sentry SDK not installed. Sentry features will be disabled.")
+    logger.warning("Sentry SDK not installed. Sentry features will be disabled.")
 
 from pipecat.processors.metrics.frame_processor_metrics import FrameProcessorMetrics
 
@@ -28,7 +27,7 @@ class SentryMetrics(FrameProcessorMetrics):
                 self._ttfb_metrics_span = sentry_sdk.start_span(
                     op="ttfb",
                     description=f"TTFB for {self._processor_name()}",
-                    start_timestamp=self._start_ttfb_time
+                    start_timestamp=self._start_ttfb_time,
                 )
                 logger.debug(f"Sentry Span ID: {self._ttfb_metrics_span.span_id} Description: {
                              self._ttfb_metrics_span.description} started.")
@@ -45,7 +44,7 @@ class SentryMetrics(FrameProcessorMetrics):
             self._processing_metrics_span = sentry_sdk.start_span(
                 op="processing",
                 description=f"Processing for {self._processor_name()}",
-                start_timestamp=self._start_processing_time
+                start_timestamp=self._start_processing_time,
             )
             logger.debug(f"Sentry Span ID: {self._processing_metrics_span.span_id} Description: {
                          self._processing_metrics_span.description} started.")
diff --git a/src/pipecat/processors/user_idle_processor.py b/src/pipecat/processors/user_idle_processor.py
index 36c394a5d..31d49cf5a 100644
--- a/src/pipecat/processors/user_idle_processor.py
+++ b/src/pipecat/processors/user_idle_processor.py
@@ -12,7 +12,8 @@ from pipecat.frames.frames import (
     BotSpeakingFrame,
     Frame,
     UserStartedSpeakingFrame,
-    UserStoppedSpeakingFrame)
+    UserStoppedSpeakingFrame,
+)
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 
 
@@ -24,11 +25,12 @@ class UserIdleProcessor(FrameProcessor):
     """
 
     def __init__(
-            self,
-            *,
-            callback: Callable[["UserIdleProcessor"], Awaitable[None]],
-            timeout: float,
-            **kwargs):
+        self,
+        *,
+        callback: Callable[["UserIdleProcessor"], Awaitable[None]],
+        timeout: float,
+        **kwargs,
+    ):
         super().__init__(sync=False, **kwargs)
 
         self._callback = callback
diff --git a/src/pipecat/serializers/base_serializer.py b/src/pipecat/serializers/base_serializer.py
index 83613d9ce..96f5fd214 100644
--- a/src/pipecat/serializers/base_serializer.py
+++ b/src/pipecat/serializers/base_serializer.py
@@ -10,7 +10,6 @@ from pipecat.frames.frames import Frame
 
 
 class FrameSerializer(ABC):
-
     @abstractmethod
     def serialize(self, frame: Frame) -> str | bytes | None:
         pass
diff --git a/src/pipecat/serializers/livekit.py b/src/pipecat/serializers/livekit.py
index fec5243f5..29d32b861 100644
--- a/src/pipecat/serializers/livekit.py
+++ b/src/pipecat/serializers/livekit.py
@@ -7,10 +7,7 @@
 import ctypes
 import pickle
 
-from pipecat.frames.frames import (
-    Frame,
-    InputAudioRawFrame,
-    OutputAudioRawFrame)
+from pipecat.frames.frames import Frame, InputAudioRawFrame, OutputAudioRawFrame
 from pipecat.serializers.base_serializer import FrameSerializer
 
 from loguru import logger
@@ -19,8 +16,7 @@ try:
     from livekit.rtc import AudioFrame
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
-    logger.error(
-        "In order to use LiveKit, you need to `pip install pipecat-ai[livekit]`.")
+    logger.error("In order to use LiveKit, you need to `pip install pipecat-ai[livekit]`.")
     raise Exception(f"Missing module: {e}")
 
 
@@ -37,7 +33,7 @@ class LivekitFrameSerializer(FrameSerializer):
         return pickle.dumps(audio_frame)
 
     def deserialize(self, data: str | bytes) -> Frame | None:
-        audio_frame: AudioFrame = pickle.loads(data)['frame']
+        audio_frame: AudioFrame = pickle.loads(data)["frame"]
         return InputAudioRawFrame(
             audio=bytes(audio_frame.data),
             sample_rate=audio_frame.sample_rate,
diff --git a/src/pipecat/serializers/protobuf.py b/src/pipecat/serializers/protobuf.py
index 6ae1b0c03..2adf403a5 100644
--- a/src/pipecat/serializers/protobuf.py
+++ b/src/pipecat/serializers/protobuf.py
@@ -8,11 +8,7 @@ import dataclasses
 
 import pipecat.frames.protobufs.frames_pb2 as frame_protos
 
-from pipecat.frames.frames import (
-    AudioRawFrame,
-    Frame,
-    TextFrame,
-    TranscriptionFrame)
+from pipecat.frames.frames import AudioRawFrame, Frame, TextFrame, TranscriptionFrame
 from pipecat.serializers.base_serializer import FrameSerializer
 
 from loguru import logger
@@ -22,7 +18,7 @@ class ProtobufFrameSerializer(FrameSerializer):
     SERIALIZABLE_TYPES = {
         TextFrame: "text",
         AudioRawFrame: "audio",
-        TranscriptionFrame: "transcription"
+        TranscriptionFrame: "transcription",
     }
 
     SERIALIZABLE_FIELDS = {v: k for k, v in SERIALIZABLE_TYPES.items()}
diff --git a/src/pipecat/serializers/twilio.py b/src/pipecat/serializers/twilio.py
index ed2905a40..c0d4c0c47 100644
--- a/src/pipecat/serializers/twilio.py
+++ b/src/pipecat/serializers/twilio.py
@@ -9,10 +9,7 @@ import json
 
 from pydantic import BaseModel
 
-from pipecat.frames.frames import (
-    AudioRawFrame,
-    Frame,
-    StartInterruptionFrame)
+from pipecat.frames.frames import AudioRawFrame, Frame, StartInterruptionFrame
 from pipecat.serializers.base_serializer import FrameSerializer
 from pipecat.utils.audio import ulaw_to_pcm, pcm_to_ulaw
 
@@ -30,15 +27,12 @@ class TwilioFrameSerializer(FrameSerializer):
         if isinstance(frame, AudioRawFrame):
             data = frame.audio
 
-            serialized_data = pcm_to_ulaw(
-                data, frame.sample_rate, self._params.twilio_sample_rate)
+            serialized_data = pcm_to_ulaw(data, frame.sample_rate, self._params.twilio_sample_rate)
             payload = base64.b64encode(serialized_data).decode("utf-8")
             answer = {
                 "event": "media",
                 "streamSid": self._stream_sid,
-                "media": {
-                    "payload": payload
-                }
+                "media": {"payload": payload},
             }
 
             return json.dumps(answer)
@@ -57,11 +51,9 @@ class TwilioFrameSerializer(FrameSerializer):
             payload = base64.b64decode(payload_base64)
 
             deserialized_data = ulaw_to_pcm(
-                payload,
-                self._params.twilio_sample_rate,
-                self._params.sample_rate)
+                payload, self._params.twilio_sample_rate, self._params.sample_rate
+            )
             audio_frame = AudioRawFrame(
-                audio=deserialized_data,
-                num_channels=1,
-                sample_rate=self._params.sample_rate)
+                audio=deserialized_data, num_channels=1, sample_rate=self._params.sample_rate
+            )
             return audio_frame
diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index dc75b9793..cdad3de52 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -31,7 +31,7 @@ from pipecat.frames.frames import (
     TTSVoiceUpdateFrame,
     TextFrame,
     UserImageRequestFrame,
-    VisionImageRawFrame
+    VisionImageRawFrame,
 )
 from pipecat.metrics.metrics import MetricsData
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
@@ -114,12 +114,8 @@ class LLMService(AIService):
         return function_name in self._callbacks.keys()
 
     async def call_function(
-            self,
-            *,
-            context: OpenAILLMContext,
-            tool_call_id: str,
-            function_name: str,
-            arguments: str) -> None:
+        self, *, context: OpenAILLMContext, tool_call_id: str, function_name: str, arguments: str
+    ) -> None:
         f = None
         if function_name in self._callbacks.keys():
             f = self._callbacks[function_name]
@@ -128,11 +124,8 @@ class LLMService(AIService):
         else:
             return None
         await context.call_function(
-            f,
-            function_name=function_name,
-            tool_call_id=tool_call_id,
-            arguments=arguments,
-            llm=self)
+            f, function_name=function_name, tool_call_id=tool_call_id, arguments=arguments, llm=self
+        )
 
     # QUESTION FOR CB: maybe this isn't needed anymore?
     async def call_start_function(self, context: OpenAILLMContext, function_name: str):
@@ -142,21 +135,23 @@ class LLMService(AIService):
             return await self._start_callbacks[None](function_name, self, context)
 
     async def request_image_frame(self, user_id: str, *, text_content: str | None = None):
-        await self.push_frame(UserImageRequestFrame(user_id=user_id, context=text_content),
-                              FrameDirection.UPSTREAM)
+        await self.push_frame(
+            UserImageRequestFrame(user_id=user_id, context=text_content), FrameDirection.UPSTREAM
+        )
 
 
 class TTSService(AIService):
     def __init__(
-            self,
-            *,
-            aggregate_sentences: bool = True,
-            # if True, TTSService will push TextFrames and LLMFullResponseEndFrames,
-            # otherwise subclass must do it
-            push_text_frames: bool = True,
-            # TTS output sample rate
-            sample_rate: int = 16000,
-            **kwargs):
+        self,
+        *,
+        aggregate_sentences: bool = True,
+        # if True, TTSService will push TextFrames and LLMFullResponseEndFrames,
+        # otherwise subclass must do it
+        push_text_frames: bool = True,
+        # TTS output sample rate
+        sample_rate: int = 16000,
+        **kwargs,
+    ):
         super().__init__(**kwargs)
         self._aggregate_sentences: bool = aggregate_sentences
         self._push_text_frames: bool = push_text_frames
@@ -247,12 +242,13 @@ class TTSService(AIService):
 
 class AsyncTTSService(TTSService):
     def __init__(
-            self,
-            # if True, TTSService will push TTSStoppedFrames, otherwise subclass must do it
-            push_stop_frames: bool = False,
-            # if push_stop_frames is True, wait for this idle period before pushing TTSStoppedFrame
-            stop_frame_timeout_s: float = 1.0,
-            **kwargs):
+        self,
+        # if True, TTSService will push TTSStoppedFrames, otherwise subclass must do it
+        push_stop_frames: bool = False,
+        # if push_stop_frames is True, wait for this idle period before pushing TTSStoppedFrame
+        stop_frame_timeout_s: float = 1.0,
+        **kwargs,
+    ):
         super().__init__(sync=False, **kwargs)
         self._push_stop_frames: bool = push_stop_frames
         self._stop_frame_timeout_s: float = stop_frame_timeout_s
@@ -286,10 +282,11 @@ class AsyncTTSService(TTSService):
         await super().push_frame(frame, direction)
 
         if self._push_stop_frames and (
-                isinstance(frame, StartInterruptionFrame) or
-                isinstance(frame, TTSStartedFrame) or
-                isinstance(frame, TTSAudioRawFrame) or
-                isinstance(frame, TTSStoppedFrame)):
+            isinstance(frame, StartInterruptionFrame)
+            or isinstance(frame, TTSStartedFrame)
+            or isinstance(frame, TTSAudioRawFrame)
+            or isinstance(frame, TTSStoppedFrame)
+        ):
             await self._stop_frame_queue.put(frame)
 
     async def _stop_frame_handler(self):
@@ -297,8 +294,9 @@ class AsyncTTSService(TTSService):
             has_started = False
             while True:
                 try:
-                    frame = await asyncio.wait_for(self._stop_frame_queue.get(),
-                                                   self._stop_frame_timeout_s)
+                    frame = await asyncio.wait_for(
+                        self._stop_frame_queue.get(), self._stop_frame_timeout_s
+                    )
                     if isinstance(frame, TTSStartedFrame):
                         has_started = True
                     elif isinstance(frame, (TTSStoppedFrame, StartInterruptionFrame)):
@@ -327,7 +325,7 @@ class AsyncWordTTSService(AsyncTTSService):
         self._word_timestamps = []
 
     async def add_word_timestamps(self, word_times: List[Tuple[str, float]]):
-        for (word, timestamp) in word_times:
+        for word, timestamp in word_times:
             await self._words_queue.put((word, seconds_to_nanoseconds(timestamp)))
 
     async def stop(self, frame: EndFrame):
@@ -414,14 +412,16 @@ class SegmentedSTTService(STTService):
 
     """
 
-    def __init__(self,
-                 *,
-                 min_volume: float = 0.6,
-                 max_silence_secs: float = 0.3,
-                 max_buffer_secs: float = 1.5,
-                 sample_rate: int = 16000,
-                 num_channels: int = 1,
-                 **kwargs):
+    def __init__(
+        self,
+        *,
+        min_volume: float = 0.6,
+        max_silence_secs: float = 0.3,
+        max_buffer_secs: float = 1.5,
+        sample_rate: int = 16000,
+        num_channels: int = 1,
+        **kwargs,
+    ):
         super().__init__(**kwargs)
         self._min_volume = min_volume
         self._max_silence_secs = max_silence_secs
@@ -450,7 +450,8 @@ class SegmentedSTTService(STTService):
         silence_secs = self._silence_num_frames / self._sample_rate
         buffer_secs = self._wave.getnframes() / self._sample_rate
         if self._content.tell() > 0 and (
-                buffer_secs > self._max_buffer_secs or silence_secs > self._max_silence_secs):
+            buffer_secs > self._max_buffer_secs or silence_secs > self._max_silence_secs
+        ):
             self._silence_num_frames = 0
             self._wave.close()
             self._content.seek(0)
@@ -477,7 +478,6 @@ class SegmentedSTTService(STTService):
 
 
 class ImageGenService(AIService):
-
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
 
diff --git a/src/pipecat/services/anthropic.py b/src/pipecat/services/anthropic.py
index 421196e2c..8b8e187ea 100644
--- a/src/pipecat/services/anthropic.py
+++ b/src/pipecat/services/anthropic.py
@@ -28,18 +28,18 @@ from pipecat.frames.frames import (
     LLMFullResponseEndFrame,
     FunctionCallResultFrame,
     FunctionCallInProgressFrame,
-    StartInterruptionFrame
+    StartInterruptionFrame,
 )
 from pipecat.metrics.metrics import LLMTokenUsage
 from pipecat.processors.frame_processor import FrameDirection
 from pipecat.services.ai_services import LLMService
 from pipecat.processors.aggregators.openai_llm_context import (
     OpenAILLMContext,
-    OpenAILLMContextFrame
+    OpenAILLMContextFrame,
 )
 from pipecat.processors.aggregators.llm_response import (
     LLMUserContextAggregator,
-    LLMAssistantContextAggregator
+    LLMAssistantContextAggregator,
 )
 
 from loguru import logger
@@ -49,8 +49,9 @@ try:
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
-        "In order to use Anthropic, you need to `pip install pipecat-ai[anthropic]`. " +
-        "Also, set `ANTHROPIC_API_KEY` environment variable.")
+        "In order to use Anthropic, you need to `pip install pipecat-ai[anthropic]`. "
+        + "Also, set `ANTHROPIC_API_KEY` environment variable."
+    )
     raise Exception(f"Missing module: {e}")
 
 
@@ -62,19 +63,19 @@ class AnthropicImageMessageFrame(Frame):
 
 @dataclass
 class AnthropicContextAggregatorPair:
-    _user: 'AnthropicUserContextAggregator'
-    _assistant: 'AnthropicAssistantContextAggregator'
+    _user: "AnthropicUserContextAggregator"
+    _assistant: "AnthropicAssistantContextAggregator"
 
-    def user(self) -> 'AnthropicUserContextAggregator':
+    def user(self) -> "AnthropicUserContextAggregator":
         return self._user
 
-    def assistant(self) -> 'AnthropicAssistantContextAggregator':
+    def assistant(self) -> "AnthropicAssistantContextAggregator":
         return self._assistant
 
 
 class AnthropicLLMService(LLMService):
-    """This class implements inference with Anthropic's AI models
-    """
+    """This class implements inference with Anthropic's AI models"""
+
     class InputParams(BaseModel):
         enable_prompt_caching_beta: Optional[bool] = False
         max_tokens: Optional[int] = Field(default_factory=lambda: 4096, ge=1)
@@ -84,12 +85,13 @@ class AnthropicLLMService(LLMService):
         extra: Optional[Dict[str, Any]] = Field(default_factory=dict)
 
     def __init__(
-            self,
-            *,
-            api_key: str,
-            model: str = "claude-3-5-sonnet-20240620",
-            params: InputParams = InputParams(),
-            **kwargs):
+        self,
+        *,
+        api_key: str,
+        model: str = "claude-3-5-sonnet-20240620",
+        params: InputParams = InputParams(),
+        **kwargs,
+    ):
         super().__init__(**kwargs)
         self._client = AsyncAnthropic(api_key=api_key)
         self.set_model_name(model)
@@ -111,10 +113,7 @@ class AnthropicLLMService(LLMService):
     def create_context_aggregator(context: OpenAILLMContext) -> AnthropicContextAggregatorPair:
         user = AnthropicUserContextAggregator(context)
         assistant = AnthropicAssistantContextAggregator(user)
-        return AnthropicContextAggregatorPair(
-            _user=user,
-            _assistant=assistant
-        )
+        return AnthropicContextAggregatorPair(_user=user, _assistant=assistant)
 
     async def set_enable_prompt_caching_beta(self, enable_prompt_caching_beta: bool):
         logger.debug(f"Switching LLM enable_prompt_caching_beta to: [{enable_prompt_caching_beta}]")
@@ -157,7 +156,8 @@ class AnthropicLLMService(LLMService):
             await self.start_processing_metrics()
 
             logger.debug(
-                f"Generating chat: {context.system} | {context.get_messages_for_logging()}")
+                f"Generating chat: {context.system} | {context.get_messages_for_logging()}"
+            )
 
             messages = context.messages
             if self._enable_prompt_caching_beta:
@@ -178,7 +178,7 @@ class AnthropicLLMService(LLMService):
                 "stream": True,
                 "temperature": self._temperature,
                 "top_k": self._top_k,
-                "top_p": self._top_p
+                "top_p": self._top_p,
             }
 
             params.update(self._extra)
@@ -189,54 +189,70 @@ class AnthropicLLMService(LLMService):
 
             # Function calling
             tool_use_block = None
-            json_accumulator = ''
+            json_accumulator = ""
 
             async for event in response:
                 # logger.debug(f"Anthropic LLM event: {event}")
 
                 # Aggregate streaming content, create frames, trigger events
 
-                if (event.type == "content_block_delta"):
-                    if hasattr(event.delta, 'text'):
+                if event.type == "content_block_delta":
+                    if hasattr(event.delta, "text"):
                         await self.push_frame(TextFrame(event.delta.text))
                         completion_tokens_estimate += self._estimate_tokens(event.delta.text)
-                    elif hasattr(event.delta, 'partial_json') and tool_use_block:
+                    elif hasattr(event.delta, "partial_json") and tool_use_block:
                         json_accumulator += event.delta.partial_json
                         completion_tokens_estimate += self._estimate_tokens(
-                            event.delta.partial_json)
-                elif (event.type == "content_block_start"):
+                            event.delta.partial_json
+                        )
+                elif event.type == "content_block_start":
                     if event.content_block.type == "tool_use":
                         tool_use_block = event.content_block
-                        json_accumulator = ''
-                elif ((event.type == "message_delta" and
-                      hasattr(event.delta, 'stop_reason')
-                      and event.delta.stop_reason == 'tool_use')):
+                        json_accumulator = ""
+                elif (
+                    event.type == "message_delta"
+                    and hasattr(event.delta, "stop_reason")
+                    and event.delta.stop_reason == "tool_use"
+                ):
                     if tool_use_block:
-                        await self.call_function(context=context,
-                                                 tool_call_id=tool_use_block.id,
-                                                 function_name=tool_use_block.name,
-                                                 arguments=json.loads(json_accumulator) if json_accumulator else dict()
-                                                 )
+                        await self.call_function(
+                            context=context,
+                            tool_call_id=tool_use_block.id,
+                            function_name=tool_use_block.name,
+                            arguments=json.loads(json_accumulator) if json_accumulator else dict(),
+                        )
 
                 # Calculate usage. Do this here in its own if statement, because there may be usage
                 # data embedded in messages that we do other processing for, above.
                 if hasattr(event, "usage"):
-                    prompt_tokens += event.usage.input_tokens if hasattr(
-                        event.usage, "input_tokens") else 0
-                    completion_tokens += event.usage.output_tokens if hasattr(
-                        event.usage, "output_tokens") else 0
+                    prompt_tokens += (
+                        event.usage.input_tokens if hasattr(event.usage, "input_tokens") else 0
+                    )
+                    completion_tokens += (
+                        event.usage.output_tokens if hasattr(event.usage, "output_tokens") else 0
+                    )
                 elif hasattr(event, "message") and hasattr(event.message, "usage"):
-                    prompt_tokens += event.message.usage.input_tokens if hasattr(
-                        event.message.usage, "input_tokens") else 0
-                    completion_tokens += event.message.usage.output_tokens if hasattr(
-                        event.message.usage, "output_tokens") else 0
+                    prompt_tokens += (
+                        event.message.usage.input_tokens
+                        if hasattr(event.message.usage, "input_tokens")
+                        else 0
+                    )
+                    completion_tokens += (
+                        event.message.usage.output_tokens
+                        if hasattr(event.message.usage, "output_tokens")
+                        else 0
+                    )
                     if hasattr(event.message.usage, "cache_creation_input_tokens"):
-                        cache_creation_input_tokens += event.message.usage.cache_creation_input_tokens
+                        cache_creation_input_tokens += (
+                            event.message.usage.cache_creation_input_tokens
+                        )
                         logger.debug(f"Cache creation input tokens: {cache_creation_input_tokens}")
                     if hasattr(event.message.usage, "cache_read_input_tokens"):
                         cache_read_input_tokens += event.message.usage.cache_read_input_tokens
                         logger.debug(f"Cache read input tokens: {cache_read_input_tokens}")
-                    total_input_tokens = prompt_tokens + cache_creation_input_tokens + cache_read_input_tokens
+                    total_input_tokens = (
+                        prompt_tokens + cache_creation_input_tokens + cache_read_input_tokens
+                    )
                     if total_input_tokens >= 1024:
                         context.turns_above_cache_threshold += 1
 
@@ -251,12 +267,16 @@ class AnthropicLLMService(LLMService):
         finally:
             await self.stop_processing_metrics()
             await self.push_frame(LLMFullResponseEndFrame())
-            comp_tokens = completion_tokens if not use_completion_tokens_estimate else completion_tokens_estimate
+            comp_tokens = (
+                completion_tokens
+                if not use_completion_tokens_estimate
+                else completion_tokens_estimate
+            )
             await self._report_usage_metrics(
                 prompt_tokens=prompt_tokens,
                 completion_tokens=comp_tokens,
                 cache_creation_input_tokens=cache_creation_input_tokens,
-                cache_read_input_tokens=cache_read_input_tokens
+                cache_read_input_tokens=cache_read_input_tokens,
             )
 
     async def process_frame(self, frame: Frame, direction: FrameDirection):
@@ -286,21 +306,27 @@ class AnthropicLLMService(LLMService):
             await self._process_context(context)
 
     def _estimate_tokens(self, text: str) -> int:
-        return int(len(re.split(r'[^\w]+', text)) * 1.3)
+        return int(len(re.split(r"[^\w]+", text)) * 1.3)
 
     async def _report_usage_metrics(
-            self,
-            prompt_tokens: int,
-            completion_tokens: int,
-            cache_creation_input_tokens: int,
-            cache_read_input_tokens: int):
-        if prompt_tokens or completion_tokens or cache_creation_input_tokens or cache_read_input_tokens:
+        self,
+        prompt_tokens: int,
+        completion_tokens: int,
+        cache_creation_input_tokens: int,
+        cache_read_input_tokens: int,
+    ):
+        if (
+            prompt_tokens
+            or completion_tokens
+            or cache_creation_input_tokens
+            or cache_read_input_tokens
+        ):
             tokens = LLMTokenUsage(
                 prompt_tokens=prompt_tokens,
                 completion_tokens=completion_tokens,
                 cache_creation_input_tokens=cache_creation_input_tokens,
                 cache_read_input_tokens=cache_read_input_tokens,
-                total_tokens=prompt_tokens + completion_tokens
+                total_tokens=prompt_tokens + completion_tokens,
             )
             await self.start_llm_usage_metrics(tokens)
 
@@ -312,7 +338,7 @@ class AnthropicLLMContext(OpenAILLMContext):
         tools: list[dict] | None = None,
         tool_choice: dict | None = None,
         *,
-        system: str | NotGiven = NOT_GIVEN
+        system: str | NotGiven = NOT_GIVEN,
     ):
         super().__init__(messages=messages, tools=tools, tool_choice=tool_choice)
         self._user_image_request_context = {}
@@ -345,10 +371,8 @@ class AnthropicLLMContext(OpenAILLMContext):
     def from_image_frame(cls, frame: VisionImageRawFrame) -> "AnthropicLLMContext":
         context = cls()
         context.add_image_frame_message(
-            format=frame.format,
-            size=frame.size,
-            image=frame.image,
-            text=frame.text)
+            format=frame.format, size=frame.size, image=frame.image, text=frame.text
+        )
         return context
 
     def set_messages(self, messages: List):
@@ -357,18 +381,23 @@ class AnthropicLLMContext(OpenAILLMContext):
         self._restructure_from_openai_messages()
 
     def add_image_frame_message(
-            self, *, format: str, size: tuple[int, int], image: bytes, text: str = None):
+        self, *, format: str, size: tuple[int, int], image: bytes, text: str = None
+    ):
         buffer = io.BytesIO()
         Image.frombytes(format, size, image).save(buffer, format="JPEG")
         encoded_image = base64.b64encode(buffer.getvalue()).decode("utf-8")
 
         # Anthropic docs say that the image should be the first content block in the message.
-        content = [{"type": "image",
-                    "source": {
-                        "type": "base64",
-                        "media_type": "image/jpeg",
-                        "data": encoded_image,
-                    }}]
+        content = [
+            {
+                "type": "image",
+                "source": {
+                    "type": "base64",
+                    "media_type": "image/jpeg",
+                    "data": encoded_image,
+                },
+            }
+        ]
         if text:
             content.append({"type": "text", "text": text})
         self.add_message({"role": "user", "content": content})
@@ -382,8 +411,9 @@ class AnthropicLLMContext(OpenAILLMContext):
                     # if the last message has just a content string, convert it to a list
                     # in the proper format
                     if isinstance(self.messages[-1]["content"], str):
-                        self.messages[-1]["content"] = [{"type": "text",
-                                                         "text": self.messages[-1]["content"]}]
+                        self.messages[-1]["content"] = [
+                            {"type": "text", "text": self.messages[-1]["content"]}
+                        ]
                     # if this message has just a content string, convert it to a list
                     # in the proper format
                     if isinstance(message["content"], str):
@@ -404,8 +434,11 @@ class AnthropicLLMContext(OpenAILLMContext):
                 if isinstance(messages[-1]["content"], str):
                     messages[-1]["content"] = [{"type": "text", "text": messages[-1]["content"]}]
                 messages[-1]["content"][-1]["cache_control"] = {"type": "ephemeral"}
-            if (self.turns_above_cache_threshold >= 2 and
-                    len(messages) > 2 and messages[-3]["role"] == "user"):
+            if (
+                self.turns_above_cache_threshold >= 2
+                and len(messages) > 2
+                and messages[-3]["role"] == "user"
+            ):
                 if isinstance(messages[-3]["content"], str):
                     messages[-3]["content"] = [{"type": "text", "text": messages[-3]["content"]}]
                 messages[-3]["content"][-1]["cache_control"] = {"type": "ephemeral"}
@@ -459,12 +492,13 @@ class AnthropicUserContextAggregator(LLMUserContextAggregator):
                 # The LLM sends a UserImageRequestFrame upstream. Cache any context provided with
                 # that frame so we can use it when we assemble the image message in the assistant
                 # context aggregator.
-                if (frame.context):
+                if frame.context:
                     if isinstance(frame.context, str):
                         self._context._user_image_request_context[frame.user_id] = frame.context
                     else:
                         logger.error(
-                            f"Unexpected UserImageRequestFrame context type: {type(frame.context)}")
+                            f"Unexpected UserImageRequestFrame context type: {type(frame.context)}"
+                        )
                         del self._context._user_image_request_context[frame.user_id]
                 else:
                     if frame.user_id in self._context._user_image_request_context:
@@ -481,6 +515,7 @@ class AnthropicUserContextAggregator(LLMUserContextAggregator):
         except Exception as e:
             logger.error(f"Error processing frame: {e}")
 
+
 #
 # Claude returns a text content block along with a tool use content block. This works quite nicely
 # with streaming. We get the text first, so we can start streaming it right away. Then we get the
@@ -508,13 +543,16 @@ class AnthropicAssistantContextAggregator(LLMAssistantContextAggregator):
         elif isinstance(frame, FunctionCallInProgressFrame):
             self._function_call_in_progress = frame
         elif isinstance(frame, FunctionCallResultFrame):
-            if (self._function_call_in_progress and self._function_call_in_progress.tool_call_id ==
-                    frame.tool_call_id):
+            if (
+                self._function_call_in_progress
+                and self._function_call_in_progress.tool_call_id == frame.tool_call_id
+            ):
                 self._function_call_in_progress = None
                 self._function_call_result = frame
             else:
                 logger.warning(
-                    "FunctionCallResultFrame tool_call_id != InProgressFrame tool_call_id")
+                    "FunctionCallResultFrame tool_call_id != InProgressFrame tool_call_id"
+                )
                 self._function_call_in_progress = None
                 self._function_call_result = None
         elif isinstance(frame, AnthropicImageMessageFrame):
@@ -534,31 +572,32 @@ class AnthropicAssistantContextAggregator(LLMAssistantContextAggregator):
                 frame = self._function_call_result
                 self._function_call_result = None
                 if frame.result:
-                    self._context.add_message({
-                        "role": "assistant",
-                        "content": [
-                            {
-                                "type": "text",
-                                "text": aggregation
-                            },
-                            {
-                                "type": "tool_use",
-                                "id": frame.tool_call_id,
-                                "name": frame.function_name,
-                                "input": frame.arguments
-                            }
-                        ]
-                    })
-                    self._context.add_message({
-                        "role": "user",
-                        "content": [
-                            {
-                                "type": "tool_result",
-                                "tool_use_id": frame.tool_call_id,
-                                "content": json.dumps(frame.result)
-                            }
-                        ]
-                    })
+                    self._context.add_message(
+                        {
+                            "role": "assistant",
+                            "content": [
+                                {"type": "text", "text": aggregation},
+                                {
+                                    "type": "tool_use",
+                                    "id": frame.tool_call_id,
+                                    "name": frame.function_name,
+                                    "input": frame.arguments,
+                                },
+                            ],
+                        }
+                    )
+                    self._context.add_message(
+                        {
+                            "role": "user",
+                            "content": [
+                                {
+                                    "type": "tool_result",
+                                    "tool_use_id": frame.tool_call_id,
+                                    "content": json.dumps(frame.result),
+                                }
+                            ],
+                        }
+                    )
                     run_llm = True
             else:
                 self._context.add_message({"role": "assistant", "content": aggregation})
@@ -570,7 +609,8 @@ class AnthropicAssistantContextAggregator(LLMAssistantContextAggregator):
                     format=frame.user_image_raw_frame.format,
                     size=frame.user_image_raw_frame.size,
                     image=frame.user_image_raw_frame.image,
-                    text=frame.text)
+                    text=frame.text,
+                )
                 run_llm = True
 
             if run_llm:
diff --git a/src/pipecat/services/azure.py b/src/pipecat/services/azure.py
index 36c8bc1bb..24e73cd2a 100644
--- a/src/pipecat/services/azure.py
+++ b/src/pipecat/services/azure.py
@@ -21,7 +21,8 @@ from pipecat.frames.frames import (
     TTSStartedFrame,
     TTSStoppedFrame,
     TranscriptionFrame,
-    URLImageRawFrame)
+    URLImageRawFrame,
+)
 from pipecat.metrics.metrics import TTSUsageMetricsData
 from pipecat.processors.frame_processor import FrameDirection
 from pipecat.services.ai_services import STTService, TTSService, ImageGenService
@@ -45,18 +46,15 @@ try:
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
-        "In order to use Azure, you need to `pip install pipecat-ai[azure]`. Also, set `AZURE_SPEECH_API_KEY` and `AZURE_SPEECH_REGION` environment variables.")
+        "In order to use Azure, you need to `pip install pipecat-ai[azure]`. Also, set `AZURE_SPEECH_API_KEY` and `AZURE_SPEECH_REGION` environment variables."
+    )
     raise Exception(f"Missing module: {e}")
 
 
 class AzureLLMService(BaseOpenAILLMService):
     def __init__(
-            self,
-            *,
-            api_key: str,
-            endpoint: str,
-            model: str,
-            api_version: str = "2023-12-01-preview"):
+        self, *, api_key: str, endpoint: str, model: str, api_version: str = "2023-12-01-preview"
+    ):
         # Initialize variables before calling parent __init__() because that
         # will call create_client() and we need those values there.
         self._endpoint = endpoint
@@ -73,13 +71,14 @@ class AzureLLMService(BaseOpenAILLMService):
 
 class AzureTTSService(TTSService):
     def __init__(
-            self,
-            *,
-            api_key: str,
-            region: str,
-            voice="en-US-SaraNeural",
-            sample_rate: int = 16000,
-            **kwargs):
+        self,
+        *,
+        api_key: str,
+        region: str,
+        voice="en-US-SaraNeural",
+        sample_rate: int = 16000,
+        **kwargs,
+    ):
         super().__init__(sample_rate=sample_rate, **kwargs)
 
         speech_config = SpeechConfig(subscription=api_key, region=region)
@@ -108,7 +107,8 @@ class AzureTTSService(TTSService):
             "<mstts:express-as style='lyrical' styledegree='2' role='SeniorFemale'>"
             "<prosody rate='1.05'>"
             f"{text}"
-            "</prosody></mstts:express-as></voice></speak> ")
+            "</prosody></mstts:express-as></voice></speak> "
+        )
 
         result = await asyncio.to_thread(self._speech_synthesizer.speak_ssml, (ssml))
 
@@ -117,7 +117,9 @@ class AzureTTSService(TTSService):
             await self.stop_ttfb_metrics()
             await self.push_frame(TTSStartedFrame())
             # Azure always sends a 44-byte header. Strip it off.
-            yield TTSAudioRawFrame(audio=result.audio_data[44:], sample_rate=self._sample_rate, num_channels=1)
+            yield TTSAudioRawFrame(
+                audio=result.audio_data[44:], sample_rate=self._sample_rate, num_channels=1
+            )
             await self.push_frame(TTSStoppedFrame())
         elif result.reason == ResultReason.Canceled:
             cancellation_details = result.cancellation_details
@@ -128,14 +130,15 @@ class AzureTTSService(TTSService):
 
 class AzureSTTService(STTService):
     def __init__(
-            self,
-            *,
-            api_key: str,
-            region: str,
-            language="en-US",
-            sample_rate=16000,
-            channels=1,
-            **kwargs):
+        self,
+        *,
+        api_key: str,
+        region: str,
+        language="en-US",
+        sample_rate=16000,
+        channels=1,
+        **kwargs,
+    ):
         super().__init__(**kwargs)
 
         speech_config = SpeechConfig(subscription=api_key, region=region)
@@ -146,7 +149,8 @@ class AzureSTTService(STTService):
 
         audio_config = AudioConfig(stream=self._audio_stream)
         self._speech_recognizer = SpeechRecognizer(
-            speech_config=speech_config, audio_config=audio_config)
+            speech_config=speech_config, audio_config=audio_config
+        )
         self._speech_recognizer.recognized.connect(self._on_handle_recognized)
 
     async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]:
@@ -176,7 +180,6 @@ class AzureSTTService(STTService):
 
 
 class AzureImageGenServiceREST(ImageGenService):
-
     def __init__(
         self,
         *,
@@ -199,9 +202,7 @@ class AzureImageGenServiceREST(ImageGenService):
     async def run_image_gen(self, prompt: str) -> AsyncGenerator[Frame, None]:
         url = f"{self._azure_endpoint}openai/images/generations:submit?api-version={self._api_version}"
 
-        headers = {
-            "api-key": self._api_key,
-            "Content-Type": "application/json"}
+        headers = {"api-key": self._api_key, "Content-Type": "application/json"}
 
         body = {
             # Enter your prompt text here
@@ -243,8 +244,6 @@ class AzureImageGenServiceREST(ImageGenService):
                 image_stream = io.BytesIO(await response.content.read())
                 image = Image.open(image_stream)
                 frame = URLImageRawFrame(
-                    url=image_url,
-                    image=image.tobytes(),
-                    size=image.size,
-                    format=image.format)
+                    url=image_url, image=image.tobytes(), size=image.size, format=image.format
+                )
                 yield frame
diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index a44daf70c..90deeda15 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -21,7 +21,7 @@ from pipecat.frames.frames import (
     TTSAudioRawFrame,
     TTSStartedFrame,
     TTSStoppedFrame,
-    LLMFullResponseEndFrame
+    LLMFullResponseEndFrame,
 )
 from pipecat.processors.frame_processor import FrameDirection
 from pipecat.transcriptions.language import Language
@@ -36,7 +36,8 @@ try:
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
-        "In order to use Cartesia, you need to `pip install pipecat-ai[cartesia]`. Also, set `CARTESIA_API_KEY` environment variable.")
+        "In order to use Cartesia, you need to `pip install pipecat-ai[cartesia]`. Also, set `CARTESIA_API_KEY` environment variable."
+    )
     raise Exception(f"Missing module: {e}")
 
 
@@ -60,19 +61,19 @@ def language_to_cartesia_language(language: Language) -> str | None:
 
 
 class CartesiaTTSService(AsyncWordTTSService):
-
     def __init__(
-            self,
-            *,
-            api_key: str,
-            voice_id: str,
-            cartesia_version: str = "2024-06-10",
-            url: str = "wss://api.cartesia.ai/tts/websocket",
-            model_id: str = "sonic-english",
-            encoding: str = "pcm_s16le",
-            sample_rate: int = 16000,
-            language: str = "en",
-            **kwargs):
+        self,
+        *,
+        api_key: str,
+        voice_id: str,
+        cartesia_version: str = "2024-06-10",
+        url: str = "wss://api.cartesia.ai/tts/websocket",
+        model_id: str = "sonic-english",
+        encoding: str = "pcm_s16le",
+        sample_rate: int = 16000,
+        language: str = "en",
+        **kwargs,
+    ):
         # Aggregating sentences still gives cleaner-sounding results and fewer
         # artifacts than streaming one word at a time. On average, waiting for a
         # full sentence should only "cost" us 15ms or so with GPT-4o or a Llama
@@ -83,7 +84,9 @@ class CartesiaTTSService(AsyncWordTTSService):
         # if we're interrupted. Cartesia gives us word-by-word timestamps. We
         # can use those to generate text frames ourselves aligned with the
         # playout timing of the audio!
-        super().__init__(aggregate_sentences=True, push_text_frames=False, sample_rate=sample_rate, **kwargs)
+        super().__init__(
+            aggregate_sentences=True, push_text_frames=False, sample_rate=sample_rate, **kwargs
+        )
 
         self._api_key = api_key
         self._cartesia_version = cartesia_version
@@ -175,10 +178,7 @@ class CartesiaTTSService(AsyncWordTTSService):
             "continue": False,
             "context_id": self._context_id,
             "model_id": self.model_name,
-            "voice": {
-                "mode": "id",
-                "id": self._voice_id
-            },
+            "voice": {"mode": "id", "id": self._voice_id},
             "output_format": self._output_format,
             "language": self._language,
             "add_timestamps": True,
@@ -209,7 +209,7 @@ class CartesiaTTSService(AsyncWordTTSService):
                     frame = TTSAudioRawFrame(
                         audio=base64.b64decode(msg["data"]),
                         sample_rate=self._output_format["sample_rate"],
-                        num_channels=1
+                        num_channels=1,
                     )
                     await self.push_frame(frame)
                 elif msg["type"] == "error":
@@ -241,10 +241,7 @@ class CartesiaTTSService(AsyncWordTTSService):
                 "continue": True,
                 "context_id": self._context_id,
                 "model_id": self.model_name,
-                "voice": {
-                    "mode": "id",
-                    "id": self._voice_id
-                },
+                "voice": {"mode": "id", "id": self._voice_id},
                 "output_format": self._output_format,
                 "language": self._language,
                 "add_timestamps": True,
@@ -264,18 +261,18 @@ class CartesiaTTSService(AsyncWordTTSService):
 
 
 class CartesiaHttpTTSService(TTSService):
-
     def __init__(
-            self,
-            *,
-            api_key: str,
-            voice_id: str,
-            model_id: str = "sonic-english",
-            base_url: str = "https://api.cartesia.ai",
-            encoding: str = "pcm_s16le",
-            sample_rate: int = 16000,
-            language: str = "en",
-            **kwargs):
+        self,
+        *,
+        api_key: str,
+        voice_id: str,
+        model_id: str = "sonic-english",
+        base_url: str = "https://api.cartesia.ai",
+        encoding: str = "pcm_s16le",
+        sample_rate: int = 16000,
+        language: str = "en",
+        **kwargs,
+    ):
         super().__init__(**kwargs)
 
         self._api_key = api_key
@@ -326,7 +323,7 @@ class CartesiaHttpTTSService(TTSService):
                 voice_id=self._voice_id,
                 output_format=self._output_format,
                 language=self._language,
-                stream=False
+                stream=False,
             )
 
             await self.stop_ttfb_metrics()
@@ -334,7 +331,7 @@ class CartesiaHttpTTSService(TTSService):
             frame = TTSAudioRawFrame(
                 audio=output["audio"],
                 sample_rate=self._output_format["sample_rate"],
-                num_channels=1
+                num_channels=1,
             )
             yield frame
         except Exception as e:
diff --git a/src/pipecat/services/deepgram.py b/src/pipecat/services/deepgram.py
index 25f7b7a56..fab12e080 100644
--- a/src/pipecat/services/deepgram.py
+++ b/src/pipecat/services/deepgram.py
@@ -18,7 +18,8 @@ from pipecat.frames.frames import (
     TTSAudioRawFrame,
     TTSStartedFrame,
     TTSStoppedFrame,
-    TranscriptionFrame)
+    TranscriptionFrame,
+)
 from pipecat.services.ai_services import STTService, TTSService
 from pipecat.transcriptions.language import Language
 from pipecat.utils.time import time_now_iso8601
@@ -34,27 +35,28 @@ try:
         DeepgramClientOptions,
         LiveTranscriptionEvents,
         LiveOptions,
-        LiveResultResponse
+        LiveResultResponse,
     )
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
-        "In order to use Deepgram, you need to `pip install pipecat-ai[deepgram]`. Also, set `DEEPGRAM_API_KEY` environment variable.")
+        "In order to use Deepgram, you need to `pip install pipecat-ai[deepgram]`. Also, set `DEEPGRAM_API_KEY` environment variable."
+    )
     raise Exception(f"Missing module: {e}")
 
 
 class DeepgramTTSService(TTSService):
-
     def __init__(
-            self,
-            *,
-            api_key: str,
-            aiohttp_session: aiohttp.ClientSession,
-            voice: str = "aura-helios-en",
-            base_url: str = "https://api.deepgram.com/v1/speak",
-            sample_rate: int = 16000,
-            encoding: str = "linear16",
-            **kwargs):
+        self,
+        *,
+        api_key: str,
+        aiohttp_session: aiohttp.ClientSession,
+        voice: str = "aura-helios-en",
+        base_url: str = "https://api.deepgram.com/v1/speak",
+        sample_rate: int = 16000,
+        encoding: str = "linear16",
+        **kwargs,
+    ):
         super().__init__(**kwargs)
 
         self._voice = voice
@@ -93,8 +95,11 @@ class DeepgramTTSService(TTSService):
                         return
 
                     logger.error(
-                        f"{self} error getting audio (status: {r.status}, error: {response_text})")
-                    yield ErrorFrame(f"Error getting audio (status: {r.status}, error: {response_text})")
+                        f"{self} error getting audio (status: {r.status}, error: {response_text})"
+                    )
+                    yield ErrorFrame(
+                        f"Error getting audio (status: {r.status}, error: {response_text})"
+                    )
                     return
 
                 await self.start_tts_usage_metrics(text)
@@ -103,7 +108,8 @@ class DeepgramTTSService(TTSService):
                 async for data in r.content:
                     await self.stop_ttfb_metrics()
                     frame = TTSAudioRawFrame(
-                        audio=data, sample_rate=self._sample_rate, num_channels=1)
+                        audio=data, sample_rate=self._sample_rate, num_channels=1
+                    )
                     yield frame
                 await self.push_frame(TTSStoppedFrame())
         except Exception as e:
@@ -111,36 +117,36 @@ class DeepgramTTSService(TTSService):
 
 
 class DeepgramSTTService(STTService):
-    def __init__(self,
-                 *,
-                 api_key: str,
-                 url: str = "",
-                 live_options: LiveOptions = LiveOptions(
-                     encoding="linear16",
-                     language="en-US",
-                     model="nova-2-conversationalai",
-                     sample_rate=16000,
-                     channels=1,
-                     interim_results=True,
-                     smart_format=True,
-                     punctuate=True,
-                     profanity_filter=True,
-                     vad_events=False,
-                 ),
-                 **kwargs):
+    def __init__(
+        self,
+        *,
+        api_key: str,
+        url: str = "",
+        live_options: LiveOptions = LiveOptions(
+            encoding="linear16",
+            language="en-US",
+            model="nova-2-conversationalai",
+            sample_rate=16000,
+            channels=1,
+            interim_results=True,
+            smart_format=True,
+            punctuate=True,
+            profanity_filter=True,
+            vad_events=False,
+        ),
+        **kwargs,
+    ):
         super().__init__(**kwargs)
 
         self._live_options = live_options
 
         self._client = DeepgramClient(
-            api_key, config=DeepgramClientOptions(url=url, options={"keepalive": "true"}))
-        self._connection: AsyncListenWebSocketClient = self._client.listen.asyncwebsocket.v(
-            "1")
-        self._connection.on(
-            LiveTranscriptionEvents.Transcript, self._on_message)
+            api_key, config=DeepgramClientOptions(url=url, options={"keepalive": "true"})
+        )
+        self._connection: AsyncListenWebSocketClient = self._client.listen.asyncwebsocket.v("1")
+        self._connection.on(LiveTranscriptionEvents.Transcript, self._on_message)
         if self.vad_enabled:
-            self._connection.on(
-                LiveTranscriptionEvents.SpeechStarted, self._on_speech_started)
+            self._connection.on(LiveTranscriptionEvents.SpeechStarted, self._on_speech_started)
 
     @property
     def vad_enabled(self):
@@ -206,7 +212,11 @@ class DeepgramSTTService(STTService):
         if len(transcript) > 0:
             await self.stop_ttfb_metrics()
             if is_final:
-                await self.push_frame(TranscriptionFrame(transcript, "", time_now_iso8601(), language))
+                await self.push_frame(
+                    TranscriptionFrame(transcript, "", time_now_iso8601(), language)
+                )
                 await self.stop_processing_metrics()
             else:
-                await self.push_frame(InterimTranscriptionFrame(transcript, "", time_now_iso8601(), language))
+                await self.push_frame(
+                    InterimTranscriptionFrame(transcript, "", time_now_iso8601(), language)
+                )
diff --git a/src/pipecat/services/fal.py b/src/pipecat/services/fal.py
index 58768180f..bb7b47dfc 100644
--- a/src/pipecat/services/fal.py
+++ b/src/pipecat/services/fal.py
@@ -22,7 +22,8 @@ try:
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
-        "In order to use Fal, you need to `pip install pipecat-ai[fal]`. Also, set `FAL_KEY` environment variable.")
+        "In order to use Fal, you need to `pip install pipecat-ai[fal]`. Also, set `FAL_KEY` environment variable."
+    )
     raise Exception(f"Missing module: {e}")
 
 
@@ -43,7 +44,7 @@ class FalImageGenService(ImageGenService):
         aiohttp_session: aiohttp.ClientSession,
         model: str = "fal-ai/fast-sdxl",
         key: str | None = None,
-        **kwargs
+        **kwargs,
     ):
         super().__init__(**kwargs)
         self.set_model_name(model)
@@ -57,7 +58,7 @@ class FalImageGenService(ImageGenService):
 
         response = await fal_client.run_async(
             self.model_name,
-            arguments={"prompt": prompt, **self._params.model_dump(exclude_none=True)}
+            arguments={"prompt": prompt, **self._params.model_dump(exclude_none=True)},
         )
 
         image_url = response["images"][0]["url"] if response else None
@@ -77,8 +78,6 @@ class FalImageGenService(ImageGenService):
             image = Image.open(image_stream)
 
             frame = URLImageRawFrame(
-                url=image_url,
-                image=image.tobytes(),
-                size=image.size,
-                format=image.format)
+                url=image_url, image=image.tobytes(), size=image.size, format=image.format
+            )
             yield frame
diff --git a/src/pipecat/services/fireworks.py b/src/pipecat/services/fireworks.py
index 87fddd838..a6e826c12 100644
--- a/src/pipecat/services/fireworks.py
+++ b/src/pipecat/services/fireworks.py
@@ -13,13 +13,16 @@ try:
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
-        "In order to use Fireworks, you need to `pip install pipecat-ai[fireworks]`. Also, set the `FIREWORKS_API_KEY` environment variable.")
+        "In order to use Fireworks, you need to `pip install pipecat-ai[fireworks]`. Also, set the `FIREWORKS_API_KEY` environment variable."
+    )
     raise Exception(f"Missing module: {e}")
 
 
 class FireworksLLMService(BaseOpenAILLMService):
-    def __init__(self,
-                 *,
-                 model: str = "accounts/fireworks/models/firefunction-v1",
-                 base_url: str = "https://api.fireworks.ai/inference/v1"):
+    def __init__(
+        self,
+        *,
+        model: str = "accounts/fireworks/models/firefunction-v1",
+        base_url: str = "https://api.fireworks.ai/inference/v1",
+    ):
         super().__init__(model=model, base_url=base_url)
diff --git a/src/pipecat/services/gladia.py b/src/pipecat/services/gladia.py
index ead8f63dc..12183adde 100644
--- a/src/pipecat/services/gladia.py
+++ b/src/pipecat/services/gladia.py
@@ -16,7 +16,8 @@ from pipecat.frames.frames import (
     Frame,
     InterimTranscriptionFrame,
     StartFrame,
-    TranscriptionFrame)
+    TranscriptionFrame,
+)
 from pipecat.services.ai_services import STTService
 from pipecat.utils.time import time_now_iso8601
 
@@ -28,7 +29,8 @@ try:
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
-        "In order to use Gladia, you need to `pip install pipecat-ai[gladia]`. Also, set `GLADIA_API_KEY` environment variable.")
+        "In order to use Gladia, you need to `pip install pipecat-ai[gladia]`. Also, set `GLADIA_API_KEY` environment variable."
+    )
     raise Exception(f"Missing module: {e}")
 
 
@@ -40,13 +42,15 @@ class GladiaSTTService(STTService):
         endpointing: Optional[int] = 200
         prosody: Optional[bool] = None
 
-    def __init__(self,
-                 *,
-                 api_key: str,
-                 url: str = "wss://api.gladia.io/audio/text/audio-transcription",
-                 confidence: float = 0.5,
-                 params: InputParams = InputParams(),
-                 **kwargs):
+    def __init__(
+        self,
+        *,
+        api_key: str,
+        url: str = "wss://api.gladia.io/audio/text/audio-transcription",
+        confidence: float = 0.5,
+        params: InputParams = InputParams(),
+        **kwargs,
+    ):
         super().__init__(sync=False, **kwargs)
 
         self._api_key = api_key
@@ -80,15 +84,13 @@ class GladiaSTTService(STTService):
             "encoding": "WAV/PCM",
             "model_type": "fast",
             "language_behaviour": "manual",
-            **self._params.model_dump(exclude_none=True)
+            **self._params.model_dump(exclude_none=True),
         }
 
         await self._websocket.send(json.dumps(configuration))
 
     async def _send_audio(self, audio: bytes):
-        message = {
-            'frames': base64.b64encode(audio).decode("utf-8")
-        }
+        message = {"frames": base64.b64encode(audio).decode("utf-8")}
         await self._websocket.send(json.dumps(message))
 
     async def _receive_task_handler(self):
@@ -106,6 +108,10 @@ class GladiaSTTService(STTService):
                 transcript = utterance["transcription"]
                 if confidence >= self._confidence:
                     if type == "final":
-                        await self.push_frame(TranscriptionFrame(transcript, "", time_now_iso8601()))
+                        await self.push_frame(
+                            TranscriptionFrame(transcript, "", time_now_iso8601())
+                        )
                     else:
-                        await self.push_frame(InterimTranscriptionFrame(transcript, "", time_now_iso8601()))
+                        await self.push_frame(
+                            InterimTranscriptionFrame(transcript, "", time_now_iso8601())
+                        )
diff --git a/src/pipecat/services/google.py b/src/pipecat/services/google.py
index b72169b70..4de6b77fa 100644
--- a/src/pipecat/services/google.py
+++ b/src/pipecat/services/google.py
@@ -15,11 +15,14 @@ from pipecat.frames.frames import (
     VisionImageRawFrame,
     LLMMessagesFrame,
     LLMFullResponseStartFrame,
-    LLMFullResponseEndFrame
+    LLMFullResponseEndFrame,
 )
 from pipecat.processors.frame_processor import FrameDirection
 from pipecat.services.ai_services import LLMService
-from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext, OpenAILLMContextFrame
+from pipecat.processors.aggregators.openai_llm_context import (
+    OpenAILLMContext,
+    OpenAILLMContextFrame,
+)
 
 from loguru import logger
 
@@ -29,7 +32,8 @@ try:
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
-        "In order to use Google AI, you need to `pip install pipecat-ai[google]`. Also, set `GOOGLE_API_KEY` environment variable.")
+        "In order to use Google AI, you need to `pip install pipecat-ai[google]`. Also, set `GOOGLE_API_KEY` environment variable."
+    )
     raise Exception(f"Missing module: {e}")
 
 
@@ -53,8 +57,7 @@ class GoogleLLMService(LLMService):
         self.set_model_name(model)
         self._client = gai.GenerativeModel(model)
 
-    def _get_messages_from_openai_context(
-            self, context: OpenAILLMContext) -> List[glm.Content]:
+    def _get_messages_from_openai_context(self, context: OpenAILLMContext) -> List[glm.Content]:
         openai_messages = context.get_messages()
         google_messages = []
 
@@ -69,10 +72,12 @@ class GoogleLLMService(LLMService):
             parts = [glm.Part(text=content)]
             if "mime_type" in message:
                 parts.append(
-                    glm.Part(inline_data=glm.Blob(
-                        mime_type=message["mime_type"],
-                        data=message["data"].getvalue()
-                    )))
+                    glm.Part(
+                        inline_data=glm.Blob(
+                            mime_type=message["mime_type"], data=message["data"].getvalue()
+                        )
+                    )
+                )
             google_messages.append({"role": role, "parts": parts})
 
         return google_messages
@@ -103,7 +108,8 @@ class GoogleLLMService(LLMService):
                     # Google LLMs seem to flag safety issues a lot!
                     if chunk.candidates[0].finish_reason == 3:
                         logger.debug(
-                            f"LLM refused to generate content for safety reasons - {messages}.")
+                            f"LLM refused to generate content for safety reasons - {messages}."
+                        )
                     else:
                         logger.exception(f"{self} error: {e}")
 
diff --git a/src/pipecat/services/lmnt.py b/src/pipecat/services/lmnt.py
index 9285f1583..1ac24d731 100644
--- a/src/pipecat/services/lmnt.py
+++ b/src/pipecat/services/lmnt.py
@@ -30,20 +30,21 @@ try:
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
-        "In order to use LMNT, you need to `pip install pipecat-ai[lmnt]`. Also, set `LMNT_API_KEY` environment variable.")
+        "In order to use LMNT, you need to `pip install pipecat-ai[lmnt]`. Also, set `LMNT_API_KEY` environment variable."
+    )
     raise Exception(f"Missing module: {e}")
 
 
 class LmntTTSService(AsyncTTSService):
-
     def __init__(
-            self,
-            *,
-            api_key: str,
-            voice_id: str,
-            sample_rate: int = 24000,
-            language: str = "en",
-            **kwargs):
+        self,
+        *,
+        api_key: str,
+        voice_id: str,
+        sample_rate: int = 24000,
+        language: str = "en",
+        **kwargs,
+    ):
         # Let TTSService produce TTSStoppedFrames after a short delay of
         # no activity.
         super().__init__(sync=False, push_stop_frames=True, sample_rate=sample_rate, **kwargs)
@@ -92,7 +93,8 @@ class LmntTTSService(AsyncTTSService):
         try:
             self._speech = Speech()
             self._connection = await self._speech.synthesize_streaming(
-                self._voice_id, format="raw", sample_rate=self._output_format["sample_rate"])
+                self._voice_id, format="raw", sample_rate=self._output_format["sample_rate"]
+            )
             self._receive_task = self.get_event_loop().create_task(self._receive_task_handler())
         except Exception as e:
             logger.exception(f"{self} initialization error: {e}")
@@ -129,7 +131,7 @@ class LmntTTSService(AsyncTTSService):
                     frame = TTSAudioRawFrame(
                         audio=msg["audio"],
                         sample_rate=self._output_format["sample_rate"],
-                        num_channels=1
+                        num_channels=1,
                     )
                     await self.push_frame(frame)
                 else:
diff --git a/src/pipecat/services/moondream.py b/src/pipecat/services/moondream.py
index b6391cc93..74442dfee 100644
--- a/src/pipecat/services/moondream.py
+++ b/src/pipecat/services/moondream.py
@@ -31,6 +31,7 @@ def detect_device():
     """
     try:
         import intel_extension_for_pytorch
+
         if torch.xpu.is_available():
             return torch.device("xpu"), torch.float32
     except ImportError:
@@ -45,12 +46,7 @@ def detect_device():
 
 class MoondreamService(VisionService):
     def __init__(
-        self,
-        *,
-        model="vikhyatk/moondream2",
-        revision="2024-08-26",
-        use_cpu=False,
-        **kwargs
+        self, *, model="vikhyatk/moondream2", revision="2024-08-26", use_cpu=False, **kwargs
     ):
         super().__init__(**kwargs)
 
@@ -85,9 +81,8 @@ class MoondreamService(VisionService):
             image = Image.frombytes(frame.format, frame.size, frame.image)
             image_embeds = self._model.encode_image(image)
             description = self._model.answer_question(
-                image_embeds=image_embeds,
-                question=frame.text,
-                tokenizer=self._tokenizer)
+                image_embeds=image_embeds, question=frame.text, tokenizer=self._tokenizer
+            )
             return description
 
         description = await asyncio.to_thread(get_image_description, frame)
diff --git a/src/pipecat/services/ollama.py b/src/pipecat/services/ollama.py
index 8fa3fc2de..0a6a4ce6a 100644
--- a/src/pipecat/services/ollama.py
+++ b/src/pipecat/services/ollama.py
@@ -8,6 +8,5 @@ from pipecat.services.openai import BaseOpenAILLMService
 
 
 class OLLamaLLMService(BaseOpenAILLMService):
-
     def __init__(self, *, model: str = "llama2", base_url: str = "http://localhost:11434/v1"):
         super().__init__(model=model, base_url=base_url, api_key="ollama")
diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py
index 4203f8194..e54898525 100644
--- a/src/pipecat/services/openai.py
+++ b/src/pipecat/services/openai.py
@@ -32,21 +32,20 @@ from pipecat.frames.frames import (
     VisionImageRawFrame,
     FunctionCallResultFrame,
     FunctionCallInProgressFrame,
-    StartInterruptionFrame
+    StartInterruptionFrame,
 )
 from pipecat.metrics.metrics import LLMTokenUsage
-from pipecat.processors.aggregators.llm_response import LLMUserContextAggregator, LLMAssistantContextAggregator
+from pipecat.processors.aggregators.llm_response import (
+    LLMUserContextAggregator,
+    LLMAssistantContextAggregator,
+)
 
 from pipecat.processors.aggregators.openai_llm_context import (
     OpenAILLMContext,
-    OpenAILLMContextFrame
+    OpenAILLMContextFrame,
 )
 from pipecat.processors.frame_processor import FrameDirection
-from pipecat.services.ai_services import (
-    ImageGenService,
-    LLMService,
-    TTSService
-)
+from pipecat.services.ai_services import ImageGenService, LLMService, TTSService
 
 try:
     from openai import AsyncOpenAI, AsyncStream, DefaultAsyncHttpxClient, BadRequestError, NOT_GIVEN
@@ -54,7 +53,8 @@ try:
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
-        "In order to use OpenAI, you need to `pip install pipecat-ai[openai]`. Also, set `OPENAI_API_KEY` environment variable.")
+        "In order to use OpenAI, you need to `pip install pipecat-ai[openai]`. Also, set `OPENAI_API_KEY` environment variable."
+    )
     raise Exception(f"Missing module: {e}")
 
 ValidVoice = Literal["alloy", "echo", "fable", "onyx", "nova", "shimmer"]
@@ -82,24 +82,28 @@ class BaseOpenAILLMService(LLMService):
     as well as tool choices and the tool, which is used if requesting function
     calls from the LLM.
     """
+
     class InputParams(BaseModel):
         frequency_penalty: Optional[float] = Field(
-            default_factory=lambda: NOT_GIVEN, ge=-2.0, le=2.0)
+            default_factory=lambda: NOT_GIVEN, ge=-2.0, le=2.0
+        )
         presence_penalty: Optional[float] = Field(
-            default_factory=lambda: NOT_GIVEN, ge=-2.0, le=2.0)
+            default_factory=lambda: NOT_GIVEN, ge=-2.0, le=2.0
+        )
         seed: Optional[int] = Field(default_factory=lambda: NOT_GIVEN, ge=0)
         temperature: Optional[float] = Field(default_factory=lambda: NOT_GIVEN, ge=0.0, le=2.0)
         top_p: Optional[float] = Field(default_factory=lambda: NOT_GIVEN, ge=0.0, le=1.0)
         extra: Optional[Dict[str, Any]] = Field(default_factory=dict)
 
     def __init__(
-            self,
-            *,
-            model: str,
-            api_key=None,
-            base_url=None,
-            params: InputParams = InputParams(),
-            **kwargs):
+        self,
+        *,
+        model: str,
+        api_key=None,
+        base_url=None,
+        params: InputParams = InputParams(),
+        **kwargs,
+    ):
         super().__init__(**kwargs)
         self.set_model_name(model)
         self._client = self.create_client(api_key=api_key, base_url=base_url, **kwargs)
@@ -116,9 +120,10 @@ class BaseOpenAILLMService(LLMService):
             base_url=base_url,
             http_client=DefaultAsyncHttpxClient(
                 limits=httpx.Limits(
-                    max_keepalive_connections=100,
-                    max_connections=1000,
-                    keepalive_expiry=None)))
+                    max_keepalive_connections=100, max_connections=1000, keepalive_expiry=None
+                )
+            ),
+        )
 
     def can_generate_metrics(self) -> bool:
         return True
@@ -148,10 +153,8 @@ class BaseOpenAILLMService(LLMService):
         self._extra = extra
 
     async def get_chat_completions(
-            self,
-            context: OpenAILLMContext,
-            messages: List[ChatCompletionMessageParam]) -> AsyncStream[ChatCompletionChunk]:
-
+        self, context: OpenAILLMContext, messages: List[ChatCompletionMessageParam]
+    ) -> AsyncStream[ChatCompletionChunk]:
         params = {
             "model": self.model_name,
             "stream": True,
@@ -172,7 +175,8 @@ class BaseOpenAILLMService(LLMService):
         return chunks
 
     async def _stream_chat_completions(
-            self, context: OpenAILLMContext) -> AsyncStream[ChatCompletionChunk]:
+        self, context: OpenAILLMContext
+    ) -> AsyncStream[ChatCompletionChunk]:
         logger.debug(f"Generating chat: {context.get_messages_json()}")
 
         messages: List[ChatCompletionMessageParam] = context.get_messages()
@@ -184,7 +188,10 @@ class BaseOpenAILLMService(LLMService):
                 text = message["content"]
                 message["content"] = [
                     {"type": "text", "text": text},
-                    {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{encoded_image}"}}
+                    {
+                        "type": "image_url",
+                        "image_url": {"url": f"data:image/jpeg;base64,{encoded_image}"},
+                    },
                 ]
                 del message["data"]
                 del message["mime_type"]
@@ -200,8 +207,8 @@ class BaseOpenAILLMService(LLMService):
 
         await self.start_ttfb_metrics()
 
-        chunk_stream: AsyncStream[ChatCompletionChunk] = (
-            await self._stream_chat_completions(context)
+        chunk_stream: AsyncStream[ChatCompletionChunk] = await self._stream_chat_completions(
+            context
         )
 
         async for chunk in chunk_stream:
@@ -209,7 +216,7 @@ class BaseOpenAILLMService(LLMService):
                 tokens = LLMTokenUsage(
                     prompt_tokens=chunk.usage.prompt_tokens,
                     completion_tokens=chunk.usage.completion_tokens,
-                    total_tokens=chunk.usage.total_tokens
+                    total_tokens=chunk.usage.total_tokens,
                 )
                 await self.start_llm_usage_metrics(tokens)
 
@@ -250,21 +257,16 @@ class BaseOpenAILLMService(LLMService):
                 await self._handle_function_call(context, tool_call_id, function_name, arguments)
             else:
                 raise OpenAIUnhandledFunctionException(
-                    f"The LLM tried to call a function named '{function_name}', but there isn't a callback registered for that function.")
+                    f"The LLM tried to call a function named '{function_name}', but there isn't a callback registered for that function."
+                )
 
-    async def _handle_function_call(
-            self,
-            context,
-            tool_call_id,
-            function_name,
-            arguments
-    ):
+    async def _handle_function_call(self, context, tool_call_id, function_name, arguments):
         arguments = json.loads(arguments)
         await self.call_function(
             context=context,
             tool_call_id=tool_call_id,
             function_name=function_name,
-            arguments=arguments
+            arguments=arguments,
         )
 
     async def process_frame(self, frame: Frame, direction: FrameDirection):
@@ -293,38 +295,34 @@ class BaseOpenAILLMService(LLMService):
 
 @dataclass
 class OpenAIContextAggregatorPair:
-    _user: 'OpenAIUserContextAggregator'
-    _assistant: 'OpenAIAssistantContextAggregator'
+    _user: "OpenAIUserContextAggregator"
+    _assistant: "OpenAIAssistantContextAggregator"
 
-    def user(self) -> 'OpenAIUserContextAggregator':
+    def user(self) -> "OpenAIUserContextAggregator":
         return self._user
 
-    def assistant(self) -> 'OpenAIAssistantContextAggregator':
+    def assistant(self) -> "OpenAIAssistantContextAggregator":
         return self._assistant
 
 
 class OpenAILLMService(BaseOpenAILLMService):
-
     def __init__(
-            self,
-            *,
-            model: str = "gpt-4o",
-            params: BaseOpenAILLMService.InputParams = BaseOpenAILLMService.InputParams(),
-            **kwargs):
+        self,
+        *,
+        model: str = "gpt-4o",
+        params: BaseOpenAILLMService.InputParams = BaseOpenAILLMService.InputParams(),
+        **kwargs,
+    ):
         super().__init__(model=model, params=params, **kwargs)
 
     @staticmethod
     def create_context_aggregator(context: OpenAILLMContext) -> OpenAIContextAggregatorPair:
         user = OpenAIUserContextAggregator(context)
         assistant = OpenAIAssistantContextAggregator(user)
-        return OpenAIContextAggregatorPair(
-            _user=user,
-            _assistant=assistant
-        )
+        return OpenAIContextAggregatorPair(_user=user, _assistant=assistant)
 
 
 class OpenAIImageGenService(ImageGenService):
-
     def __init__(
         self,
         *,
@@ -343,10 +341,7 @@ class OpenAIImageGenService(ImageGenService):
         logger.debug(f"Generating image from prompt: {prompt}")
 
         image = await self._client.images.generate(
-            prompt=prompt,
-            model=self.model_name,
-            n=1,
-            size=self._image_size
+            prompt=prompt, model=self.model_name, n=1, size=self._image_size
         )
 
         image_url = image.data[0].url
@@ -376,13 +371,14 @@ class OpenAITTSService(TTSService):
     """
 
     def __init__(
-            self,
-            *,
-            api_key: str | None = None,
-            voice: str = "alloy",
-            model: Literal["tts-1", "tts-1-hd"] = "tts-1",
-            sample_rate: int = 24000,
-            **kwargs):
+        self,
+        *,
+        api_key: str | None = None,
+        voice: str = "alloy",
+        model: Literal["tts-1", "tts-1-hd"] = "tts-1",
+        sample_rate: int = 24000,
+        **kwargs,
+    ):
         super().__init__(sample_rate=sample_rate, **kwargs)
 
         self._voice: ValidVoice = VALID_VOICES.get(voice, "alloy")
@@ -408,16 +404,19 @@ class OpenAITTSService(TTSService):
             await self.start_ttfb_metrics()
 
             async with self._client.audio.speech.with_streaming_response.create(
-                    input=text,
-                    model=self.model_name,
-                    voice=self._voice,
-                    response_format="pcm",
+                input=text,
+                model=self.model_name,
+                voice=self._voice,
+                response_format="pcm",
             ) as r:
                 if r.status_code != 200:
                     error = await r.text()
                     logger.error(
-                        f"{self} error getting audio (status: {r.status_code}, error: {error})")
-                    yield ErrorFrame(f"Error getting audio (status: {r.status_code}, error: {error})")
+                        f"{self} error getting audio (status: {r.status_code}, error: {error})"
+                    )
+                    yield ErrorFrame(
+                        f"Error getting audio (status: {r.status_code}, error: {error})"
+                    )
                     return
 
                 await self.start_tts_usage_metrics(text)
@@ -454,14 +453,18 @@ class OpenAIAssistantContextAggregator(LLMAssistantContextAggregator):
         elif isinstance(frame, FunctionCallInProgressFrame):
             self._function_call_in_progress = frame
         elif isinstance(frame, FunctionCallResultFrame):
-            if self._function_call_in_progress and self._function_call_in_progress.tool_call_id == frame.tool_call_id:
+            if (
+                self._function_call_in_progress
+                and self._function_call_in_progress.tool_call_id == frame.tool_call_id
+            ):
                 self._function_call_in_progress = None
                 self._function_call_result = frame
                 # TODO-CB: Kwin wants us to refactor this out of here but I REFUSE
                 await self._push_aggregation()
             else:
                 logger.warning(
-                    f"FunctionCallResultFrame tool_call_id does not match FunctionCallInProgressFrame tool_call_id")
+                    f"FunctionCallResultFrame tool_call_id does not match FunctionCallInProgressFrame tool_call_id"
+                )
                 self._function_call_in_progress = None
                 self._function_call_result = None
 
@@ -479,24 +482,28 @@ class OpenAIAssistantContextAggregator(LLMAssistantContextAggregator):
                 frame = self._function_call_result
                 self._function_call_result = None
                 if frame.result:
-                    self._context.add_message({
-                        "role": "assistant",
-                        "tool_calls": [
-                            {
-                                "id": frame.tool_call_id,
-                                "function": {
-                                    "name": frame.function_name,
-                                    "arguments": json.dumps(frame.arguments)
-                                },
-                                "type": "function"
-                            }
-                        ]
-                    })
-                    self._context.add_message({
-                        "role": "tool",
-                        "content": json.dumps(frame.result),
-                        "tool_call_id": frame.tool_call_id
-                    })
+                    self._context.add_message(
+                        {
+                            "role": "assistant",
+                            "tool_calls": [
+                                {
+                                    "id": frame.tool_call_id,
+                                    "function": {
+                                        "name": frame.function_name,
+                                        "arguments": json.dumps(frame.arguments),
+                                    },
+                                    "type": "function",
+                                }
+                            ],
+                        }
+                    )
+                    self._context.add_message(
+                        {
+                            "role": "tool",
+                            "content": json.dumps(frame.result),
+                            "tool_call_id": frame.tool_call_id,
+                        }
+                    )
                     run_llm = True
             else:
                 self._context.add_message({"role": "assistant", "content": aggregation})
diff --git a/src/pipecat/services/openpipe.py b/src/pipecat/services/openpipe.py
index e4e14dc15..1f28a85b1 100644
--- a/src/pipecat/services/openpipe.py
+++ b/src/pipecat/services/openpipe.py
@@ -13,33 +13,35 @@ from loguru import logger
 
 try:
     from openpipe import AsyncOpenAI as OpenPipeAI, AsyncStream
-    from openai.types.chat import (ChatCompletionMessageParam, ChatCompletionChunk)
+    from openai.types.chat import ChatCompletionMessageParam, ChatCompletionChunk
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
-        "In order to use OpenPipe, you need to `pip install pipecat-ai[openpipe]`. Also, set `OPENPIPE_API_KEY` and `OPENAI_API_KEY` environment variables.")
+        "In order to use OpenPipe, you need to `pip install pipecat-ai[openpipe]`. Also, set `OPENPIPE_API_KEY` and `OPENAI_API_KEY` environment variables."
+    )
     raise Exception(f"Missing module: {e}")
 
 
 class OpenPipeLLMService(BaseOpenAILLMService):
-
     def __init__(
-            self,
-            *,
-            model: str = "gpt-4o",
-            api_key: str | None = None,
-            base_url: str | None = None,
-            openpipe_api_key: str | None = None,
-            openpipe_base_url: str = "https://app.openpipe.ai/api/v1",
-            tags: Dict[str, str] | None = None,
-            **kwargs):
+        self,
+        *,
+        model: str = "gpt-4o",
+        api_key: str | None = None,
+        base_url: str | None = None,
+        openpipe_api_key: str | None = None,
+        openpipe_base_url: str = "https://app.openpipe.ai/api/v1",
+        tags: Dict[str, str] | None = None,
+        **kwargs,
+    ):
         super().__init__(
             model=model,
             api_key=api_key,
             base_url=base_url,
             openpipe_api_key=openpipe_api_key,
             openpipe_base_url=openpipe_base_url,
-            **kwargs)
+            **kwargs,
+        )
         self._tags = tags
 
     def create_client(self, api_key=None, base_url=None, **kwargs):
@@ -48,24 +50,17 @@ class OpenPipeLLMService(BaseOpenAILLMService):
         client = OpenPipeAI(
             api_key=api_key,
             base_url=base_url,
-            openpipe={
-                "api_key": openpipe_api_key,
-                "base_url": openpipe_base_url
-            }
+            openpipe={"api_key": openpipe_api_key, "base_url": openpipe_base_url},
         )
         return client
 
     async def get_chat_completions(
-            self,
-            context: OpenAILLMContext,
-            messages: List[ChatCompletionMessageParam]) -> AsyncStream[ChatCompletionChunk]:
+        self, context: OpenAILLMContext, messages: List[ChatCompletionMessageParam]
+    ) -> AsyncStream[ChatCompletionChunk]:
         chunks = await self._client.chat.completions.create(
             model=self.model_name,
             stream=True,
             messages=messages,
-            openpipe={
-                "tags": self._tags,
-                "log_request": True
-            }
+            openpipe={"tags": self._tags, "log_request": True},
         )
         return chunks
diff --git a/src/pipecat/services/playht.py b/src/pipecat/services/playht.py
index ae8606e91..2ffa3a419 100644
--- a/src/pipecat/services/playht.py
+++ b/src/pipecat/services/playht.py
@@ -9,11 +9,7 @@ import struct
 
 from typing import AsyncGenerator
 
-from pipecat.frames.frames import (
-    Frame,
-    TTSAudioRawFrame,
-    TTSStartedFrame,
-    TTSStoppedFrame)
+from pipecat.frames.frames import Frame, TTSAudioRawFrame, TTSStartedFrame, TTSStoppedFrame
 from pipecat.services.ai_services import TTSService
 
 from loguru import logger
@@ -25,20 +21,15 @@ try:
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
-        "In order to use PlayHT, you need to `pip install pipecat-ai[playht]`. Also, set `PLAY_HT_USER_ID` and `PLAY_HT_API_KEY` environment variables.")
+        "In order to use PlayHT, you need to `pip install pipecat-ai[playht]`. Also, set `PLAY_HT_USER_ID` and `PLAY_HT_API_KEY` environment variables."
+    )
     raise Exception(f"Missing module: {e}")
 
 
 class PlayHTTTSService(TTSService):
-
     def __init__(
-            self,
-            *,
-            api_key: str,
-            user_id: str,
-            voice_url: str,
-            sample_rate: int = 16000,
-            **kwargs):
+        self, *, api_key: str, user_id: str, voice_url: str, sample_rate: int = 16000, **kwargs
+    ):
         super().__init__(sample_rate=sample_rate, **kwargs)
 
         self._user_id = user_id
@@ -49,10 +40,8 @@ class PlayHTTTSService(TTSService):
             api_key=self._speech_key,
         )
         self._options = TTSOptions(
-            voice=voice_url,
-            sample_rate=sample_rate,
-            quality="higher",
-            format=Format.FORMAT_WAV)
+            voice=voice_url, sample_rate=sample_rate, quality="higher", format=Format.FORMAT_WAV
+        )
 
     def can_generate_metrics(self) -> bool:
         return True
@@ -71,9 +60,8 @@ class PlayHTTTSService(TTSService):
             await self.start_ttfb_metrics()
 
             playht_gen = self._client.tts(
-                text,
-                voice_engine="PlayHT2.0-turbo",
-                options=self._options)
+                text, voice_engine="PlayHT2.0-turbo", options=self._options
+            )
 
             await self.start_tts_usage_metrics(text)
 
@@ -87,10 +75,10 @@ class PlayHTTTSService(TTSService):
                     else:
                         fh = io.BytesIO(b)
                         fh.seek(36)
-                        (data, size) = struct.unpack('<4sI', fh.read(8))
-                        while data != b'data':
+                        (data, size) = struct.unpack("<4sI", fh.read(8))
+                        while data != b"data":
                             fh.read(size)
-                            (data, size) = struct.unpack('<4sI', fh.read(8))
+                            (data, size) = struct.unpack("<4sI", fh.read(8))
                         in_header = False
                 else:
                     if len(chunk):
diff --git a/src/pipecat/services/to_be_updated/cloudflare_ai_service.py b/src/pipecat/services/to_be_updated/cloudflare_ai_service.py
index 058e2212c..1329f9c79 100644
--- a/src/pipecat/services/to_be_updated/cloudflare_ai_service.py
+++ b/src/pipecat/services/to_be_updated/cloudflare_ai_service.py
@@ -12,15 +12,14 @@ class CloudflareAIService(AIService):
         self.cloudflare_account_id = os.getenv("CLOUDFLARE_ACCOUNT_ID")
         self.cloudflare_api_token = os.getenv("CLOUDFLARE_API_TOKEN")
 
-        self.api_base_url = f'https://api.cloudflare.com/client/v4/accounts/{self.cloudflare_account_id}/ai/run/'
-        self.headers = {"Authorization": f'Bearer {self.cloudflare_api_token}'}
+        self.api_base_url = (
+            f"https://api.cloudflare.com/client/v4/accounts/{self.cloudflare_account_id}/ai/run/"
+        )
+        self.headers = {"Authorization": f"Bearer {self.cloudflare_api_token}"}
 
     # base endpoint, used by the others
     def run(self, model, input):
-        response = requests.post(
-            f"{self.api_base_url}{model}",
-            headers=self.headers,
-            json=input)
+        response = requests.post(f"{self.api_base_url}{model}", headers=self.headers, json=input)
         return response.json()
 
     # https://developers.cloudflare.com/workers-ai/models/llm/
@@ -28,7 +27,7 @@ class CloudflareAIService(AIService):
         input = {
             "messages": [
                 {"role": "system", "content": "You are a friendly assistant"},
-                {"role": "user", "content": sentence}
+                {"role": "user", "content": sentence},
             ]
         }
 
@@ -36,16 +35,14 @@ class CloudflareAIService(AIService):
 
     # https://developers.cloudflare.com/workers-ai/models/translation/
     def run_text_translation(self, sentence, source_language, target_language):
-        return self.run('@cf/meta/m2m100-1.2b', {
-            "text": sentence,
-            "source_lang": source_language,
-            "target_lang": target_language
-        })
+        return self.run(
+            "@cf/meta/m2m100-1.2b",
+            {"text": sentence, "source_lang": source_language, "target_lang": target_language},
+        )
 
     # https://developers.cloudflare.com/workers-ai/models/sentiment-analysis/
     def run_text_sentiment(self, sentence):
-        return self.run("@cf/huggingface/distilbert-sst-2-int8",
-                        {"text": sentence})
+        return self.run("@cf/huggingface/distilbert-sst-2-int8", {"text": sentence})
 
     # https://developers.cloudflare.com/workers-ai/models/image-classification/
     def run_image_classification(self, image_url):
@@ -65,7 +62,7 @@ class CloudflareAIService(AIService):
         models = {
             "small": "@cf/baai/bge-small-en-v1.5",  # 384 output dimensions
             "medium": "@cf/baai/bge-base-en-v1.5",  # 768 output dimensions
-            "large": "@cf/baai/bge-large-en-v1.5"  # 1024 output dimensions
+            "large": "@cf/baai/bge-large-en-v1.5",  # 1024 output dimensions
         }
 
         return self.run(models[size], {"text": texts})
diff --git a/src/pipecat/services/to_be_updated/google_ai_service.py b/src/pipecat/services/to_be_updated/google_ai_service.py
index 7272964f4..25668ca0a 100644
--- a/src/pipecat/services/to_be_updated/google_ai_service.py
+++ b/src/pipecat/services/to_be_updated/google_ai_service.py
@@ -18,14 +18,12 @@ class GoogleAIService(AIService):
         )
 
         self.audio_config = texttospeech.AudioConfig(
-            audio_encoding=texttospeech.AudioEncoding.LINEAR16,
-            sample_rate_hertz=16000
+            audio_encoding=texttospeech.AudioEncoding.LINEAR16, sample_rate_hertz=16000
         )
 
     def run_tts(self, sentence):
         synthesis_input = texttospeech.SynthesisInput(text=sentence.strip())
         result = self.client.synthesize_speech(
-            input=synthesis_input,
-            voice=self.voice,
-            audio_config=self.audio_config)
+            input=synthesis_input, voice=self.voice, audio_config=self.audio_config
+        )
         return result
diff --git a/src/pipecat/services/to_be_updated/huggingface_ai_service.py b/src/pipecat/services/to_be_updated/huggingface_ai_service.py
index 7c4984067..09f0b8248 100644
--- a/src/pipecat/services/to_be_updated/huggingface_ai_service.py
+++ b/src/pipecat/services/to_be_updated/huggingface_ai_service.py
@@ -19,8 +19,8 @@ class HuggingFaceAIService(AIService):
     # models use 2-character language codes**)
     def run_text_translation(self, sentence, source_language, target_language):
         translator = pipeline(
-            f"translation",
-            model=f"Helsinki-NLP/opus-mt-{source_language}-{target_language}")
+            f"translation", model=f"Helsinki-NLP/opus-mt-{source_language}-{target_language}"
+        )
 
         return translator(sentence)[0]["translation_text"]
 
diff --git a/src/pipecat/services/together.py b/src/pipecat/services/together.py
index ce8c62730..b1365bc69 100644
--- a/src/pipecat/services/together.py
+++ b/src/pipecat/services/together.py
@@ -23,13 +23,19 @@ from pipecat.frames.frames import (
     LLMFullResponseEndFrame,
     FunctionCallResultFrame,
     FunctionCallInProgressFrame,
-    StartInterruptionFrame
+    StartInterruptionFrame,
 )
 from pipecat.metrics.metrics import LLMTokenUsage
 from pipecat.processors.frame_processor import FrameDirection
 from pipecat.services.ai_services import LLMService
-from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext, OpenAILLMContextFrame
-from pipecat.processors.aggregators.llm_response import LLMUserContextAggregator, LLMAssistantContextAggregator
+from pipecat.processors.aggregators.openai_llm_context import (
+    OpenAILLMContext,
+    OpenAILLMContextFrame,
+)
+from pipecat.processors.aggregators.llm_response import (
+    LLMUserContextAggregator,
+    LLMAssistantContextAggregator,
+)
 
 from loguru import logger
 
@@ -38,25 +44,26 @@ try:
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
-        "In order to use Together.ai, you need to `pip install pipecat-ai[together]`. Also, set `TOGETHER_API_KEY` environment variable.")
+        "In order to use Together.ai, you need to `pip install pipecat-ai[together]`. Also, set `TOGETHER_API_KEY` environment variable."
+    )
     raise Exception(f"Missing module: {e}")
 
 
 @dataclass
 class TogetherContextAggregatorPair:
-    _user: 'TogetherUserContextAggregator'
-    _assistant: 'TogetherAssistantContextAggregator'
+    _user: "TogetherUserContextAggregator"
+    _assistant: "TogetherAssistantContextAggregator"
 
-    def user(self) -> 'TogetherUserContextAggregator':
+    def user(self) -> "TogetherUserContextAggregator":
         return self._user
 
-    def assistant(self) -> 'TogetherAssistantContextAggregator':
+    def assistant(self) -> "TogetherAssistantContextAggregator":
         return self._assistant
 
 
 class TogetherLLMService(LLMService):
-    """This class implements inference with Together's Llama 3.1 models
-    """
+    """This class implements inference with Together's Llama 3.1 models"""
+
     class InputParams(BaseModel):
         frequency_penalty: Optional[float] = Field(default=None, ge=-2.0, le=2.0)
         max_tokens: Optional[int] = Field(default=4096, ge=1)
@@ -67,12 +74,13 @@ class TogetherLLMService(LLMService):
         extra: Optional[Dict[str, Any]] = Field(default_factory=dict)
 
     def __init__(
-            self,
-            *,
-            api_key: str,
-            model: str = "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo",
-            params: InputParams = InputParams(),
-            **kwargs):
+        self,
+        *,
+        api_key: str,
+        model: str = "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo",
+        params: InputParams = InputParams(),
+        **kwargs,
+    ):
         super().__init__(**kwargs)
         self._client = AsyncTogether(api_key=api_key)
         self.set_model_name(model)
@@ -91,10 +99,7 @@ class TogetherLLMService(LLMService):
     def create_context_aggregator(context: OpenAILLMContext) -> TogetherContextAggregatorPair:
         user = TogetherUserContextAggregator(context)
         assistant = TogetherAssistantContextAggregator(user)
-        return TogetherContextAggregatorPair(
-            _user=user,
-            _assistant=assistant
-        )
+        return TogetherContextAggregatorPair(_user=user, _assistant=assistant)
 
     async def set_frequency_penalty(self, frequency_penalty: float):
         logger.debug(f"Switching LLM frequency_penalty to: [{frequency_penalty}]")
@@ -142,7 +147,7 @@ class TogetherLLMService(LLMService):
                 "presence_penalty": self._presence_penalty,
                 "temperature": self._temperature,
                 "top_k": self._top_k,
-                "top_p": self._top_p
+                "top_p": self._top_p,
             }
 
             params.update(self._extra)
@@ -160,7 +165,7 @@ class TogetherLLMService(LLMService):
                     tokens = LLMTokenUsage(
                         prompt_tokens=chunk.usage.prompt_tokens,
                         completion_tokens=chunk.usage.completion_tokens,
-                        total_tokens=chunk.usage.total_tokens
+                        total_tokens=chunk.usage.total_tokens,
                     )
                     await self.start_llm_usage_metrics(tokens)
 
@@ -180,7 +185,7 @@ class TogetherLLMService(LLMService):
                     else:
                         await self.push_frame(TextFrame(chunk.choices[0].delta.content))
 
-                if chunk.choices[0].finish_reason == 'eos' and accumulating_function_call:
+                if chunk.choices[0].finish_reason == "eos" and accumulating_function_call:
                     await self._extract_function_call(context, function_call_accumulator)
 
         except CancelledError as e:
@@ -219,10 +224,12 @@ class TogetherLLMService(LLMService):
             function_name, args_string = match.groups()
             try:
                 arguments = json.loads(args_string)
-                await self.call_function(context=context,
-                                         tool_call_id=str(uuid.uuid4()),
-                                         function_name=function_name,
-                                         arguments=arguments)
+                await self.call_function(
+                    context=context,
+                    tool_call_id=str(uuid.uuid4()),
+                    function_name=function_name,
+                    arguments=arguments,
+                )
                 return
             except json.JSONDecodeError as error:
                 # We get here if the LLM returns a function call with invalid JSON arguments. This could happen
@@ -281,12 +288,13 @@ class TogetherUserContextAggregator(LLMUserContextAggregator):
                 # The LLM sends a UserImageRequestFrame upstream. Cache any context provided with
                 # that frame so we can use it when we assemble the image message in the assistant
                 # context aggregator.
-                if (frame.context):
+                if frame.context:
                     if isinstance(frame.context, str):
                         self._context._user_image_request_context[frame.user_id] = frame.context
                     else:
                         logger.error(
-                            f"Unexpected UserImageRequestFrame context type: {type(frame.context)}")
+                            f"Unexpected UserImageRequestFrame context type: {type(frame.context)}"
+                        )
                         del self._context._user_image_request_context[frame.user_id]
                 else:
                     if frame.user_id in self._context._user_image_request_context:
@@ -294,6 +302,7 @@ class TogetherUserContextAggregator(LLMUserContextAggregator):
         except Exception as e:
             logger.error(f"Error processing frame: {e}")
 
+
 #
 # Claude returns a text content block along with a tool use content block. This works quite nicely
 # with streaming. We get the text first, so we can start streaming it right away. Then we get the
@@ -320,13 +329,17 @@ class TogetherAssistantContextAggregator(LLMAssistantContextAggregator):
         elif isinstance(frame, FunctionCallInProgressFrame):
             self._function_call_in_progress = frame
         elif isinstance(frame, FunctionCallResultFrame):
-            if self._function_call_in_progress and self._function_call_in_progress.tool_call_id == frame.tool_call_id:
+            if (
+                self._function_call_in_progress
+                and self._function_call_in_progress.tool_call_id == frame.tool_call_id
+            ):
                 self._function_call_in_progress = None
                 self._function_call_result = frame
                 await self._push_aggregation()
             else:
                 logger.warning(
-                    f"FunctionCallResultFrame tool_call_id does not match FunctionCallInProgressFrame tool_call_id")
+                    f"FunctionCallResultFrame tool_call_id does not match FunctionCallInProgressFrame tool_call_id"
+                )
                 self._function_call_in_progress = None
                 self._function_call_result = None
 
@@ -346,11 +359,13 @@ class TogetherAssistantContextAggregator(LLMAssistantContextAggregator):
             if self._function_call_result:
                 frame = self._function_call_result
                 self._function_call_result = None
-                self._context.add_message({
-                    "role": "tool",
-                    # Together expects the content here to be a string, so stringify it
-                    "content": str(frame.result)
-                })
+                self._context.add_message(
+                    {
+                        "role": "tool",
+                        # Together expects the content here to be a string, so stringify it
+                        "content": str(frame.result),
+                    }
+                )
                 run_llm = True
             else:
                 self._context.add_message({"role": "assistant", "content": aggregation})
diff --git a/src/pipecat/services/whisper.py b/src/pipecat/services/whisper.py
index 9f54f9ca0..a4635c6cb 100644
--- a/src/pipecat/services/whisper.py
+++ b/src/pipecat/services/whisper.py
@@ -23,13 +23,13 @@ try:
     from faster_whisper import WhisperModel
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
-    logger.error(
-        "In order to use Whisper, you need to `pip install pipecat-ai[whisper]`.")
+    logger.error("In order to use Whisper, you need to `pip install pipecat-ai[whisper]`.")
     raise Exception(f"Missing module: {e}")
 
 
 class Model(Enum):
     """Class of basic Whisper model selection options"""
+
     TINY = "tiny"
     BASE = "base"
     MEDIUM = "medium"
@@ -41,14 +41,15 @@ class Model(Enum):
 class WhisperSTTService(SegmentedSTTService):
     """Class to transcribe audio with a locally-downloaded Whisper model"""
 
-    def __init__(self,
-                 *,
-                 model: str | Model = Model.DISTIL_MEDIUM_EN,
-                 device: str = "auto",
-                 compute_type: str = "default",
-                 no_speech_prob: float = 0.4,
-                 **kwargs):
-
+    def __init__(
+        self,
+        *,
+        model: str | Model = Model.DISTIL_MEDIUM_EN,
+        device: str = "auto",
+        compute_type: str = "default",
+        no_speech_prob: float = 0.4,
+        **kwargs,
+    ):
         super().__init__(**kwargs)
         self._device: str = device
         self._compute_type = compute_type
@@ -65,9 +66,8 @@ class WhisperSTTService(SegmentedSTTService):
         this model is being run, it will take time to download."""
         logger.debug("Loading Whisper model...")
         self._model = WhisperModel(
-            self.model_name,
-            device=self._device,
-            compute_type=self._compute_type)
+            self.model_name, device=self._device, compute_type=self._compute_type
+        )
         logger.debug("Loaded Whisper model")
 
     async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]:
diff --git a/src/pipecat/services/xtts.py b/src/pipecat/services/xtts.py
index 69b754f55..5161efcf6 100644
--- a/src/pipecat/services/xtts.py
+++ b/src/pipecat/services/xtts.py
@@ -14,7 +14,8 @@ from pipecat.frames.frames import (
     StartFrame,
     TTSAudioRawFrame,
     TTSStartedFrame,
-    TTSStoppedFrame)
+    TTSStoppedFrame,
+)
 from pipecat.services.ai_services import TTSService
 
 from loguru import logger
@@ -38,15 +39,15 @@ except ModuleNotFoundError as e:
 
 
 class XTTSService(TTSService):
-
     def __init__(
-            self,
-            *,
-            voice_id: str,
-            language: str,
-            base_url: str,
-            aiohttp_session: aiohttp.ClientSession,
-            **kwargs):
+        self,
+        *,
+        voice_id: str,
+        language: str,
+        base_url: str,
+        aiohttp_session: aiohttp.ClientSession,
+        **kwargs,
+    ):
         super().__init__(**kwargs)
 
         self._voice_id = voice_id
@@ -64,9 +65,13 @@ class XTTSService(TTSService):
             if r.status != 200:
                 text = await r.text()
                 logger.error(
-                    f"{self} error getting studio speakers (status: {r.status}, error: {text})")
+                    f"{self} error getting studio speakers (status: {r.status}, error: {text})"
+                )
                 await self.push_error(
-                    ErrorFrame(f"Error error getting studio speakers (status: {r.status}, error: {text})"))
+                    ErrorFrame(
+                        f"Error error getting studio speakers (status: {r.status}, error: {text})"
+                    )
+                )
                 return
             self._studio_speakers = await r.json()
 
@@ -86,7 +91,7 @@ class XTTSService(TTSService):
         url = self._base_url + "/tts_stream"
 
         payload = {
-            "text": text.replace('.', '').replace('*', ''),
+            "text": text.replace(".", "").replace("*", ""),
             "language": self._language,
             "speaker_embedding": embeddings["speaker_embedding"],
             "gpt_cond_latent": embeddings["gpt_cond_latent"],
@@ -115,7 +120,9 @@ class XTTSService(TTSService):
                     buffer.extend(chunk)
 
                     # Check if buffer has enough data for processing
-                    while len(buffer) >= 48000:  # Assuming at least 0.5 seconds of audio data at 24000 Hz
+                    while (
+                        len(buffer) >= 48000
+                    ):  # Assuming at least 0.5 seconds of audio data at 24000 Hz
                         # Process the buffer up to a safe size for resampling
                         process_data = buffer[:48000]
                         # Remove processed data from buffer
diff --git a/src/pipecat/transcriptions/language.py b/src/pipecat/transcriptions/language.py
index f9e98104b..2ee3d9e95 100644
--- a/src/pipecat/transcriptions/language.py
+++ b/src/pipecat/transcriptions/language.py
@@ -9,6 +9,7 @@ import sys
 from enum import Enum
 
 if sys.version_info < (3, 11):
+
     class StrEnum(str, Enum):
         def __new__(cls, value):
             obj = str.__new__(cls, value)
@@ -19,46 +20,46 @@ else:
 
 
 class Language(StrEnum):
-    BG = "bg"            # Bulgarian
-    CA = "ca"            # Catalan
-    ZH = "zh"            # Chinese simplified
-    ZH_TW = "zh-TW"      # Chinese traditional
-    CS = "cs"            # Czech
-    DA = "da"            # Danish
-    NL = "nl"            # Dutch
-    EN = "en"            # English
-    EN_US = "en-US"      # English (USA)
-    EN_AU = "en-AU"      # English (Australia)
-    EN_GB = "en-GB"      # English (Great Britain)
-    EN_NZ = "en-NZ"      # English (New Zealand)
-    EN_IN = "en-IN"      # English (India)
-    ET = "et"            # Estonian
-    FI = "fi"            # Finnish
-    NL_BE = "nl-BE"      # Flemmish
-    FR = "fr"            # French
-    FR_CA = "fr-CA"      # French (Canada)
-    DE = "de"            # German
-    DE_CH = "de-CH"      # German (Switzerland)
-    EL = "el"            # Greek
-    HI = "hi"            # Hindi
-    HU = "hu"            # Hungarian
-    ID = "id"            # Indonesian
-    IT = "it"            # Italian
-    JA = "ja"            # Japanese
-    KO = "ko"            # Korean
-    LV = "lv"            # Latvian
-    LT = "lt"            # Lithuanian
-    MS = "ms"            # Malay
-    NO = "no"            # Norwegian
-    PL = "pl"            # Polish
-    PT = "pt"            # Portuguese
-    PT_BR = "pt-BR"      # Portuguese (Brazil)
-    RO = "ro"            # Romanian
-    RU = "ru"            # Russian
-    SK = "sk"            # Slovak
-    ES = "es"            # Spanish
-    SV = "sv"            # Swedish
-    TH = "th"            # Thai
-    TR = "tr"            # Turkish
-    UK = "uk"            # Ukrainian
-    VI = "vi"            # Vietnamese
+    BG = "bg"  # Bulgarian
+    CA = "ca"  # Catalan
+    ZH = "zh"  # Chinese simplified
+    ZH_TW = "zh-TW"  # Chinese traditional
+    CS = "cs"  # Czech
+    DA = "da"  # Danish
+    NL = "nl"  # Dutch
+    EN = "en"  # English
+    EN_US = "en-US"  # English (USA)
+    EN_AU = "en-AU"  # English (Australia)
+    EN_GB = "en-GB"  # English (Great Britain)
+    EN_NZ = "en-NZ"  # English (New Zealand)
+    EN_IN = "en-IN"  # English (India)
+    ET = "et"  # Estonian
+    FI = "fi"  # Finnish
+    NL_BE = "nl-BE"  # Flemmish
+    FR = "fr"  # French
+    FR_CA = "fr-CA"  # French (Canada)
+    DE = "de"  # German
+    DE_CH = "de-CH"  # German (Switzerland)
+    EL = "el"  # Greek
+    HI = "hi"  # Hindi
+    HU = "hu"  # Hungarian
+    ID = "id"  # Indonesian
+    IT = "it"  # Italian
+    JA = "ja"  # Japanese
+    KO = "ko"  # Korean
+    LV = "lv"  # Latvian
+    LT = "lt"  # Lithuanian
+    MS = "ms"  # Malay
+    NO = "no"  # Norwegian
+    PL = "pl"  # Polish
+    PT = "pt"  # Portuguese
+    PT_BR = "pt-BR"  # Portuguese (Brazil)
+    RO = "ro"  # Romanian
+    RU = "ru"  # Russian
+    SK = "sk"  # Slovak
+    ES = "es"  # Spanish
+    SV = "sv"  # Swedish
+    TH = "th"  # Thai
+    TR = "tr"  # Turkish
+    UK = "uk"  # Ukrainian
+    VI = "vi"  # Vietnamese
diff --git a/src/pipecat/transports/base_input.py b/src/pipecat/transports/base_input.py
index 4e398e779..73ad3f5e3 100644
--- a/src/pipecat/transports/base_input.py
+++ b/src/pipecat/transports/base_input.py
@@ -21,7 +21,8 @@ from pipecat.frames.frames import (
     SystemFrame,
     UserStartedSpeakingFrame,
     UserStoppedSpeakingFrame,
-    VADParamsUpdateFrame)
+    VADParamsUpdateFrame,
+)
 from pipecat.transports.base_transport import TransportParams
 from pipecat.vad.vad_analyzer import VADAnalyzer, VADState
 
@@ -29,7 +30,6 @@ from loguru import logger
 
 
 class BaseInputTransport(FrameProcessor):
-
     def __init__(self, params: TransportParams, **kwargs):
         super().__init__(sync=False, **kwargs)
 
@@ -129,12 +129,17 @@ class BaseInputTransport(FrameProcessor):
         vad_analyzer = self.vad_analyzer()
         if vad_analyzer:
             state = await self.get_event_loop().run_in_executor(
-                self._executor, vad_analyzer.analyze_audio, audio_frames)
+                self._executor, vad_analyzer.analyze_audio, audio_frames
+            )
         return state
 
     async def _handle_vad(self, audio_frames: bytes, vad_state: VADState):
         new_vad_state = await self._vad_analyze(audio_frames)
-        if new_vad_state != vad_state and new_vad_state != VADState.STARTING and new_vad_state != VADState.STOPPING:
+        if (
+            new_vad_state != vad_state
+            and new_vad_state != VADState.STARTING
+            and new_vad_state != VADState.STOPPING
+        ):
             frame = None
             if new_vad_state == VADState.SPEAKING:
                 frame = UserStartedSpeakingFrame()
diff --git a/src/pipecat/transports/base_output.py b/src/pipecat/transports/base_output.py
index 263bb64f4..5423b122f 100644
--- a/src/pipecat/transports/base_output.py
+++ b/src/pipecat/transports/base_output.py
@@ -32,7 +32,8 @@ from pipecat.frames.frames import (
     TTSStartedFrame,
     TTSStoppedFrame,
     TextFrame,
-    TransportMessageFrame)
+    TransportMessageFrame,
+)
 from pipecat.transports.base_transport import TransportParams
 
 from loguru import logger
@@ -41,7 +42,6 @@ from pipecat.utils.time import nanoseconds_to_seconds
 
 
 class BaseOutputTransport(FrameProcessor):
-
     def __init__(self, params: TransportParams, **kwargs):
         super().__init__(sync=False, **kwargs)
 
@@ -53,8 +53,9 @@ class BaseOutputTransport(FrameProcessor):
 
         # We will write 20ms audio at a time. If we receive long audio frames we
         # will chunk them. This will help with interruption handling.
-        audio_bytes_10ms = int(self._params.audio_out_sample_rate / 100) * \
-            self._params.audio_out_channels * 2
+        audio_bytes_10ms = (
+            int(self._params.audio_out_sample_rate / 100) * self._params.audio_out_channels * 2
+        )
         self._audio_chunk_size = audio_bytes_10ms * 2
         self._audio_buffer = bytearray()
 
@@ -74,7 +75,9 @@ class BaseOutputTransport(FrameProcessor):
         # Create camera output queue and task if needed.
         if self._params.camera_out_enabled:
             self._camera_out_queue = asyncio.Queue()
-            self._camera_out_task = self.get_event_loop().create_task(self._camera_out_task_handler())
+            self._camera_out_task = self.get_event_loop().create_task(
+                self._camera_out_task_handler()
+            )
         # Create audio output queue and task if needed.
         if self._params.audio_out_enabled and self._params.audio_out_is_live:
             self._audio_out_queue = asyncio.Queue()
@@ -201,11 +204,12 @@ class BaseOutputTransport(FrameProcessor):
             self._audio_buffer.extend(frame.audio)
             while len(self._audio_buffer) >= self._audio_chunk_size:
                 chunk = OutputAudioRawFrame(
-                    bytes(self._audio_buffer[:self._audio_chunk_size]),
-                    sample_rate=frame.sample_rate, num_channels=frame.num_channels
+                    bytes(self._audio_buffer[: self._audio_chunk_size]),
+                    sample_rate=frame.sample_rate,
+                    num_channels=frame.num_channels,
                 )
                 await self._sink_queue.put(chunk)
-                self._audio_buffer = self._audio_buffer[self._audio_chunk_size:]
+                self._audio_buffer = self._audio_buffer[self._audio_chunk_size :]
 
     async def _handle_image(self, frame: OutputImageRawFrame | SpriteFrame):
         if not self._params.camera_out_enabled:
@@ -316,12 +320,10 @@ class BaseOutputTransport(FrameProcessor):
         if frame.size != desired_size:
             image = Image.frombytes(frame.format, frame.size, frame.image)
             resized_image = image.resize(desired_size)
-            logger.warning(
-                f"{frame} does not have the expected size {desired_size}, resizing")
+            logger.warning(f"{frame} does not have the expected size {desired_size}, resizing")
             frame = OutputImageRawFrame(
-                resized_image.tobytes(),
-                resized_image.size,
-                resized_image.format)
+                resized_image.tobytes(), resized_image.size, resized_image.format
+            )
 
         await self.write_frame_to_camera(frame)
 
diff --git a/src/pipecat/transports/base_transport.py b/src/pipecat/transports/base_transport.py
index 083aeac37..5802993fa 100644
--- a/src/pipecat/transports/base_transport.py
+++ b/src/pipecat/transports/base_transport.py
@@ -42,11 +42,12 @@ class TransportParams(BaseModel):
 
 
 class BaseTransport(ABC):
-
-    def __init__(self,
-                 input_name: str | None = None,
-                 output_name: str | None = None,
-                 loop: asyncio.AbstractEventLoop | None = None):
+    def __init__(
+        self,
+        input_name: str | None = None,
+        output_name: str | None = None,
+        loop: asyncio.AbstractEventLoop | None = None,
+    ):
         self._input_name = input_name
         self._output_name = output_name
         self._loop = loop or asyncio.get_running_loop()
@@ -64,6 +65,7 @@ class BaseTransport(ABC):
         def decorator(handler):
             self.add_event_handler(event_name, handler)
             return handler
+
         return decorator
 
     def add_event_handler(self, event_name: str, handler):
diff --git a/src/pipecat/transports/local/audio.py b/src/pipecat/transports/local/audio.py
index 45d18db52..e1ccefec2 100644
--- a/src/pipecat/transports/local/audio.py
+++ b/src/pipecat/transports/local/audio.py
@@ -21,12 +21,12 @@ try:
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
-        "In order to use local audio, you need to `pip install pipecat-ai[local]`. On MacOS, you also need to `brew install portaudio`.")
+        "In order to use local audio, you need to `pip install pipecat-ai[local]`. On MacOS, you also need to `brew install portaudio`."
+    )
     raise Exception(f"Missing module: {e}")
 
 
 class LocalAudioInputTransport(BaseInputTransport):
-
     def __init__(self, py_audio: pyaudio.PyAudio, params: TransportParams):
         super().__init__(params)
 
@@ -39,7 +39,8 @@ class LocalAudioInputTransport(BaseInputTransport):
             rate=params.audio_in_sample_rate,
             frames_per_buffer=num_frames,
             stream_callback=self._audio_in_callback,
-            input=True)
+            input=True,
+        )
 
     async def start(self, frame: StartFrame):
         await super().start(frame)
@@ -54,9 +55,11 @@ class LocalAudioInputTransport(BaseInputTransport):
         self._in_stream.close()
 
     def _audio_in_callback(self, in_data, frame_count, time_info, status):
-        frame = InputAudioRawFrame(audio=in_data,
-                                   sample_rate=self._params.audio_in_sample_rate,
-                                   num_channels=self._params.audio_in_channels)
+        frame = InputAudioRawFrame(
+            audio=in_data,
+            sample_rate=self._params.audio_in_sample_rate,
+            num_channels=self._params.audio_in_channels,
+        )
 
         asyncio.run_coroutine_threadsafe(self.push_audio_frame(frame), self.get_event_loop())
 
@@ -64,7 +67,6 @@ class LocalAudioInputTransport(BaseInputTransport):
 
 
 class LocalAudioOutputTransport(BaseOutputTransport):
-
     def __init__(self, py_audio: pyaudio.PyAudio, params: TransportParams):
         super().__init__(params)
 
@@ -74,7 +76,8 @@ class LocalAudioOutputTransport(BaseOutputTransport):
             format=py_audio.get_format_from_width(2),
             channels=params.audio_out_channels,
             rate=params.audio_out_sample_rate,
-            output=True)
+            output=True,
+        )
 
     async def start(self, frame: StartFrame):
         await super().start(frame)
@@ -93,7 +96,6 @@ class LocalAudioOutputTransport(BaseOutputTransport):
 
 
 class LocalAudioTransport(BaseTransport):
-
     def __init__(self, params: TransportParams):
         self._params = params
         self._pyaudio = pyaudio.PyAudio()
diff --git a/src/pipecat/transports/local/tk.py b/src/pipecat/transports/local/tk.py
index 75dd30331..ed7cdbea6 100644
--- a/src/pipecat/transports/local/tk.py
+++ b/src/pipecat/transports/local/tk.py
@@ -23,7 +23,8 @@ try:
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
-        "In order to use local audio, you need to `pip install pipecat-ai[local]`. On MacOS, you also need to `brew install portaudio`.")
+        "In order to use local audio, you need to `pip install pipecat-ai[local]`. On MacOS, you also need to `brew install portaudio`."
+    )
     raise Exception(f"Missing module: {e}")
 
 try:
@@ -35,7 +36,6 @@ except ModuleNotFoundError as e:
 
 
 class TkInputTransport(BaseInputTransport):
-
     def __init__(self, py_audio: pyaudio.PyAudio, params: TransportParams):
         super().__init__(params)
 
@@ -48,7 +48,8 @@ class TkInputTransport(BaseInputTransport):
             rate=params.audio_in_sample_rate,
             frames_per_buffer=num_frames,
             stream_callback=self._audio_in_callback,
-            input=True)
+            input=True,
+        )
 
     async def start(self, frame: StartFrame):
         await super().start(frame)
@@ -63,9 +64,11 @@ class TkInputTransport(BaseInputTransport):
         self._in_stream.close()
 
     def _audio_in_callback(self, in_data, frame_count, time_info, status):
-        frame = InputAudioRawFrame(audio=in_data,
-                                   sample_rate=self._params.audio_in_sample_rate,
-                                   num_channels=self._params.audio_in_channels)
+        frame = InputAudioRawFrame(
+            audio=in_data,
+            sample_rate=self._params.audio_in_sample_rate,
+            num_channels=self._params.audio_in_channels,
+        )
 
         asyncio.run_coroutine_threadsafe(self.push_audio_frame(frame), self.get_event_loop())
 
@@ -73,7 +76,6 @@ class TkInputTransport(BaseInputTransport):
 
 
 class TkOutputTransport(BaseOutputTransport):
-
     def __init__(self, tk_root: tk.Tk, py_audio: pyaudio.PyAudio, params: TransportParams):
         super().__init__(params)
 
@@ -83,7 +85,8 @@ class TkOutputTransport(BaseOutputTransport):
             format=py_audio.get_format_from_width(2),
             channels=params.audio_out_channels,
             rate=params.audio_out_sample_rate,
-            output=True)
+            output=True,
+        )
 
         # Start with a neutral gray background.
         array = np.ones((1024, 1024, 3)) * 128
@@ -114,11 +117,7 @@ class TkOutputTransport(BaseOutputTransport):
         width = frame.size[0]
         height = frame.size[1]
         data = f"P6 {width} {height} 255 ".encode() + frame.image
-        photo = tk.PhotoImage(
-            width=width,
-            height=height,
-            data=data,
-            format="PPM")
+        photo = tk.PhotoImage(width=width, height=height, data=data, format="PPM")
         self._image_label.config(image=photo)
 
         # This holds a reference to the photo, preventing it from being garbage
@@ -127,7 +126,6 @@ class TkOutputTransport(BaseOutputTransport):
 
 
 class TkLocalTransport(BaseTransport):
-
     def __init__(self, tk_root: tk.Tk, params: TransportParams):
         self._tk_root = tk_root
         self._params = params
diff --git a/src/pipecat/transports/network/fastapi_websocket.py b/src/pipecat/transports/network/fastapi_websocket.py
index 815d7c2ef..dac162530 100644
--- a/src/pipecat/transports/network/fastapi_websocket.py
+++ b/src/pipecat/transports/network/fastapi_websocket.py
@@ -19,7 +19,7 @@ from pipecat.frames.frames import (
     Frame,
     InputAudioRawFrame,
     StartFrame,
-    StartInterruptionFrame
+    StartInterruptionFrame,
 )
 from pipecat.processors.frame_processor import FrameDirection
 from pipecat.serializers.base_serializer import FrameSerializer
@@ -35,7 +35,8 @@ try:
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
-        "In order to use FastAPI websockets, you need to `pip install pipecat-ai[websocket]`.")
+        "In order to use FastAPI websockets, you need to `pip install pipecat-ai[websocket]`."
+    )
     raise Exception(f"Missing module: {e}")
 
 
@@ -51,13 +52,13 @@ class FastAPIWebsocketCallbacks(BaseModel):
 
 
 class FastAPIWebsocketInputTransport(BaseInputTransport):
-
     def __init__(
-            self,
-            websocket: WebSocket,
-            params: FastAPIWebsocketParams,
-            callbacks: FastAPIWebsocketCallbacks,
-            **kwargs):
+        self,
+        websocket: WebSocket,
+        params: FastAPIWebsocketParams,
+        callbacks: FastAPIWebsocketCallbacks,
+        **kwargs,
+    ):
         super().__init__(params, **kwargs)
 
         self._websocket = websocket
@@ -87,17 +88,18 @@ class FastAPIWebsocketInputTransport(BaseInputTransport):
                 continue
 
             if isinstance(frame, AudioRawFrame):
-                await self.push_audio_frame(InputAudioRawFrame(
-                    audio=frame.audio,
-                    sample_rate=frame.sample_rate,
-                    num_channels=frame.num_channels)
+                await self.push_audio_frame(
+                    InputAudioRawFrame(
+                        audio=frame.audio,
+                        sample_rate=frame.sample_rate,
+                        num_channels=frame.num_channels,
+                    )
                 )
 
         await self._callbacks.on_client_disconnected(self._websocket)
 
 
 class FastAPIWebsocketOutputTransport(BaseOutputTransport):
-
     def __init__(self, websocket: WebSocket, params: FastAPIWebsocketParams, **kwargs):
         super().__init__(params, **kwargs)
 
@@ -115,10 +117,9 @@ class FastAPIWebsocketOutputTransport(BaseOutputTransport):
         self._websocket_audio_buffer += frames
         while len(self._websocket_audio_buffer):
             frame = AudioRawFrame(
-                audio=self._websocket_audio_buffer[:
-                                                   self._params.audio_frame_size],
+                audio=self._websocket_audio_buffer[: self._params.audio_frame_size],
                 sample_rate=self._params.audio_out_sample_rate,
-                num_channels=self._params.audio_out_channels
+                num_channels=self._params.audio_out_channels,
             )
 
             if self._params.add_wav_header:
@@ -131,9 +132,8 @@ class FastAPIWebsocketOutputTransport(BaseOutputTransport):
                 ww.close()
                 content.seek(0)
                 wav_frame = AudioRawFrame(
-                    content.read(),
-                    sample_rate=frame.sample_rate,
-                    num_channels=frame.num_channels)
+                    content.read(), sample_rate=frame.sample_rate, num_channels=frame.num_channels
+                )
                 frame = wav_frame
 
             payload = self._params.serializer.serialize(frame)
@@ -141,7 +141,8 @@ class FastAPIWebsocketOutputTransport(BaseOutputTransport):
                 await self._websocket.send_text(payload)
 
             self._websocket_audio_buffer = self._websocket_audio_buffer[
-                self._params.audio_frame_size:]
+                self._params.audio_frame_size :
+            ]
 
     async def _write_frame(self, frame: Frame):
         payload = self._params.serializer.serialize(frame)
@@ -150,26 +151,28 @@ class FastAPIWebsocketOutputTransport(BaseOutputTransport):
 
 
 class FastAPIWebsocketTransport(BaseTransport):
-
     def __init__(
-            self,
-            websocket: WebSocket,
-            params: FastAPIWebsocketParams,
-            input_name: str | None = None,
-            output_name: str | None = None,
-            loop: asyncio.AbstractEventLoop | None = None):
+        self,
+        websocket: WebSocket,
+        params: FastAPIWebsocketParams,
+        input_name: str | None = None,
+        output_name: str | None = None,
+        loop: asyncio.AbstractEventLoop | None = None,
+    ):
         super().__init__(input_name=input_name, output_name=output_name, loop=loop)
         self._params = params
 
         self._callbacks = FastAPIWebsocketCallbacks(
             on_client_connected=self._on_client_connected,
-            on_client_disconnected=self._on_client_disconnected
+            on_client_disconnected=self._on_client_disconnected,
         )
 
         self._input = FastAPIWebsocketInputTransport(
-            websocket, self._params, self._callbacks, name=self._input_name)
+            websocket, self._params, self._callbacks, name=self._input_name
+        )
         self._output = FastAPIWebsocketOutputTransport(
-            websocket, self._params, name=self._output_name)
+            websocket, self._params, name=self._output_name
+        )
 
         # Register supported handlers. The user will only be able to register
         # these handlers.
diff --git a/src/pipecat/transports/network/websocket_server.py b/src/pipecat/transports/network/websocket_server.py
index 329ae8994..b5d38f60e 100644
--- a/src/pipecat/transports/network/websocket_server.py
+++ b/src/pipecat/transports/network/websocket_server.py
@@ -11,7 +11,13 @@ import wave
 from typing import Awaitable, Callable
 from pydantic.main import BaseModel
 
-from pipecat.frames.frames import AudioRawFrame, CancelFrame, EndFrame, InputAudioRawFrame, StartFrame
+from pipecat.frames.frames import (
+    AudioRawFrame,
+    CancelFrame,
+    EndFrame,
+    InputAudioRawFrame,
+    StartFrame,
+)
 from pipecat.serializers.base_serializer import FrameSerializer
 from pipecat.serializers.protobuf import ProtobufFrameSerializer
 from pipecat.transports.base_input import BaseInputTransport
@@ -40,14 +46,14 @@ class WebsocketServerCallbacks(BaseModel):
 
 
 class WebsocketServerInputTransport(BaseInputTransport):
-
     def __init__(
-            self,
-            host: str,
-            port: int,
-            params: WebsocketServerParams,
-            callbacks: WebsocketServerCallbacks,
-            **kwargs):
+        self,
+        host: str,
+        port: int,
+        params: WebsocketServerParams,
+        callbacks: WebsocketServerCallbacks,
+        **kwargs,
+    ):
         super().__init__(params, **kwargs)
 
         self._host = host
@@ -97,10 +103,12 @@ class WebsocketServerInputTransport(BaseInputTransport):
                 continue
 
             if isinstance(frame, AudioRawFrame):
-                await self.push_audio_frame(InputAudioRawFrame(
-                    audio=frame.audio,
-                    sample_rate=frame.sample_rate,
-                    num_channels=frame.num_channels)
+                await self.push_audio_frame(
+                    InputAudioRawFrame(
+                        audio=frame.audio,
+                        sample_rate=frame.sample_rate,
+                        num_channels=frame.num_channels,
+                    )
                 )
             else:
                 await self.push_frame(frame)
@@ -115,7 +123,6 @@ class WebsocketServerInputTransport(BaseInputTransport):
 
 
 class WebsocketServerOutputTransport(BaseOutputTransport):
-
     def __init__(self, params: WebsocketServerParams, **kwargs):
         super().__init__(params, **kwargs)
 
@@ -138,9 +145,9 @@ class WebsocketServerOutputTransport(BaseOutputTransport):
         self._websocket_audio_buffer += frames
         while len(self._websocket_audio_buffer) >= self._params.audio_frame_size:
             frame = AudioRawFrame(
-                audio=self._websocket_audio_buffer[:self._params.audio_frame_size],
+                audio=self._websocket_audio_buffer[: self._params.audio_frame_size],
                 sample_rate=self._params.audio_out_sample_rate,
-                num_channels=self._params.audio_out_channels
+                num_channels=self._params.audio_out_channels,
             )
 
             if self._params.add_wav_header:
@@ -153,28 +160,29 @@ class WebsocketServerOutputTransport(BaseOutputTransport):
                 ww.close()
                 content.seek(0)
                 wav_frame = AudioRawFrame(
-                    content.read(),
-                    sample_rate=frame.sample_rate,
-                    num_channels=frame.num_channels)
+                    content.read(), sample_rate=frame.sample_rate, num_channels=frame.num_channels
+                )
                 frame = wav_frame
 
             proto = self._params.serializer.serialize(frame)
             if proto:
                 await self._websocket.send(proto)
 
-            self._websocket_audio_buffer = self._websocket_audio_buffer[self._params.audio_frame_size:]
+            self._websocket_audio_buffer = self._websocket_audio_buffer[
+                self._params.audio_frame_size :
+            ]
 
 
 class WebsocketServerTransport(BaseTransport):
-
     def __init__(
-            self,
-            host: str = "localhost",
-            port: int = 8765,
-            params: WebsocketServerParams = WebsocketServerParams(),
-            input_name: str | None = None,
-            output_name: str | None = None,
-            loop: asyncio.AbstractEventLoop | None = None):
+        self,
+        host: str = "localhost",
+        port: int = 8765,
+        params: WebsocketServerParams = WebsocketServerParams(),
+        input_name: str | None = None,
+        output_name: str | None = None,
+        loop: asyncio.AbstractEventLoop | None = None,
+    ):
         super().__init__(input_name=input_name, output_name=output_name, loop=loop)
         self._host = host
         self._port = port
@@ -182,7 +190,7 @@ class WebsocketServerTransport(BaseTransport):
 
         self._callbacks = WebsocketServerCallbacks(
             on_client_connected=self._on_client_connected,
-            on_client_disconnected=self._on_client_disconnected
+            on_client_disconnected=self._on_client_disconnected,
         )
         self._input: WebsocketServerInputTransport | None = None
         self._output: WebsocketServerOutputTransport | None = None
@@ -196,7 +204,8 @@ class WebsocketServerTransport(BaseTransport):
     def input(self) -> WebsocketServerInputTransport:
         if not self._input:
             self._input = WebsocketServerInputTransport(
-                self._host, self._port, self._params, self._callbacks, name=self._input_name)
+                self._host, self._port, self._params, self._callbacks, name=self._input_name
+            )
         return self._input
 
     def output(self) -> WebsocketServerOutputTransport:
diff --git a/src/pipecat/transports/services/daily.py b/src/pipecat/transports/services/daily.py
index eb2d6da7a..48b59d8ff 100644
--- a/src/pipecat/transports/services/daily.py
+++ b/src/pipecat/transports/services/daily.py
@@ -18,7 +18,8 @@ from daily import (
     EventHandler,
     VirtualCameraDevice,
     VirtualMicrophoneDevice,
-    VirtualSpeakerDevice)
+    VirtualSpeakerDevice,
+)
 from pydantic.main import BaseModel
 
 from pipecat.frames.frames import (
@@ -35,8 +36,14 @@ from pipecat.frames.frames import (
     TranscriptionFrame,
     TransportMessageFrame,
     UserImageRawFrame,
-    UserImageRequestFrame)
-from pipecat.metrics.metrics import LLMUsageMetricsData, ProcessingMetricsData, TTFBMetricsData, TTSUsageMetricsData
+    UserImageRequestFrame,
+)
+from pipecat.metrics.metrics import (
+    LLMUsageMetricsData,
+    ProcessingMetricsData,
+    TTFBMetricsData,
+    TTSUsageMetricsData,
+)
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.transcriptions.language import Language
 from pipecat.transports.base_input import BaseInputTransport
@@ -47,11 +54,12 @@ from pipecat.vad.vad_analyzer import VADAnalyzer, VADParams
 from loguru import logger
 
 try:
-    from daily import (EventHandler, CallClient, Daily)
+    from daily import EventHandler, CallClient, Daily
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
-        "In order to use the Daily transport, you need to `pip install pipecat-ai[daily]`.")
+        "In order to use the Daily transport, you need to `pip install pipecat-ai[daily]`."
+    )
     raise Exception(f"Missing module: {e}")
 
 VAD_RESET_PERIOD_MS = 2000
@@ -63,14 +71,11 @@ class DailyTransportMessageFrame(TransportMessageFrame):
 
 
 class WebRTCVADAnalyzer(VADAnalyzer):
-
     def __init__(self, *, sample_rate=16000, num_channels=1, params: VADParams = VADParams()):
         super().__init__(sample_rate=sample_rate, num_channels=num_channels, params=params)
 
         self._webrtc_vad = Daily.create_native_vad(
-            reset_period_ms=VAD_RESET_PERIOD_MS,
-            sample_rate=sample_rate,
-            channels=num_channels
+            reset_period_ms=VAD_RESET_PERIOD_MS, sample_rate=sample_rate, channels=num_channels
         )
         logger.debug("Loaded native WebRTC VAD")
 
@@ -98,9 +103,7 @@ class DailyTranscriptionSettings(BaseModel):
     endpointing: bool = True
     punctuate: bool = True
     includeRawResponse: bool = True
-    extra: Mapping[str, Any] = {
-        "interim_results": True
-    }
+    extra: Mapping[str, Any] = {"interim_results": True}
 
 
 class DailyParams(TransportParams):
@@ -139,12 +142,13 @@ def completion_callback(future):
                     future.set_result(*args)
             except asyncio.InvalidStateError:
                 pass
+
         future.get_loop().call_soon_threadsafe(set_result, future, *args)
+
     return _callback
 
 
 class DailyTransportClient(EventHandler):
-
     _daily_initialized: bool = False
 
     # This is necessary to override EventHandler's __new__ method.
@@ -152,13 +156,14 @@ class DailyTransportClient(EventHandler):
         return super().__new__(cls)
 
     def __init__(
-            self,
-            room_url: str,
-            token: str | None,
-            bot_name: str,
-            params: DailyParams,
-            callbacks: DailyCallbacks,
-            loop: asyncio.AbstractEventLoop):
+        self,
+        room_url: str,
+        token: str | None,
+        bot_name: str,
+        params: DailyParams,
+        callbacks: DailyCallbacks,
+        loop: asyncio.AbstractEventLoop,
+    ):
         super().__init__()
 
         if not DailyTransportClient._daily_initialized:
@@ -191,7 +196,8 @@ class DailyTransportClient(EventHandler):
                 self._camera_name(),
                 width=self._params.camera_out_width,
                 height=self._params.camera_out_height,
-                color_format=self._params.camera_out_color_format)
+                color_format=self._params.camera_out_color_format,
+            )
 
         self._mic: VirtualMicrophoneDevice | None = None
         if self._params.audio_out_enabled:
@@ -199,7 +205,8 @@ class DailyTransportClient(EventHandler):
                 self._mic_name(),
                 sample_rate=self._params.audio_out_sample_rate,
                 channels=self._params.audio_out_channels,
-                non_blocking=True)
+                non_blocking=True,
+            )
 
         self._speaker: VirtualSpeakerDevice | None = None
         if self._params.audio_in_enabled or self._params.vad_enabled:
@@ -207,7 +214,8 @@ class DailyTransportClient(EventHandler):
                 self._speaker_name(),
                 sample_rate=self._params.audio_in_sample_rate,
                 channels=self._params.audio_in_channels,
-                non_blocking=True)
+                non_blocking=True,
+            )
             Daily.select_speaker_device(self._speaker_name())
 
     def _camera_name(self):
@@ -236,9 +244,8 @@ class DailyTransportClient(EventHandler):
 
         future = self._loop.create_future()
         self._client.send_app_message(
-            frame.message,
-            participant_id,
-            completion=completion_callback(future))
+            frame.message, participant_id, completion=completion_callback(future)
+        )
         await future
 
     async def read_next_audio_frame(self) -> InputAudioRawFrame | None:
@@ -255,9 +262,8 @@ class DailyTransportClient(EventHandler):
 
         if len(audio) > 0:
             return InputAudioRawFrame(
-                audio=audio,
-                sample_rate=sample_rate,
-                num_channels=num_channels)
+                audio=audio, sample_rate=sample_rate, num_channels=num_channels
+            )
         else:
             # If we don't read any audio it could be there's no participant
             # connected. daily-python will return immediately if that's the
@@ -290,12 +296,9 @@ class DailyTransportClient(EventHandler):
 
         # For performance reasons, never subscribe to video streams (unless a
         # video renderer is registered).
-        self._client.update_subscription_profiles({
-            "base": {
-                "camera": "unsubscribed",
-                "screenVideo": "unsubscribed"
-            }
-        })
+        self._client.update_subscription_profiles(
+            {"base": {"camera": "unsubscribed", "screenVideo": "unsubscribed"}}
+        )
 
         self._client.set_user_name(self._bot_name)
 
@@ -327,7 +330,7 @@ class DailyTransportClient(EventHandler):
         future = self._loop.create_future()
         self._client.start_transcription(
             settings=self._params.transcription_settings.model_dump(exclude_none=True),
-            completion=completion_callback(future)
+            completion=completion_callback(future),
         )
         error = await future
         if error:
@@ -374,12 +377,15 @@ class DailyTransportClient(EventHandler):
                     },
                     "microphone": {
                         "sendSettings": {
-                            "channelConfig": "stereo" if self._params.audio_out_channels == 2 else "mono",
+                            "channelConfig": "stereo"
+                            if self._params.audio_out_channels == 2
+                            else "mono",
                             "bitrate": self._params.audio_out_bitrate,
                         }
-                    }
+                    },
                 },
-            })
+            },
+        )
 
         return await asyncio.wait_for(future, timeout=10)
 
@@ -456,18 +462,17 @@ class DailyTransportClient(EventHandler):
         self._transcription_renderers[participant_id] = callback
 
     def capture_participant_video(
-            self,
-            participant_id: str,
-            callback: Callable,
-            framerate: int = 30,
-            video_source: str = "camera",
-            color_format: str = "RGB"):
+        self,
+        participant_id: str,
+        callback: Callable,
+        framerate: int = 30,
+        video_source: str = "camera",
+        color_format: str = "RGB",
+    ):
         # Only enable camera subscription on this participant
-        self._client.update_subscriptions(participant_settings={
-            participant_id: {
-                "media": "subscribed"
-            }
-        })
+        self._client.update_subscriptions(
+            participant_settings={participant_id: {"media": "subscribed"}}
+        )
 
         self._video_renderers[participant_id] = callback
 
@@ -475,7 +480,8 @@ class DailyTransportClient(EventHandler):
             participant_id,
             self._video_frame_received,
             video_source=video_source,
-            color_format=color_format)
+            color_format=color_format,
+        )
 
     #
     #
@@ -553,9 +559,9 @@ class DailyTransportClient(EventHandler):
             callback,
             participant_id,
             video_frame.buffer,
-            (video_frame.width,
-             video_frame.height),
-            video_frame.color_format)
+            (video_frame.width, video_frame.height),
+            video_frame.color_format,
+        )
 
     def _call_async_callback(self, callback, *args):
         future = asyncio.run_coroutine_threadsafe(callback(*args), self._loop)
@@ -563,7 +569,6 @@ class DailyTransportClient(EventHandler):
 
 
 class DailyInputTransport(BaseInputTransport):
-
     def __init__(self, client: DailyTransportClient, params: DailyParams, **kwargs):
         super().__init__(params, **kwargs)
 
@@ -576,7 +581,8 @@ class DailyInputTransport(BaseInputTransport):
         if params.vad_enabled and not params.vad_analyzer:
             self._vad_analyzer = WebRTCVADAnalyzer(
                 sample_rate=self._params.audio_in_sample_rate,
-                num_channels=self._params.audio_in_channels)
+                num_channels=self._params.audio_in_channels,
+            )
 
     async def start(self, frame: StartFrame):
         # Parent start.
@@ -654,11 +660,12 @@ class DailyInputTransport(BaseInputTransport):
     #
 
     def capture_participant_video(
-            self,
-            participant_id: str,
-            framerate: int = 30,
-            video_source: str = "camera",
-            color_format: str = "RGB"):
+        self,
+        participant_id: str,
+        framerate: int = 30,
+        video_source: str = "camera",
+        color_format: str = "RGB",
+    ):
         self._video_renderers[participant_id] = {
             "framerate": framerate,
             "timestamp": 0,
@@ -666,11 +673,7 @@ class DailyInputTransport(BaseInputTransport):
         }
 
         self._client.capture_participant_video(
-            participant_id,
-            self._on_participant_video_frame,
-            framerate,
-            video_source,
-            color_format
+            participant_id, self._on_participant_video_frame, framerate, video_source, color_format
         )
 
     def request_participant_image(self, participant_id: str):
@@ -693,17 +696,14 @@ class DailyInputTransport(BaseInputTransport):
 
         if render_frame:
             frame = UserImageRawFrame(
-                user_id=participant_id,
-                image=buffer,
-                size=size,
-                format=format)
+                user_id=participant_id, image=buffer, size=size, format=format
+            )
             await self.push_frame(frame)
 
         self._video_renderers[participant_id]["timestamp"] = curr_time
 
 
 class DailyOutputTransport(BaseOutputTransport):
-
     def __init__(self, client: DailyTransportClient, params: DailyParams, **kwargs):
         super().__init__(params, **kwargs)
 
@@ -754,10 +754,9 @@ class DailyOutputTransport(BaseOutputTransport):
                     metrics["characters"] = []
                 metrics["characters"].append(d.model_dump(exclude_none=True))
 
-        message = DailyTransportMessageFrame(message={
-            "type": "pipecat-metrics",
-            "metrics": metrics
-        })
+        message = DailyTransportMessageFrame(
+            message={"type": "pipecat-metrics", "metrics": metrics}
+        )
         await self._client.send_message(message)
 
     async def write_raw_audio_frames(self, frames: bytes):
@@ -768,16 +767,16 @@ class DailyOutputTransport(BaseOutputTransport):
 
 
 class DailyTransport(BaseTransport):
-
     def __init__(
-            self,
-            room_url: str,
-            token: str | None,
-            bot_name: str,
-            params: DailyParams = DailyParams(),
-            input_name: str | None = None,
-            output_name: str | None = None,
-            loop: asyncio.AbstractEventLoop | None = None):
+        self,
+        room_url: str,
+        token: str | None,
+        bot_name: str,
+        params: DailyParams = DailyParams(),
+        input_name: str | None = None,
+        output_name: str | None = None,
+        loop: asyncio.AbstractEventLoop | None = None,
+    ):
         super().__init__(input_name=input_name, output_name=output_name, loop=loop)
 
         callbacks = DailyCallbacks(
@@ -800,7 +799,8 @@ class DailyTransport(BaseTransport):
         self._params = params
 
         self._client = DailyTransportClient(
-            room_url, token, bot_name, params, callbacks, self._loop)
+            room_url, token, bot_name, params, callbacks, self._loop
+        )
         self._input: DailyInputTransport | None = None
         self._output: DailyOutputTransport | None = None
 
@@ -871,19 +871,20 @@ class DailyTransport(BaseTransport):
 
     def capture_participant_transcription(self, participant_id: str):
         self._client.capture_participant_transcription(
-            participant_id,
-            self._on_transcription_message
+            participant_id, self._on_transcription_message
         )
 
     def capture_participant_video(
-            self,
-            participant_id: str,
-            framerate: int = 30,
-            video_source: str = "camera",
-            color_format: str = "RGB"):
+        self,
+        participant_id: str,
+        framerate: int = 30,
+        video_source: str = "camera",
+        color_format: str = "RGB",
+    ):
         if self._input:
             self._input.capture_participant_video(
-                participant_id, framerate, video_source, color_format)
+                participant_id, framerate, video_source, color_format
+            )
 
     async def _on_joined(self, data):
         await self._call_event_handler("on_joined", data)
@@ -911,12 +912,12 @@ class DailyTransport(BaseTransport):
         async with aiohttp.ClientSession() as session:
             headers = {
                 "Authorization": f"Bearer {self._params.api_key}",
-                "Content-Type": "application/json"
+                "Content-Type": "application/json",
             }
             data = {
                 "callId": self._params.dialin_settings.call_id,
                 "callDomain": self._params.dialin_settings.call_domain,
-                "sipUri": sip_endpoint
+                "sipUri": sip_endpoint,
             }
 
             url = f"{self._params.api_url}/dialin/pinlessCallUpdate"
@@ -926,7 +927,8 @@ class DailyTransport(BaseTransport):
                     if r.status != 200:
                         text = await r.text()
                         logger.error(
-                            f"Unable to handle dialin-ready event (status: {r.status}, error: {text})")
+                            f"Unable to handle dialin-ready event (status: {r.status}, error: {text})"
+                        )
                         return
 
                     logger.debug("Event dialin-ready was handled successfully")
diff --git a/src/pipecat/transports/services/helpers/daily_rest.py b/src/pipecat/transports/services/helpers/daily_rest.py
index 40c314613..4f15fc28a 100644
--- a/src/pipecat/transports/services/helpers/daily_rest.py
+++ b/src/pipecat/transports/services/helpers/daily_rest.py
@@ -41,12 +41,12 @@ class DailyRoomProperties(BaseModel, extra="allow"):
         if not self.sip_uri:
             return ""
         else:
-            return "sip:%s" % self.sip_uri['endpoint']
+            return "sip:%s" % self.sip_uri["endpoint"]
 
 
 class DailyRoomParams(BaseModel):
     name: Optional[str] = None
-    privacy: Literal['private', 'public'] = "public"
+    privacy: Literal["private", "public"] = "public"
     properties: DailyRoomProperties = Field(default_factory=DailyRoomProperties)
 
 
@@ -61,11 +61,13 @@ class DailyRoomObject(BaseModel):
 
 
 class DailyRESTHelper:
-    def __init__(self,
-                 *,
-                 daily_api_key: str,
-                 daily_api_url: str = "https://api.daily.co/v1",
-                 aiohttp_session: aiohttp.ClientSession):
+    def __init__(
+        self,
+        *,
+        daily_api_key: str,
+        daily_api_url: str = "https://api.daily.co/v1",
+        aiohttp_session: aiohttp.ClientSession,
+    ):
         self.daily_api_key = daily_api_key
         self.daily_api_url = daily_api_url
         self.aiohttp_session = aiohttp_session
@@ -80,7 +82,9 @@ class DailyRESTHelper:
     async def create_room(self, params: DailyRoomParams) -> DailyRoomObject:
         headers = {"Authorization": f"Bearer {self.daily_api_key}"}
         json = {**params.model_dump(exclude_none=True)}
-        async with self.aiohttp_session.post(f"{self.daily_api_url}/rooms", headers=headers, json=json) as r:
+        async with self.aiohttp_session.post(
+            f"{self.daily_api_url}/rooms", headers=headers, json=json
+        ) as r:
             if r.status != 200:
                 text = await r.text()
                 raise Exception(f"Unable to create room (status: {r.status}): {text}")
@@ -95,27 +99,22 @@ class DailyRESTHelper:
         return room
 
     async def get_token(
-            self,
-            room_url: str,
-            expiry_time: float = 60 * 60,
-            owner: bool = True) -> str:
+        self, room_url: str, expiry_time: float = 60 * 60, owner: bool = True
+    ) -> str:
         if not room_url:
             raise Exception(
-                "No Daily room specified. You must specify a Daily room in order a token to be generated.")
+                "No Daily room specified. You must specify a Daily room in order a token to be generated."
+            )
 
         expiration: float = time.time() + expiry_time
 
         room_name = self.get_name_from_url(room_url)
 
         headers = {"Authorization": f"Bearer {self.daily_api_key}"}
-        json = {
-            "properties": {
-                "room_name": room_name,
-                "is_owner": owner,
-                "exp": expiration
-            }
-        }
-        async with self.aiohttp_session.post(f"{self.daily_api_url}/meeting-tokens", headers=headers, json=json) as r:
+        json = {"properties": {"room_name": room_name, "is_owner": owner, "exp": expiration}}
+        async with self.aiohttp_session.post(
+            f"{self.daily_api_url}/meeting-tokens", headers=headers, json=json
+        ) as r:
             if r.status != 200:
                 text = await r.text()
                 raise Exception(f"Failed to create meeting token (status: {r.status}): {text}")
@@ -130,7 +129,9 @@ class DailyRESTHelper:
 
     async def delete_room_by_name(self, room_name: str) -> bool:
         headers = {"Authorization": f"Bearer {self.daily_api_key}"}
-        async with self.aiohttp_session.delete(f"{self.daily_api_url}/rooms/{room_name}", headers=headers) as r:
+        async with self.aiohttp_session.delete(
+            f"{self.daily_api_url}/rooms/{room_name}", headers=headers
+        ) as r:
             if r.status != 200 and r.status != 404:
                 text = await r.text()
                 raise Exception(f"Failed to delete room [{room_name}] (status: {r.status}): {text}")
@@ -139,7 +140,9 @@ class DailyRESTHelper:
 
     async def _get_room_from_name(self, room_name: str) -> DailyRoomObject:
         headers = {"Authorization": f"Bearer {self.daily_api_key}"}
-        async with self.aiohttp_session.get(f"{self.daily_api_url}/rooms/{room_name}", headers=headers) as r:
+        async with self.aiohttp_session.get(
+            f"{self.daily_api_url}/rooms/{room_name}", headers=headers
+        ) as r:
             if r.status != 200:
                 raise Exception(f"Room not found: {room_name}")
 
diff --git a/src/pipecat/utils/test_frame_processor.py b/src/pipecat/utils/test_frame_processor.py
index ed9429443..e46bae7ad 100644
--- a/src/pipecat/utils/test_frame_processor.py
+++ b/src/pipecat/utils/test_frame_processor.py
@@ -15,7 +15,9 @@ class TestFrameProcessor(FrameProcessor):
     async def process_frame(self, frame, direction):
         await super().process_frame(frame, direction)
 
-        if not self.test_frames[0]:  # then we've run out of required frames but the generator is still going?
+        if not self.test_frames[
+            0
+        ]:  # then we've run out of required frames but the generator is still going?
             raise TestException(f"Oops, got an extra frame, {frame}")
         if isinstance(self.test_frames[0], List):
             # We need to consume frames until we see the next frame type after this
diff --git a/src/pipecat/vad/silero.py b/src/pipecat/vad/silero.py
index c07ee2ae9..3e852b38b 100644
--- a/src/pipecat/vad/silero.py
+++ b/src/pipecat/vad/silero.py
@@ -8,7 +8,12 @@ import time
 
 import numpy as np
 
-from pipecat.frames.frames import AudioRawFrame, Frame, UserStartedSpeakingFrame, UserStoppedSpeakingFrame
+from pipecat.frames.frames import (
+    AudioRawFrame,
+    Frame,
+    UserStartedSpeakingFrame,
+    UserStoppedSpeakingFrame,
+)
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.vad.vad_analyzer import VADAnalyzer, VADParams, VADState
 
@@ -26,19 +31,20 @@ except ModuleNotFoundError as e:
     raise Exception(f"Missing module(s): {e}")
 
 
-class SileroOnnxModel():
-
+class SileroOnnxModel:
     def __init__(self, path, force_onnx_cpu=True):
         import numpy as np
+
         global np
 
         opts = onnxruntime.SessionOptions()
         opts.inter_op_num_threads = 1
         opts.intra_op_num_threads = 1
 
-        if force_onnx_cpu and 'CPUExecutionProvider' in onnxruntime.get_available_providers():
+        if force_onnx_cpu and "CPUExecutionProvider" in onnxruntime.get_available_providers():
             self.session = onnxruntime.InferenceSession(
-                path, providers=['CPUExecutionProvider'], sess_options=opts)
+                path, providers=["CPUExecutionProvider"], sess_options=opts
+            )
         else:
             self.session = onnxruntime.InferenceSession(path, sess_options=opts)
 
@@ -53,26 +59,27 @@ class SileroOnnxModel():
 
         if sr not in self.sample_rates:
             raise ValueError(
-                f"Supported sampling rates: {self.sample_rates} (or multiply of 16000)")
+                f"Supported sampling rates: {self.sample_rates} (or multiply of 16000)"
+            )
         if sr / np.shape(x)[1] > 31.25:
             raise ValueError("Input audio chunk is too short")
 
         return x, sr
 
     def reset_states(self, batch_size=1):
-        self._state = np.zeros((2, batch_size, 128), dtype='float32')
-        self._context = np.zeros((batch_size, 0), dtype='float32')
+        self._state = np.zeros((2, batch_size, 128), dtype="float32")
+        self._context = np.zeros((batch_size, 0), dtype="float32")
         self._last_sr = 0
         self._last_batch_size = 0
 
     def __call__(self, x, sr: int):
-
         x, sr = self._validate_input(x, sr)
         num_samples = 512 if sr == 16000 else 256
 
         if np.shape(x)[-1] != num_samples:
             raise ValueError(
-                f"Provided number of samples is {np.shape(x)[-1]} (Supported values: 256 for 8000 sample rate, 512 for 16000)")
+                f"Provided number of samples is {np.shape(x)[-1]} (Supported values: 256 for 8000 sample rate, 512 for 16000)"
+            )
 
         batch_size = np.shape(x)[0]
         context_size = 64 if sr == 16000 else 32
@@ -85,12 +92,12 @@ class SileroOnnxModel():
             self.reset_states(batch_size)
 
         if not np.shape(self._context)[1]:
-            self._context = np.zeros((batch_size, context_size), dtype='float32')
+            self._context = np.zeros((batch_size, context_size), dtype="float32")
 
         x = np.concatenate((self._context, x), axis=1)
 
         if sr in [8000, 16000]:
-            ort_inputs = {'input': x, 'state': self._state, 'sr': np.array(sr, dtype='int64')}
+            ort_inputs = {"input": x, "state": self._state, "sr": np.array(sr, dtype="int64")}
             ort_outs = self.session.run(None, ort_inputs)
             out, state = ort_outs
             self._state = state
@@ -105,12 +112,7 @@ class SileroOnnxModel():
 
 
 class SileroVADAnalyzer(VADAnalyzer):
-
-    def __init__(
-            self,
-            *,
-            sample_rate: int = 16000,
-            params: VADParams = VADParams()):
+    def __init__(self, *, sample_rate: int = 16000, params: VADParams = VADParams()):
         super().__init__(sample_rate=sample_rate, num_channels=1, params=params)
 
         if sample_rate != 16000 and sample_rate != 8000:
@@ -118,14 +120,16 @@ class SileroVADAnalyzer(VADAnalyzer):
 
         logger.debug("Loading Silero VAD model...")
 
-        model_name = 'silero_vad.onnx'
+        model_name = "silero_vad.onnx"
         package_path = "pipecat.vad.data"
 
         try:
             import importlib_resources as impresources
+
             model_file_path = str(impresources.files(package_path).joinpath(model_name))
         except BaseException:
             from importlib import resources as impresources
+
             try:
                 with impresources.path(package_path, model_name) as f:
                     model_file_path = f
@@ -168,18 +172,16 @@ class SileroVADAnalyzer(VADAnalyzer):
 
 
 class SileroVAD(FrameProcessor):
-
     def __init__(
-            self,
-            *,
-            sample_rate: int = 16000,
-            vad_params: VADParams = VADParams(),
-            audio_passthrough: bool = False):
+        self,
+        *,
+        sample_rate: int = 16000,
+        vad_params: VADParams = VADParams(),
+        audio_passthrough: bool = False,
+    ):
         super().__init__()
 
-        self._vad_analyzer = SileroVADAnalyzer(
-            sample_rate=sample_rate,
-            params=vad_params)
+        self._vad_analyzer = SileroVADAnalyzer(sample_rate=sample_rate, params=vad_params)
         self._audio_passthrough = audio_passthrough
 
         self._processor_vad_state: VADState = VADState.QUIET
@@ -202,7 +204,11 @@ class SileroVAD(FrameProcessor):
         # Check VAD and push event if necessary. We just care about changes
         # from QUIET to SPEAKING and vice versa.
         new_vad_state = self._vad_analyzer.analyze_audio(frame.audio)
-        if new_vad_state != self._processor_vad_state and new_vad_state != VADState.STARTING and new_vad_state != VADState.STOPPING:
+        if (
+            new_vad_state != self._processor_vad_state
+            and new_vad_state != VADState.STARTING
+            and new_vad_state != VADState.STOPPING
+        ):
             new_frame = None
 
             if new_vad_state == VADState.SPEAKING:
diff --git a/src/pipecat/vad/vad_analyzer.py b/src/pipecat/vad/vad_analyzer.py
index 3b7f9931d..198eb84ed 100644
--- a/src/pipecat/vad/vad_analyzer.py
+++ b/src/pipecat/vad/vad_analyzer.py
@@ -29,7 +29,6 @@ class VADParams(BaseModel):
 
 
 class VADAnalyzer:
-
     def __init__(self, *, sample_rate: int, num_channels: int, params: VADParams):
         self._sample_rate = sample_rate
         self._num_channels = num_channels
diff --git a/tests/integration/integration_azure_llm.py b/tests/integration/integration_azure_llm.py
index b2e7a50cf..5a2b68c37 100644
--- a/tests/integration/integration_azure_llm.py
+++ b/tests/integration/integration_azure_llm.py
@@ -4,7 +4,7 @@ import asyncio
 import os
 from pipecat.processors.aggregators.openai_llm_context import (
     OpenAILLMContext,
-    OpenAILLMContextFrame
+    OpenAILLMContextFrame,
 )
 from pipecat.services.azure import AzureLLMService
 
@@ -13,6 +13,7 @@ from openai.types.chat import (
 )
 
 if __name__ == "__main__":
+
     @unittest.skip("Skip azure integration test")
     async def test_chat():
         llm = AzureLLMService(
@@ -22,7 +23,8 @@ if __name__ == "__main__":
         )
         context = OpenAILLMContext()
         message: ChatCompletionSystemMessageParam = ChatCompletionSystemMessageParam(
-            content="Please tell the world hello.", name="system", role="system")
+            content="Please tell the world hello.", name="system", role="system"
+        )
         context.add_message(message)
         frame = OpenAILLMContextFrame(context)
         async for s in llm.process_frame(frame):
diff --git a/tests/integration/integration_ollama_llm.py b/tests/integration/integration_ollama_llm.py
index cbafa6324..ced24ed68 100644
--- a/tests/integration/integration_ollama_llm.py
+++ b/tests/integration/integration_ollama_llm.py
@@ -3,7 +3,7 @@ import unittest
 import asyncio
 from pipecat.processors.aggregators.openai_llm_context import (
     OpenAILLMContext,
-    OpenAILLMContextFrame
+    OpenAILLMContextFrame,
 )
 
 from openai.types.chat import (
@@ -12,12 +12,14 @@ from openai.types.chat import (
 from pipecat.services.ollama import OLLamaLLMService
 
 if __name__ == "__main__":
+
     @unittest.skip("Skip azure integration test")
     async def test_chat():
         llm = OLLamaLLMService()
         context = OpenAILLMContext()
         message: ChatCompletionSystemMessageParam = ChatCompletionSystemMessageParam(
-            content="Please tell the world hello.", name="system", role="system")
+            content="Please tell the world hello.", name="system", role="system"
+        )
         context.add_message(message)
         frame = OpenAILLMContextFrame(context)
         async for s in llm.process_frame(frame):
diff --git a/tests/integration/integration_openai_llm.py b/tests/integration/integration_openai_llm.py
index e5dd12057..164dcba8d 100644
--- a/tests/integration/integration_openai_llm.py
+++ b/tests/integration/integration_openai_llm.py
@@ -5,11 +5,7 @@ from typing import List
 
 from pipecat.services.openai import OpenAILLMContextFrame, OpenAILLMContext
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
-from pipecat.frames.frames import (
-    LLMFullResponseStartFrame,
-    LLMFullResponseEndFrame,
-    TextFrame
-)
+from pipecat.frames.frames import LLMFullResponseStartFrame, LLMFullResponseEndFrame, TextFrame
 from pipecat.utils.test_frame_processor import TestFrameProcessor
 from openai.types.chat import (
     ChatCompletionSystemMessageParam,
@@ -34,21 +30,19 @@ tools = [
                     },
                     "format": {
                         "type": "string",
-                        "enum": [
-                            "celsius",
-                            "fahrenheit"],
+                        "enum": ["celsius", "fahrenheit"],
                         "description": "The temperature unit to use. Infer this from the users location.",
                     },
                 },
-                "required": [
-                    "location",
-                    "format"],
+                "required": ["location", "format"],
             },
-        })]
+        },
+    )
+]
 
 if __name__ == "__main__":
-    async def test_simple_functions():
 
+    async def test_simple_functions():
         async def get_weather_from_api(llm, args):
             return json.dumps({"conditions": "nice", "temperature": "75"})
 
@@ -60,11 +54,7 @@ if __name__ == "__main__":
         )
 
         llm.register_function("get_current_weather", get_weather_from_api)
-        t = TestFrameProcessor([
-            LLMFullResponseStartFrame,
-            TextFrame,
-            LLMFullResponseEndFrame
-        ])
+        t = TestFrameProcessor([LLMFullResponseStartFrame, TextFrame, LLMFullResponseEndFrame])
         llm.link(t)
 
         context = OpenAILLMContext(tools=tools)
@@ -82,9 +72,13 @@ if __name__ == "__main__":
         await llm.process_frame(frame, FrameDirection.DOWNSTREAM)
 
     async def test_advanced_functions():
-
         async def get_weather_from_api(llm, args):
-            return [{"role": "system", "content": "The user has asked for live weather. Respond by telling them we don't currently support live weather for that area, but it's coming soon."}]
+            return [
+                {
+                    "role": "system",
+                    "content": "The user has asked for live weather. Respond by telling them we don't currently support live weather for that area, but it's coming soon.",
+                }
+            ]
 
         api_key = os.getenv("OPENAI_API_KEY")
 
@@ -94,11 +88,7 @@ if __name__ == "__main__":
         )
 
         llm.register_function("get_current_weather", get_weather_from_api)
-        t = TestFrameProcessor([
-            LLMFullResponseStartFrame,
-            TextFrame,
-            LLMFullResponseEndFrame
-        ])
+        t = TestFrameProcessor([LLMFullResponseStartFrame, TextFrame, LLMFullResponseEndFrame])
         llm.link(t)
 
         context = OpenAILLMContext(tools=tools)
@@ -117,11 +107,7 @@ if __name__ == "__main__":
 
     async def test_chat():
         api_key = os.getenv("OPENAI_API_KEY")
-        t = TestFrameProcessor([
-            LLMFullResponseStartFrame,
-            TextFrame,
-            LLMFullResponseEndFrame
-        ])
+        t = TestFrameProcessor([LLMFullResponseStartFrame, TextFrame, LLMFullResponseEndFrame])
         llm = OpenAILLMService(
             api_key=api_key or "",
             model="gpt-4o",
@@ -129,7 +115,8 @@ if __name__ == "__main__":
         llm.link(t)
         context = OpenAILLMContext()
         message: ChatCompletionSystemMessageParam = ChatCompletionSystemMessageParam(
-            content="Please tell the world hello.", name="system", role="system")
+            content="Please tell the world hello.", name="system", role="system"
+        )
         context.add_message(message)
         frame = OpenAILLMContextFrame(context)
         await llm.process_frame(frame, FrameDirection.DOWNSTREAM)
diff --git a/tests/test_aggregators.py b/tests/test_aggregators.py
index 2fc6d226c..76834183c 100644
--- a/tests/test_aggregators.py
+++ b/tests/test_aggregators.py
@@ -47,9 +47,10 @@ class TestDailyFrameAggregators(unittest.IsolatedAsyncioTestCase):
     @unittest.skip("FIXME: This test is failing")
     async def test_gated_accumulator(self):
         gated_aggregator = GatedAggregator(
-            gate_open_fn=lambda frame: isinstance(
-                frame, ImageRawFrame), gate_close_fn=lambda frame: isinstance(
-                frame, LLMFullResponseStartFrame), start_open=False, )
+            gate_open_fn=lambda frame: isinstance(frame, ImageRawFrame),
+            gate_close_fn=lambda frame: isinstance(frame, LLMFullResponseStartFrame),
+            start_open=False,
+        )
 
         frames = [
             LLMFullResponseStartFrame(),
@@ -77,15 +78,12 @@ class TestDailyFrameAggregators(unittest.IsolatedAsyncioTestCase):
 
     @unittest.skip("FIXME: This test is failing")
     async def test_parallel_pipeline(self):
-
         async def slow_add(sleep_time: float, name: str, x: str):
             await asyncio.sleep(sleep_time)
             return ":".join([x, name])
 
-        pipe1_annotation = StatelessTextTransformer(
-            functools.partial(slow_add, 0.1, 'pipe1'))
-        pipe2_annotation = StatelessTextTransformer(
-            functools.partial(slow_add, 0.2, 'pipe2'))
+        pipe1_annotation = StatelessTextTransformer(functools.partial(slow_add, 0.1, "pipe1"))
+        pipe2_annotation = StatelessTextTransformer(functools.partial(slow_add, 0.2, "pipe2"))
         sentence_aggregator = SentenceAggregator()
         add_dots = StatelessTextTransformer(lambda x: x + ".")
 
@@ -93,26 +91,20 @@ class TestDailyFrameAggregators(unittest.IsolatedAsyncioTestCase):
         sink = asyncio.Queue()
         pipeline = Pipeline(
             [
-                ParallelPipeline(
-                    [[pipe1_annotation], [sentence_aggregator, pipe2_annotation]]
-                ),
+                ParallelPipeline([[pipe1_annotation], [sentence_aggregator, pipe2_annotation]]),
                 add_dots,
             ],
             source,
             sink,
         )
 
-        frames = [
-            TextFrame("Hello, "),
-            TextFrame("world."),
-            EndFrame()
-        ]
+        frames = [TextFrame("Hello, "), TextFrame("world."), EndFrame()]
 
         expected_output_frames: list[Frame] = [
-            TextFrame(text='Hello, :pipe1.'),
-            TextFrame(text='world.:pipe1.'),
-            TextFrame(text='Hello, world.:pipe2.'),
-            EndFrame()
+            TextFrame(text="Hello, :pipe1."),
+            TextFrame(text="world.:pipe1."),
+            TextFrame(text="Hello, world.:pipe2."),
+            EndFrame(),
         ]
 
         for frame in frames:
@@ -126,7 +118,8 @@ class TestDailyFrameAggregators(unittest.IsolatedAsyncioTestCase):
 
 
 def load_tests(loader, tests, ignore):
-    """ Run doctests on the aggregators module. """
+    """Run doctests on the aggregators module."""
     from pipecat.processors import aggregators
+
     tests.addTests(doctest.DocTestSuite(aggregators))
     return tests
diff --git a/tests/test_ai_services.py b/tests/test_ai_services.py
index fb00fc893..c52b0cb56 100644
--- a/tests/test_ai_services.py
+++ b/tests/test_ai_services.py
@@ -15,10 +15,7 @@ class TestBaseAIService(unittest.IsolatedAsyncioTestCase):
     async def test_simple_processing(self):
         service = SimpleAIService()
 
-        input_frames = [
-            TextFrame("hello"),
-            EndFrame()
-        ]
+        input_frames = [TextFrame("hello"), EndFrame()]
 
         output_frames = []
         for input_frame in input_frames:
diff --git a/tests/test_daily_transport_service.py b/tests/test_daily_transport_service.py
index db85742c5..8c2788c9e 100644
--- a/tests/test_daily_transport_service.py
+++ b/tests/test_daily_transport_service.py
@@ -2,7 +2,6 @@ import unittest
 
 
 class TestDailyTransport(unittest.IsolatedAsyncioTestCase):
-
     @unittest.skip("FIXME: This test is failing")
     async def test_event_handler(self):
         from pipecat.transports.daily_transport import DailyTransport
diff --git a/tests/test_langchain.py b/tests/test_langchain.py
index 7b32b2a9a..fb222205b 100644
--- a/tests/test_langchain.py
+++ b/tests/test_langchain.py
@@ -6,16 +6,22 @@
 
 import unittest
 
-from pipecat.frames.frames import (LLMFullResponseEndFrame,
-                                   LLMFullResponseStartFrame, StopTaskFrame,
-                                   TextFrame, TranscriptionFrame,
-                                   UserStartedSpeakingFrame,
-                                   UserStoppedSpeakingFrame)
+from pipecat.frames.frames import (
+    LLMFullResponseEndFrame,
+    LLMFullResponseStartFrame,
+    StopTaskFrame,
+    TextFrame,
+    TranscriptionFrame,
+    UserStartedSpeakingFrame,
+    UserStoppedSpeakingFrame,
+)
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator, LLMUserResponseAggregator)
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
+)
 from pipecat.processors.frame_processor import FrameProcessor
 from pipecat.processors.frameworks.langchain import LangchainProcessor
 
@@ -24,7 +30,6 @@ from langchain_core.language_models import FakeStreamingListLLM
 
 
 class TestLangchain(unittest.IsolatedAsyncioTestCase):
-
     class MockProcessor(FrameProcessor):
         def __init__(self, name):
             self.name = name
@@ -53,7 +58,6 @@ class TestLangchain(unittest.IsolatedAsyncioTestCase):
         self.mock_proc = self.MockProcessor("token_collector")
 
     async def test_langchain(self):
-
         messages = [("system", "Say hello to {name}"), ("human", "{input}")]
         prompt = ChatPromptTemplate.from_messages(messages).partial(name="Thomas")
         chain = prompt | self.fake_llm
diff --git a/tests/test_openai_tts.py b/tests/test_openai_tts.py
index 5bb97b87d..1dc3929a6 100644
--- a/tests/test_openai_tts.py
+++ b/tests/test_openai_tts.py
@@ -15,10 +15,7 @@ class TestWhisperOpenAIService(unittest.IsolatedAsyncioTestCase):
     @unittest.skip("FIXME: This test is failing")
     async def test_whisper_tts(self):
         pa = pyaudio.PyAudio()
-        stream = pa.open(format=pyaudio.paInt16,
-                         channels=1,
-                         rate=24_000,
-                         output=True)
+        stream = pa.open(format=pyaudio.paInt16, channels=1, rate=24_000, output=True)
 
         tts = OpenAITTSService(voice="nova")
 
@@ -26,7 +23,7 @@ class TestWhisperOpenAIService(unittest.IsolatedAsyncioTestCase):
             self.assertIsInstance(frame, AudioRawFrame)
             stream.write(frame.audio)
 
-        await asyncio.sleep(.5)
+        await asyncio.sleep(0.5)
         stream.stop_stream()
         pa.terminate()
 
diff --git a/tests/test_pipeline.py b/tests/test_pipeline.py
index 35974d2a0..ba82974bc 100644
--- a/tests/test_pipeline.py
+++ b/tests/test_pipeline.py
@@ -11,7 +11,6 @@ from pipecat.pipeline.pipeline import Pipeline
 
 
 class TestDailyPipeline(unittest.IsolatedAsyncioTestCase):
-
     @unittest.skip("FIXME: This test is failing")
     async def test_pipeline_simple(self):
         aggregator = SentenceAggregator()
@@ -38,9 +37,7 @@ class TestDailyPipeline(unittest.IsolatedAsyncioTestCase):
         outgoing_queue = asyncio.Queue()
         incoming_queue = asyncio.Queue()
         pipeline = Pipeline(
-            [add_space, sentence_aggregator, to_upper],
-            incoming_queue,
-            outgoing_queue
+            [add_space, sentence_aggregator, to_upper], incoming_queue, outgoing_queue
         )
 
         sentence = "Hello, world. It's me, a pipeline."
@@ -50,9 +47,7 @@ class TestDailyPipeline(unittest.IsolatedAsyncioTestCase):
 
         await pipeline.run_pipeline()
 
-        self.assertEqual(
-            await outgoing_queue.get(), TextFrame("H E L L O ,   W O R L D .")
-        )
+        self.assertEqual(await outgoing_queue.get(), TextFrame("H E L L O ,   W O R L D ."))
         self.assertEqual(
             await outgoing_queue.get(),
             TextFrame("   I T ' S   M E ,   A   P I P E L I N E ."),
@@ -74,45 +69,49 @@ class TestLogFrame(unittest.TestCase):
             return self.name
 
     def setUp(self):
-        self.processor1 = self.MockProcessor('processor1')
-        self.processor2 = self.MockProcessor('processor2')
-        self.pipeline = Pipeline(
-            processors=[self.processor1, self.processor2])
-        self.pipeline._name = 'MyClass'
+        self.processor1 = self.MockProcessor("processor1")
+        self.processor2 = self.MockProcessor("processor2")
+        self.pipeline = Pipeline(processors=[self.processor1, self.processor2])
+        self.pipeline._name = "MyClass"
         self.pipeline._logger = Mock()
 
     @unittest.skip("FIXME: This test is failing")
     def test_log_frame_from_source(self):
-        frame = Mock(__class__=Mock(__name__='MyFrame'))
+        frame = Mock(__class__=Mock(__name__="MyFrame"))
         self.pipeline._log_frame(frame, depth=1)
         self.pipeline._logger.debug.assert_called_once_with(
-            'MyClass  source -> MyFrame -> processor1')
+            "MyClass  source -> MyFrame -> processor1"
+        )
 
     @unittest.skip("FIXME: This test is failing")
     def test_log_frame_to_sink(self):
-        frame = Mock(__class__=Mock(__name__='MyFrame'))
+        frame = Mock(__class__=Mock(__name__="MyFrame"))
         self.pipeline._log_frame(frame, depth=3)
         self.pipeline._logger.debug.assert_called_once_with(
-            'MyClass      processor2 -> MyFrame -> sink')
+            "MyClass      processor2 -> MyFrame -> sink"
+        )
 
     @unittest.skip("FIXME: This test is failing")
     def test_log_frame_repeated_log(self):
-        frame = Mock(__class__=Mock(__name__='MyFrame'))
+        frame = Mock(__class__=Mock(__name__="MyFrame"))
         self.pipeline._log_frame(frame, depth=2)
         self.pipeline._logger.debug.assert_called_once_with(
-            'MyClass    processor1 -> MyFrame -> processor2')
+            "MyClass    processor1 -> MyFrame -> processor2"
+        )
         self.pipeline._log_frame(frame, depth=2)
-        self.pipeline._logger.debug.assert_called_with('MyClass    ... repeated')
+        self.pipeline._logger.debug.assert_called_with("MyClass    ... repeated")
 
     @unittest.skip("FIXME: This test is failing")
     def test_log_frame_reset_repeated_log(self):
-        frame1 = Mock(__class__=Mock(__name__='MyFrame1'))
-        frame2 = Mock(__class__=Mock(__name__='MyFrame2'))
+        frame1 = Mock(__class__=Mock(__name__="MyFrame1"))
+        frame2 = Mock(__class__=Mock(__name__="MyFrame2"))
         self.pipeline._log_frame(frame1, depth=2)
         self.pipeline._logger.debug.assert_called_once_with(
-            'MyClass    processor1 -> MyFrame1 -> processor2')
+            "MyClass    processor1 -> MyFrame1 -> processor2"
+        )
         self.pipeline._log_frame(frame1, depth=2)
-        self.pipeline._logger.debug.assert_called_with('MyClass    ... repeated')
+        self.pipeline._logger.debug.assert_called_with("MyClass    ... repeated")
         self.pipeline._log_frame(frame2, depth=2)
         self.pipeline._logger.debug.assert_called_with(
-            'MyClass    processor1 -> MyFrame2 -> processor2')
+            "MyClass    processor1 -> MyFrame2 -> processor2"
+        )
diff --git a/tests/test_protobuf_serializer.py b/tests/test_protobuf_serializer.py
index 2e74e88f4..7f9841622 100644
--- a/tests/test_protobuf_serializer.py
+++ b/tests/test_protobuf_serializer.py
@@ -10,20 +10,18 @@ class TestProtobufFrameSerializer(unittest.IsolatedAsyncioTestCase):
 
     @unittest.skip("FIXME: This test is failing")
     async def test_roundtrip(self):
-        text_frame = TextFrame(text='hello world')
-        frame = self.serializer.deserialize(
-            self.serializer.serialize(text_frame))
-        self.assertEqual(frame, TextFrame(text='hello world'))
+        text_frame = TextFrame(text="hello world")
+        frame = self.serializer.deserialize(self.serializer.serialize(text_frame))
+        self.assertEqual(frame, TextFrame(text="hello world"))
 
         transcription_frame = TranscriptionFrame(
-            text="Hello there!", participantId="123", timestamp="2021-01-01")
-        frame = self.serializer.deserialize(
-            self.serializer.serialize(transcription_frame))
+            text="Hello there!", participantId="123", timestamp="2021-01-01"
+        )
+        frame = self.serializer.deserialize(self.serializer.serialize(transcription_frame))
         self.assertEqual(frame, transcription_frame)
 
-        audio_frame = AudioRawFrame(data=b'1234567890')
-        frame = self.serializer.deserialize(
-            self.serializer.serialize(audio_frame))
+        audio_frame = AudioRawFrame(data=b"1234567890")
+        frame = self.serializer.deserialize(self.serializer.serialize(audio_frame))
         self.assertEqual(frame, audio_frame)
 
 

From a4420dc88b105d14a105a9349d0c2c4576478823 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Mon, 23 Sep 2024 09:29:02 -0700
Subject: [PATCH 052/135] README: add vscode and emacs ruff instructions

---
 README.md            | 26 ++++++++++++--------------
 dev-requirements.txt |  2 +-
 2 files changed, 13 insertions(+), 15 deletions(-)

diff --git a/README.md b/README.md
index 5dfc1ad95..faf0137dc 100644
--- a/README.md
+++ b/README.md
@@ -170,22 +170,24 @@ pytest --doctest-modules --ignore-glob="*to_be_updated*" --ignore-glob=*pipeline
 
 ## Setting up your editor
 
-This project uses strict [PEP 8](https://peps.python.org/pep-0008/) formatting.
+This project uses strict [PEP 8](https://peps.python.org/pep-0008/) formatting via [Ruff](https://github.com/astral-sh/ruff).
 
 ### Emacs
 
-You can use [use-package](https://github.com/jwiegley/use-package) to install [py-autopep8](https://codeberg.org/ideasman42/emacs-py-autopep8) package and configure `autopep8` arguments:
+You can use [use-package](https://github.com/jwiegley/use-package) to install [emacs-lazy-ruff](https://github.com/christophermadsen/emacs-lazy-ruff) package and configure `ruff` arguments:
 
 ```elisp
-(use-package py-autopep8
+(use-package lazy-ruff
   :ensure t
-  :defer t
-  :hook ((python-mode . py-autopep8-mode))
+  :hook ((python-mode . lazy-ruff-mode))
   :config
-  (setq py-autopep8-options '("-a" "-a", "--max-line-length=100")))
+  (setq lazy-ruff-format-command "ruff format --config line-length=100")
+  (setq lazy-ruff-only-format-block t)
+  (setq lazy-ruff-only-format-region t)
+  (setq lazy-ruff-only-format-buffer t))
 ```
 
-`autopep8` was installed in the `venv` environment described before, so you should be able to use [pyvenv-auto](https://github.com/ryotaro612/pyvenv-auto) to automatically load that environment inside Emacs.
+`ruff` was installed in the `venv` environment described before, so you should be able to use [pyvenv-auto](https://github.com/ryotaro612/pyvenv-auto) to automatically load that environment inside Emacs.
 
 ```elisp
 (use-package pyvenv-auto
@@ -198,18 +200,14 @@ You can use [use-package](https://github.com/jwiegley/use-package) to install [p
 ### Visual Studio Code
 
 Install the
-[autopep8](https://marketplace.visualstudio.com/items?itemName=ms-python.autopep8) extension. Then edit the user settings (_Ctrl-Shift-P_ `Open User Settings (JSON)`) and set it as the default Python formatter, enable formatting on save and configure `autopep8` arguments:
+[Ruff](https://marketplace.visualstudio.com/items?itemName=charliermarsh.ruff) extension. Then edit the user settings (_Ctrl-Shift-P_ `Open User Settings (JSON)`) and set it as the default Python formatter, enable formatting on save and configure `ruff` arguments:
 
 ```json
 "[python]": {
-    "editor.defaultFormatter": "ms-python.autopep8",
+    "editor.defaultFormatter": "charliermarsh.ruff",
     "editor.formatOnSave": true
 },
-"autopep8.args": [
-    "-a",
-    "-a",
-    "--max-line-length=100"
-],
+"ruff.format.args": ["--config", "line-length=100"]
 ```
 
 ## Getting help
diff --git a/dev-requirements.txt b/dev-requirements.txt
index cce356b14..c706d8fe6 100644
--- a/dev-requirements.txt
+++ b/dev-requirements.txt
@@ -3,6 +3,6 @@ grpcio-tools~=1.62.2
 pip-tools~=7.4.1
 pyright~=1.1.376
 pytest~=8.3.2
-ruff~=0.6.6
+ruff~=0.6.7
 setuptools~=72.2.0
 setuptools_scm~=8.1.0

From da81df52847aa5dc3c65b81dcd78adea21d1d4c9 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Mon, 23 Sep 2024 09:29:21 -0700
Subject: [PATCH 053/135] github: install dev-requirements when running tests

---
 .github/workflows/tests.yaml |  2 +-
 test-requirements.txt        | 10 +---------
 2 files changed, 2 insertions(+), 10 deletions(-)

diff --git a/.github/workflows/tests.yaml b/.github/workflows/tests.yaml
index 740848cee..ce3e13494 100644
--- a/.github/workflows/tests.yaml
+++ b/.github/workflows/tests.yaml
@@ -38,7 +38,7 @@ jobs:
         run: |
           source .venv/bin/activate
           python -m pip install --upgrade pip
-          pip install -r test-requirements.txt
+          pip install -r dev-requirements.txt -r test-requirements.txt
       - name: Test with pytest
         run: |
           source .venv/bin/activate
diff --git a/test-requirements.txt b/test-requirements.txt
index 7f52a49a1..78280b139 100644
--- a/test-requirements.txt
+++ b/test-requirements.txt
@@ -1,15 +1,12 @@
 aiohttp~=3.10.3
-anthropic
-autopep8~=2.3.1
+anthropic~=0.30.0
 azure-cognitiveservices-speech~=1.40.0
-build~=1.2.1
 daily-python~=0.10.1
 deepgram-sdk~=3.5.0
 fal-client~=0.4.1
 fastapi~=0.112.1
 faster-whisper~=1.0.3
 google-generativeai~=0.7.2
-grpcio-tools~=1.62.2
 langchain~=0.2.14
 livekit~=0.13.1
 lmnt~=1.1.4
@@ -18,17 +15,12 @@ numpy~=1.26.4
 openai~=1.37.2
 openpipe~=4.24.0
 Pillow~=10.4.0
-pip-tools~=7.4.1
 pyaudio~=0.2.14
 pydantic~=2.8.2
 pyloudnorm~=0.1.1
 pyht~=0.0.28
-pyright~=1.1.376
-pytest~=8.3.2
 python-dotenv~=1.0.1
 resampy~=0.4.3
-setuptools~=72.2.0
-setuptools_scm~=8.1.0
 silero-vad~=5.1
 together~=1.2.7
 transformers~=4.44.0

From c7ff79a652f432bb466b8ae7620906ba16b5ea2b Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Mon, 23 Sep 2024 09:38:40 -0700
Subject: [PATCH 054/135] processors: fix formatting string

---
 src/pipecat/processors/frame_processor.py                 | 3 +--
 src/pipecat/processors/metrics/frame_processor_metrics.py | 3 +--
 2 files changed, 2 insertions(+), 4 deletions(-)

diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py
index 9dd92599e..1bf42311d 100644
--- a/src/pipecat/processors/frame_processor.py
+++ b/src/pipecat/processors/frame_processor.py
@@ -193,8 +193,7 @@ class FrameProcessor:
                 logger.trace(f"Pushing {frame} from {self} to {self._next}")
                 await self._next.process_frame(frame, direction)
             elif direction == FrameDirection.UPSTREAM and self._prev:
-                logger.trace(f"Pushing {frame} upstream from {
-                             self} to {self._prev}")
+                logger.trace(f"Pushing {frame} upstream from {self} to {self._prev}")
                 await self._prev.process_frame(frame, direction)
         except Exception as e:
             logger.exception(f"Uncaught exception in {self}: {e}")
diff --git a/src/pipecat/processors/metrics/frame_processor_metrics.py b/src/pipecat/processors/metrics/frame_processor_metrics.py
index 52ea7e34c..a22639239 100644
--- a/src/pipecat/processors/metrics/frame_processor_metrics.py
+++ b/src/pipecat/processors/metrics/frame_processor_metrics.py
@@ -76,6 +76,5 @@ class FrameProcessorMetrics:
         characters = TTSUsageMetricsData(
             processor=self._processor_name(), model=self._model_name(), value=len(text)
         )
-        logger.debug(f"{self._processor_name()} usage characters: {
-                     characters.value}")
+        logger.debug(f"{self._processor_name()} usage characters: {characters.value}")
         return MetricsFrame(data=[characters])

From c262b272fa672afe8c592db4afa075e1ac9c3161 Mon Sep 17 00:00:00 2001
From: chadbailey59 <chadbailey59@users.noreply.github.com>
Date: Mon, 23 Sep 2024 14:51:17 -0500
Subject: [PATCH 055/135] Added RTVIActionFrame (#464)

* added RTVIActionFrame

* server-sent events

* reverted log changes

* fixup
---
 src/pipecat/processors/frameworks/rtvi.py | 19 ++++++++++++++++---
 1 file changed, 16 insertions(+), 3 deletions(-)

diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py
index 0450102a7..820ea716c 100644
--- a/src/pipecat/processors/frameworks/rtvi.py
+++ b/src/pipecat/processors/frameworks/rtvi.py
@@ -8,12 +8,14 @@ import asyncio
 
 from typing import Any, Awaitable, Callable, Dict, List, Literal, Optional, Union
 from pydantic import BaseModel, Field, PrivateAttr, ValidationError
+from dataclasses import dataclass
 
 from pipecat.frames.frames import (
     BotInterruptionFrame,
     BotStartedSpeakingFrame,
     BotStoppedSpeakingFrame,
     CancelFrame,
+    DataFrame,
     EndFrame,
     ErrorFrame,
     Frame,
@@ -119,6 +121,12 @@ class RTVIActionRun(BaseModel):
     arguments: Optional[List[RTVIActionRunArgument]] = None
 
 
+@dataclass
+class RTVIActionFrame(DataFrame):
+    rtvi_action_run: RTVIActionRun
+    message_id: Optional[str] = None
+
+
 class RTVIMessage(BaseModel):
     label: Literal["rtvi-ai"] = "rtvi-ai"
     type: str
@@ -376,6 +384,8 @@ class RTVIProcessor(FrameProcessor):
             await self.push_frame(frame, direction)
         elif isinstance(frame, TransportMessageFrame):
             await self._message_queue.put(frame)
+        elif isinstance(frame, RTVIActionFrame):
+            await self._handle_action(frame.message_id, frame.rtvi_action_run)
         # Other frames
         else:
             await self.push_frame(frame, direction)
@@ -548,7 +558,7 @@ class RTVIProcessor(FrameProcessor):
         )
         await self.push_frame(frame)
 
-    async def _handle_action(self, request_id: str, data: RTVIActionRun):
+    async def _handle_action(self, request_id: str | None, data: RTVIActionRun):
         action_id = self._action_id(data.service, data.action)
         if action_id not in self._registered_actions:
             await self._send_error_response(request_id, f"Action {action_id} not registered")
@@ -559,8 +569,11 @@ class RTVIProcessor(FrameProcessor):
             for arg in data.arguments:
                 arguments[arg.name] = arg.value
         result = await action.handler(self, action.service, arguments)
-        message = RTVIActionResponse(id=request_id, data=RTVIActionResponseData(result=result))
-        await self._push_transport_message(message)
+        # Only send a response if request_id is present. Things that don't care about
+        # action responses (such as webhooks) don't set a request_id
+        if request_id:
+            message = RTVIActionResponse(id=request_id, data=RTVIActionResponseData(result=result))
+            await self._push_transport_message(message)
 
     async def _maybe_send_bot_ready(self):
         if self._pipeline_started and self._client_ready:

From 8edee8155dbf7d7a47ee491a3d1caafdcd3910d5 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Mon, 23 Sep 2024 10:07:05 -0400
Subject: [PATCH 056/135] Add input params to Azure TTS

---
 src/pipecat/services/azure.py | 113 ++++++++++++++++++++++------------
 1 file changed, 75 insertions(+), 38 deletions(-)

diff --git a/src/pipecat/services/azure.py b/src/pipecat/services/azure.py
index 24e73cd2a..efb6a6fe4 100644
--- a/src/pipecat/services/azure.py
+++ b/src/pipecat/services/azure.py
@@ -4,45 +4,34 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-import aiohttp
 import asyncio
 import io
+from typing import AsyncGenerator, Optional
 
+import aiohttp
+from loguru import logger
 from PIL import Image
-from typing import AsyncGenerator
+from pydantic import BaseModel
 
-from pipecat.frames.frames import (
-    CancelFrame,
-    EndFrame,
-    ErrorFrame,
-    Frame,
-    StartFrame,
-    TTSAudioRawFrame,
-    TTSStartedFrame,
-    TTSStoppedFrame,
-    TranscriptionFrame,
-    URLImageRawFrame,
-)
-from pipecat.metrics.metrics import TTSUsageMetricsData
-from pipecat.processors.frame_processor import FrameDirection
-from pipecat.services.ai_services import STTService, TTSService, ImageGenService
+from pipecat.frames.frames import (CancelFrame, EndFrame, ErrorFrame, Frame,
+                                   StartFrame, TranscriptionFrame,
+                                   TTSAudioRawFrame, TTSStartedFrame,
+                                   TTSStoppedFrame, URLImageRawFrame)
+from pipecat.services.ai_services import (ImageGenService, STTService,
+                                          TTSService)
 from pipecat.services.openai import BaseOpenAILLMService
 from pipecat.utils.time import time_now_iso8601
 
-from loguru import logger
-
 # See .env.example for Azure configuration needed
 try:
-    from openai import AsyncAzureOpenAI
-    from azure.cognitiveservices.speech import (
-        SpeechConfig,
-        SpeechRecognizer,
-        SpeechSynthesizer,
-        ResultReason,
-        CancellationReason,
-    )
-    from azure.cognitiveservices.speech.audio import AudioStreamFormat, PushAudioInputStream
+    from azure.cognitiveservices.speech import (CancellationReason,
+                                                ResultReason, SpeechConfig,
+                                                SpeechRecognizer,
+                                                SpeechSynthesizer)
+    from azure.cognitiveservices.speech.audio import (AudioStreamFormat,
+                                                      PushAudioInputStream)
     from azure.cognitiveservices.speech.dialog import AudioConfig
+    from openai import AsyncAzureOpenAI
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
@@ -70,6 +59,17 @@ class AzureLLMService(BaseOpenAILLMService):
 
 
 class AzureTTSService(TTSService):
+    class InputParams(BaseModel):
+        emphasis: Optional[str] = None
+        language_code: Optional[str] = "en-US"
+        pitch: Optional[str] = None
+        rate: Optional[str] = "1.05"
+        role: Optional[str] = None
+        style: Optional[str] = None
+        style_degree: Optional[str] = None
+        volume: Optional[str] = None
+
+
     def __init__(
         self,
         *,
@@ -77,6 +77,7 @@ class AzureTTSService(TTSService):
         region: str,
         voice="en-US-SaraNeural",
         sample_rate: int = 16000,
+        params: InputParams = InputParams(),
         **kwargs,
     ):
         super().__init__(sample_rate=sample_rate, **kwargs)
@@ -86,10 +87,55 @@ class AzureTTSService(TTSService):
 
         self._voice = voice
         self._sample_rate = sample_rate
+        self._params = params
 
     def can_generate_metrics(self) -> bool:
         return True
 
+    def _construct_ssml(self, text: str) -> str:
+        ssml = (
+            f"<speak version='1.0' xml:lang='{self._params.language_code}' "
+            "xmlns='http://www.w3.org/2001/10/synthesis' "
+            "xmlns:mstts='http://www.w3.org/2001/mstts'>"
+            f"<voice name='{self._voice}'>"
+            "<mstts:silence type='Sentenceboundary' value='20ms' />"
+        )
+
+        if self._params.style:
+            ssml += f"<mstts:express-as style='{self._params.style}'"
+            if self._params.style_degree:
+                ssml += f" styledegree='{self._params.style_degree}'"
+            if self._params.role:
+                ssml += f" role='{self._params.role}'"
+            ssml += ">"
+
+        prosody_attrs = []
+        if self._params.rate:
+            prosody_attrs.append(f"rate='{self._params.rate}'")
+        if self._params.pitch:
+            prosody_attrs.append(f"pitch='{self._params.pitch}'")
+        if self._params.volume:
+            prosody_attrs.append(f"volume='{self._params.volume}'")
+        
+        ssml += f"<prosody {' '.join(prosody_attrs)}>"
+
+        if self._params.emphasis:
+            ssml += f"<emphasis level='{self._params.emphasis}'>"
+
+        ssml += text
+
+        if self._params.emphasis:
+            ssml += "</emphasis>"
+
+        ssml += "</prosody>"
+
+        if self._params.style:
+            ssml += "</mstts:express-as>"
+
+        ssml += "</voice></speak>"
+
+        return ssml
+
     async def set_voice(self, voice: str):
         logger.debug(f"Switching TTS voice to: [{voice}]")
         self._voice = voice
@@ -99,16 +145,7 @@ class AzureTTSService(TTSService):
 
         await self.start_ttfb_metrics()
 
-        ssml = (
-            "<speak version='1.0' xml:lang='en-US' xmlns='http://www.w3.org/2001/10/synthesis' "
-            "xmlns:mstts='http://www.w3.org/2001/mstts'>"
-            f"<voice name='{self._voice}'>"
-            "<mstts:silence type='Sentenceboundary' value='20ms' />"
-            "<mstts:express-as style='lyrical' styledegree='2' role='SeniorFemale'>"
-            "<prosody rate='1.05'>"
-            f"{text}"
-            "</prosody></mstts:express-as></voice></speak> "
-        )
+        ssml = self._construct_ssml(text)
 
         result = await asyncio.to_thread(self._speech_synthesizer.speak_ssml, (ssml))
 

From 49f212389305465791eab139083b2e3286a05dee Mon Sep 17 00:00:00 2001
From: Jin Kim <golbin@gmail.com>
Date: Tue, 24 Sep 2024 07:59:26 +0900
Subject: [PATCH 057/135] Apply and Fix upstream changes for Cartesia

---
 src/pipecat/services/cartesia.py | 113 +++++++++++++++++++------------
 1 file changed, 69 insertions(+), 44 deletions(-)

diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index 40475343c..f08c06dea 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -9,7 +9,7 @@ import uuid
 import base64
 import asyncio
 
-from typing import AsyncGenerator, Optional
+from typing import AsyncGenerator, Optional, Union, List
 from pydantic.main import BaseModel
 
 from pipecat.frames.frames import (
@@ -67,8 +67,8 @@ class CartesiaTTSService(AsyncWordTTSService):
         sample_rate: Optional[int] = 16000
         container: Optional[str] = "raw"
         language: Optional[str] = "en"
-        speed: Optional[str] = None
-        emotion: Optional[list[str]] = []
+        speed: Optional[Union[str, float]] = ""
+        emotion: Optional[List[str]] = []
 
     def __init__(
             self,
@@ -91,13 +91,14 @@ class CartesiaTTSService(AsyncWordTTSService):
         # can use those to generate text frames ourselves aligned with the
         # playout timing of the audio!
         super().__init__(
-            aggregate_sentences=True, push_text_frames=False, sample_rate=sample_rate, **kwargs
+            aggregate_sentences=True, push_text_frames=False, sample_rate=params.sample_rate, **kwargs
         )
 
         self._api_key = api_key
         self._cartesia_version = cartesia_version
         self._url = url
         self._voice_id = voice_id
+        self._model_id = model_id
         self.set_model_name(model_id)
         self._output_format = {
             "container": params.container,
@@ -116,6 +117,7 @@ class CartesiaTTSService(AsyncWordTTSService):
         return True
 
     async def set_model(self, model: str):
+        self._model_id = model
         await super().set_model(model)
         logger.debug(f"Switching TTS model to: [{model}]")
 
@@ -135,6 +137,31 @@ class CartesiaTTSService(AsyncWordTTSService):
         logger.debug(f"Switching TTS language to: [{language}]")
         self._language = language_to_cartesia_language(language)
 
+    def _build_msg(self, text: str = "", continue_transcript: bool = True, add_timestamps: bool = True):
+        voice_config = {
+            "mode": "id",
+            "id": self._voice_id
+        }
+
+        if self._speed or self._emotion:
+            voice_config["__experimental_controls"] = {}
+            if self._speed:
+                voice_config["__experimental_controls"]["speed"] = self._speed
+            if self._emotion:
+                voice_config["__experimental_controls"]["emotion"] = self._emotion
+
+        msg = {
+            "transcript": text,
+            "continue": continue_transcript,
+            "context_id": self._context_id,
+            "model_id": self._model_name,
+            "voice": voice_config,
+            "output_format": self._output_format,
+            "language": self._language,
+            "add_timestamps": add_timestamps,
+        }
+        return json.dumps(msg)
+
     async def start(self, frame: StartFrame):
         await super().start(frame)
         await self._connect()
@@ -190,17 +217,8 @@ class CartesiaTTSService(AsyncWordTTSService):
         if not self._context_id or not self._websocket:
             return
         logger.trace("Flushing audio")
-        msg = {
-            "transcript": "",
-            "continue": False,
-            "context_id": self._context_id,
-            "model_id": self.model_name,
-            "voice": {"mode": "id", "id": self._voice_id},
-            "output_format": self._output_format,
-            "language": self._language,
-            "add_timestamps": True,
-        }
-        await self._websocket.send(json.dumps(msg))
+        msg = self._build_msg(text="", continue_transcript=False)
+        await self._websocket.send(msg)
 
     async def _receive_task_handler(self):
         try:
@@ -255,30 +273,10 @@ class CartesiaTTSService(AsyncWordTTSService):
                 await self.start_ttfb_metrics()
                 self._context_id = str(uuid.uuid4())
 
-            voice_config = {
-                "mode": "id",
-                "id": self._voice_id
-            }
+            msg = self._build_msg(text=text)
 
-            if self._speed or self._emotion:
-                voice_config["__experimental_controls"] = {}
-                if self._speed:
-                    voice_config["__experimental_controls"]["speed"] = self._speed
-                if self._emotion:
-                    voice_config["__experimental_controls"]["emotion"] = self._emotion
-
-            msg = {
-                "transcript": text + " ",
-                "continue": True,
-                "context_id": self._context_id,
-                "model_id": self._model_id,
-                "voice": voice_config,
-                "output_format": self._output_format,
-                "language": self._language,
-                "add_timestamps": True,
-            }
             try:
-                await self._get_websocket().send(json.dumps(msg))
+                await self._get_websocket().send(msg)
                 await self.start_tts_usage_metrics(text)
             except Exception as e:
                 logger.error(f"{self} error sending message: {e}")
@@ -292,6 +290,14 @@ class CartesiaTTSService(AsyncWordTTSService):
 
 
 class CartesiaHttpTTSService(TTSService):
+    class InputParams(BaseModel):
+        encoding: Optional[str] = "pcm_s16le"
+        sample_rate: Optional[int] = 16000
+        container: Optional[str] = "raw"
+        language: Optional[str] = "en"
+        speed: Optional[Union[str, float]] = ""
+        emotion: Optional[List[str]] = []
+
     def __init__(
         self,
         *,
@@ -299,9 +305,7 @@ class CartesiaHttpTTSService(TTSService):
         voice_id: str,
         model_id: str = "sonic-english",
         base_url: str = "https://api.cartesia.ai",
-        encoding: str = "pcm_s16le",
-        sample_rate: int = 16000,
-        language: str = "en",
+        params: InputParams = InputParams(),
         **kwargs,
     ):
         super().__init__(**kwargs)
@@ -309,12 +313,15 @@ class CartesiaHttpTTSService(TTSService):
         self._api_key = api_key
         self._voice_id = voice_id
         self._model_id = model_id
+        self.set_model_name(model_id)
         self._output_format = {
-            "container": "raw",
-            "encoding": encoding,
-            "sample_rate": sample_rate,
+            "container": params.container,
+            "encoding": params.encoding,
+            "sample_rate": params.sample_rate,
         }
-        self._language = language
+        self._language = params.language
+        self._speed = params.speed
+        self._emotion = params.emotion
 
         self._client = AsyncCartesia(api_key=api_key, base_url=base_url)
 
@@ -324,11 +331,20 @@ class CartesiaHttpTTSService(TTSService):
     async def set_model(self, model: str):
         logger.debug(f"Switching TTS model to: [{model}]")
         self._model_id = model
+        await super().set_model(model)
 
     async def set_voice(self, voice: str):
         logger.debug(f"Switching TTS voice to: [{voice}]")
         self._voice_id = voice
 
+    async def set_speed(self, speed: str):
+        logger.debug(f"Switching TTS speed to: [{speed}]")
+        self._speed = speed
+
+    async def set_emotion(self, emotion: list[str]):
+        logger.debug(f"Switching TTS emotion to: [{emotion}]")
+        self._emotion = emotion
+
     async def set_language(self, language: Language):
         logger.debug(f"Switching TTS language to: [{language}]")
         self._language = language_to_cartesia_language(language)
@@ -348,6 +364,14 @@ class CartesiaHttpTTSService(TTSService):
         await self.start_ttfb_metrics()
 
         try:
+            voice_controls = None
+            if self._speed or self._emotion:
+                voice_controls = {}
+                if self._speed:
+                    voice_controls["speed"] = self._speed
+                if self._emotion:
+                    voice_controls["emotion"] = self._emotion
+
             output = await self._client.tts.sse(
                 model_id=self._model_id,
                 transcript=text,
@@ -355,6 +379,7 @@ class CartesiaHttpTTSService(TTSService):
                 output_format=self._output_format,
                 language=self._language,
                 stream=False,
+                _experimental_voice_controls=voice_controls
             )
 
             await self.stop_ttfb_metrics()

From 8ee9621d6614e8f5c5d9e0252411f5b9c3569149 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Mon, 23 Sep 2024 10:49:50 -0400
Subject: [PATCH 058/135] Add setter functions

---
 src/pipecat/services/azure.py | 89 +++++++++++++++++++++++++++++------
 1 file changed, 75 insertions(+), 14 deletions(-)

diff --git a/src/pipecat/services/azure.py b/src/pipecat/services/azure.py
index efb6a6fe4..41fc7598b 100644
--- a/src/pipecat/services/azure.py
+++ b/src/pipecat/services/azure.py
@@ -13,23 +13,32 @@ from loguru import logger
 from PIL import Image
 from pydantic import BaseModel
 
-from pipecat.frames.frames import (CancelFrame, EndFrame, ErrorFrame, Frame,
-                                   StartFrame, TranscriptionFrame,
-                                   TTSAudioRawFrame, TTSStartedFrame,
-                                   TTSStoppedFrame, URLImageRawFrame)
-from pipecat.services.ai_services import (ImageGenService, STTService,
-                                          TTSService)
+from pipecat.frames.frames import (
+    CancelFrame,
+    EndFrame,
+    ErrorFrame,
+    Frame,
+    StartFrame,
+    TranscriptionFrame,
+    TTSAudioRawFrame,
+    TTSStartedFrame,
+    TTSStoppedFrame,
+    URLImageRawFrame,
+)
+from pipecat.services.ai_services import ImageGenService, STTService, TTSService
 from pipecat.services.openai import BaseOpenAILLMService
 from pipecat.utils.time import time_now_iso8601
 
 # See .env.example for Azure configuration needed
 try:
-    from azure.cognitiveservices.speech import (CancellationReason,
-                                                ResultReason, SpeechConfig,
-                                                SpeechRecognizer,
-                                                SpeechSynthesizer)
-    from azure.cognitiveservices.speech.audio import (AudioStreamFormat,
-                                                      PushAudioInputStream)
+    from azure.cognitiveservices.speech import (
+        CancellationReason,
+        ResultReason,
+        SpeechConfig,
+        SpeechRecognizer,
+        SpeechSynthesizer,
+    )
+    from azure.cognitiveservices.speech.audio import AudioStreamFormat, PushAudioInputStream
     from azure.cognitiveservices.speech.dialog import AudioConfig
     from openai import AsyncAzureOpenAI
 except ModuleNotFoundError as e:
@@ -69,7 +78,6 @@ class AzureTTSService(TTSService):
         style_degree: Optional[str] = None
         volume: Optional[str] = None
 
-
     def __init__(
         self,
         *,
@@ -116,7 +124,7 @@ class AzureTTSService(TTSService):
             prosody_attrs.append(f"pitch='{self._params.pitch}'")
         if self._params.volume:
             prosody_attrs.append(f"volume='{self._params.volume}'")
-        
+
         ssml += f"<prosody {' '.join(prosody_attrs)}>"
 
         if self._params.emphasis:
@@ -140,6 +148,59 @@ class AzureTTSService(TTSService):
         logger.debug(f"Switching TTS voice to: [{voice}]")
         self._voice = voice
 
+    async def set_emphasis(self, emphasis: str):
+        logger.debug(f"Setting TTS emphasis to: [{emphasis}]")
+        self._params.emphasis = emphasis
+
+    async def set_language_code(self, language_code: str):
+        logger.debug(f"Setting TTS language code to: [{language_code}]")
+        self._params.language_code = language_code
+
+    async def set_pitch(self, pitch: str):
+        logger.debug(f"Setting TTS pitch to: [{pitch}]")
+        self._params.pitch = pitch
+
+    async def set_rate(self, rate: str):
+        logger.debug(f"Setting TTS rate to: [{rate}]")
+        self._params.rate = rate
+
+    async def set_role(self, role: str):
+        logger.debug(f"Setting TTS role to: [{role}]")
+        self._params.role = role
+
+    async def set_style(self, style: str):
+        logger.debug(f"Setting TTS style to: [{style}]")
+        self._params.style = style
+
+    async def set_style_degree(self, style_degree: str):
+        logger.debug(f"Setting TTS style degree to: [{style_degree}]")
+        self._params.style_degree = style_degree
+
+    async def set_volume(self, volume: str):
+        logger.debug(f"Setting TTS volume to: [{volume}]")
+        self._params.volume = volume
+
+    async def set_params(self, **kwargs):
+        valid_params = {
+            "voice": self.set_voice,
+            "emphasis": self.set_emphasis,
+            "language_code": self.set_language_code,
+            "pitch": self.set_pitch,
+            "rate": self.set_rate,
+            "role": self.set_role,
+            "style": self.set_style,
+            "style_degree": self.set_style_degree,
+            "volume": self.set_volume,
+        }
+
+        for param, value in kwargs.items():
+            if param in valid_params:
+                await valid_params[param](value)
+            else:
+                logger.warning(f"Ignoring unknown parameter: {param}")
+
+        logger.debug(f"Updated TTS parameters: {', '.join(kwargs.keys())}")
+
     async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
         logger.debug(f"Generating TTS: [{text}]")
 

From a9390d96a1e23447386e0a7580839eb2f03dc764 Mon Sep 17 00:00:00 2001
From: joachimchauvet <13382894+joachimchauvet@users.noreply.github.com>
Date: Sat, 14 Sep 2024 21:13:25 +0300
Subject: [PATCH 059/135] add LiveKit audio transport

---
 examples/foundational/01b-livekit-audio.py |  95 ++++
 src/pipecat/transports/services/livekit.py | 556 +++++++++++++++++++++
 2 files changed, 651 insertions(+)
 create mode 100644 examples/foundational/01b-livekit-audio.py
 create mode 100644 src/pipecat/transports/services/livekit.py

diff --git a/examples/foundational/01b-livekit-audio.py b/examples/foundational/01b-livekit-audio.py
new file mode 100644
index 000000000..9a6d80709
--- /dev/null
+++ b/examples/foundational/01b-livekit-audio.py
@@ -0,0 +1,95 @@
+import argparse
+import asyncio
+import os
+import sys
+
+import aiohttp
+from dotenv import load_dotenv
+from livekit import api  # pip install livekit-api
+from loguru import logger
+from pipecat.frames.frames import TextFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineTask
+from pipecat.services.cartesia import CartesiaTTSService
+from pipecat.transports.services.livekit import LiveKitParams, LiveKitTransport
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+def generate_token(room_name: str, participant_name: str, api_key: str, api_secret: str) -> str:
+    token = api.AccessToken(api_key, api_secret)
+    token.with_identity(participant_name).with_name(participant_name).with_grants(
+        api.VideoGrants(
+            room_join=True,
+            room=room_name,
+        )
+    )
+
+    return token.to_jwt()
+
+
+async def configure_livekit():
+    parser = argparse.ArgumentParser(description="LiveKit AI SDK Bot Sample")
+    parser.add_argument("-r", "--room", type=str, required=False, help="Name of the LiveKit room to join")
+    parser.add_argument("-u", "--url", type=str, required=False, help="URL of the LiveKit server")
+
+    args, unknown = parser.parse_known_args()
+
+    room_name = args.room or os.getenv("LIVEKIT_ROOM_NAME")
+    url = args.url or os.getenv("LIVEKIT_URL")
+    api_key = os.getenv("LIVEKIT_API_KEY")
+    api_secret = os.getenv("LIVEKIT_API_SECRET")
+
+    if not room_name:
+        raise Exception(
+            "No LiveKit room specified. Use the -r/--room option from the command line, or set LIVEKIT_ROOM_NAME in your environment."
+        )
+
+    if not url:
+        raise Exception(
+            "No LiveKit server URL specified. Use the -u/--url option from the command line, or set LIVEKIT_URL in your environment."
+        )
+
+    if not api_key or not api_secret:
+        raise Exception("LIVEKIT_API_KEY and LIVEKIT_API_SECRET must be set in environment variables.")
+
+    token = generate_token(room_name, "Say One Thing", api_key, api_secret)
+
+    return (url, token, room_name)
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (url, token, room_name) = await configure_livekit()
+
+        transport = LiveKitTransport(
+            url=url,
+            token=token,
+            room_name=room_name,
+            params=LiveKitParams(audio_out_enabled=True)
+        )
+
+        tts = CartesiaTTSService(
+            api_key=os.getenv("CARTESIA_API_KEY"),
+            voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
+        )
+
+        runner = PipelineRunner()
+
+        task = PipelineTask(Pipeline([tts, transport.output()]))
+
+        # Register an event handler so we can play the audio when the
+        # participant joins.
+        @transport.event_handler("on_participant_joined")
+        async def on_first_participant_joined(transport, participant_id):
+            await task.queue_frame(TextFrame(f"Hello there!"))
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
diff --git a/src/pipecat/transports/services/livekit.py b/src/pipecat/transports/services/livekit.py
new file mode 100644
index 000000000..168f86aeb
--- /dev/null
+++ b/src/pipecat/transports/services/livekit.py
@@ -0,0 +1,556 @@
+import asyncio
+from dataclasses import dataclass
+from typing import Any, Awaitable, Callable, List
+
+import numpy as np
+from loguru import logger
+from pipecat.frames.frames import (
+    AudioRawFrame,
+    CancelFrame,
+    EndFrame,
+    Frame,
+    MetricsFrame,
+    StartFrame,
+    TransportMessageFrame,
+)
+from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
+from pipecat.transports.base_input import BaseInputTransport
+from pipecat.transports.base_output import BaseOutputTransport
+from pipecat.transports.base_transport import BaseTransport, TransportParams
+from pipecat.vad.vad_analyzer import VADAnalyzer
+from pydantic import BaseModel
+from scipy import signal
+from tenacity import retry, stop_after_attempt, wait_exponential
+
+try:
+    from livekit import rtc
+except ModuleNotFoundError as e:
+    logger.error(f"Exception: {e}")
+    logger.error("In order to use LiveKit, you need to `pip install pipecat-ai[livekit]`.")
+    raise Exception(f"Missing module: {e}")
+
+
+@dataclass
+class LiveKitTransportMessageFrame(TransportMessageFrame):
+    participant_id: str | None = None
+
+
+class LiveKitParams(TransportParams):
+    audio_out_sample_rate: int = 48000
+    audio_out_channels: int = 1
+    vad_enabled: bool = True
+    vad_analyzer: VADAnalyzer | None = None
+    audio_in_sample_rate: int = 16000
+
+
+class LiveKitCallbacks(BaseModel):
+    on_connected: Callable[[], Awaitable[None]]
+    on_disconnected: Callable[[], Awaitable[None]]
+    on_participant_connected: Callable[[str], Awaitable[None]]
+    on_participant_disconnected: Callable[[str], Awaitable[None]]
+    on_audio_track_subscribed: Callable[[str], Awaitable[None]]
+    on_audio_track_unsubscribed: Callable[[str], Awaitable[None]]
+    on_data_received: Callable[[bytes, str], Awaitable[None]]
+
+
+class LiveKitTransportClient:
+    def __init__(
+        self,
+        url: str,
+        token: str,
+        room_name: str,
+        params: LiveKitParams,
+        callbacks: LiveKitCallbacks,
+        loop: asyncio.AbstractEventLoop,
+    ):
+        self._url = url
+        self._token = token
+        self._room_name = room_name
+        self._params = params
+        self._callbacks = callbacks
+        self._loop = loop
+        self._room = rtc.Room(loop=loop)
+        self._participant_id: str = ""
+        self._connected = False
+        self._audio_source: rtc.AudioSource | None = None
+        self._audio_track: rtc.LocalAudioTrack | None = None
+        self._audio_tracks = {}
+        self._audio_queue = asyncio.Queue()
+
+        # Set up room event handlers
+        self._room.on("participant_connected")(self._on_participant_connected_wrapper)
+        self._room.on("participant_disconnected")(self._on_participant_disconnected_wrapper)
+        self._room.on("track_subscribed")(self._on_track_subscribed_wrapper)
+        self._room.on("track_unsubscribed")(self._on_track_unsubscribed_wrapper)
+        self._room.on("data_received")(self._on_data_received_wrapper)
+        self._room.on("connected")(self._on_connected_wrapper)
+        self._room.on("disconnected")(self._on_disconnected_wrapper)
+
+    @property
+    def participant_id(self) -> str:
+        return self._participant_id
+
+    @retry(stop=stop_after_attempt(3), wait=wait_exponential(multiplier=1, min=4, max=10))
+    async def connect(self):
+        if self._connected:
+            return
+
+        logger.info(f"Connecting to {self._room_name}")
+
+        try:
+            await self._room.connect(
+                self._url,
+                self._token,
+                options=rtc.RoomOptions(auto_subscribe=True),
+            )
+            self._connected = True
+            self._participant_id = self._room.local_participant.sid
+            logger.info(f"Connected to {self._room_name}")
+
+            # Set up audio source and track
+            self._audio_source = rtc.AudioSource(self._params.audio_out_sample_rate, self._params.audio_out_channels)
+            self._audio_track = rtc.LocalAudioTrack.create_audio_track("pipecat-audio", self._audio_source)
+            options = rtc.TrackPublishOptions()
+            options.source = rtc.TrackSource.SOURCE_MICROPHONE
+            await self._room.local_participant.publish_track(self._audio_track, options)
+
+            await self._callbacks.on_connected()
+        except Exception as e:
+            logger.error(f"Error connecting to {self._room_name}: {e}")
+            raise
+
+    async def disconnect(self):
+        if not self._connected:
+            return
+
+        logger.info(f"Disconnecting from {self._room_name}")
+        await self._room.disconnect()
+        self._connected = False
+        logger.info(f"Disconnected from {self._room_name}")
+        await self._callbacks.on_disconnected()
+
+    async def send_data(self, data: bytes, participant_id: str | None = None):
+        if not self._connected:
+            return
+
+        try:
+            if participant_id:
+                await self._room.local_participant.publish_data(data, reliable=True, destination_identities=[participant_id])
+            else:
+                await self._room.local_participant.publish_data(data, reliable=True)
+        except Exception as e:
+            logger.error(f"Error sending data: {e}")
+
+    async def publish_audio(self, audio_frame: rtc.AudioFrame):
+        if not self._connected or not self._audio_source:
+            return
+
+        try:
+            await self._audio_source.capture_frame(audio_frame)
+        except Exception as e:
+            logger.error(f"Error publishing audio: {e}")
+
+    def get_participants(self) -> List[str]:
+        return [p.sid for p in self._room.remote_participants.values()]
+
+    async def get_participant_metadata(self, participant_id: str) -> dict:
+        participant = self._room.remote_participants.get(participant_id)
+        if participant:
+            return {
+                "id": participant.sid,
+                "name": participant.name,
+                "metadata": participant.metadata,
+                "is_speaking": participant.is_speaking,
+            }
+        return {}
+
+    async def set_participant_metadata(self, metadata: str):
+        await self._room.local_participant.set_metadata(metadata)
+
+    async def mute_participant(self, participant_id: str):
+        participant = self._room.remote_participants.get(participant_id)
+        if participant:
+            for track in participant.tracks.values():
+                if track.kind == "audio":
+                    await track.set_enabled(False)
+
+    async def unmute_participant(self, participant_id: str):
+        participant = self._room.remote_participants.get(participant_id)
+        if participant:
+            for track in participant.tracks.values():
+                if track.kind == "audio":
+                    await track.set_enabled(True)
+
+    # Wrapper methods for event handlers
+    def _on_participant_connected_wrapper(self, participant: rtc.RemoteParticipant):
+        asyncio.create_task(self._async_on_participant_connected(participant))
+
+    def _on_participant_disconnected_wrapper(self, participant: rtc.RemoteParticipant):
+        asyncio.create_task(self._async_on_participant_disconnected(participant))
+
+    def _on_track_subscribed_wrapper(
+        self, track: rtc.Track, publication: rtc.RemoteTrackPublication, participant: rtc.RemoteParticipant
+    ):
+        asyncio.create_task(self._async_on_track_subscribed(track, publication, participant))
+
+    def _on_track_unsubscribed_wrapper(
+        self, track: rtc.Track, publication: rtc.RemoteTrackPublication, participant: rtc.RemoteParticipant
+    ):
+        asyncio.create_task(self._async_on_track_unsubscribed(track, publication, participant))
+
+    def _on_data_received_wrapper(self, data: rtc.DataPacket):
+        asyncio.create_task(self._async_on_data_received(data))
+
+    def _on_connected_wrapper(self):
+        asyncio.create_task(self._async_on_connected())
+
+    def _on_disconnected_wrapper(self):
+        asyncio.create_task(self._async_on_disconnected())
+
+    # Async methods for event handling
+    async def _async_on_participant_connected(self, participant: rtc.RemoteParticipant):
+        logger.info(f"Participant connected: {participant.identity}")
+        await self._callbacks.on_participant_connected(participant.sid)
+
+    async def _async_on_participant_disconnected(self, participant: rtc.RemoteParticipant):
+        logger.info(f"Participant disconnected: {participant.identity}")
+        await self._callbacks.on_participant_disconnected(participant.sid)
+
+    async def _async_on_track_subscribed(
+        self, track: rtc.Track, publication: rtc.RemoteTrackPublication, participant: rtc.RemoteParticipant
+    ):
+        if track.kind == rtc.TrackKind.KIND_AUDIO:
+            logger.info(f"Audio track subscribed: {track.sid} from participant {participant.sid}")
+            self._audio_tracks[participant.sid] = track
+            audio_stream = rtc.AudioStream(track)
+            asyncio.create_task(self._process_audio_stream(audio_stream, participant.sid))
+
+    async def _async_on_track_unsubscribed(
+        self, track: rtc.Track, publication: rtc.RemoteTrackPublication, participant: rtc.RemoteParticipant
+    ):
+        logger.info(f"Track unsubscribed: {publication.sid} from {participant.identity}")
+        if track.kind == rtc.TrackKind.KIND_AUDIO:
+            await self._callbacks.on_audio_track_unsubscribed(participant.sid)
+
+    async def _async_on_data_received(self, data: rtc.DataPacket):
+        await self._callbacks.on_data_received(data.data, data.participant.sid)
+
+    async def _async_on_connected(self):
+        await self._callbacks.on_connected()
+
+    async def _async_on_disconnected(self):
+        self._connected = False
+        logger.info(f"Disconnected from {self._room_name}")
+        await self._callbacks.on_disconnected()
+
+    async def _process_audio_stream(self, audio_stream: rtc.AudioStream, participant_id: str):
+        logger.info(f"Started processing audio stream for participant {participant_id}")
+        async for event in audio_stream:
+            if isinstance(event, rtc.AudioFrameEvent):
+                await self._audio_queue.put((event, participant_id))
+            else:
+                logger.warning(f"Received unexpected event type: {type(event)}")
+
+    async def cleanup(self):
+        await self.disconnect()
+
+    async def get_next_audio_frame(self):
+        frame, participant_id = await self._audio_queue.get()
+        return frame, participant_id
+
+
+class LiveKitInputTransport(BaseInputTransport):
+    def __init__(self, client: LiveKitTransportClient, params: LiveKitParams, **kwargs):
+        super().__init__(params, **kwargs)
+        self._client = client
+        self._audio_in_task = None
+        self._vad_analyzer: VADAnalyzer | None = params.vad_analyzer
+        self._current_sample_rate: int = params.audio_in_sample_rate
+        if params.vad_enabled and not params.vad_analyzer:
+            self._vad_analyzer = VADAnalyzer(sample_rate=self._current_sample_rate, num_channels=self._params.audio_in_channels)
+
+    async def start(self, frame: StartFrame):
+        await super().start(frame)
+        await self._client.connect()
+        if self._params.audio_in_enabled or self._params.vad_enabled:
+            self._audio_in_task = asyncio.create_task(self._audio_in_task_handler())
+        logger.info("LiveKitInputTransport started")
+
+    async def stop(self, frame: EndFrame):
+        if self._audio_in_task:
+            self._audio_in_task.cancel()
+            try:
+                await self._audio_in_task
+            except asyncio.CancelledError:
+                pass
+        await super().stop(frame)
+        await self._client.disconnect()
+        logger.info("LiveKitInputTransport stopped")
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        if isinstance(frame, EndFrame):
+            await self.stop(frame)
+        else:
+            await super().process_frame(frame, direction)
+
+    async def cancel(self, frame: CancelFrame):
+        await super().cancel(frame)
+        await self._client.disconnect()
+        if self._audio_in_task and (self._params.audio_in_enabled or self._params.vad_enabled):
+            self._audio_in_task.cancel()
+            await self._audio_in_task
+
+    def vad_analyzer(self) -> VADAnalyzer | None:
+        return self._vad_analyzer
+
+    async def push_app_message(self, message: Any, sender: str):
+        frame = LiveKitTransportMessageFrame(message=message, participant_id=sender)
+        await self._internal_push_frame(frame)
+
+    async def _audio_in_task_handler(self):
+        logger.info("Audio input task started")
+        while True:
+            try:
+                audio_data = await self._client.get_next_audio_frame()
+                if audio_data:
+                    audio_frame_event, participant_id = audio_data
+                    pipecat_audio_frame = self._convert_livekit_audio_to_pipecat(audio_frame_event)
+                    await self.push_audio_frame(pipecat_audio_frame)
+                    await self._internal_push_frame(
+                        pipecat_audio_frame
+                    )  # TODO: ensure audio frames are pushed with the default BaseInputTransport.push_audio_frame()
+            except asyncio.CancelledError:
+                logger.info("Audio input task cancelled")
+                break
+            except Exception as e:
+                logger.error(f"Error in audio input task: {e}")
+
+    def _convert_livekit_audio_to_pipecat(self, audio_frame_event: rtc.AudioFrameEvent) -> AudioRawFrame:
+        audio_frame = audio_frame_event.frame
+        audio_data = np.frombuffer(audio_frame.data, dtype=np.int16)
+        original_sample_rate = audio_frame.sample_rate
+
+        # Allow 8kHz and 16kHz, convert anything else to 16kHz
+        if original_sample_rate not in [8000, 16000]:
+            audio_data = self._resample_audio(audio_data, original_sample_rate, 16000)
+            sample_rate = 16000
+        else:
+            sample_rate = original_sample_rate
+
+        if sample_rate != self._current_sample_rate:
+            self._current_sample_rate = sample_rate
+            self._vad_analyzer = VADAnalyzer(sample_rate=self._current_sample_rate, num_channels=self._params.audio_in_channels)
+
+        return AudioRawFrame(audio=audio_data.tobytes(), sample_rate=sample_rate, num_channels=audio_frame.num_channels)
+
+    def _resample_audio(self, audio_data: np.ndarray, original_rate: int, target_rate: int) -> np.ndarray:
+        num_samples = int(len(audio_data) * target_rate / original_rate)
+        resampled_audio = signal.resample(audio_data, num_samples)
+        return resampled_audio.astype(np.int16)
+
+
+class LiveKitOutputTransport(BaseOutputTransport):
+    def __init__(self, client: LiveKitTransportClient, params: LiveKitParams, **kwargs):
+        super().__init__(params, **kwargs)
+        self._client = client
+
+    async def start(self, frame: StartFrame):
+        await super().start(frame)
+        await self._client.connect()
+        logger.info("LiveKitOutputTransport started")
+
+    async def stop(self, frame: EndFrame):
+        await super().stop(frame)
+        await self._client.disconnect()
+        logger.info("LiveKitOutputTransport stopped")
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        if isinstance(frame, EndFrame):
+            await self.stop(frame)
+        else:
+            await super().process_frame(frame, direction)
+
+    async def cancel(self, frame: CancelFrame):
+        await super().cancel(frame)
+        await self._client.disconnect()
+
+    async def send_message(self, frame: TransportMessageFrame):
+        if isinstance(frame, LiveKitTransportMessageFrame):
+            await self._client.send_data(frame.message.encode(), frame.participant_id)
+        else:
+            await self._client.send_data(frame.message.encode())
+
+    async def send_metrics(self, frame: MetricsFrame):
+        metrics = {}
+        if frame.ttfb:
+            metrics["ttfb"] = frame.ttfb
+        if frame.processing:
+            metrics["processing"] = frame.processing
+        if hasattr(frame, "tokens"):
+            metrics["tokens"] = frame.tokens
+        if hasattr(frame, "characters"):
+            metrics["characters"] = frame.characters
+
+        message = LiveKitTransportMessageFrame(message={"type": "pipecat-metrics", "metrics": metrics})
+        await self._client.send_data(str(message.message).encode())
+
+    async def write_raw_audio_frames(self, frames: bytes):
+        livekit_audio = self._convert_pipecat_audio_to_livekit(frames)
+        await self._client.publish_audio(livekit_audio)
+
+    def _convert_pipecat_audio_to_livekit(self, pipecat_audio: bytes) -> rtc.AudioFrame:
+        bytes_per_sample = 2  # Assuming 16-bit audio
+        total_samples = len(pipecat_audio) // bytes_per_sample
+        samples_per_channel = total_samples // self._params.audio_out_channels
+
+        return rtc.AudioFrame(
+            data=pipecat_audio,
+            sample_rate=self._params.audio_out_sample_rate,
+            num_channels=self._params.audio_out_channels,
+            samples_per_channel=samples_per_channel,
+        )
+
+
+class LiveKitTransport(BaseTransport):
+    def __init__(
+        self,
+        url: str,
+        token: str,
+        room_name: str,
+        params: LiveKitParams = LiveKitParams(),
+        input_name: str | None = None,
+        output_name: str | None = None,
+        loop: asyncio.AbstractEventLoop | None = None,
+    ):
+        super().__init__(input_name=input_name, output_name=output_name, loop=loop)
+
+        self._url = url
+        self._token = token
+        self._room_name = room_name
+        self._params = params
+
+        self._client = LiveKitTransportClient(url, token, room_name, self._params, self._create_callbacks(), self._loop)
+        self._input: LiveKitInputTransport | None = None
+        self._output: LiveKitOutputTransport | None = None
+
+        self._register_event_handler("on_connected")
+        self._register_event_handler("on_disconnected")
+        self._register_event_handler("on_participant_connected")
+        self._register_event_handler("on_participant_disconnected")
+        self._register_event_handler("on_audio_track_subscribed")
+        self._register_event_handler("on_audio_track_unsubscribed")
+        self._register_event_handler("on_data_received")
+        self._register_event_handler("on_first_participant_joined")
+        self._register_event_handler("on_participant_left")
+        self._register_event_handler("on_call_state_updated")
+
+    def _create_callbacks(self) -> LiveKitCallbacks:
+        return LiveKitCallbacks(
+            on_connected=self._on_connected,
+            on_disconnected=self._on_disconnected,
+            on_participant_connected=self._on_participant_connected,
+            on_participant_disconnected=self._on_participant_disconnected,
+            on_audio_track_subscribed=self._on_audio_track_subscribed,
+            on_audio_track_unsubscribed=self._on_audio_track_unsubscribed,
+            on_data_received=self._on_data_received,
+        )
+
+    def input(self) -> FrameProcessor:
+        if not self._input:
+            self._input = LiveKitInputTransport(self._client, self._params, name=self._input_name)
+        return self._input
+
+    def output(self) -> FrameProcessor:
+        if not self._output:
+            self._output = LiveKitOutputTransport(self._client, self._params, name=self._output_name)
+        return self._output
+
+    @property
+    def participant_id(self) -> str:
+        return self._client.participant_id
+
+    async def send_audio(self, frame: AudioRawFrame):
+        if self._output:
+            await self._output.process_frame(frame, FrameDirection.DOWNSTREAM)
+
+    def get_participants(self) -> List[str]:
+        return self._client.get_participants()
+
+    async def get_participant_metadata(self, participant_id: str) -> dict:
+        return await self._client.get_participant_metadata(participant_id)
+
+    async def set_metadata(self, metadata: str):
+        await self._client.set_participant_metadata(metadata)
+
+    async def mute_participant(self, participant_id: str):
+        await self._client.mute_participant(participant_id)
+
+    async def unmute_participant(self, participant_id: str):
+        await self._client.unmute_participant(participant_id)
+
+    async def _on_connected(self):
+        await self._call_event_handler("on_connected")
+
+    async def _on_disconnected(self):
+        await self._call_event_handler("on_disconnected")
+        # Attempt to reconnect
+        try:
+            await self._client.connect()
+            await self._call_event_handler("on_connected")
+        except Exception as e:
+            logger.error(f"Failed to reconnect: {e}")
+
+    async def _on_participant_connected(self, participant_id: str):
+        await self._call_event_handler("on_participant_connected", participant_id)
+        if len(self.get_participants()) == 1:
+            await self._call_event_handler("on_first_participant_joined", participant_id)
+
+    async def _on_participant_disconnected(self, participant_id: str):
+        await self._call_event_handler("on_participant_disconnected", participant_id)
+        await self._call_event_handler("on_participant_left", participant_id, "disconnected")
+        if self._input:
+            await self._input.process_frame(EndFrame(), FrameDirection.DOWNSTREAM)
+        if self._output:
+            await self._output.process_frame(EndFrame(), FrameDirection.DOWNSTREAM)
+
+    async def _on_audio_track_subscribed(self, participant_id: str):
+        await self._call_event_handler("on_audio_track_subscribed", participant_id)
+        participant = self._client._room.remote_participants.get(participant_id)
+        if participant:
+            for publication in participant.audio_tracks.values():
+                self._client._on_track_subscribed_wrapper(publication.track, publication, participant)
+
+    async def _on_audio_track_unsubscribed(self, participant_id: str):
+        await self._call_event_handler("on_audio_track_unsubscribed", participant_id)
+
+    async def _on_data_received(self, data: bytes, participant_id: str):
+        if self._input:
+            await self._input.push_app_message(data.decode(), participant_id)
+        await self._call_event_handler("on_data_received", data, participant_id)
+
+    async def send_message(self, message: str, participant_id: str | None = None):
+        if self._output:
+            frame = LiveKitTransportMessageFrame(message=message, participant_id=participant_id)
+            await self._output.send_message(frame)
+
+    async def cleanup(self):
+        if self._input:
+            await self._input.cleanup()
+        if self._output:
+            await self._output.cleanup()
+        await self._client.disconnect()
+
+    async def on_room_event(self, event):
+        # Handle room events
+        pass
+
+    async def on_participant_event(self, event):
+        # Handle participant events
+        pass
+
+    async def on_track_event(self, event):
+        # Handle track events
+        pass
+
+    async def _on_call_state_updated(self, state: str):
+        await self._call_event_handler("on_call_state_updated", self, state)

From 2e5b0c1d6bbcf89baf4365df8a94d749ad5d7edc Mon Sep 17 00:00:00 2001
From: joachimchauvet <joachim@generativestudio.dev>
Date: Tue, 17 Sep 2024 22:04:42 +0300
Subject: [PATCH 060/135] add tenacity dependency

---
 examples/foundational/01b-livekit-audio.py | 3 ++-
 pyproject.toml                             | 2 +-
 2 files changed, 3 insertions(+), 2 deletions(-)

diff --git a/examples/foundational/01b-livekit-audio.py b/examples/foundational/01b-livekit-audio.py
index 9a6d80709..8cfb265ca 100644
--- a/examples/foundational/01b-livekit-audio.py
+++ b/examples/foundational/01b-livekit-audio.py
@@ -7,6 +7,7 @@ import aiohttp
 from dotenv import load_dotenv
 from livekit import api  # pip install livekit-api
 from loguru import logger
+
 from pipecat.frames.frames import TextFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
@@ -84,7 +85,7 @@ async def main():
 
         # Register an event handler so we can play the audio when the
         # participant joins.
-        @transport.event_handler("on_participant_joined")
+        @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant_id):
             await task.queue_frame(TextFrame(f"Hello there!"))
 
diff --git a/pyproject.toml b/pyproject.toml
index aebccda2f..943153d2d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -47,7 +47,7 @@ google = [ "google-generativeai~=0.7.2" ]
 gstreamer = [ "pygobject~=3.48.2" ]
 fireworks = [ "openai~=1.37.2" ]
 langchain = [ "langchain~=0.2.14", "langchain-community~=0.2.12", "langchain-openai~=0.1.20" ]
-livekit = [ "livekit~=0.13.1" ]
+livekit = [ "livekit~=0.13.1", "tenacity~=9.0.0" ]
 lmnt = [ "lmnt~=1.1.4" ]
 local = [ "pyaudio~=0.2.14" ]
 moondream = [ "einops~=0.8.0", "timm~=1.0.8", "transformers~=4.44.0" ]

From 470b5eafe7fbdf691e94195622e986fe9aba093d Mon Sep 17 00:00:00 2001
From: joachimchauvet <joachim@generativestudio.dev>
Date: Tue, 17 Sep 2024 22:14:06 +0300
Subject: [PATCH 061/135] move tenacity imports inside try block

---
 src/pipecat/transports/services/livekit.py | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/src/pipecat/transports/services/livekit.py b/src/pipecat/transports/services/livekit.py
index 168f86aeb..b0c630c90 100644
--- a/src/pipecat/transports/services/livekit.py
+++ b/src/pipecat/transports/services/livekit.py
@@ -4,6 +4,9 @@ from typing import Any, Awaitable, Callable, List
 
 import numpy as np
 from loguru import logger
+from pydantic import BaseModel
+from scipy import signal
+
 from pipecat.frames.frames import (
     AudioRawFrame,
     CancelFrame,
@@ -18,12 +21,10 @@ from pipecat.transports.base_input import BaseInputTransport
 from pipecat.transports.base_output import BaseOutputTransport
 from pipecat.transports.base_transport import BaseTransport, TransportParams
 from pipecat.vad.vad_analyzer import VADAnalyzer
-from pydantic import BaseModel
-from scipy import signal
-from tenacity import retry, stop_after_attempt, wait_exponential
 
 try:
     from livekit import rtc
+    from tenacity import retry, stop_after_attempt, wait_exponential
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error("In order to use LiveKit, you need to `pip install pipecat-ai[livekit]`.")

From fa609f1afc01dd8601f95dc3a451ef54bd5c4c9e Mon Sep 17 00:00:00 2001
From: joachimchauvet <joachim@generativestudio.dev>
Date: Thu, 19 Sep 2024 21:21:42 +0300
Subject: [PATCH 062/135] adjust output sample rate and create user token

---
 examples/foundational/01b-livekit-audio.py | 11 ++++++-----
 1 file changed, 6 insertions(+), 5 deletions(-)

diff --git a/examples/foundational/01b-livekit-audio.py b/examples/foundational/01b-livekit-audio.py
index 8cfb265ca..8b3f38cd8 100644
--- a/examples/foundational/01b-livekit-audio.py
+++ b/examples/foundational/01b-livekit-audio.py
@@ -60,6 +60,9 @@ async def configure_livekit():
 
     token = generate_token(room_name, "Say One Thing", api_key, api_secret)
 
+    user_token = generate_token(room_name, "User", api_key, api_secret)
+    logger.info(f"User token: {user_token}")
+
     return (url, token, room_name)
 
 
@@ -68,10 +71,7 @@ async def main():
         (url, token, room_name) = await configure_livekit()
 
         transport = LiveKitTransport(
-            url=url,
-            token=token,
-            room_name=room_name,
-            params=LiveKitParams(audio_out_enabled=True)
+            url=url, token=token, room_name=room_name, params=LiveKitParams(audio_out_enabled=True, audio_out_sample_rate=16000)
         )
 
         tts = CartesiaTTSService(
@@ -87,7 +87,8 @@ async def main():
         # participant joins.
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant_id):
-            await task.queue_frame(TextFrame(f"Hello there!"))
+            await asyncio.sleep(1)
+            await task.queue_frame(TextFrame("Hello there! How are you doing today? Would you like to talk about the weather?"))
 
         await runner.run(task)
 

From b6e1d6e6aedd61831e6b6cef6cb1a1b462891bb9 Mon Sep 17 00:00:00 2001
From: joachimchauvet <joachim@generativestudio.dev>
Date: Tue, 24 Sep 2024 10:21:02 +0300
Subject: [PATCH 063/135] format with ruff

---
 examples/foundational/01b-livekit-audio.py | 19 ++++--
 src/pipecat/transports/services/livekit.py | 70 +++++++++++++++++-----
 2 files changed, 69 insertions(+), 20 deletions(-)

diff --git a/examples/foundational/01b-livekit-audio.py b/examples/foundational/01b-livekit-audio.py
index 8b3f38cd8..68e0d2803 100644
--- a/examples/foundational/01b-livekit-audio.py
+++ b/examples/foundational/01b-livekit-audio.py
@@ -35,7 +35,9 @@ def generate_token(room_name: str, participant_name: str, api_key: str, api_secr
 
 async def configure_livekit():
     parser = argparse.ArgumentParser(description="LiveKit AI SDK Bot Sample")
-    parser.add_argument("-r", "--room", type=str, required=False, help="Name of the LiveKit room to join")
+    parser.add_argument(
+        "-r", "--room", type=str, required=False, help="Name of the LiveKit room to join"
+    )
     parser.add_argument("-u", "--url", type=str, required=False, help="URL of the LiveKit server")
 
     args, unknown = parser.parse_known_args()
@@ -56,7 +58,9 @@ async def configure_livekit():
         )
 
     if not api_key or not api_secret:
-        raise Exception("LIVEKIT_API_KEY and LIVEKIT_API_SECRET must be set in environment variables.")
+        raise Exception(
+            "LIVEKIT_API_KEY and LIVEKIT_API_SECRET must be set in environment variables."
+        )
 
     token = generate_token(room_name, "Say One Thing", api_key, api_secret)
 
@@ -71,7 +75,10 @@ async def main():
         (url, token, room_name) = await configure_livekit()
 
         transport = LiveKitTransport(
-            url=url, token=token, room_name=room_name, params=LiveKitParams(audio_out_enabled=True, audio_out_sample_rate=16000)
+            url=url,
+            token=token,
+            room_name=room_name,
+            params=LiveKitParams(audio_out_enabled=True, audio_out_sample_rate=16000),
         )
 
         tts = CartesiaTTSService(
@@ -88,7 +95,11 @@ async def main():
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant_id):
             await asyncio.sleep(1)
-            await task.queue_frame(TextFrame("Hello there! How are you doing today? Would you like to talk about the weather?"))
+            await task.queue_frame(
+                TextFrame(
+                    "Hello there! How are you doing today? Would you like to talk about the weather?"
+                )
+            )
 
         await runner.run(task)
 
diff --git a/src/pipecat/transports/services/livekit.py b/src/pipecat/transports/services/livekit.py
index b0c630c90..1dcb069ee 100644
--- a/src/pipecat/transports/services/livekit.py
+++ b/src/pipecat/transports/services/livekit.py
@@ -109,8 +109,12 @@ class LiveKitTransportClient:
             logger.info(f"Connected to {self._room_name}")
 
             # Set up audio source and track
-            self._audio_source = rtc.AudioSource(self._params.audio_out_sample_rate, self._params.audio_out_channels)
-            self._audio_track = rtc.LocalAudioTrack.create_audio_track("pipecat-audio", self._audio_source)
+            self._audio_source = rtc.AudioSource(
+                self._params.audio_out_sample_rate, self._params.audio_out_channels
+            )
+            self._audio_track = rtc.LocalAudioTrack.create_audio_track(
+                "pipecat-audio", self._audio_source
+            )
             options = rtc.TrackPublishOptions()
             options.source = rtc.TrackSource.SOURCE_MICROPHONE
             await self._room.local_participant.publish_track(self._audio_track, options)
@@ -136,7 +140,9 @@ class LiveKitTransportClient:
 
         try:
             if participant_id:
-                await self._room.local_participant.publish_data(data, reliable=True, destination_identities=[participant_id])
+                await self._room.local_participant.publish_data(
+                    data, reliable=True, destination_identities=[participant_id]
+                )
             else:
                 await self._room.local_participant.publish_data(data, reliable=True)
         except Exception as e:
@@ -190,12 +196,18 @@ class LiveKitTransportClient:
         asyncio.create_task(self._async_on_participant_disconnected(participant))
 
     def _on_track_subscribed_wrapper(
-        self, track: rtc.Track, publication: rtc.RemoteTrackPublication, participant: rtc.RemoteParticipant
+        self,
+        track: rtc.Track,
+        publication: rtc.RemoteTrackPublication,
+        participant: rtc.RemoteParticipant,
     ):
         asyncio.create_task(self._async_on_track_subscribed(track, publication, participant))
 
     def _on_track_unsubscribed_wrapper(
-        self, track: rtc.Track, publication: rtc.RemoteTrackPublication, participant: rtc.RemoteParticipant
+        self,
+        track: rtc.Track,
+        publication: rtc.RemoteTrackPublication,
+        participant: rtc.RemoteParticipant,
     ):
         asyncio.create_task(self._async_on_track_unsubscribed(track, publication, participant))
 
@@ -218,7 +230,10 @@ class LiveKitTransportClient:
         await self._callbacks.on_participant_disconnected(participant.sid)
 
     async def _async_on_track_subscribed(
-        self, track: rtc.Track, publication: rtc.RemoteTrackPublication, participant: rtc.RemoteParticipant
+        self,
+        track: rtc.Track,
+        publication: rtc.RemoteTrackPublication,
+        participant: rtc.RemoteParticipant,
     ):
         if track.kind == rtc.TrackKind.KIND_AUDIO:
             logger.info(f"Audio track subscribed: {track.sid} from participant {participant.sid}")
@@ -227,7 +242,10 @@ class LiveKitTransportClient:
             asyncio.create_task(self._process_audio_stream(audio_stream, participant.sid))
 
     async def _async_on_track_unsubscribed(
-        self, track: rtc.Track, publication: rtc.RemoteTrackPublication, participant: rtc.RemoteParticipant
+        self,
+        track: rtc.Track,
+        publication: rtc.RemoteTrackPublication,
+        participant: rtc.RemoteParticipant,
     ):
         logger.info(f"Track unsubscribed: {publication.sid} from {participant.identity}")
         if track.kind == rtc.TrackKind.KIND_AUDIO:
@@ -268,7 +286,9 @@ class LiveKitInputTransport(BaseInputTransport):
         self._vad_analyzer: VADAnalyzer | None = params.vad_analyzer
         self._current_sample_rate: int = params.audio_in_sample_rate
         if params.vad_enabled and not params.vad_analyzer:
-            self._vad_analyzer = VADAnalyzer(sample_rate=self._current_sample_rate, num_channels=self._params.audio_in_channels)
+            self._vad_analyzer = VADAnalyzer(
+                sample_rate=self._current_sample_rate, num_channels=self._params.audio_in_channels
+            )
 
     async def start(self, frame: StartFrame):
         await super().start(frame)
@@ -326,7 +346,9 @@ class LiveKitInputTransport(BaseInputTransport):
             except Exception as e:
                 logger.error(f"Error in audio input task: {e}")
 
-    def _convert_livekit_audio_to_pipecat(self, audio_frame_event: rtc.AudioFrameEvent) -> AudioRawFrame:
+    def _convert_livekit_audio_to_pipecat(
+        self, audio_frame_event: rtc.AudioFrameEvent
+    ) -> AudioRawFrame:
         audio_frame = audio_frame_event.frame
         audio_data = np.frombuffer(audio_frame.data, dtype=np.int16)
         original_sample_rate = audio_frame.sample_rate
@@ -340,11 +362,19 @@ class LiveKitInputTransport(BaseInputTransport):
 
         if sample_rate != self._current_sample_rate:
             self._current_sample_rate = sample_rate
-            self._vad_analyzer = VADAnalyzer(sample_rate=self._current_sample_rate, num_channels=self._params.audio_in_channels)
+            self._vad_analyzer = VADAnalyzer(
+                sample_rate=self._current_sample_rate, num_channels=self._params.audio_in_channels
+            )
 
-        return AudioRawFrame(audio=audio_data.tobytes(), sample_rate=sample_rate, num_channels=audio_frame.num_channels)
+        return AudioRawFrame(
+            audio=audio_data.tobytes(),
+            sample_rate=sample_rate,
+            num_channels=audio_frame.num_channels,
+        )
 
-    def _resample_audio(self, audio_data: np.ndarray, original_rate: int, target_rate: int) -> np.ndarray:
+    def _resample_audio(
+        self, audio_data: np.ndarray, original_rate: int, target_rate: int
+    ) -> np.ndarray:
         num_samples = int(len(audio_data) * target_rate / original_rate)
         resampled_audio = signal.resample(audio_data, num_samples)
         return resampled_audio.astype(np.int16)
@@ -392,7 +422,9 @@ class LiveKitOutputTransport(BaseOutputTransport):
         if hasattr(frame, "characters"):
             metrics["characters"] = frame.characters
 
-        message = LiveKitTransportMessageFrame(message={"type": "pipecat-metrics", "metrics": metrics})
+        message = LiveKitTransportMessageFrame(
+            message={"type": "pipecat-metrics", "metrics": metrics}
+        )
         await self._client.send_data(str(message.message).encode())
 
     async def write_raw_audio_frames(self, frames: bytes):
@@ -430,7 +462,9 @@ class LiveKitTransport(BaseTransport):
         self._room_name = room_name
         self._params = params
 
-        self._client = LiveKitTransportClient(url, token, room_name, self._params, self._create_callbacks(), self._loop)
+        self._client = LiveKitTransportClient(
+            url, token, room_name, self._params, self._create_callbacks(), self._loop
+        )
         self._input: LiveKitInputTransport | None = None
         self._output: LiveKitOutputTransport | None = None
 
@@ -463,7 +497,9 @@ class LiveKitTransport(BaseTransport):
 
     def output(self) -> FrameProcessor:
         if not self._output:
-            self._output = LiveKitOutputTransport(self._client, self._params, name=self._output_name)
+            self._output = LiveKitOutputTransport(
+                self._client, self._params, name=self._output_name
+            )
         return self._output
 
     @property
@@ -519,7 +555,9 @@ class LiveKitTransport(BaseTransport):
         participant = self._client._room.remote_participants.get(participant_id)
         if participant:
             for publication in participant.audio_tracks.values():
-                self._client._on_track_subscribed_wrapper(publication.track, publication, participant)
+                self._client._on_track_subscribed_wrapper(
+                    publication.track, publication, participant
+                )
 
     async def _on_audio_track_unsubscribed(self, participant_id: str):
         await self._call_event_handler("on_audio_track_unsubscribed", participant_id)

From b1e17ee34792326350c4040216bff69a50f3c4b8 Mon Sep 17 00:00:00 2001
From: mercuryyy <mercuryyy@users.noreply.github.com>
Date: Tue, 24 Sep 2024 07:45:29 -0400
Subject: [PATCH 064/135] Fix syntax error in deepgram.py

---
 src/pipecat/services/deepgram.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/src/pipecat/services/deepgram.py b/src/pipecat/services/deepgram.py
index fab12e080..914bc2ec2 100644
--- a/src/pipecat/services/deepgram.py
+++ b/src/pipecat/services/deepgram.py
@@ -77,8 +77,7 @@ class DeepgramTTSService(TTSService):
         logger.debug(f"Generating TTS: [{text}]")
 
         base_url = self._base_url
-        request_url = f"{base_url}?model={self._voice}&encoding={
-            self._encoding}&container=none&sample_rate={self._sample_rate}"
+        request_url = f"{base_url}?model={self._voice}&encoding={self._encoding}&container=none&sample_rate={self._sample_rate}"
         headers = {"authorization": f"token {self._api_key}"}
         body = {"text": text}
 

From ec5998bc36a4991d4964cfee106376f6e9af8fd5 Mon Sep 17 00:00:00 2001
From: joachimchauvet <joachim@generativestudio.dev>
Date: Tue, 24 Sep 2024 14:54:37 +0300
Subject: [PATCH 065/135] remove _internal_push_frame from
 LiveKitInputTransport

---
 src/pipecat/transports/services/livekit.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/pipecat/transports/services/livekit.py b/src/pipecat/transports/services/livekit.py
index 1dcb069ee..d6f00c3ef 100644
--- a/src/pipecat/transports/services/livekit.py
+++ b/src/pipecat/transports/services/livekit.py
@@ -326,7 +326,7 @@ class LiveKitInputTransport(BaseInputTransport):
 
     async def push_app_message(self, message: Any, sender: str):
         frame = LiveKitTransportMessageFrame(message=message, participant_id=sender)
-        await self._internal_push_frame(frame)
+        await self.push_frame(frame)
 
     async def _audio_in_task_handler(self):
         logger.info("Audio input task started")
@@ -337,7 +337,7 @@ class LiveKitInputTransport(BaseInputTransport):
                     audio_frame_event, participant_id = audio_data
                     pipecat_audio_frame = self._convert_livekit_audio_to_pipecat(audio_frame_event)
                     await self.push_audio_frame(pipecat_audio_frame)
-                    await self._internal_push_frame(
+                    await self.push_frame(
                         pipecat_audio_frame
                     )  # TODO: ensure audio frames are pushed with the default BaseInputTransport.push_audio_frame()
             except asyncio.CancelledError:

From cb49b6a0d678662cdc2483b2497e00fbf0af28bc Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Mon, 23 Sep 2024 23:39:05 -0700
Subject: [PATCH 066/135] rtvi: add llm-text and tts-text server messages

---
 src/pipecat/processors/frameworks/rtvi.py | 16 ++++++++++++++++
 1 file changed, 16 insertions(+)

diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py
index 820ea716c..7a35c5c06 100644
--- a/src/pipecat/processors/frameworks/rtvi.py
+++ b/src/pipecat/processors/frameworks/rtvi.py
@@ -242,6 +242,22 @@ class RTVILLMFunctionCallResultData(BaseModel):
     result: dict | str
 
 
+class RTVITextMessageData(BaseModel):
+    text: str
+
+
+class RTVILLMTextMessage(BaseModel):
+    label: Literal["rtvi-ai"] = "rtvi-ai"
+    type: Literal["llm-text"] = "llm-text"
+    data: RTVITextMessageData
+
+
+class RTVITTSTextMessage(BaseModel):
+    label: Literal["rtvi-ai"] = "rtvi-ai"
+    type: Literal["tts-text"] = "tts-text"
+    data: RTVITextMessageData
+
+
 class RTVITranscriptionMessageData(BaseModel):
     text: str
     user_id: str

From 08ac311971afb82fff28efa58af81814d9c052c0 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Tue, 24 Sep 2024 09:35:36 -0700
Subject: [PATCH 067/135] rtvi: use task to process incoming action frames

---
 src/pipecat/processors/frameworks/rtvi.py | 24 ++++++++++++++++++++---
 1 file changed, 21 insertions(+), 3 deletions(-)

diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py
index 7a35c5c06..bb23c9856 100644
--- a/src/pipecat/processors/frameworks/rtvi.py
+++ b/src/pipecat/processors/frameworks/rtvi.py
@@ -316,6 +316,11 @@ class RTVIProcessor(FrameProcessor):
         self._registered_actions: Dict[str, RTVIAction] = {}
         self._registered_services: Dict[str, RTVIService] = {}
 
+        # A task to process incoming action frames.
+        self._action_task = self.get_event_loop().create_task(self._action_task_handler())
+        self._action_queue = asyncio.Queue()
+
+        # A task to process incoming transport messages.
         self._message_task = self.get_event_loop().create_task(self._message_task_handler())
         self._message_queue = asyncio.Queue()
 
@@ -401,7 +406,7 @@ class RTVIProcessor(FrameProcessor):
         elif isinstance(frame, TransportMessageFrame):
             await self._message_queue.put(frame)
         elif isinstance(frame, RTVIActionFrame):
-            await self._handle_action(frame.message_id, frame.rtvi_action_run)
+            await self._action_queue.put(frame)
         # Other frames
         else:
             await self.push_frame(frame, direction)
@@ -415,12 +420,16 @@ class RTVIProcessor(FrameProcessor):
         await self._maybe_send_bot_ready()
 
     async def _stop(self, frame: EndFrame):
-        # We need to cancel the message task handler because that one is not
-        # processing EndFrames.
+        self._action_task.cancel()
+        await self._action_task
+
         self._message_task.cancel()
         await self._message_task
 
     async def _cancel(self, frame: CancelFrame):
+        self._action_task.cancel()
+        await self._action_task
+
         self._message_task.cancel()
         await self._message_task
 
@@ -471,6 +480,15 @@ class RTVIProcessor(FrameProcessor):
         if message:
             await self._push_transport_message(message)
 
+    async def _action_task_handler(self):
+        while True:
+            try:
+                frame = await self._action_queue.get()
+                await self._handle_action(frame.message_id, frame.rtvi_action_run)
+                self._action_queue.task_done()
+            except asyncio.CancelledError:
+                break
+
     async def _message_task_handler(self):
         while True:
             try:

From a483f1a083d7d97e932c680fa542c78926dba1a6 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Tue, 24 Sep 2024 10:48:15 -0700
Subject: [PATCH 068/135] rtvi: handle all actions from the action task

---
 src/pipecat/processors/frameworks/rtvi.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py
index bb23c9856..49095b2e4 100644
--- a/src/pipecat/processors/frameworks/rtvi.py
+++ b/src/pipecat/processors/frameworks/rtvi.py
@@ -521,7 +521,8 @@ class RTVIProcessor(FrameProcessor):
                     await self._handle_update_config(message.id, update_config)
                 case "action":
                     action = RTVIActionRun.model_validate(message.data)
-                    await self._handle_action(message.id, action)
+                    action_frame = RTVIActionFrame(message_id=message.id, rtvi_action_run=action)
+                    await self._action_queue.put(action_frame)
                 case "llm-function-call-result":
                     data = RTVILLMFunctionCallResultData.model_validate(message.data)
                     await self._handle_function_call_result(data)

From 31b5667cee272651478aebc13e5ca4f5ab1bd2c3 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Tue, 24 Sep 2024 13:10:40 -0700
Subject: [PATCH 069/135] frames: log text with [] so we can distinguish spaces
 better

---
 src/pipecat/frames/frames.py | 10 ++++------
 1 file changed, 4 insertions(+), 6 deletions(-)

diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py
index e4495098b..768e53e39 100644
--- a/src/pipecat/frames/frames.py
+++ b/src/pipecat/frames/frames.py
@@ -132,9 +132,7 @@ class VisionImageRawFrame(InputImageRawFrame):
 
     def __str__(self):
         pts = format_pts(self.pts)
-        return (
-            f"{self.name}(pts: {pts}, text: {self.text}, size: {self.size}, format: {self.format})"
-        )
+        return f"{self.name}(pts: {pts}, text: [{self.text}], size: {self.size}, format: {self.format})"
 
 
 @dataclass
@@ -177,7 +175,7 @@ class TextFrame(DataFrame):
 
     def __str__(self):
         pts = format_pts(self.pts)
-        return f"{self.name}(pts: {pts}, text: {self.text})"
+        return f"{self.name}(pts: {pts}, text: [{self.text}])"
 
 
 @dataclass
@@ -192,7 +190,7 @@ class TranscriptionFrame(TextFrame):
     language: Language | None = None
 
     def __str__(self):
-        return f"{self.name}(user: {self.user_id}, text: {self.text}, language: {self.language}, timestamp: {self.timestamp})"
+        return f"{self.name}(user: {self.user_id}, text: [{self.text}], language: {self.language}, timestamp: {self.timestamp})"
 
 
 @dataclass
@@ -205,7 +203,7 @@ class InterimTranscriptionFrame(TextFrame):
     language: Language | None = None
 
     def __str__(self):
-        return f"{self.name}(user: {self.user_id}, text: {self.text}, language: {self.language}, timestamp: {self.timestamp})"
+        return f"{self.name}(user: {self.user_id}, text: [{self.text}], language: {self.language}, timestamp: {self.timestamp})"
 
 
 @dataclass

From ee3786fe155a426843707d465b302f3419d569f5 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Tue, 24 Sep 2024 19:10:22 -0700
Subject: [PATCH 070/135] frames: add EndTaskFrame and CancelTaskFrame

---
 CHANGELOG.md                 |  4 ++++
 src/pipecat/frames/frames.py | 21 +++++++++++++++++++++
 src/pipecat/pipeline/task.py | 16 ++++++++++++++--
 3 files changed, 39 insertions(+), 2 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index c1d571da5..fb08aab2e 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,6 +9,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 
+- Added `EndTaskFrame` and `CancelTaskFrame`. These are new frames that are
+  meant to be pushed upstream to tell the pipeline task to stop nicely or
+  immediately respectively.
+
 - Added configurable LLM parameters (e.g., temperature, top_p, max_tokens, seed)
   for OpenAI, Anthropic, and Together AI services along with corresponding
   setter functions.
diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py
index 768e53e39..273aad214 100644
--- a/src/pipecat/frames/frames.py
+++ b/src/pipecat/frames/frames.py
@@ -339,6 +339,27 @@ class FatalErrorFrame(ErrorFrame):
     fatal: bool = field(default=True, init=False)
 
 
+@dataclass
+class EndTaskFrame(SystemFrame):
+    """This is used to notify the pipeline task that the pipeline should be
+    closed nicely (flushing all the queued frames) by pushing an EndFrame
+    downstream.
+
+    """
+
+    pass
+
+
+@dataclass
+class CancelTaskFrame(SystemFrame):
+    """This is used to notify the pipeline task that the pipeline should be
+    stopped immediately by pushing a CancelFrame downstream.
+
+    """
+
+    pass
+
+
 @dataclass
 class StopTaskFrame(SystemFrame):
     """Indicates that a pipeline task should be stopped but that the pipeline
diff --git a/src/pipecat/pipeline/task.py b/src/pipecat/pipeline/task.py
index 2b46c47c2..f79ff6f39 100644
--- a/src/pipecat/pipeline/task.py
+++ b/src/pipecat/pipeline/task.py
@@ -14,7 +14,9 @@ from pipecat.clocks.base_clock import BaseClock
 from pipecat.clocks.system_clock import SystemClock
 from pipecat.frames.frames import (
     CancelFrame,
+    CancelTaskFrame,
     EndFrame,
+    EndTaskFrame,
     ErrorFrame,
     Frame,
     MetricsFrame,
@@ -52,7 +54,13 @@ class Source(FrameProcessor):
                 await self.push_frame(frame, direction)
 
     async def _handle_upstream_frame(self, frame: Frame):
-        if isinstance(frame, ErrorFrame):
+        if isinstance(frame, EndTaskFrame):
+            # Tell the task we should end nicely.
+            await self._up_queue.put(EndTaskFrame())
+        elif isinstance(frame, CancelTaskFrame):
+            # Tell the task we should end right away.
+            await self._up_queue.put(CancelTaskFrame())
+        elif isinstance(frame, ErrorFrame):
             logger.error(f"Error running app: {frame}")
             if frame.fatal:
                 # Cancel all tasks downstream.
@@ -165,7 +173,11 @@ class PipelineTask:
         while True:
             try:
                 frame = await self._up_queue.get()
-                if isinstance(frame, StopTaskFrame):
+                if isinstance(frame, EndTaskFrame):
+                    await self.queue_frame(EndFrame())
+                elif isinstance(frame, CancelTaskFrame):
+                    await self.queue_frame(CancelFrame())
+                elif isinstance(frame, StopTaskFrame):
                     await self.queue_frame(StopTaskFrame())
                 self._up_queue.task_done()
             except asyncio.CancelledError:

From 1a3de0e8191a7529a474ec17f49b906d78c82623 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Tue, 24 Sep 2024 19:12:06 -0700
Subject: [PATCH 071/135] rtvi: add RTVIProcessor.handle_message()

---
 src/pipecat/processors/frameworks/rtvi.py | 20 ++++++++++++--------
 1 file changed, 12 insertions(+), 8 deletions(-)

diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py
index 49095b2e4..b75b65627 100644
--- a/src/pipecat/processors/frameworks/rtvi.py
+++ b/src/pipecat/processors/frameworks/rtvi.py
@@ -343,6 +343,9 @@ class RTVIProcessor(FrameProcessor):
             self._client_ready = True
             await self._maybe_send_bot_ready()
 
+    async def handle_message(self, message: RTVIMessage):
+        await self._message_queue.put(message)
+
     async def handle_function_call(
         self,
         function_name: str,
@@ -492,20 +495,21 @@ class RTVIProcessor(FrameProcessor):
     async def _message_task_handler(self):
         while True:
             try:
-                frame = await self._message_queue.get()
-                await self._handle_message(frame)
+                message = await self._message_queue.get()
+                await self._handle_message(message)
                 self._message_queue.task_done()
             except asyncio.CancelledError:
                 break
 
-    async def _handle_message(self, frame: TransportMessageFrame):
+    async def _handle_transport_message(self, frame: TransportMessageFrame):
         try:
             message = RTVIMessage.model_validate(frame.message)
+            await self._message_queue.put(message)
         except ValidationError as e:
-            await self.send_error(f"Invalid incoming message: {e}")
-            logger.warning(f"Invalid incoming  message: {e}")
-            return
+            await self.send_error(f"Invalid RTVI transport message: {e}")
+            logger.warning(f"Invalid RTVI transport message: {e}")
 
+    async def _handle_message(self, message: RTVIMessage):
         try:
             match message.type:
                 case "client-ready":
@@ -531,8 +535,8 @@ class RTVIProcessor(FrameProcessor):
                     await self._send_error_response(message.id, f"Unsupported type {message.type}")
 
         except ValidationError as e:
-            await self._send_error_response(message.id, f"Invalid incoming message: {e}")
-            logger.warning(f"Invalid incoming  message: {e}")
+            await self._send_error_response(message.id, f"Invalid message: {e}")
+            logger.warning(f"Invalid message: {e}")
         except Exception as e:
             await self._send_error_response(message.id, f"Exception processing message: {e}")
             logger.warning(f"Exception processing message: {e}")

From e276dcbab78907dac1df1e5ab1176da74255b4bb Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Tue, 24 Sep 2024 19:19:00 -0700
Subject: [PATCH 072/135] initialize task variables and add minor description

---
 src/pipecat/processors/frame_processor.py |  1 -
 src/pipecat/processors/frameworks/rtvi.py | 24 ++++++---
 src/pipecat/services/ai_services.py       |  1 +
 src/pipecat/transports/base_input.py      | 13 +++--
 src/pipecat/transports/base_output.py     | 59 +++++++++++++++++------
 src/pipecat/transports/services/daily.py  |  5 ++
 6 files changed, 76 insertions(+), 27 deletions(-)

diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py
index 1bf42311d..b56846aa6 100644
--- a/src/pipecat/processors/frame_processor.py
+++ b/src/pipecat/processors/frame_processor.py
@@ -5,7 +5,6 @@
 #
 
 import asyncio
-import time
 
 from enum import Enum
 
diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py
index 49095b2e4..994be3fad 100644
--- a/src/pipecat/processors/frameworks/rtvi.py
+++ b/src/pipecat/processors/frameworks/rtvi.py
@@ -420,18 +420,26 @@ class RTVIProcessor(FrameProcessor):
         await self._maybe_send_bot_ready()
 
     async def _stop(self, frame: EndFrame):
-        self._action_task.cancel()
-        await self._action_task
+        if self._action_task:
+            self._action_task.cancel()
+            await self._action_task
+            self._action_task = None
 
-        self._message_task.cancel()
-        await self._message_task
+        if self._message_task:
+            self._message_task.cancel()
+            await self._message_task
+            self._message_task = None
 
     async def _cancel(self, frame: CancelFrame):
-        self._action_task.cancel()
-        await self._action_task
+        if self._action_task:
+            self._action_task.cancel()
+            await self._action_task
+            self._action_task = None
 
-        self._message_task.cancel()
-        await self._message_task
+        if self._message_task:
+            self._message_task.cancel()
+            await self._message_task
+            self._message_task = None
 
     async def _push_transport_message(self, model: BaseModel, exclude_none: bool = True):
         frame = TransportMessageFrame(
diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index cdad3de52..197067adc 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -350,6 +350,7 @@ class AsyncWordTTSService(AsyncTTSService):
         if self._words_task:
             self._words_task.cancel()
             await self._words_task
+            self._words_task = None
 
     async def _words_task_handler(self):
         while True:
diff --git a/src/pipecat/transports/base_input.py b/src/pipecat/transports/base_input.py
index 73ad3f5e3..df7babff1 100644
--- a/src/pipecat/transports/base_input.py
+++ b/src/pipecat/transports/base_input.py
@@ -37,6 +37,10 @@ class BaseInputTransport(FrameProcessor):
 
         self._executor = ThreadPoolExecutor(max_workers=5)
 
+        # Task to process incoming audio (VAD) and push audio frames downstream
+        # if passthrough is enabled.
+        self._audio_task = None
+
     async def start(self, frame: StartFrame):
         # Create audio input queue and task if needed.
         if self._params.audio_in_enabled or self._params.vad_enabled:
@@ -45,16 +49,17 @@ class BaseInputTransport(FrameProcessor):
 
     async def stop(self, frame: EndFrame):
         # Cancel and wait for the audio input task to finish.
-        if self._params.audio_in_enabled or self._params.vad_enabled:
+        if self._audio_task and (self._params.audio_in_enabled or self._params.vad_enabled):
             self._audio_task.cancel()
             await self._audio_task
+            self._audio_task = None
 
     async def cancel(self, frame: CancelFrame):
-        # Cancel all the tasks and wait for them to finish.
-
-        if self._params.audio_in_enabled or self._params.vad_enabled:
+        # Cancel and wait for the audio input task to finish.
+        if self._audio_task and (self._params.audio_in_enabled or self._params.vad_enabled):
             self._audio_task.cancel()
             await self._audio_task
+            self._audio_task = None
 
     def vad_analyzer(self) -> VADAnalyzer | None:
         return self._params.vad_analyzer
diff --git a/src/pipecat/transports/base_output.py b/src/pipecat/transports/base_output.py
index 5423b122f..941a3505a 100644
--- a/src/pipecat/transports/base_output.py
+++ b/src/pipecat/transports/base_output.py
@@ -47,6 +47,18 @@ class BaseOutputTransport(FrameProcessor):
 
         self._params = params
 
+        # Task to process incoming frames so we don't block upstream elements.
+        self._sink_task = None
+
+        # Task to process incoming frames using a clock.
+        self._sink_clock_task = None
+
+        # Task to write/send audio frames.
+        self._audio_out_task = None
+
+        # Task to write/send image frames.
+        self._camera_out_task = None
+
         # These are the images that we should send to the camera at our desired
         # framerate.
         self._camera_images = None
@@ -88,36 +100,53 @@ class BaseOutputTransport(FrameProcessor):
         # that EndFrame to be processed by the sink tasks. We also need to wait
         # for these tasks before cancelling the camera and audio tasks below
         # because they might be still rendering.
-        await self._sink_task
-        await self._sink_clock_task
+        if self._sink_task:
+            await self._sink_task
+        if self._sink_clock_task:
+            await self._sink_clock_task
 
         # Cancel and wait for the camera output task to finish.
-        if self._params.camera_out_enabled:
+        if self._camera_out_task and self._params.camera_out_enabled:
             self._camera_out_task.cancel()
             await self._camera_out_task
+            self._camera_out_task = None
 
         # Cancel and wait for the audio output task to finish.
-        if self._params.audio_out_enabled and self._params.audio_out_is_live:
+        if (
+            self._audio_out_task
+            and self._params.audio_out_enabled
+            and self._params.audio_out_is_live
+        ):
             self._audio_out_task.cancel()
             await self._audio_out_task
+            self._audio_out_task = None
 
     async def cancel(self, frame: CancelFrame):
         # Since we are cancelling everything it doesn't matter if we cancel sink
         # tasks first or not.
-        self._sink_task.cancel()
-        self._sink_clock_task.cancel()
-        await self._sink_task
-        await self._sink_clock_task
+        if self._sink_task:
+            self._sink_task.cancel()
+            await self._sink_task
+            self._sink_task = None
+
+        if self._sink_clock_task:
+            self._sink_clock_task.cancel()
+            await self._sink_clock_task
+            self._sink_clock_task = None
 
         # Cancel and wait for the camera output task to finish.
-        if self._params.camera_out_enabled:
+        if self._camera_out_task and self._params.camera_out_enabled:
             self._camera_out_task.cancel()
             await self._camera_out_task
+            self._camera_out_task = None
 
         # Cancel and wait for the audio output task to finish.
-        if self._params.audio_out_enabled and self._params.audio_out_is_live:
+        if self._audio_out_task and (
+            self._params.audio_out_enabled and self._params.audio_out_is_live
+        ):
             self._audio_out_task.cancel()
             await self._audio_out_task
+            self._audio_out_task = None
 
     async def send_message(self, frame: TransportMessageFrame):
         pass
@@ -183,11 +212,13 @@ class BaseOutputTransport(FrameProcessor):
 
         if isinstance(frame, StartInterruptionFrame):
             # Stop sink tasks.
-            self._sink_task.cancel()
-            await self._sink_task
+            if self._sink_task:
+                self._sink_task.cancel()
+                await self._sink_task
             # Stop sink clock tasks.
-            self._sink_clock_task.cancel()
-            await self._sink_clock_task
+            if self._sink_clock_task:
+                self._sink_clock_task.cancel()
+                await self._sink_clock_task
             # Create sink tasks.
             self._create_sink_tasks()
             # Let's send a bot stopped speaking if we have to.
diff --git a/src/pipecat/transports/services/daily.py b/src/pipecat/transports/services/daily.py
index 48b59d8ff..50c2ae085 100644
--- a/src/pipecat/transports/services/daily.py
+++ b/src/pipecat/transports/services/daily.py
@@ -575,6 +575,9 @@ class DailyInputTransport(BaseInputTransport):
         self._client = client
 
         self._video_renderers = {}
+
+        # Task that gets audio data from a device or the network and queues it
+        # internally to be processed.
         self._audio_in_task = None
 
         self._vad_analyzer: VADAnalyzer | None = params.vad_analyzer
@@ -603,6 +606,7 @@ class DailyInputTransport(BaseInputTransport):
         if self._audio_in_task and (self._params.audio_in_enabled or self._params.vad_enabled):
             self._audio_in_task.cancel()
             await self._audio_in_task
+            self._audio_in_task = None
 
     async def cancel(self, frame: CancelFrame):
         # Parent stop.
@@ -613,6 +617,7 @@ class DailyInputTransport(BaseInputTransport):
         if self._audio_in_task and (self._params.audio_in_enabled or self._params.vad_enabled):
             self._audio_in_task.cancel()
             await self._audio_in_task
+            self._audio_in_task = None
 
     async def cleanup(self):
         await super().cleanup()

From 9461bacf0d6793661b20d7cc5367ad083188a433 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Tue, 24 Sep 2024 19:24:37 -0700
Subject: [PATCH 073/135] pyproject: update fastapi to 0.115.0

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index aebccda2f..46345ed71 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -56,7 +56,7 @@ openpipe = [ "openpipe~=4.24.0" ]
 playht = [ "pyht~=0.0.28" ]
 silero = [ "onnxruntime>=1.16.1" ]
 together = [ "together~=1.2.7" ]
-websocket = [ "websockets~=12.0", "fastapi~=0.112.1" ]
+websocket = [ "websockets~=12.0", "fastapi~=0.115.0" ]
 whisper = [ "faster-whisper~=1.0.3" ]
 xtts = [ "resampy~=0.4.3" ]
 

From b8713666c23d19989abdfd6512838e0cefd2df0f Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Tue, 24 Sep 2024 19:35:05 -0700
Subject: [PATCH 074/135] processors: add AsyncGeneratorProcessor

---
 CHANGELOG.md                              |  4 +++
 src/pipecat/processors/async_generator.py | 42 +++++++++++++++++++++++
 2 files changed, 46 insertions(+)
 create mode 100644 src/pipecat/processors/async_generator.py

diff --git a/CHANGELOG.md b/CHANGELOG.md
index fb08aab2e..6c4bf3c92 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,6 +9,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 
+- Added `AsyncGeneratorProcessor`. This processor can be used together with a
+  `FrameSerializer` as an async generator. It provides a `generator()` function
+  that returns an `AsyncGenerator` and that yields serialized frames.
+
 - Added `EndTaskFrame` and `CancelTaskFrame`. These are new frames that are
   meant to be pushed upstream to tell the pipeline task to stop nicely or
   immediately respectively.
diff --git a/src/pipecat/processors/async_generator.py b/src/pipecat/processors/async_generator.py
new file mode 100644
index 000000000..66b2a3e99
--- /dev/null
+++ b/src/pipecat/processors/async_generator.py
@@ -0,0 +1,42 @@
+#
+# Copyright (c) 2024, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+
+from typing import Any, AsyncGenerator
+
+from pipecat.frames.frames import (
+    CancelFrame,
+    EndFrame,
+    Frame,
+)
+from pipecat.processors.frame_processor import FrameProcessor, FrameDirection
+from pipecat.serializers.base_serializer import FrameSerializer
+
+
+class AsyncGeneratorProcessor(FrameProcessor):
+    def __init__(self, *, serializer: FrameSerializer, **kwargs):
+        super().__init__(**kwargs)
+        self._serializer = serializer
+        self._data_queue = asyncio.Queue()
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        if isinstance(frame, (CancelFrame, EndFrame)):
+            await self._data_queue.put(None)
+        else:
+            data = self._serializer.serialize(frame)
+            if data:
+                await self._data_queue.put(data)
+
+    async def generator(self) -> AsyncGenerator[Any, None]:
+        running = True
+        while running:
+            data = await self._data_queue.get()
+            running = data is not None
+            if data:
+                yield data

From 3621fceae2555ca24fac993086b19241740f780a Mon Sep 17 00:00:00 2001
From: Kwindla Hultman Kramer <kwindla@gmail.com>
Date: Wed, 25 Sep 2024 09:19:28 -0700
Subject: [PATCH 075/135] fixes as noted by aleix

---
 src/pipecat/services/ai_services.py | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index 197067adc..b32eb708d 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -259,6 +259,10 @@ class AsyncTTSService(TTSService):
     async def flush_audio(self):
         pass
 
+    async def say(self, text: str):
+        await super.say(text)
+        await self.flush_audio()
+
     async def start(self, frame: StartFrame):
         await super().start(frame)
         if self._push_stop_frames:
@@ -278,6 +282,11 @@ class AsyncTTSService(TTSService):
             await self._stop_frame_task
             self._stop_frame_task = None
 
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        super().process_frame(frame, direction)
+        if isinstance(frame, TTSSpeakFrame):
+            await self.flush_audio()
+
     async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM):
         await super().push_frame(frame, direction)
 

From 3d43ad0f4dcb9570202516dd0095a26226853aca Mon Sep 17 00:00:00 2001
From: Kwindla Hultman Kramer <kwindla@gmail.com>
Date: Wed, 25 Sep 2024 10:59:00 -0700
Subject: [PATCH 076/135] actually save the file

---
 src/pipecat/services/ai_services.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index b32eb708d..21ef8dfca 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -283,7 +283,7 @@ class AsyncTTSService(TTSService):
             self._stop_frame_task = None
 
     async def process_frame(self, frame: Frame, direction: FrameDirection):
-        super().process_frame(frame, direction)
+        await super().process_frame(frame, direction)
         if isinstance(frame, TTSSpeakFrame):
             await self.flush_audio()
 

From 447baad5c315a697fafb74e881851b97dc61efa4 Mon Sep 17 00:00:00 2001
From: joachimchauvet <joachim@generativestudio.dev>
Date: Wed, 25 Sep 2024 21:38:55 +0300
Subject: [PATCH 077/135] update send_metrics() to support changes introduced
 in #474

---
 src/pipecat/transports/services/livekit.py | 35 +++++++++++++++-------
 1 file changed, 25 insertions(+), 10 deletions(-)

diff --git a/src/pipecat/transports/services/livekit.py b/src/pipecat/transports/services/livekit.py
index d6f00c3ef..52bbbf89d 100644
--- a/src/pipecat/transports/services/livekit.py
+++ b/src/pipecat/transports/services/livekit.py
@@ -16,6 +16,12 @@ from pipecat.frames.frames import (
     StartFrame,
     TransportMessageFrame,
 )
+from pipecat.metrics.metrics import (
+    LLMUsageMetricsData,
+    ProcessingMetricsData,
+    TTFBMetricsData,
+    TTSUsageMetricsData,
+)
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.transports.base_input import BaseInputTransport
 from pipecat.transports.base_output import BaseOutputTransport
@@ -257,9 +263,9 @@ class LiveKitTransportClient:
     async def _async_on_connected(self):
         await self._callbacks.on_connected()
 
-    async def _async_on_disconnected(self):
+    async def _async_on_disconnected(self, reason=None):
         self._connected = False
-        logger.info(f"Disconnected from {self._room_name}")
+        logger.info(f"Disconnected from {self._room_name}. Reason: {reason}")
         await self._callbacks.on_disconnected()
 
     async def _process_audio_stream(self, audio_stream: rtc.AudioStream, participant_id: str):
@@ -413,14 +419,23 @@ class LiveKitOutputTransport(BaseOutputTransport):
 
     async def send_metrics(self, frame: MetricsFrame):
         metrics = {}
-        if frame.ttfb:
-            metrics["ttfb"] = frame.ttfb
-        if frame.processing:
-            metrics["processing"] = frame.processing
-        if hasattr(frame, "tokens"):
-            metrics["tokens"] = frame.tokens
-        if hasattr(frame, "characters"):
-            metrics["characters"] = frame.characters
+        for d in frame.data:
+            if isinstance(d, TTFBMetricsData):
+                if "ttfb" not in metrics:
+                    metrics["ttfb"] = []
+                metrics["ttfb"].append(d.model_dump())
+            elif isinstance(d, ProcessingMetricsData):
+                if "processing" not in metrics:
+                    metrics["processing"] = []
+                metrics["processing"].append(d.model_dump())
+            elif isinstance(d, LLMUsageMetricsData):
+                if "tokens" not in metrics:
+                    metrics["tokens"] = []
+                metrics["tokens"].append(d.value.model_dump(exclude_none=True))
+            elif isinstance(d, TTSUsageMetricsData):
+                if "characters" not in metrics:
+                    metrics["characters"] = []
+                metrics["characters"].append(d.model_dump())
 
         message = LiveKitTransportMessageFrame(
             message={"type": "pipecat-metrics", "metrics": metrics}

From c4e94e280eca9e6a2fcbfacae2bcba8b3448f57d Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Wed, 25 Sep 2024 16:35:33 -0700
Subject: [PATCH 078/135] processors: add support for event handlers

---
 CHANGELOG.md                              | 10 ++++++++
 src/pipecat/processors/frame_processor.py | 30 +++++++++++++++++++++++
 2 files changed, 40 insertions(+)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 6c4bf3c92..f35978dcd 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,6 +9,16 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 
+- All `FrameProcessors` can now register event handlers.
+
+```
+tts = SomeTTSService(...)
+
+@tts.event_handler("on_connected"):
+async def on_connected(processor):
+  ...
+```
+
 - Added `AsyncGeneratorProcessor`. This processor can be used together with a
   `FrameSerializer` as an async generator. It provides a `generator()` function
   that returns an `AsyncGenerator` and that yields serialized frames.
diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py
index b56846aa6..f71e066d7 100644
--- a/src/pipecat/processors/frame_processor.py
+++ b/src/pipecat/processors/frame_processor.py
@@ -5,6 +5,7 @@
 #
 
 import asyncio
+import inspect
 
 from enum import Enum
 
@@ -48,6 +49,8 @@ class FrameProcessor:
         self._loop: asyncio.AbstractEventLoop = loop or asyncio.get_running_loop()
         self._sync = sync
 
+        self._event_handlers: dict = {}
+
         # Clock
         self._clock: BaseClock | None = None
 
@@ -169,6 +172,23 @@ class FrameProcessor:
         else:
             await self.__push_queue.put((frame, direction))
 
+    def event_handler(self, event_name: str):
+        def decorator(handler):
+            self.add_event_handler(event_name, handler)
+            return handler
+
+        return decorator
+
+    def add_event_handler(self, event_name: str, handler):
+        if event_name not in self._event_handlers:
+            raise Exception(f"Event handler {event_name} not registered")
+        self._event_handlers[event_name].append(handler)
+
+    def _register_event_handler(self, event_name: str):
+        if event_name in self._event_handlers:
+            raise Exception(f"Event handler {event_name} already registered")
+        self._event_handlers[event_name] = []
+
     #
     # Handle interruptions
     #
@@ -212,5 +232,15 @@ class FrameProcessor:
             except asyncio.CancelledError:
                 break
 
+    async def _call_event_handler(self, event_name: str, *args, **kwargs):
+        try:
+            for handler in self._event_handlers[event_name]:
+                if inspect.iscoroutinefunction(handler):
+                    await handler(self, *args, **kwargs)
+                else:
+                    handler(self, *args, **kwargs)
+        except Exception as e:
+            logger.exception(f"Exception in event handler {event_name}: {e}")
+
     def __str__(self):
         return self.name

From f06aa300d01b202f018265c3e880f147566b302c Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Wed, 25 Sep 2024 16:35:49 -0700
Subject: [PATCH 079/135] rtvi: add on_bot_ready event

---
 src/pipecat/processors/frameworks/rtvi.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py
index 1458cc21d..930b2331d 100644
--- a/src/pipecat/processors/frameworks/rtvi.py
+++ b/src/pipecat/processors/frameworks/rtvi.py
@@ -324,6 +324,8 @@ class RTVIProcessor(FrameProcessor):
         self._message_task = self.get_event_loop().create_task(self._message_task_handler())
         self._message_queue = asyncio.Queue()
 
+        self._register_event_handler("on_bot_ready")
+
     def register_action(self, action: RTVIAction):
         id = self._action_id(action.service, action.action)
         self._registered_actions[id] = action
@@ -624,8 +626,9 @@ class RTVIProcessor(FrameProcessor):
 
     async def _maybe_send_bot_ready(self):
         if self._pipeline_started and self._client_ready:
-            await self._send_bot_ready()
             await self._update_config(self._config, False)
+            await self._send_bot_ready()
+            await self._call_event_handler("on_bot_ready")
 
     async def _send_bot_ready(self):
         if not self._params.send_bot_ready:

From 73da8c1910fc7ae37f3f1ac6bf8c50d89aabd927 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Wed, 25 Sep 2024 22:40:36 -0400
Subject: [PATCH 080/135] Improve usability of Deepgram TTS: use Deepgram
 client, remove aiohttp

---
 .../07c-interruptible-deepgram.py             | 16 ++--
 src/pipecat/services/deepgram.py              | 79 +++++++++----------
 2 files changed, 44 insertions(+), 51 deletions(-)

diff --git a/examples/foundational/07c-interruptible-deepgram.py b/examples/foundational/07c-interruptible-deepgram.py
index 41bef8a47..fc33c246f 100644
--- a/examples/foundational/07c-interruptible-deepgram.py
+++ b/examples/foundational/07c-interruptible-deepgram.py
@@ -5,10 +5,14 @@
 #
 
 import asyncio
-import aiohttp
 import os
 import sys
 
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+from runner import configure
+
 from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
@@ -22,12 +26,6 @@ from pipecat.services.openai import OpenAILLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 from pipecat.vad.silero import SileroVADAnalyzer
 
-from runner import configure
-
-from loguru import logger
-
-from dotenv import load_dotenv
-
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -52,9 +50,7 @@ async def main():
 
         stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
 
-        tts = DeepgramTTSService(
-            aiohttp_session=session, api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-helios-en"
-        )
+        tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-helios-en")
 
         llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
diff --git a/src/pipecat/services/deepgram.py b/src/pipecat/services/deepgram.py
index 914bc2ec2..6929e66e5 100644
--- a/src/pipecat/services/deepgram.py
+++ b/src/pipecat/services/deepgram.py
@@ -4,10 +4,11 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-import aiohttp
-
+import asyncio
 from typing import AsyncGenerator
 
+from loguru import logger
+
 from pipecat.frames.frames import (
     CancelFrame,
     EndFrame,
@@ -15,27 +16,25 @@ from pipecat.frames.frames import (
     Frame,
     InterimTranscriptionFrame,
     StartFrame,
+    TranscriptionFrame,
     TTSAudioRawFrame,
     TTSStartedFrame,
     TTSStoppedFrame,
-    TranscriptionFrame,
 )
 from pipecat.services.ai_services import STTService, TTSService
 from pipecat.transcriptions.language import Language
 from pipecat.utils.time import time_now_iso8601
 
-from loguru import logger
-
-
 # See .env.example for Deepgram configuration needed
 try:
     from deepgram import (
         AsyncListenWebSocketClient,
         DeepgramClient,
         DeepgramClientOptions,
-        LiveTranscriptionEvents,
         LiveOptions,
         LiveResultResponse,
+        LiveTranscriptionEvents,
+        SpeakOptions,
     )
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
@@ -50,9 +49,7 @@ class DeepgramTTSService(TTSService):
         self,
         *,
         api_key: str,
-        aiohttp_session: aiohttp.ClientSession,
         voice: str = "aura-helios-en",
-        base_url: str = "https://api.deepgram.com/v1/speak",
         sample_rate: int = 16000,
         encoding: str = "linear16",
         **kwargs,
@@ -60,11 +57,9 @@ class DeepgramTTSService(TTSService):
         super().__init__(**kwargs)
 
         self._voice = voice
-        self._api_key = api_key
-        self._base_url = base_url
         self._sample_rate = sample_rate
         self._encoding = encoding
-        self._aiohttp_session = aiohttp_session
+        self._deepgram_client = DeepgramClient(api_key=api_key)
 
     def can_generate_metrics(self) -> bool:
         return True
@@ -76,43 +71,45 @@ class DeepgramTTSService(TTSService):
     async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
         logger.debug(f"Generating TTS: [{text}]")
 
-        base_url = self._base_url
-        request_url = f"{base_url}?model={self._voice}&encoding={self._encoding}&container=none&sample_rate={self._sample_rate}"
-        headers = {"authorization": f"token {self._api_key}"}
-        body = {"text": text}
+        options = SpeakOptions(
+            model=self._voice,
+            encoding=self._encoding,
+            sample_rate=self._sample_rate,
+            container="none",
+        )
 
         try:
             await self.start_ttfb_metrics()
-            async with self._aiohttp_session.post(request_url, headers=headers, json=body) as r:
-                if r.status != 200:
-                    response_text = await r.text()
-                    # If we get a a "Bad Request: Input is unutterable", just print out a debug log.
-                    # All other unsuccesful requests should emit an error frame. If not specifically
-                    # handled by the running PipelineTask, the ErrorFrame will cancel the task.
-                    if "unutterable" in response_text:
-                        logger.debug(f"Unutterable text: [{text}]")
-                        return
 
-                    logger.error(
-                        f"{self} error getting audio (status: {r.status}, error: {response_text})"
-                    )
-                    yield ErrorFrame(
-                        f"Error getting audio (status: {r.status}, error: {response_text})"
-                    )
-                    return
+            response = await asyncio.to_thread(
+                self._deepgram_client.speak.v("1").stream, {"text": text}, options
+            )
 
-                await self.start_tts_usage_metrics(text)
+            await self.start_tts_usage_metrics(text)
+            await self.push_frame(TTSStartedFrame())
+
+            # The response.stream_memory is already a BytesIO object
+            audio_buffer = response.stream_memory
+
+            if audio_buffer is None:
+                raise ValueError("No audio data received from Deepgram")
+
+            # Read and yield the audio data in chunks
+            audio_buffer.seek(0)  # Ensure we're at the start of the buffer
+            chunk_size = 8192  # Use a fixed buffer size
+            while True:
+                await self.stop_ttfb_metrics()
+                chunk = audio_buffer.read(chunk_size)
+                if not chunk:
+                    break
+                frame = TTSAudioRawFrame(audio=chunk, sample_rate=self._sample_rate, num_channels=1)
+                yield frame
+
+            await self.push_frame(TTSStoppedFrame())
 
-                await self.push_frame(TTSStartedFrame())
-                async for data in r.content:
-                    await self.stop_ttfb_metrics()
-                    frame = TTSAudioRawFrame(
-                        audio=data, sample_rate=self._sample_rate, num_channels=1
-                    )
-                    yield frame
-                await self.push_frame(TTSStoppedFrame())
         except Exception as e:
             logger.exception(f"{self} exception: {e}")
+            yield ErrorFrame(f"Error getting audio: {str(e)}")
 
 
 class DeepgramSTTService(STTService):

From d05717a1bd709ecbf475bb2ff410763bcd8783cd Mon Sep 17 00:00:00 2001
From: Jin Kim <golbin@gmail.com>
Date: Thu, 26 Sep 2024 19:52:25 +0900
Subject: [PATCH 081/135] Apply Ruff formater

---
 src/pipecat/services/cartesia.py | 41 ++++++++++++++++----------------
 1 file changed, 21 insertions(+), 20 deletions(-)

diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index f08c06dea..c1c296046 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -71,15 +71,16 @@ class CartesiaTTSService(AsyncWordTTSService):
         emotion: Optional[List[str]] = []
 
     def __init__(
-            self,
-            *,
-            api_key: str,
-            voice_id: str,
-            cartesia_version: str = "2024-06-10",
-            url: str = "wss://api.cartesia.ai/tts/websocket",
-            model_id: str = "sonic-english",
-            params: InputParams = InputParams(),
-            **kwargs):
+        self,
+        *,
+        api_key: str,
+        voice_id: str,
+        cartesia_version: str = "2024-06-10",
+        url: str = "wss://api.cartesia.ai/tts/websocket",
+        model_id: str = "sonic-english",
+        params: InputParams = InputParams(),
+        **kwargs,
+    ):
         # Aggregating sentences still gives cleaner-sounding results and fewer
         # artifacts than streaming one word at a time. On average, waiting for a
         # full sentence should only "cost" us 15ms or so with GPT-4o or a Llama
@@ -91,7 +92,10 @@ class CartesiaTTSService(AsyncWordTTSService):
         # can use those to generate text frames ourselves aligned with the
         # playout timing of the audio!
         super().__init__(
-            aggregate_sentences=True, push_text_frames=False, sample_rate=params.sample_rate, **kwargs
+            aggregate_sentences=True,
+            push_text_frames=False,
+            sample_rate=params.sample_rate,
+            **kwargs,
         )
 
         self._api_key = api_key
@@ -137,11 +141,10 @@ class CartesiaTTSService(AsyncWordTTSService):
         logger.debug(f"Switching TTS language to: [{language}]")
         self._language = language_to_cartesia_language(language)
 
-    def _build_msg(self, text: str = "", continue_transcript: bool = True, add_timestamps: bool = True):
-        voice_config = {
-            "mode": "id",
-            "id": self._voice_id
-        }
+    def _build_msg(
+        self, text: str = "", continue_transcript: bool = True, add_timestamps: bool = True
+    ):
+        voice_config = {"mode": "id", "id": self._voice_id}
 
         if self._speed or self._emotion:
             voice_config["__experimental_controls"] = {}
@@ -236,8 +239,7 @@ class CartesiaTTSService(AsyncWordTTSService):
                     await self.add_word_timestamps([("LLMFullResponseEndFrame", 0)])
                 elif msg["type"] == "timestamps":
                     await self.add_word_timestamps(
-                        list(zip(msg["word_timestamps"]["words"],
-                             msg["word_timestamps"]["start"]))
+                        list(zip(msg["word_timestamps"]["words"], msg["word_timestamps"]["start"]))
                     )
                 elif msg["type"] == "chunk":
                     await self.stop_ttfb_metrics()
@@ -254,8 +256,7 @@ class CartesiaTTSService(AsyncWordTTSService):
                     await self.stop_all_metrics()
                     await self.push_error(ErrorFrame(f'{self} error: {msg["error"]}'))
                 else:
-                    logger.error(
-                        f"Cartesia error, unknown message type: {msg}")
+                    logger.error(f"Cartesia error, unknown message type: {msg}")
         except asyncio.CancelledError:
             pass
         except Exception as e:
@@ -379,7 +380,7 @@ class CartesiaHttpTTSService(TTSService):
                 output_format=self._output_format,
                 language=self._language,
                 stream=False,
-                _experimental_voice_controls=voice_controls
+                _experimental_voice_controls=voice_controls,
             )
 
             await self.stop_ttfb_metrics()

From f5e0b946c74695549f26135c8b92546fff22270d Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Thu, 26 Sep 2024 09:08:37 -0700
Subject: [PATCH 082/135] services(cartesia): fix string formatting

---
 src/pipecat/services/cartesia.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index c1c296046..e38d56db3 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -180,8 +180,7 @@ class CartesiaTTSService(AsyncWordTTSService):
     async def _connect(self):
         try:
             self._websocket = await websockets.connect(
-                f"{self._url}?api_key={self._api_key}&cartesia_version={
-                    self._cartesia_version}"
+                f"{self._url}?api_key={self._api_key}&cartesia_version={self._cartesia_version}"
             )
             self._receive_task = self.get_event_loop().create_task(self._receive_task_handler())
         except Exception as e:

From c7c709a0a79a27c542761c23f06606ec6d3dc0dd Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Thu, 26 Sep 2024 10:31:53 -0700
Subject: [PATCH 083/135] github: cache venv when running tests

---
 .github/workflows/tests.yaml | 7 +++++++
 1 file changed, 7 insertions(+)

diff --git a/.github/workflows/tests.yaml b/.github/workflows/tests.yaml
index ce3e13494..b806efad4 100644
--- a/.github/workflows/tests.yaml
+++ b/.github/workflows/tests.yaml
@@ -27,6 +27,13 @@ jobs:
         uses: actions/setup-python@v4
         with:
           python-version: "3.10"
+      - name: Cache virtual environment
+        uses: actions/cache@v3
+        with:
+          # We are hashing dev-requirements.txt and test-requirements.txt which
+          # contain all dependencies needed to run the tests.
+          key: venv-${{ runner.os }}-${{ steps.setup_python.outputs.python-version}}-${{ hashFiles('dev-requirements.txt') }}-${{ hashFiles('test-requirements.txt') }}
+          path: .venv
       - name: Install system packages
         id: install_system_packages
         run: |

From 6a6ea251aec1f32425d9a5fb0031119feaaceed5 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Thu, 26 Sep 2024 09:31:09 -0400
Subject: [PATCH 084/135] Add AWS Polly TTS support

---
 README.md                                     |   4 +-
 dot-env.template                              |   5 +
 .../foundational/07m-interruptible-aws.py     |  98 ++++++++++++
 pyproject.toml                                |   1 +
 src/pipecat/services/aws.py                   | 146 ++++++++++++++++++
 test-requirements.txt                         |   1 +
 6 files changed, 252 insertions(+), 3 deletions(-)
 create mode 100644 examples/foundational/07m-interruptible-aws.py
 create mode 100644 src/pipecat/services/aws.py

diff --git a/README.md b/README.md
index faf0137dc..793d1f630 100644
--- a/README.md
+++ b/README.md
@@ -38,7 +38,7 @@ pip install "pipecat-ai[option,...]"
 
 Your project may or may not need these, so they're made available as optional requirements. Here is a list:
 
-- **AI services**: `anthropic`, `azure`, `deepgram`, `gladia`, `google`, `fal`, `lmnt`, `moondream`, `openai`, `openpipe`, `playht`, `silero`, `whisper`, `xtts`
+- **AI services**: `anthropic`, `aws`, `azure`, `deepgram`, `gladia`, `google`, `fal`, `lmnt`, `moondream`, `openai`, `openpipe`, `playht`, `silero`, `whisper`, `xtts`
 - **Transports**: `local`, `websocket`, `daily`
 
 ## Code examples
@@ -110,7 +110,6 @@ python app.py
 
 Daily provides a prebuilt WebRTC user interface. Whilst the app is running, you can visit at `https://<yourdomain>.daily.co/<room_url>` and listen to the bot say hello!
 
-
 ## WebRTC for production use
 
 WebSockets are fine for server-to-server communication or for initial development. But for production use, you’ll need client-server audio to use a protocol designed for real-time media transport. (For an explanation of the difference between WebSockets and WebRTC, see [this post.](https://www.daily.co/blog/how-to-talk-to-an-llm-with-your-voice/#webrtc))
@@ -131,7 +130,6 @@ pip install pipecat-ai[silero]
 
 The first time your run your bot with Silero, startup may take a while whilst it downloads and caches the model in the background. You can check the progress of this in the console.
 
-
 ## Hacking on the framework itself
 
 _Note that you may need to set up a virtual environment before following the instructions below. For instance, you might need to run the following from the root of the repo:_
diff --git a/dot-env.template b/dot-env.template
index 085e8b19d..e940b1076 100644
--- a/dot-env.template
+++ b/dot-env.template
@@ -1,6 +1,11 @@
 # Anthropic
 ANTHROPIC_API_KEY=...
 
+# AWS
+AWS_SECRET_ACCESS_KEY=...
+AWS_ACCESS_KEY_ID=...
+AWS_REGION=...
+
 # Azure
 AZURE_SPEECH_REGION=...
 AZURE_SPEECH_API_KEY=...
diff --git a/examples/foundational/07m-interruptible-aws.py b/examples/foundational/07m-interruptible-aws.py
new file mode 100644
index 000000000..891ffd381
--- /dev/null
+++ b/examples/foundational/07m-interruptible-aws.py
@@ -0,0 +1,98 @@
+#
+# Copyright (c) 2024, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import os
+import sys
+
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+from runner import configure
+
+from pipecat.frames.frames import LLMMessagesFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.llm_response import (
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
+)
+from pipecat.services.aws import AWSTTSService
+from pipecat.services.openai import OpenAILLMService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+from pipecat.vad.silero import SileroVADAnalyzer
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, token) = await configure(session)
+
+        transport = DailyTransport(
+            room_url,
+            token,
+            "Respond bot",
+            DailyParams(
+                audio_out_enabled=True,
+                audio_out_sample_rate=16000,
+                transcription_enabled=True,
+                vad_enabled=True,
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
+        )
+
+        tts = AWSTTSService(
+            api_key=os.getenv("AWS_SECRET_ACCESS_KEY"),
+            aws_access_key_id=os.getenv("AWS_ACCESS_KEY_ID"),
+            region=os.getenv("AWS_REGION"),
+            voice_id="Amy",
+            params=AWSTTSService.InputParams(engine="neural", language="en-GB", rate="1.05"),
+        )
+
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
+
+        messages = [
+            {
+                "role": "system",
+                "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+            },
+        ]
+
+        tma_in = LLMUserResponseAggregator(messages)
+        tma_out = LLMAssistantResponseAggregator(messages)
+
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                tma_in,  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                tma_out,  # Assistant spoken responses
+            ]
+        )
+
+        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            transport.capture_participant_transcription(participant["id"])
+            # Kick off the conversation.
+            messages.append({"role": "system", "content": "Please introduce yourself to the user."})
+            await task.queue_frames([LLMMessagesFrame(messages)])
+
+        runner = PipelineRunner()
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
diff --git a/pyproject.toml b/pyproject.toml
index 46345ed71..8dcfd7cb0 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -35,6 +35,7 @@ Website = "https://pipecat.ai"
 
 [project.optional-dependencies]
 anthropic = [ "anthropic~=0.34.0" ]
+aws = [ "boto3~=1.35.27" ]
 azure = [ "azure-cognitiveservices-speech~=1.40.0" ]
 cartesia = [ "cartesia~=1.0.13", "websockets~=12.0" ]
 daily = [ "daily-python~=0.10.1" ]
diff --git a/src/pipecat/services/aws.py b/src/pipecat/services/aws.py
new file mode 100644
index 000000000..dfca10131
--- /dev/null
+++ b/src/pipecat/services/aws.py
@@ -0,0 +1,146 @@
+#
+# Copyright (c) 2024, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+from typing import AsyncGenerator, Optional
+
+from loguru import logger
+from pydantic import BaseModel
+
+from pipecat.frames.frames import (
+    Frame,
+    TTSAudioRawFrame,
+    TTSStartedFrame,
+    TTSStoppedFrame,
+)
+from pipecat.services.ai_services import TTSService
+
+try:
+    import boto3
+    from botocore.exceptions import BotoCoreError, ClientError
+except ModuleNotFoundError as e:
+    logger.error(f"Exception: {e}")
+    logger.error(
+        "In order to use Deepgram, you need to `pip install pipecat-ai[aws]`. Also, set `AWS_SECRET_ACCESS_KEY`, `AWS_ACCESS_KEY_ID`, and `AWS_REGION` environment variable."
+    )
+    raise Exception(f"Missing module: {e}")
+
+
+class AWSTTSService(TTSService):
+    class InputParams(BaseModel):
+        engine: Optional[str] = None
+        language: Optional[str] = None
+        pitch: Optional[str] = None
+        rate: Optional[str] = None
+        volume: Optional[str] = None
+
+    def __init__(
+        self,
+        *,
+        api_key: str,
+        aws_access_key_id: str,
+        region: str,
+        voice_id: str = "Joanna",
+        sample_rate: int = 16000,
+        params: InputParams = InputParams(),
+        **kwargs,
+    ):
+        super().__init__(sample_rate=sample_rate, **kwargs)
+
+        self._polly_client = boto3.client(
+            "polly",
+            aws_access_key_id=aws_access_key_id,
+            aws_secret_access_key=api_key,
+            region_name=region,
+        )
+        self._voice_id = voice_id
+        self._sample_rate = sample_rate
+        self._params = params
+
+    def can_generate_metrics(self) -> bool:
+        return True
+
+    def _construct_ssml(self, text: str) -> str:
+        ssml = "<speak>"
+
+        if self._params.language:
+            ssml += f"<lang xml:lang='{self._params.language}'>"
+
+        prosody_attrs = []
+        # Prosody tags are only supported for standard and neural engines
+        if self._params.engine != "generative":
+            if self._params.rate:
+                prosody_attrs.append(f"rate='{self._params.rate}'")
+            if self._params.pitch:
+                prosody_attrs.append(f"pitch='{self._params.pitch}'")
+            if self._params.volume:
+                prosody_attrs.append(f"volume='{self._params.volume}'")
+
+            if prosody_attrs:
+                ssml += f"<prosody {' '.join(prosody_attrs)}>"
+        else:
+            logger.warning("Prosody tags are not supported for generative engine. Ignoring.")
+
+        ssml += text
+
+        if prosody_attrs:
+            ssml += "</prosody>"
+
+        if self._params.language:
+            ssml += "</lang>"
+
+        ssml += "</speak>"
+
+        return ssml
+
+    async def set_voice(self, voice: str):
+        logger.debug(f"Switching TTS voice to: [{voice}]")
+        self._voice_id = voice
+
+    async def set_engine(self, engine: str):
+        logger.debug(f"Switching TTS engine to: [{engine}]")
+        self._params.engine = engine
+
+    async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
+        logger.debug(f"Generating TTS: [{text}]")
+
+        try:
+            await self.start_ttfb_metrics()
+
+            # Construct the parameters dictionary
+            ssml = self._construct_ssml(text)
+
+            params = {
+                "Text": ssml,
+                "TextType": "ssml",
+                "OutputFormat": "pcm",
+                "VoiceId": self._voice_id,
+                "Engine": self._params.engine,
+                "SampleRate": str(self._sample_rate),
+            }
+
+            # Filter out None values
+            filtered_params = {k: v for k, v in params.items() if v is not None}
+
+            response = self._polly_client.synthesize_speech(**filtered_params)
+
+            await self.start_tts_usage_metrics(text)
+
+            await self.push_frame(TTSStartedFrame())
+
+            if "AudioStream" in response:
+                with response["AudioStream"] as stream:
+                    audio_data = stream.read()
+                    chunk_size = 4096  # You can adjust this value
+                    for i in range(0, len(audio_data), chunk_size):
+                        chunk = audio_data[i : i + chunk_size]
+                        if len(chunk) > 0:
+                            await self.stop_ttfb_metrics()
+                            frame = TTSAudioRawFrame(chunk, self._sample_rate, 1)
+                            yield frame
+
+            await self.push_frame(TTSStoppedFrame())
+
+        except (BotoCoreError, ClientError) as error:
+            logger.exception(f"{self} error generating TTS: {error}")
diff --git a/test-requirements.txt b/test-requirements.txt
index 78280b139..94c81331d 100644
--- a/test-requirements.txt
+++ b/test-requirements.txt
@@ -1,6 +1,7 @@
 aiohttp~=3.10.3
 anthropic~=0.30.0
 azure-cognitiveservices-speech~=1.40.0
+boto3~=1.35.27
 daily-python~=0.10.1
 deepgram-sdk~=3.5.0
 fal-client~=0.4.1

From 298b1514862c6a374869c051e6b44a517f2c706c Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Thu, 26 Sep 2024 13:05:39 -0400
Subject: [PATCH 085/135] Add setter methods

---
 src/pipecat/services/aws.py | 20 ++++++++++++++++++++
 1 file changed, 20 insertions(+)

diff --git a/src/pipecat/services/aws.py b/src/pipecat/services/aws.py
index dfca10131..b32ab05f0 100644
--- a/src/pipecat/services/aws.py
+++ b/src/pipecat/services/aws.py
@@ -102,6 +102,26 @@ class AWSTTSService(TTSService):
         logger.debug(f"Switching TTS engine to: [{engine}]")
         self._params.engine = engine
 
+    async def set_language(self, language: str):
+        logger.debug(f"Switching TTS language to: [{language}]")
+        self._params.language = language
+
+    async def set_pitch(self, pitch: str):
+        logger.debug(f"Switching TTS pitch to: [{pitch}]")
+        self._params.pitch = pitch
+
+    async def set_rate(self, rate: str):
+        logger.debug(f"Switching TTS rate to: [{rate}]")
+        self._params.rate = rate
+
+    async def set_volume(self, volume: str):
+        logger.debug(f"Switching TTS volume to: [{volume}]")
+        self._params.volume = volume
+
+    async def set_params(self, params: InputParams):
+        logger.debug(f"Switching TTS params to: [{params}]")
+        self._params = params
+
     async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
         logger.debug(f"Generating TTS: [{text}]")
 

From d3a477902b079388067ed41bb969de4454fae07b Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Thu, 26 Sep 2024 13:08:11 -0400
Subject: [PATCH 086/135] Add changelog entry

---
 CHANGELOG.md | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index f35978dcd..c7a525c82 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,6 +9,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 
+- Added AWS Polly TTS support.
+
+- Added InputParams to Azure TTS service.
+
 - All `FrameProcessors` can now register event handlers.
 
 ```

From b8ece84c6ecf4bf74119371f241a4499d675b7e8 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Thu, 26 Sep 2024 10:39:00 -0700
Subject: [PATCH 087/135] services: super should be super()

---
 src/pipecat/services/ai_services.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index 21ef8dfca..16280b024 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -260,7 +260,7 @@ class AsyncTTSService(TTSService):
         pass
 
     async def say(self, text: str):
-        await super.say(text)
+        await super().say(text)
         await self.flush_audio()
 
     async def start(self, frame: StartFrame):

From d323ea9e95960b17f8a541cbd616bd4272de1caa Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Thu, 26 Sep 2024 16:44:49 -0700
Subject: [PATCH 088/135] async_generator: keep pushing frames downstream

---
 src/pipecat/processors/async_generator.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/src/pipecat/processors/async_generator.py b/src/pipecat/processors/async_generator.py
index 66b2a3e99..4f9bc85d0 100644
--- a/src/pipecat/processors/async_generator.py
+++ b/src/pipecat/processors/async_generator.py
@@ -26,6 +26,8 @@ class AsyncGeneratorProcessor(FrameProcessor):
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
+        await self.push_frame(frame, direction)
+
         if isinstance(frame, (CancelFrame, EndFrame)):
             await self._data_queue.put(None)
         else:

From 706c00d89704f6797e464df9de7c5587bdffd719 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Thu, 26 Sep 2024 22:13:37 -0400
Subject: [PATCH 089/135] Code review feedback

---
 CHANGELOG.md                                   | 2 +-
 examples/foundational/07m-interruptible-aws.py | 6 +++++-
 src/pipecat/services/aws.py                    | 8 +++++++-
 3 files changed, 13 insertions(+), 3 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index c7a525c82..474f06989 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,7 +9,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 
-- Added AWS Polly TTS support.
+- Added AWS Polly TTS support and `07m-interruptible-aws.py` as an example.
 
 - Added InputParams to Azure TTS service.
 
diff --git a/examples/foundational/07m-interruptible-aws.py b/examples/foundational/07m-interruptible-aws.py
index 891ffd381..69d4b84c1 100644
--- a/examples/foundational/07m-interruptible-aws.py
+++ b/examples/foundational/07m-interruptible-aws.py
@@ -22,6 +22,7 @@ from pipecat.processors.aggregators.llm_response import (
     LLMUserResponseAggregator,
 )
 from pipecat.services.aws import AWSTTSService
+from pipecat.services.deepgram import DeepgramSTTService
 from pipecat.services.openai import OpenAILLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 from pipecat.vad.silero import SileroVADAnalyzer
@@ -43,12 +44,14 @@ async def main():
             DailyParams(
                 audio_out_enabled=True,
                 audio_out_sample_rate=16000,
-                transcription_enabled=True,
                 vad_enabled=True,
                 vad_analyzer=SileroVADAnalyzer(),
+                vad_audio_passthrough=True,
             ),
         )
 
+        stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
+
         tts = AWSTTSService(
             api_key=os.getenv("AWS_SECRET_ACCESS_KEY"),
             aws_access_key_id=os.getenv("AWS_ACCESS_KEY_ID"),
@@ -72,6 +75,7 @@ async def main():
         pipeline = Pipeline(
             [
                 transport.input(),  # Transport user input
+                stt,  # STT
                 tma_in,  # User responses
                 llm,  # LLM
                 tts,  # TTS
diff --git a/src/pipecat/services/aws.py b/src/pipecat/services/aws.py
index b32ab05f0..f3b2766bc 100644
--- a/src/pipecat/services/aws.py
+++ b/src/pipecat/services/aws.py
@@ -9,6 +9,7 @@ from loguru import logger
 from pydantic import BaseModel
 
 from pipecat.frames.frames import (
+    ErrorFrame,
     Frame,
     TTSAudioRawFrame,
     TTSStartedFrame,
@@ -152,7 +153,7 @@ class AWSTTSService(TTSService):
             if "AudioStream" in response:
                 with response["AudioStream"] as stream:
                     audio_data = stream.read()
-                    chunk_size = 4096  # You can adjust this value
+                    chunk_size = 8192
                     for i in range(0, len(audio_data), chunk_size):
                         chunk = audio_data[i : i + chunk_size]
                         if len(chunk) > 0:
@@ -164,3 +165,8 @@ class AWSTTSService(TTSService):
 
         except (BotoCoreError, ClientError) as error:
             logger.exception(f"{self} error generating TTS: {error}")
+            error_message = f"AWS Polly TTS error: {str(error)}"
+            yield ErrorFrame(error=error_message)
+
+        finally:
+            await self.push_frame(TTSStoppedFrame())

From 2a05cd35b0b5a295126d88a2170c0fd78cad0695 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Thu, 26 Sep 2024 16:45:20 -0700
Subject: [PATCH 090/135] rtvi: add multiple RTVI frame processors

---
 src/pipecat/processors/frameworks/rtvi.py | 281 +++++++++++++++++-----
 1 file changed, 220 insertions(+), 61 deletions(-)

diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py
index 930b2331d..03d63c7f0 100644
--- a/src/pipecat/processors/frameworks/rtvi.py
+++ b/src/pipecat/processors/frameworks/rtvi.py
@@ -5,6 +5,7 @@
 #
 
 import asyncio
+import base64
 
 from typing import Any, Awaitable, Callable, Dict, List, Literal, Optional, Union
 from pydantic import BaseModel, Field, PrivateAttr, ValidationError
@@ -20,8 +21,14 @@ from pipecat.frames.frames import (
     ErrorFrame,
     Frame,
     InterimTranscriptionFrame,
+    LLMFullResponseEndFrame,
+    LLMFullResponseStartFrame,
+    OutputAudioRawFrame,
     StartFrame,
     SystemFrame,
+    TTSStartedFrame,
+    TTSStoppedFrame,
+    TextFrame,
     TranscriptionFrame,
     TransportMessageFrame,
     UserStartedSpeakingFrame,
@@ -242,33 +249,75 @@ class RTVILLMFunctionCallResultData(BaseModel):
     result: dict | str
 
 
+class RTVIBotLLMStartedMessage(BaseModel):
+    label: Literal["rtvi-ai"] = "rtvi-ai"
+    type: Literal["bot-llm-started"] = "bot-llm-started"
+
+
+class RTVIBotLLMStoppedMessage(BaseModel):
+    label: Literal["rtvi-ai"] = "rtvi-ai"
+    type: Literal["bot-llm-stopped"] = "bot-llm-stopped"
+
+
+class RTVIBotTTSStartedMessage(BaseModel):
+    label: Literal["rtvi-ai"] = "rtvi-ai"
+    type: Literal["bot-tts-started"] = "bot-tts-started"
+
+
+class RTVIBotTTSStoppedMessage(BaseModel):
+    label: Literal["rtvi-ai"] = "rtvi-ai"
+    type: Literal["bot-tts-stopped"] = "bot-tts-stopped"
+
+
 class RTVITextMessageData(BaseModel):
     text: str
 
 
-class RTVILLMTextMessage(BaseModel):
+class RTVIBotLLMTextMessage(BaseModel):
     label: Literal["rtvi-ai"] = "rtvi-ai"
-    type: Literal["llm-text"] = "llm-text"
+    type: Literal["bot-llm-text"] = "bot-llm-text"
     data: RTVITextMessageData
 
 
-class RTVITTSTextMessage(BaseModel):
+class RTVIBotTTSTextMessage(BaseModel):
     label: Literal["rtvi-ai"] = "rtvi-ai"
-    type: Literal["tts-text"] = "tts-text"
+    type: Literal["bot-tts-text"] = "bot-tts-text"
     data: RTVITextMessageData
 
 
-class RTVITranscriptionMessageData(BaseModel):
+class RTVIAudioMessageData(BaseModel):
+    audio: str
+    sample_rate: int
+    num_channels: int
+
+
+class RTVIBotAudioMessage(BaseModel):
+    label: Literal["rtvi-ai"] = "rtvi-ai"
+    type: Literal["bot-audio"] = "bot-audio"
+    data: RTVIAudioMessageData
+
+
+class RTVIBotTranscriptionMessageData(BaseModel):
+    text: str
+
+
+class RTVIBotTranscriptionMessage(BaseModel):
+    label: Literal["rtvi-ai"] = "rtvi-ai"
+    type: Literal["bot-transcription"] = "bot-transcription"
+    data: RTVIBotTranscriptionMessageData
+
+
+class RTVIUserTranscriptionMessageData(BaseModel):
     text: str
     user_id: str
     timestamp: str
     final: bool
 
 
-class RTVITranscriptionMessage(BaseModel):
+class RTVIUserTranscriptionMessage(BaseModel):
     label: Literal["rtvi-ai"] = "rtvi-ai"
     type: Literal["user-transcription"] = "user-transcription"
-    data: RTVITranscriptionMessageData
+    data: RTVIUserTranscriptionMessageData
 
 
 class RTVIUserStartedSpeakingMessage(BaseModel):
@@ -295,6 +344,170 @@ class RTVIProcessorParams(BaseModel):
     send_bot_ready: bool = True
 
 
+class RTVIFrameProcessor(FrameProcessor):
+    def __init__(self, direction: FrameDirection = FrameDirection.DOWNSTREAM, **kwargs):
+        super().__init__(**kwargs)
+        self._direction = direction
+
+    async def _push_transport_message(self, model: BaseModel, exclude_none: bool = True):
+        frame = TransportMessageFrame(
+            message=model.model_dump(exclude_none=exclude_none), urgent=True
+        )
+        await self.push_frame(frame, self._direction)
+
+
+class RTVISpeakingProcessor(RTVIFrameProcessor):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        await self.push_frame(frame, direction)
+
+        if isinstance(frame, (UserStartedSpeakingFrame, UserStoppedSpeakingFrame)):
+            await self._handle_interruptions(frame)
+        elif isinstance(frame, (BotStartedSpeakingFrame, BotStoppedSpeakingFrame)):
+            await self._handle_bot_speaking(frame)
+
+    async def _handle_interruptions(self, frame: Frame):
+        message = None
+        if isinstance(frame, UserStartedSpeakingFrame):
+            message = RTVIUserStartedSpeakingMessage()
+        elif isinstance(frame, UserStoppedSpeakingFrame):
+            message = RTVIUserStoppedSpeakingMessage()
+
+        if message:
+            await self._push_transport_message(message)
+
+    async def _handle_bot_speaking(self, frame: Frame):
+        message = None
+        if isinstance(frame, BotStartedSpeakingFrame):
+            message = RTVIBotStartedSpeakingMessage()
+        elif isinstance(frame, BotStoppedSpeakingFrame):
+            message = RTVIBotStoppedSpeakingMessage()
+
+        if message:
+            await self._push_transport_message(message)
+
+
+class RTVIUserTranscriptionProcessor(RTVIFrameProcessor):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        await self.push_frame(frame, direction)
+
+        if isinstance(frame, (TranscriptionFrame, InterimTranscriptionFrame)):
+            await self._handle_user_transcriptions(frame)
+
+    async def _handle_user_transcriptions(self, frame: Frame):
+        message = None
+        if isinstance(frame, TranscriptionFrame):
+            message = RTVIUserTranscriptionMessage(
+                data=RTVIUserTranscriptionMessageData(
+                    text=frame.text, user_id=frame.user_id, timestamp=frame.timestamp, final=True
+                )
+            )
+        elif isinstance(frame, InterimTranscriptionFrame):
+            message = RTVIUserTranscriptionMessage(
+                data=RTVIUserTranscriptionMessageData(
+                    text=frame.text, user_id=frame.user_id, timestamp=frame.timestamp, final=False
+                )
+            )
+
+        if message:
+            await self._push_transport_message(message)
+
+
+class RTVIBotLLMProcessor(RTVIFrameProcessor):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        await self.push_frame(frame, direction)
+
+        if isinstance(frame, LLMFullResponseStartFrame):
+            await self._push_transport_message(RTVIBotLLMStartedMessage())
+        elif isinstance(frame, LLMFullResponseEndFrame):
+            await self._push_transport_message(RTVIBotLLMStoppedMessage())
+
+
+class RTVIBotTTSProcessor(RTVIFrameProcessor):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        await self.push_frame(frame, direction)
+
+        if isinstance(frame, TTSStartedFrame):
+            await self._push_transport_message(RTVIBotTTSStartedMessage())
+        elif isinstance(frame, TTSStoppedFrame):
+            await self._push_transport_message(RTVIBotTTSStoppedMessage())
+
+
+class RTVIBotLLMTextProcessor(RTVIFrameProcessor):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        await self.push_frame(frame, direction)
+
+        if isinstance(frame, TextFrame):
+            await self._handle_text(frame)
+
+    async def _handle_text(self, frame: TextFrame):
+        message = RTVIBotLLMTextMessage(data=RTVITextMessageData(text=frame.text))
+        await self._push_transport_message(message)
+
+
+class RTVIBotTTSTextProcessor(RTVIFrameProcessor):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        await self.push_frame(frame, direction)
+
+        if isinstance(frame, TextFrame):
+            await self._handle_text(frame)
+
+    async def _handle_text(self, frame: TextFrame):
+        message = RTVIBotTTSTextMessage(data=RTVITextMessageData(text=frame.text))
+        await self._push_transport_message(message)
+
+
+class RTVIBotAudioProcessor(RTVIFrameProcessor):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        await self.push_frame(frame, direction)
+
+        if isinstance(frame, OutputAudioRawFrame):
+            await self._handle_audio(frame)
+
+    async def _handle_audio(self, frame: OutputAudioRawFrame):
+        encoded = base64.b64encode(frame.audio).decode("utf-8")
+        message = RTVIBotAudioMessage(
+            data=RTVIAudioMessageData(
+                audio=encoded, sample_rate=frame.sample_rate, num_channels=frame.num_channels
+            )
+        )
+        await self._push_transport_message(message)
+
+
 class RTVIProcessor(FrameProcessor):
     def __init__(
         self,
@@ -394,20 +607,7 @@ class RTVIProcessor(FrameProcessor):
             # finish and the task finishes when EndFrame is processed.
             await self.push_frame(frame, direction)
             await self._stop(frame)
-        elif isinstance(frame, UserStartedSpeakingFrame) or isinstance(
-            frame, UserStoppedSpeakingFrame
-        ):
-            await self._handle_interruptions(frame)
-            await self.push_frame(frame, direction)
-        elif isinstance(frame, BotStartedSpeakingFrame) or isinstance(
-            frame, BotStoppedSpeakingFrame
-        ):
-            await self._handle_bot_speaking(frame)
-            await self.push_frame(frame, direction)
         # Data frames
-        elif isinstance(frame, TranscriptionFrame) or isinstance(frame, InterimTranscriptionFrame):
-            await self._handle_transcriptions(frame)
-            await self.push_frame(frame, direction)
         elif isinstance(frame, TransportMessageFrame):
             await self._message_queue.put(frame)
         elif isinstance(frame, RTVIActionFrame):
@@ -452,47 +652,6 @@ class RTVIProcessor(FrameProcessor):
         )
         await self.push_frame(frame)
 
-    async def _handle_transcriptions(self, frame: Frame):
-        # TODO(aleix): Once we add support for using custom pipelines, the STTs will
-        # be in the pipeline after this processor.
-
-        message = None
-        if isinstance(frame, TranscriptionFrame):
-            message = RTVITranscriptionMessage(
-                data=RTVITranscriptionMessageData(
-                    text=frame.text, user_id=frame.user_id, timestamp=frame.timestamp, final=True
-                )
-            )
-        elif isinstance(frame, InterimTranscriptionFrame):
-            message = RTVITranscriptionMessage(
-                data=RTVITranscriptionMessageData(
-                    text=frame.text, user_id=frame.user_id, timestamp=frame.timestamp, final=False
-                )
-            )
-
-        if message:
-            await self._push_transport_message(message)
-
-    async def _handle_interruptions(self, frame: Frame):
-        message = None
-        if isinstance(frame, UserStartedSpeakingFrame):
-            message = RTVIUserStartedSpeakingMessage()
-        elif isinstance(frame, UserStoppedSpeakingFrame):
-            message = RTVIUserStoppedSpeakingMessage()
-
-        if message:
-            await self._push_transport_message(message)
-
-    async def _handle_bot_speaking(self, frame: Frame):
-        message = None
-        if isinstance(frame, BotStartedSpeakingFrame):
-            message = RTVIBotStartedSpeakingMessage()
-        elif isinstance(frame, BotStoppedSpeakingFrame):
-            message = RTVIBotStoppedSpeakingMessage()
-
-        if message:
-            await self._push_transport_message(message)
-
     async def _action_task_handler(self):
         while True:
             try:

From 6e8a202107ad31f4d0987792128fab662321c5b6 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Thu, 26 Sep 2024 22:42:19 -0700
Subject: [PATCH 091/135] rtvi: fix handling transport messages

---
 src/pipecat/processors/frameworks/rtvi.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py
index 03d63c7f0..9721a6613 100644
--- a/src/pipecat/processors/frameworks/rtvi.py
+++ b/src/pipecat/processors/frameworks/rtvi.py
@@ -609,7 +609,7 @@ class RTVIProcessor(FrameProcessor):
             await self._stop(frame)
         # Data frames
         elif isinstance(frame, TransportMessageFrame):
-            await self._message_queue.put(frame)
+            await self._handle_transport_message(frame)
         elif isinstance(frame, RTVIActionFrame):
             await self._action_queue.put(frame)
         # Other frames

From 2c8e5665076ad9f187982a196e3cab2f1bd11b68 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Thu, 26 Sep 2024 22:42:36 -0700
Subject: [PATCH 092/135] rtvi: update version to 0.2

---
 src/pipecat/processors/frameworks/rtvi.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py
index 9721a6613..f88660f60 100644
--- a/src/pipecat/processors/frameworks/rtvi.py
+++ b/src/pipecat/processors/frameworks/rtvi.py
@@ -41,7 +41,7 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from loguru import logger
 
 
-RTVI_PROTOCOL_VERSION = "0.1"
+RTVI_PROTOCOL_VERSION = "0.2"
 
 ActionResult = Union[bool, int, float, str, list, dict]
 

From 830d2df671a93a8b2293ee9e4a7767fd6abc2874 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Thu, 26 Sep 2024 13:03:46 -0400
Subject: [PATCH 093/135] Add Google TTS

---
 CHANGELOG.md                                  |   2 +
 .../foundational/07n-interruptible-google.py  | 100 ++++++++
 pyproject.toml                                |   2 +-
 src/pipecat/services/google.py                | 217 +++++++++++++++++-
 test-requirements.txt                         |   1 +
 5 files changed, 312 insertions(+), 10 deletions(-)
 create mode 100644 examples/foundational/07n-interruptible-google.py

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 474f06989..37189eb47 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,6 +9,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 
+- Added Google TTS service and corresponding foundational example `07n-interruptible-google.py`
+
 - Added AWS Polly TTS support and `07m-interruptible-aws.py` as an example.
 
 - Added InputParams to Azure TTS service.
diff --git a/examples/foundational/07n-interruptible-google.py b/examples/foundational/07n-interruptible-google.py
new file mode 100644
index 000000000..713b3dce3
--- /dev/null
+++ b/examples/foundational/07n-interruptible-google.py
@@ -0,0 +1,100 @@
+#
+# Copyright (c) 2024, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import os
+import sys
+
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+from runner import configure
+
+from pipecat.frames.frames import LLMMessagesFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.llm_response import (
+    LLMAssistantResponseAggregator,
+    LLMUserResponseAggregator,
+)
+from pipecat.services.deepgram import DeepgramSTTService
+from pipecat.services.google import GoogleTTSService
+from pipecat.services.openai import OpenAILLMService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+from pipecat.vad.silero import SileroVADAnalyzer
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, token) = await configure(session)
+
+        transport = DailyTransport(
+            room_url,
+            token,
+            "Respond bot",
+            DailyParams(
+                audio_out_enabled=True,
+                audio_out_sample_rate=24000,
+                vad_enabled=True,
+                vad_analyzer=SileroVADAnalyzer(),
+                vad_audio_passthrough=True,
+            ),
+        )
+
+        stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
+
+        tts = GoogleTTSService(
+            credentials=os.getenv("GOOGLE_CREDENTIALS"),
+            voice_id="en-US-Neural2-J",
+            params=GoogleTTSService.InputParams(language="en-US", rate="1.05"),
+        )
+
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
+
+        messages = [
+            {
+                "role": "system",
+                "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+            },
+        ]
+
+        tma_in = LLMUserResponseAggregator(messages)
+        tma_out = LLMAssistantResponseAggregator(messages)
+
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                stt,  # STT
+                tma_in,  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                tma_out,  # Assistant spoken responses
+            ]
+        )
+
+        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            transport.capture_participant_transcription(participant["id"])
+            # Kick off the conversation.
+            messages.append({"role": "system", "content": "Please introduce yourself to the user."})
+            await task.queue_frames([LLMMessagesFrame(messages)])
+
+        runner = PipelineRunner()
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
diff --git a/pyproject.toml b/pyproject.toml
index 8dcfd7cb0..876242343 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -44,7 +44,7 @@ elevenlabs = [ "websockets~=12.0" ]
 examples = [ "python-dotenv~=1.0.1", "flask~=3.0.3", "flask_cors~=4.0.1" ]
 fal = [ "fal-client~=0.4.1" ]
 gladia = [ "websockets~=12.0" ]
-google = [ "google-generativeai~=0.7.2" ]
+google = [ "google-generativeai~=0.7.2", "google-cloud-texttospeech~=2.17.2" ]
 gstreamer = [ "pygobject~=3.48.2" ]
 fireworks = [ "openai~=1.37.2" ]
 langchain = [ "langchain~=0.2.14", "langchain-community~=0.2.12", "langchain-openai~=0.1.20" ]
diff --git a/src/pipecat/services/google.py b/src/pipecat/services/google.py
index 4de6b77fa..2a0a7d1e1 100644
--- a/src/pipecat/services/google.py
+++ b/src/pipecat/services/google.py
@@ -5,30 +5,37 @@
 #
 
 import asyncio
+import json
+from typing import AsyncGenerator, List, Literal, Optional
 
-from typing import List
+import numpy as np
+from loguru import logger
+from pydantic import BaseModel
 
 from pipecat.frames.frames import (
     Frame,
+    LLMFullResponseEndFrame,
+    LLMFullResponseStartFrame,
+    LLMMessagesFrame,
     LLMModelUpdateFrame,
     TextFrame,
+    TTSAudioRawFrame,
+    TTSStartedFrame,
+    TTSStoppedFrame,
     VisionImageRawFrame,
-    LLMMessagesFrame,
-    LLMFullResponseStartFrame,
-    LLMFullResponseEndFrame,
 )
-from pipecat.processors.frame_processor import FrameDirection
-from pipecat.services.ai_services import LLMService
 from pipecat.processors.aggregators.openai_llm_context import (
     OpenAILLMContext,
     OpenAILLMContextFrame,
 )
-
-from loguru import logger
+from pipecat.processors.frame_processor import FrameDirection
+from pipecat.services.ai_services import LLMService, TTSService
 
 try:
-    import google.generativeai as gai
     import google.ai.generativelanguage as glm
+    import google.generativeai as gai
+    from google.cloud import texttospeech_v1
+    from google.oauth2 import service_account
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
@@ -137,3 +144,195 @@ class GoogleLLMService(LLMService):
 
         if context:
             await self._process_context(context)
+
+
+class GoogleTTSService(TTSService):
+    class InputParams(BaseModel):
+        pitch: Optional[str] = None
+        rate: Optional[str] = None
+        volume: Optional[str] = None
+        emphasis: Optional[Literal["strong", "moderate", "reduced", "none"]] = None
+        language: Optional[str] = None
+        gender: Optional[Literal["male", "female", "neutral"]] = None
+        google_style: Optional[Literal["apologetic", "calm", "empathetic", "firm", "lively"]] = None
+
+    def __init__(
+        self,
+        *,
+        credentials: Optional[str] = None,
+        credentials_path: Optional[str] = None,
+        voice_id: str = "en-US-Neural2-A",
+        sample_rate: int = 24000,
+        params: InputParams = InputParams(),
+        **kwargs,
+    ):
+        super().__init__(sample_rate=sample_rate, **kwargs)
+
+        self._voice_id: str = voice_id
+        self._params = params
+        self._client: texttospeech_v1.TextToSpeechAsyncClient = self._create_client(
+            credentials, credentials_path
+        )
+
+    def _create_client(
+        self, credentials: Optional[str], credentials_path: Optional[str]
+    ) -> texttospeech_v1.TextToSpeechAsyncClient:
+        creds: Optional[service_account.Credentials] = None
+
+        # Create a Google Cloud service account for the Cloud Text-to-Speech API
+        # Using either the provided credentials JSON string or the path to a service account JSON
+        # file, create a Google Cloud service account and use it to authenticate with the API.
+        if credentials:
+            # Use provided credentials JSON string
+            json_account_info = json.loads(credentials)
+            creds = service_account.Credentials.from_service_account_info(json_account_info)
+        elif credentials_path:
+            # Use service account JSON file if provided
+            creds = service_account.Credentials.from_service_account_file(credentials_path)
+        else:
+            raise ValueError("Either 'credentials' or 'credentials_path' must be provided.")
+
+        return texttospeech_v1.TextToSpeechAsyncClient(credentials=creds)
+
+    def can_generate_metrics(self) -> bool:
+        return True
+
+    def _construct_ssml(self, text: str) -> str:
+        ssml = "<speak>"
+
+        # Voice tag
+        voice_attrs = [f"name='{self._voice_id}'"]
+        if self._params.language:
+            voice_attrs.append(f"language='{self._params.language}'")
+        if self._params.gender:
+            voice_attrs.append(f"gender='{self._params.gender}'")
+        ssml += f"<voice {' '.join(voice_attrs)}>"
+
+        # Prosody tag
+        prosody_attrs = []
+        if self._params.pitch:
+            prosody_attrs.append(f"pitch='{self._params.pitch}'")
+        if self._params.rate:
+            prosody_attrs.append(f"rate='{self._params.rate}'")
+        if self._params.volume:
+            prosody_attrs.append(f"volume='{self._params.volume}'")
+
+        if prosody_attrs:
+            ssml += f"<prosody {' '.join(prosody_attrs)}>"
+
+        # Emphasis tag
+        if self._params.emphasis:
+            ssml += f"<emphasis level='{self._params.emphasis}'>"
+
+        # Google style tag
+        if self._params.google_style:
+            ssml += f"<google:style name='{self._params.google_style}'>"
+
+        ssml += text
+
+        # Close tags
+        if self._params.google_style:
+            ssml += "</google:style>"
+        if self._params.emphasis:
+            ssml += "</emphasis>"
+        if prosody_attrs:
+            ssml += "</prosody>"
+        ssml += "</voice></speak>"
+
+        return ssml
+
+    async def set_voice(self, voice: str) -> None:
+        logger.debug(f"Switching TTS voice to: [{voice}]")
+        self._voice_id = voice
+
+    async def set_language(self, language: str) -> None:
+        logger.debug(f"Switching TTS language to: [{language}]")
+        self._params.language = language
+
+    async def set_pitch(self, pitch: str) -> None:
+        logger.debug(f"Switching TTS pitch to: [{pitch}]")
+        self._params.pitch = pitch
+
+    async def set_rate(self, rate: str) -> None:
+        logger.debug(f"Switching TTS rate to: [{rate}]")
+        self._params.rate = rate
+
+    async def set_volume(self, volume: str) -> None:
+        logger.debug(f"Switching TTS volume to: [{volume}]")
+        self._params.volume = volume
+
+    async def set_emphasis(
+        self, emphasis: Literal["strong", "moderate", "reduced", "none"]
+    ) -> None:
+        logger.debug(f"Switching TTS emphasis to: [{emphasis}]")
+        self._params.emphasis = emphasis
+
+    async def set_gender(self, gender: Literal["male", "female", "neutral"]) -> None:
+        logger.debug(f"Switch TTS gender to [{gender}]")
+        self._params.gender = gender
+
+    async def google_style(
+        self, google_style: Literal["apologetic", "calm", "empathetic", "firm", "lively"]
+    ) -> None:
+        logger.debug(f"Switching TTS google style to: [{google_style}]")
+        self._params.google_style = google_style
+
+    async def set_params(self, params: InputParams) -> None:
+        logger.debug(f"Switching TTS params to: [{params}]")
+        self._params = params
+
+    async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
+        logger.debug(f"Generating TTS: [{text}]")
+
+        try:
+            await self.start_ttfb_metrics()
+
+            ssml = self._construct_ssml(text)
+            synthesis_input = texttospeech_v1.SynthesisInput(ssml=ssml)
+            voice = texttospeech_v1.VoiceSelectionParams(
+                language_code=self._params.language, name=self._voice_id
+            )
+            audio_config = texttospeech_v1.AudioConfig(
+                audio_encoding=texttospeech_v1.AudioEncoding.LINEAR16,
+                sample_rate_hertz=self.sample_rate,
+            )
+
+            request = texttospeech_v1.SynthesizeSpeechRequest(
+                input=synthesis_input, voice=voice, audio_config=audio_config
+            )
+
+            response = await self._client.synthesize_speech(request=request)
+
+            await self.start_tts_usage_metrics(text)
+
+            await self.push_frame(TTSStartedFrame())
+
+            # The audio produced by the TTS service has an audible click or pop at the beginning.
+            # This is due to the abrupt start of the audio waveform. To mitigate this, we apply a
+            # short fade-in effect to the audio data.
+
+            # Convert the response to a mutable numpy array
+            audio_content = np.frombuffer(response.audio_content, dtype=np.int16).copy()
+
+            # Apply a smooth, short fade-in
+            fade_duration = int(0.01 * self.sample_rate)  # 10ms fade-in
+            fade_in = np.square(
+                np.linspace(0, 1, fade_duration)
+            )  # Quadratic fade for smoother start
+            audio_content[:fade_duration] = audio_content[:fade_duration] * fade_in
+
+            # Read and yield audio data in chunks
+            chunk_size = 8192
+            for i in range(0, len(audio_content), chunk_size):
+                chunk = audio_content[i : i + chunk_size].tobytes()
+                if not chunk:
+                    break
+                await self.stop_ttfb_metrics()
+                frame = TTSAudioRawFrame(chunk, self.sample_rate, 1)
+                yield frame
+                await asyncio.sleep(0)  # Allow other tasks to run
+
+            await self.push_frame(TTSStoppedFrame())
+
+        except Exception as e:
+            logger.exception(f"{self} error generating TTS: {e}")
diff --git a/test-requirements.txt b/test-requirements.txt
index 94c81331d..8c7db7377 100644
--- a/test-requirements.txt
+++ b/test-requirements.txt
@@ -7,6 +7,7 @@ deepgram-sdk~=3.5.0
 fal-client~=0.4.1
 fastapi~=0.112.1
 faster-whisper~=1.0.3
+google-cloud-texttospeech~=2.17.2
 google-generativeai~=0.7.2
 langchain~=0.2.14
 livekit~=0.13.1

From e7548f9494cc8cd0ab27eba8dae53bb3c9f3af36 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Fri, 27 Sep 2024 08:02:44 -0400
Subject: [PATCH 094/135] Code review feedback

---
 src/pipecat/services/google.py | 23 ++++++++---------------
 1 file changed, 8 insertions(+), 15 deletions(-)

diff --git a/src/pipecat/services/google.py b/src/pipecat/services/google.py
index 2a0a7d1e1..38af3e41f 100644
--- a/src/pipecat/services/google.py
+++ b/src/pipecat/services/google.py
@@ -8,11 +8,11 @@ import asyncio
 import json
 from typing import AsyncGenerator, List, Literal, Optional
 
-import numpy as np
 from loguru import logger
 from pydantic import BaseModel
 
 from pipecat.frames.frames import (
+    ErrorFrame,
     Frame,
     LLMFullResponseEndFrame,
     LLMFullResponseStartFrame,
@@ -307,24 +307,13 @@ class GoogleTTSService(TTSService):
 
             await self.push_frame(TTSStartedFrame())
 
-            # The audio produced by the TTS service has an audible click or pop at the beginning.
-            # This is due to the abrupt start of the audio waveform. To mitigate this, we apply a
-            # short fade-in effect to the audio data.
-
-            # Convert the response to a mutable numpy array
-            audio_content = np.frombuffer(response.audio_content, dtype=np.int16).copy()
-
-            # Apply a smooth, short fade-in
-            fade_duration = int(0.01 * self.sample_rate)  # 10ms fade-in
-            fade_in = np.square(
-                np.linspace(0, 1, fade_duration)
-            )  # Quadratic fade for smoother start
-            audio_content[:fade_duration] = audio_content[:fade_duration] * fade_in
+            # Skip the first 44 bytes to remove the WAV header
+            audio_content = response.audio_content[44:]
 
             # Read and yield audio data in chunks
             chunk_size = 8192
             for i in range(0, len(audio_content), chunk_size):
-                chunk = audio_content[i : i + chunk_size].tobytes()
+                chunk = audio_content[i : i + chunk_size]
                 if not chunk:
                     break
                 await self.stop_ttfb_metrics()
@@ -336,3 +325,7 @@ class GoogleTTSService(TTSService):
 
         except Exception as e:
             logger.exception(f"{self} error generating TTS: {e}")
+            error_message = f"TTS generation error: {str(e)}"
+            yield ErrorFrame(error=error_message)
+        finally:
+            await self.push_frame(TTSStoppedFrame())

From 50b6580fbb44b6f686fc249ae2fd160b8f60947b Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Fri, 27 Sep 2024 13:28:33 -0700
Subject: [PATCH 095/135] livekit: add license notice

---
 src/pipecat/transports/services/livekit.py | 13 +++++++++++--
 1 file changed, 11 insertions(+), 2 deletions(-)

diff --git a/src/pipecat/transports/services/livekit.py b/src/pipecat/transports/services/livekit.py
index 52bbbf89d..6e5e48d0b 100644
--- a/src/pipecat/transports/services/livekit.py
+++ b/src/pipecat/transports/services/livekit.py
@@ -1,10 +1,17 @@
+#
+# Copyright (c) 2024, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
 import asyncio
+
 from dataclasses import dataclass
 from typing import Any, Awaitable, Callable, List
 
-import numpy as np
-from loguru import logger
 from pydantic import BaseModel
+
+import numpy as np
 from scipy import signal
 
 from pipecat.frames.frames import (
@@ -28,6 +35,8 @@ from pipecat.transports.base_output import BaseOutputTransport
 from pipecat.transports.base_transport import BaseTransport, TransportParams
 from pipecat.vad.vad_analyzer import VADAnalyzer
 
+from loguru import logger
+
 try:
     from livekit import rtc
     from tenacity import retry, stop_after_attempt, wait_exponential

From d9b16d4f738f405287bfc79fd350852c48fb829a Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Fri, 27 Sep 2024 13:32:27 -0700
Subject: [PATCH 096/135] services: import cosmetics

---
 src/pipecat/services/aws.py      | 4 +++-
 src/pipecat/services/azure.py    | 9 ++++++---
 src/pipecat/services/deepgram.py | 5 +++--
 src/pipecat/services/fal.py      | 3 ++-
 src/pipecat/services/openai.py   | 9 +++++----
 src/pipecat/services/xtts.py     | 4 ++--
 6 files changed, 21 insertions(+), 13 deletions(-)

diff --git a/src/pipecat/services/aws.py b/src/pipecat/services/aws.py
index f3b2766bc..80240985f 100644
--- a/src/pipecat/services/aws.py
+++ b/src/pipecat/services/aws.py
@@ -3,9 +3,9 @@
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
+
 from typing import AsyncGenerator, Optional
 
-from loguru import logger
 from pydantic import BaseModel
 
 from pipecat.frames.frames import (
@@ -17,6 +17,8 @@ from pipecat.frames.frames import (
 )
 from pipecat.services.ai_services import TTSService
 
+from loguru import logger
+
 try:
     import boto3
     from botocore.exceptions import BotoCoreError, ClientError
diff --git a/src/pipecat/services/azure.py b/src/pipecat/services/azure.py
index 41fc7598b..c8fa095ab 100644
--- a/src/pipecat/services/azure.py
+++ b/src/pipecat/services/azure.py
@@ -4,13 +4,12 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
+import aiohttp
 import asyncio
 import io
+
 from typing import AsyncGenerator, Optional
 
-import aiohttp
-from loguru import logger
-from PIL import Image
 from pydantic import BaseModel
 
 from pipecat.frames.frames import (
@@ -29,6 +28,10 @@ from pipecat.services.ai_services import ImageGenService, STTService, TTSService
 from pipecat.services.openai import BaseOpenAILLMService
 from pipecat.utils.time import time_now_iso8601
 
+from PIL import Image
+
+from loguru import logger
+
 # See .env.example for Azure configuration needed
 try:
     from azure.cognitiveservices.speech import (
diff --git a/src/pipecat/services/deepgram.py b/src/pipecat/services/deepgram.py
index 6929e66e5..d109cce3c 100644
--- a/src/pipecat/services/deepgram.py
+++ b/src/pipecat/services/deepgram.py
@@ -5,9 +5,8 @@
 #
 
 import asyncio
-from typing import AsyncGenerator
 
-from loguru import logger
+from typing import AsyncGenerator
 
 from pipecat.frames.frames import (
     CancelFrame,
@@ -25,6 +24,8 @@ from pipecat.services.ai_services import STTService, TTSService
 from pipecat.transcriptions.language import Language
 from pipecat.utils.time import time_now_iso8601
 
+from loguru import logger
+
 # See .env.example for Deepgram configuration needed
 try:
     from deepgram import (
diff --git a/src/pipecat/services/fal.py b/src/pipecat/services/fal.py
index bb7b47dfc..aecdeb709 100644
--- a/src/pipecat/services/fal.py
+++ b/src/pipecat/services/fal.py
@@ -8,13 +8,14 @@ import aiohttp
 import io
 import os
 
-from PIL import Image
 from pydantic import BaseModel
 from typing import AsyncGenerator, Optional, Union, Dict
 
 from pipecat.frames.frames import ErrorFrame, Frame, URLImageRawFrame
 from pipecat.services.ai_services import ImageGenService
 
+from PIL import Image
+
 from loguru import logger
 
 try:
diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py
index e54898525..47bee5ec1 100644
--- a/src/pipecat/services/openai.py
+++ b/src/pipecat/services/openai.py
@@ -9,14 +9,12 @@ import base64
 import io
 import json
 import httpx
+
 from dataclasses import dataclass
 
 from typing import Any, AsyncGenerator, Dict, List, Literal, Optional
 from pydantic import BaseModel, Field
 
-from loguru import logger
-from PIL import Image
-
 from pipecat.frames.frames import (
     ErrorFrame,
     Frame,
@@ -39,7 +37,6 @@ from pipecat.processors.aggregators.llm_response import (
     LLMUserContextAggregator,
     LLMAssistantContextAggregator,
 )
-
 from pipecat.processors.aggregators.openai_llm_context import (
     OpenAILLMContext,
     OpenAILLMContextFrame,
@@ -47,6 +44,10 @@ from pipecat.processors.aggregators.openai_llm_context import (
 from pipecat.processors.frame_processor import FrameDirection
 from pipecat.services.ai_services import ImageGenService, LLMService, TTSService
 
+from PIL import Image
+
+from loguru import logger
+
 try:
     from openai import AsyncOpenAI, AsyncStream, DefaultAsyncHttpxClient, BadRequestError, NOT_GIVEN
     from openai.types.chat import ChatCompletionChunk, ChatCompletionMessageParam
diff --git a/src/pipecat/services/xtts.py b/src/pipecat/services/xtts.py
index 5161efcf6..2c47d59e8 100644
--- a/src/pipecat/services/xtts.py
+++ b/src/pipecat/services/xtts.py
@@ -18,10 +18,10 @@ from pipecat.frames.frames import (
 )
 from pipecat.services.ai_services import TTSService
 
-from loguru import logger
-
 import numpy as np
 
+from loguru import logger
+
 try:
     import resampy
 except ModuleNotFoundError as e:

From 44a349386c135df45beb07c32b82f6e17747c2c7 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Fri, 27 Sep 2024 10:43:49 -0400
Subject: [PATCH 097/135] Consolidate update frames classes into a single
 UpdateSettingsFrame class

---
 CHANGELOG.md                        |   3 +
 src/pipecat/frames/frames.py        | 121 +++++-----------------------
 src/pipecat/services/ai_services.py |  38 +++++----
 src/pipecat/services/anthropic.py   |  67 ++++++++-------
 src/pipecat/services/google.py      |   9 ++-
 src/pipecat/services/openai.py      |  54 ++++++++-----
 src/pipecat/services/together.py    |  62 ++++++++------
 7 files changed, 159 insertions(+), 195 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 37189eb47..0f489556c 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -93,6 +93,9 @@ async def on_connected(processor):
 
 ### Changed
 
+- Updated individual update settings frame classes into a single UpdateSettingsFrame
+  class for STT, LLM, and TTS.
+
 - We now distinguish between input and output audio and image frames. We
   introduce `InputAudioRawFrame`, `OutputAudioRawFrame`, `InputImageRawFrame`
   and `OutputImageRawFrame` (and other subclasses of those). The input frames
diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py
index 273aad214..1b31b9c88 100644
--- a/src/pipecat/frames/frames.py
+++ b/src/pipecat/frames/frames.py
@@ -4,9 +4,8 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-from typing import Any, List, Optional, Tuple
-
 from dataclasses import dataclass, field
+from typing import Any, List, Optional, Tuple
 
 from pipecat.clocks.base_clock import BaseClock
 from pipecat.metrics.metrics import MetricsData
@@ -528,113 +527,35 @@ class UserImageRequestFrame(ControlFrame):
 
 
 @dataclass
-class LLMModelUpdateFrame(ControlFrame):
-    """A control frame containing a request to update to a new LLM model."""
+class LLMUpdateSettingsFrame(ControlFrame):
+    """A control frame containing a request to update LLM settings."""
 
-    model: str
+    model: Optional[str] = None
+    temperature: Optional[float] = None
+    top_k: Optional[int] = None
+    top_p: Optional[float] = None
+    frequency_penalty: Optional[float] = None
+    presence_penalty: Optional[float] = None
+    max_tokens: Optional[int] = None
+    seed: Optional[int] = None
+    extra: dict = field(default_factory=dict)
 
 
 @dataclass
-class LLMTemperatureUpdateFrame(ControlFrame):
-    """A control frame containing a request to update to a new LLM temperature."""
+class TTSUpdateSettingsFrame(ControlFrame):
+    """A control frame containing a request to update TTS settings."""
 
-    temperature: float
+    model: Optional[str] = None
+    voice: Optional[str] = None
+    language: Optional[Language] = None
 
 
 @dataclass
-class LLMTopKUpdateFrame(ControlFrame):
-    """A control frame containing a request to update to a new LLM top_k."""
+class STTUpdateSettingsFrame(ControlFrame):
+    """A control frame containing a request to update STT settings."""
 
-    top_k: int
-
-
-@dataclass
-class LLMTopPUpdateFrame(ControlFrame):
-    """A control frame containing a request to update to a new LLM top_p."""
-
-    top_p: float
-
-
-@dataclass
-class LLMFrequencyPenaltyUpdateFrame(ControlFrame):
-    """A control frame containing a request to update to a new LLM frequency
-    penalty.
-
-    """
-
-    frequency_penalty: float
-
-
-@dataclass
-class LLMPresencePenaltyUpdateFrame(ControlFrame):
-    """A control frame containing a request to update to a new LLM presence
-    penalty.
-
-    """
-
-    presence_penalty: float
-
-
-@dataclass
-class LLMMaxTokensUpdateFrame(ControlFrame):
-    """A control frame containing a request to update to a new LLM max tokens."""
-
-    max_tokens: int
-
-
-@dataclass
-class LLMSeedUpdateFrame(ControlFrame):
-    """A control frame containing a request to update to a new LLM seed."""
-
-    seed: int
-
-
-@dataclass
-class LLMExtraUpdateFrame(ControlFrame):
-    """A control frame containing a request to update to a new LLM extra params."""
-
-    extra: dict
-
-
-@dataclass
-class TTSModelUpdateFrame(ControlFrame):
-    """A control frame containing a request to update the TTS model."""
-
-    model: str
-
-
-@dataclass
-class TTSVoiceUpdateFrame(ControlFrame):
-    """A control frame containing a request to update to a new TTS voice."""
-
-    voice: str
-
-
-@dataclass
-class TTSLanguageUpdateFrame(ControlFrame):
-    """A control frame containing a request to update to a new TTS language and
-    optional voice.
-
-    """
-
-    language: Language
-
-
-@dataclass
-class STTModelUpdateFrame(ControlFrame):
-    """A control frame containing a request to update the STT model and optional
-    language.
-
-    """
-
-    model: str
-
-
-@dataclass
-class STTLanguageUpdateFrame(ControlFrame):
-    """A control frame containing a request to update to STT language."""
-
-    language: Language
+    model: Optional[str] = None
+    language: Optional[Language] = None
 
 
 @dataclass
diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index 16280b024..79e52531d 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -7,10 +7,11 @@
 import asyncio
 import io
 import wave
-
 from abc import abstractmethod
 from typing import AsyncGenerator, List, Optional, Tuple
 
+from loguru import logger
+
 from pipecat.frames.frames import (
     AudioRawFrame,
     CancelFrame,
@@ -18,31 +19,26 @@ from pipecat.frames.frames import (
     ErrorFrame,
     Frame,
     LLMFullResponseEndFrame,
-    STTLanguageUpdateFrame,
-    STTModelUpdateFrame,
     StartFrame,
     StartInterruptionFrame,
+    STTUpdateSettingsFrame,
+    TextFrame,
     TTSAudioRawFrame,
-    TTSLanguageUpdateFrame,
-    TTSModelUpdateFrame,
     TTSSpeakFrame,
     TTSStartedFrame,
     TTSStoppedFrame,
-    TTSVoiceUpdateFrame,
-    TextFrame,
+    TTSUpdateSettingsFrame,
     UserImageRequestFrame,
     VisionImageRawFrame,
 )
 from pipecat.metrics.metrics import MetricsData
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.transcriptions.language import Language
 from pipecat.utils.audio import calculate_audio_volume
 from pipecat.utils.string import match_endofsentence
 from pipecat.utils.time import seconds_to_nanoseconds
 from pipecat.utils.utils import exp_smoothing
-from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-
-from loguru import logger
 
 
 class AIService(FrameProcessor):
@@ -230,12 +226,13 @@ class TTSService(AIService):
                 await self.push_frame(frame, direction)
         elif isinstance(frame, TTSSpeakFrame):
             await self._push_tts_frames(frame.text)
-        elif isinstance(frame, TTSModelUpdateFrame):
-            await self.set_model(frame.model)
-        elif isinstance(frame, TTSVoiceUpdateFrame):
-            await self.set_voice(frame.voice)
-        elif isinstance(frame, TTSLanguageUpdateFrame):
-            await self.set_language(frame.language)
+        elif isinstance(frame, TTSUpdateSettingsFrame):
+            if frame.model is not None:
+                await self.set_model(frame.model)
+            if frame.voice is not None:
+                await self.set_voice(frame.voice)
+            if frame.language is not None:
+                await self.set_language(frame.language)
         else:
             await self.push_frame(frame, direction)
 
@@ -408,10 +405,11 @@ class STTService(AIService):
             # In this service we accumulate audio internally and at the end we
             # push a TextFrame. We don't really want to push audio frames down.
             await self.process_audio_frame(frame)
-        elif isinstance(frame, STTModelUpdateFrame):
-            await self.set_model(frame.model)
-        elif isinstance(frame, STTLanguageUpdateFrame):
-            await self.set_language(frame.language)
+        elif isinstance(frame, STTUpdateSettingsFrame):
+            if frame.model is not None:
+                await self.set_model(frame.model)
+            if frame.language is not None:
+                await self.set_language(frame.language)
         else:
             await self.push_frame(frame, direction)
 
diff --git a/src/pipecat/services/anthropic.py b/src/pipecat/services/anthropic.py
index 8b8e187ea..1c4cd284e 100644
--- a/src/pipecat/services/anthropic.py
+++ b/src/pipecat/services/anthropic.py
@@ -5,47 +5,47 @@
 #
 
 import base64
-import json
-import io
 import copy
-from typing import Any, Dict, List, Optional
-from dataclasses import dataclass
-from PIL import Image
-from asyncio import CancelledError
+import io
+import json
 import re
+from asyncio import CancelledError
+from dataclasses import dataclass
+from typing import Any, Dict, List, Optional
+
+from loguru import logger
+from PIL import Image
 from pydantic import BaseModel, Field
 
 from pipecat.frames.frames import (
     Frame,
-    LLMEnablePromptCachingFrame,
-    LLMModelUpdateFrame,
-    TextFrame,
-    VisionImageRawFrame,
-    UserImageRequestFrame,
-    UserImageRawFrame,
-    LLMMessagesFrame,
-    LLMFullResponseStartFrame,
-    LLMFullResponseEndFrame,
-    FunctionCallResultFrame,
     FunctionCallInProgressFrame,
+    FunctionCallResultFrame,
+    LLMEnablePromptCachingFrame,
+    LLMFullResponseEndFrame,
+    LLMFullResponseStartFrame,
+    LLMMessagesFrame,
+    LLMUpdateSettingsFrame,
     StartInterruptionFrame,
+    TextFrame,
+    UserImageRawFrame,
+    UserImageRequestFrame,
+    VisionImageRawFrame,
 )
 from pipecat.metrics.metrics import LLMTokenUsage
-from pipecat.processors.frame_processor import FrameDirection
-from pipecat.services.ai_services import LLMService
+from pipecat.processors.aggregators.llm_response import (
+    LLMAssistantContextAggregator,
+    LLMUserContextAggregator,
+)
 from pipecat.processors.aggregators.openai_llm_context import (
     OpenAILLMContext,
     OpenAILLMContextFrame,
 )
-from pipecat.processors.aggregators.llm_response import (
-    LLMUserContextAggregator,
-    LLMAssistantContextAggregator,
-)
-
-from loguru import logger
+from pipecat.processors.frame_processor import FrameDirection
+from pipecat.services.ai_services import LLMService
 
 try:
-    from anthropic import AsyncAnthropic, NOT_GIVEN, NotGiven
+    from anthropic import NOT_GIVEN, AsyncAnthropic, NotGiven
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
@@ -293,9 +293,20 @@ class AnthropicLLMService(LLMService):
             # UserImageRawFrames coming through the pipeline and add them
             # to the context.
             context = AnthropicLLMContext.from_image_frame(frame)
-        elif isinstance(frame, LLMModelUpdateFrame):
-            logger.debug(f"Switching LLM model to: [{frame.model}]")
-            self.set_model_name(frame.model)
+        elif isinstance(frame, LLMUpdateSettingsFrame):
+            if frame.model is not None:
+                logger.debug(f"Switching LLM model to: [{frame.model}]")
+                self.set_model_name(frame.model)
+            if frame.max_tokens is not None:
+                await self.set_max_tokens(frame.max_tokens)
+            if frame.temperature is not None:
+                await self.set_temperature(frame.temperature)
+            if frame.top_k is not None:
+                await self.set_top_k(frame.top_k)
+            if frame.top_p is not None:
+                await self.set_top_p(frame.top_p)
+            if frame.extra:
+                await self.set_extra(frame.extra)
         elif isinstance(frame, LLMEnablePromptCachingFrame):
             logger.debug(f"Setting enable prompt caching to: [{frame.enable}]")
             self._enable_prompt_caching_beta = frame.enable
diff --git a/src/pipecat/services/google.py b/src/pipecat/services/google.py
index 38af3e41f..53efd8c17 100644
--- a/src/pipecat/services/google.py
+++ b/src/pipecat/services/google.py
@@ -17,7 +17,7 @@ from pipecat.frames.frames import (
     LLMFullResponseEndFrame,
     LLMFullResponseStartFrame,
     LLMMessagesFrame,
-    LLMModelUpdateFrame,
+    LLMUpdateSettingsFrame,
     TextFrame,
     TTSAudioRawFrame,
     TTSStartedFrame,
@@ -136,9 +136,10 @@ class GoogleLLMService(LLMService):
             context = OpenAILLMContext.from_messages(frame.messages)
         elif isinstance(frame, VisionImageRawFrame):
             context = OpenAILLMContext.from_image_frame(frame)
-        elif isinstance(frame, LLMModelUpdateFrame):
-            logger.debug(f"Switching LLM model to: [{frame.model}]")
-            self._create_client(frame.model)
+        elif isinstance(frame, LLMUpdateSettingsFrame):
+            if frame.model is not None:
+                logger.debug(f"Switching LLM model to: [{frame.model}]")
+                self.set_model_name(frame.model)
         else:
             await self.push_frame(frame, direction)
 
diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py
index 47bee5ec1..a830b65a8 100644
--- a/src/pipecat/services/openai.py
+++ b/src/pipecat/services/openai.py
@@ -4,38 +4,39 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-import aiohttp
 import base64
 import io
 import json
-import httpx
-
 from dataclasses import dataclass
-
 from typing import Any, AsyncGenerator, Dict, List, Literal, Optional
+
+import aiohttp
+import httpx
+from loguru import logger
+from PIL import Image
 from pydantic import BaseModel, Field
 
 from pipecat.frames.frames import (
     ErrorFrame,
     Frame,
+    FunctionCallInProgressFrame,
+    FunctionCallResultFrame,
     LLMFullResponseEndFrame,
     LLMFullResponseStartFrame,
     LLMMessagesFrame,
-    LLMModelUpdateFrame,
+    LLMUpdateSettingsFrame,
+    StartInterruptionFrame,
+    TextFrame,
     TTSAudioRawFrame,
     TTSStartedFrame,
     TTSStoppedFrame,
-    TextFrame,
     URLImageRawFrame,
     VisionImageRawFrame,
-    FunctionCallResultFrame,
-    FunctionCallInProgressFrame,
-    StartInterruptionFrame,
 )
 from pipecat.metrics.metrics import LLMTokenUsage
 from pipecat.processors.aggregators.llm_response import (
-    LLMUserContextAggregator,
     LLMAssistantContextAggregator,
+    LLMUserContextAggregator,
 )
 from pipecat.processors.aggregators.openai_llm_context import (
     OpenAILLMContext,
@@ -44,12 +45,14 @@ from pipecat.processors.aggregators.openai_llm_context import (
 from pipecat.processors.frame_processor import FrameDirection
 from pipecat.services.ai_services import ImageGenService, LLMService, TTSService
 
-from PIL import Image
-
-from loguru import logger
-
 try:
-    from openai import AsyncOpenAI, AsyncStream, DefaultAsyncHttpxClient, BadRequestError, NOT_GIVEN
+    from openai import (
+        NOT_GIVEN,
+        AsyncOpenAI,
+        AsyncStream,
+        BadRequestError,
+        DefaultAsyncHttpxClient,
+    )
     from openai.types.chat import ChatCompletionChunk, ChatCompletionMessageParam
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
@@ -280,9 +283,22 @@ class BaseOpenAILLMService(LLMService):
             context = OpenAILLMContext.from_messages(frame.messages)
         elif isinstance(frame, VisionImageRawFrame):
             context = OpenAILLMContext.from_image_frame(frame)
-        elif isinstance(frame, LLMModelUpdateFrame):
-            logger.debug(f"Switching LLM model to: [{frame.model}]")
-            self.set_model_name(frame.model)
+        elif isinstance(frame, LLMUpdateSettingsFrame):
+            if frame.model is not None:
+                logger.debug(f"Switching LLM model to: [{frame.model}]")
+                self.set_model_name(frame.model)
+            if frame.frequency_penalty is not None:
+                await self.set_frequency_penalty(frame.frequency_penalty)
+            if frame.presence_penalty is not None:
+                await self.set_presence_penalty(frame.presence_penalty)
+            if frame.seed is not None:
+                await self.set_seed(frame.seed)
+            if frame.temperature is not None:
+                await self.set_temperature(frame.temperature)
+            if frame.top_p is not None:
+                await self.set_top_p(frame.top_p)
+            if frame.extra:
+                await self.set_extra(frame.extra)
         else:
             await self.push_frame(frame, direction)
 
@@ -464,7 +480,7 @@ class OpenAIAssistantContextAggregator(LLMAssistantContextAggregator):
                 await self._push_aggregation()
             else:
                 logger.warning(
-                    f"FunctionCallResultFrame tool_call_id does not match FunctionCallInProgressFrame tool_call_id"
+                    "FunctionCallResultFrame tool_call_id does not match FunctionCallInProgressFrame tool_call_id"
                 )
                 self._function_call_in_progress = None
                 self._function_call_result = None
diff --git a/src/pipecat/services/together.py b/src/pipecat/services/together.py
index b1365bc69..981aa6de2 100644
--- a/src/pipecat/services/together.py
+++ b/src/pipecat/services/together.py
@@ -7,37 +7,36 @@
 import json
 import re
 import uuid
-from pydantic import BaseModel, Field
-
-from typing import Any, Dict, List, Optional
-from dataclasses import dataclass
 from asyncio import CancelledError
+from dataclasses import dataclass
+from typing import Any, Dict, List, Optional
+
+from loguru import logger
+from pydantic import BaseModel, Field
 
 from pipecat.frames.frames import (
     Frame,
-    LLMModelUpdateFrame,
+    FunctionCallInProgressFrame,
+    FunctionCallResultFrame,
+    LLMFullResponseEndFrame,
+    LLMFullResponseStartFrame,
+    LLMMessagesFrame,
+    LLMUpdateSettingsFrame,
+    StartInterruptionFrame,
     TextFrame,
     UserImageRequestFrame,
-    LLMMessagesFrame,
-    LLMFullResponseStartFrame,
-    LLMFullResponseEndFrame,
-    FunctionCallResultFrame,
-    FunctionCallInProgressFrame,
-    StartInterruptionFrame,
 )
 from pipecat.metrics.metrics import LLMTokenUsage
-from pipecat.processors.frame_processor import FrameDirection
-from pipecat.services.ai_services import LLMService
+from pipecat.processors.aggregators.llm_response import (
+    LLMAssistantContextAggregator,
+    LLMUserContextAggregator,
+)
 from pipecat.processors.aggregators.openai_llm_context import (
     OpenAILLMContext,
     OpenAILLMContextFrame,
 )
-from pipecat.processors.aggregators.llm_response import (
-    LLMUserContextAggregator,
-    LLMAssistantContextAggregator,
-)
-
-from loguru import logger
+from pipecat.processors.frame_processor import FrameDirection
+from pipecat.services.ai_services import LLMService
 
 try:
     from together import AsyncTogether
@@ -188,7 +187,7 @@ class TogetherLLMService(LLMService):
                 if chunk.choices[0].finish_reason == "eos" and accumulating_function_call:
                     await self._extract_function_call(context, function_call_accumulator)
 
-        except CancelledError as e:
+        except CancelledError:
             # todo: implement token counting estimates for use when the user interrupts a long generation
             # we do this in the anthropic.py service
             raise
@@ -206,9 +205,24 @@ class TogetherLLMService(LLMService):
             context = frame.context
         elif isinstance(frame, LLMMessagesFrame):
             context = TogetherLLMContext.from_messages(frame.messages)
-        elif isinstance(frame, LLMModelUpdateFrame):
-            logger.debug(f"Switching LLM model to: [{frame.model}]")
-            self.set_model_name(frame.model)
+        elif isinstance(frame, LLMUpdateSettingsFrame):
+            if frame.model is not None:
+                logger.debug(f"Switching LLM model to: [{frame.model}]")
+                self.set_model_name(frame.model)
+            if frame.frequency_penalty is not None:
+                await self.set_frequency_penalty(frame.frequency_penalty)
+            if frame.max_tokens is not None:
+                await self.set_max_tokens(frame.max_tokens)
+            if frame.presence_penalty is not None:
+                await self.set_presence_penalty(frame.presence_penalty)
+            if frame.temperature is not None:
+                await self.set_temperature(frame.temperature)
+            if frame.top_k is not None:
+                await self.set_top_k(frame.top_k)
+            if frame.top_p is not None:
+                await self.set_top_p(frame.top_p)
+            if frame.extra:
+                await self.set_extra(frame.extra)
         else:
             await self.push_frame(frame, direction)
 
@@ -338,7 +352,7 @@ class TogetherAssistantContextAggregator(LLMAssistantContextAggregator):
                 await self._push_aggregation()
             else:
                 logger.warning(
-                    f"FunctionCallResultFrame tool_call_id does not match FunctionCallInProgressFrame tool_call_id"
+                    "FunctionCallResultFrame tool_call_id does not match FunctionCallInProgressFrame tool_call_id"
                 )
                 self._function_call_in_progress = None
                 self._function_call_result = None

From 7fe118ce639aeac6bd84c7c2e721f3cf6dd298e0 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Fri, 27 Sep 2024 11:22:03 -0400
Subject: [PATCH 098/135] Align use of language param across TTS services

---
 src/pipecat/services/azure.py      | 17 ++++++++++-------
 src/pipecat/services/elevenlabs.py | 10 +++++-----
 2 files changed, 15 insertions(+), 12 deletions(-)

diff --git a/src/pipecat/services/azure.py b/src/pipecat/services/azure.py
index c8fa095ab..a1349cefe 100644
--- a/src/pipecat/services/azure.py
+++ b/src/pipecat/services/azure.py
@@ -41,7 +41,10 @@ try:
         SpeechRecognizer,
         SpeechSynthesizer,
     )
-    from azure.cognitiveservices.speech.audio import AudioStreamFormat, PushAudioInputStream
+    from azure.cognitiveservices.speech.audio import (
+        AudioStreamFormat,
+        PushAudioInputStream,
+    )
     from azure.cognitiveservices.speech.dialog import AudioConfig
     from openai import AsyncAzureOpenAI
 except ModuleNotFoundError as e:
@@ -73,7 +76,7 @@ class AzureLLMService(BaseOpenAILLMService):
 class AzureTTSService(TTSService):
     class InputParams(BaseModel):
         emphasis: Optional[str] = None
-        language_code: Optional[str] = "en-US"
+        language: Optional[str] = "en-US"
         pitch: Optional[str] = None
         rate: Optional[str] = "1.05"
         role: Optional[str] = None
@@ -105,7 +108,7 @@ class AzureTTSService(TTSService):
 
     def _construct_ssml(self, text: str) -> str:
         ssml = (
-            f"<speak version='1.0' xml:lang='{self._params.language_code}' "
+            f"<speak version='1.0' xml:lang='{self._params.language}' "
             "xmlns='http://www.w3.org/2001/10/synthesis' "
             "xmlns:mstts='http://www.w3.org/2001/mstts'>"
             f"<voice name='{self._voice}'>"
@@ -155,9 +158,9 @@ class AzureTTSService(TTSService):
         logger.debug(f"Setting TTS emphasis to: [{emphasis}]")
         self._params.emphasis = emphasis
 
-    async def set_language_code(self, language_code: str):
-        logger.debug(f"Setting TTS language code to: [{language_code}]")
-        self._params.language_code = language_code
+    async def set_language(self, language: str):
+        logger.debug(f"Setting TTS language code to: [{language}]")
+        self._params.language = language
 
     async def set_pitch(self, pitch: str):
         logger.debug(f"Setting TTS pitch to: [{pitch}]")
@@ -187,7 +190,7 @@ class AzureTTSService(TTSService):
         valid_params = {
             "voice": self.set_voice,
             "emphasis": self.set_emphasis,
-            "language_code": self.set_language_code,
+            "language_code": self.set_language,
             "pitch": self.set_pitch,
             "rate": self.set_rate,
             "role": self.set_role,
diff --git a/src/pipecat/services/elevenlabs.py b/src/pipecat/services/elevenlabs.py
index 79d90bc58..ca4713f5f 100644
--- a/src/pipecat/services/elevenlabs.py
+++ b/src/pipecat/services/elevenlabs.py
@@ -72,7 +72,7 @@ def calculate_word_times(
 
 class ElevenLabsTTSService(AsyncWordTTSService):
     class InputParams(BaseModel):
-        language_code: Optional[str] = None
+        language: Optional[str] = None
         output_format: Literal["pcm_16000", "pcm_22050", "pcm_24000", "pcm_44100"] = "pcm_16000"
         optimize_streaming_latency: Optional[str] = None
         stability: Optional[float] = None
@@ -229,13 +229,13 @@ class ElevenLabsTTSService(AsyncWordTTSService):
             if self._params.optimize_streaming_latency:
                 url += f"&optimize_streaming_latency={self._params.optimize_streaming_latency}"
 
-            # language_code can only be used with the 'eleven_turbo_v2_5' model
-            if self._params.language_code:
+            # language can only be used with the 'eleven_turbo_v2_5' model
+            if self._params.language:
                 if model == "eleven_turbo_v2_5":
-                    url += f"&language_code={self._params.language_code}"
+                    url += f"&language_code={self._params.language}"
                 else:
                     logger.debug(
-                        f"Language code [{self._params.language_code}] not applied. Language codes can only be used with the 'eleven_turbo_v2_5' model."
+                        f"Language code [{self._params.language}] not applied. Language codes can only be used with the 'eleven_turbo_v2_5' model."
                     )
 
             self._websocket = await websockets.connect(url)

From d7555609fd752e27ea34879356613d50d4055e8b Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Fri, 27 Sep 2024 11:57:50 -0400
Subject: [PATCH 099/135] Add TTS update settings options

---
 src/pipecat/frames/frames.py        | 12 +++++-
 src/pipecat/services/ai_services.py | 62 ++++++++++++++++++++++++++++-
 2 files changed, 72 insertions(+), 2 deletions(-)

diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py
index 1b31b9c88..8059b904b 100644
--- a/src/pipecat/frames/frames.py
+++ b/src/pipecat/frames/frames.py
@@ -5,7 +5,7 @@
 #
 
 from dataclasses import dataclass, field
-from typing import Any, List, Optional, Tuple
+from typing import Any, List, Optional, Tuple, Union
 
 from pipecat.clocks.base_clock import BaseClock
 from pipecat.metrics.metrics import MetricsData
@@ -548,6 +548,16 @@ class TTSUpdateSettingsFrame(ControlFrame):
     model: Optional[str] = None
     voice: Optional[str] = None
     language: Optional[Language] = None
+    speed: Optional[Union[str, float]] = None
+    emotion: Optional[List[str]] = None
+    engine: Optional[str] = None
+    pitch: Optional[str] = None
+    rate: Optional[str] = None
+    volume: Optional[str] = None
+    emphasis: Optional[str] = None
+    style: Optional[str] = None
+    style_degree: Optional[str] = None
+    role: Optional[str] = None
 
 
 @dataclass
diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index 79e52531d..1cb91d6a2 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -8,7 +8,7 @@ import asyncio
 import io
 import wave
 from abc import abstractmethod
-from typing import AsyncGenerator, List, Optional, Tuple
+from typing import AsyncGenerator, List, Optional, Tuple, Union
 
 from loguru import logger
 
@@ -170,6 +170,46 @@ class TTSService(AIService):
     async def set_language(self, language: Language):
         pass
 
+    @abstractmethod
+    async def set_speed(self, speed: Union[str, float]):
+        pass
+
+    @abstractmethod
+    async def set_emotion(self, emotion: List[str]):
+        pass
+
+    @abstractmethod
+    async def set_engine(self, engine: str):
+        pass
+
+    @abstractmethod
+    async def set_pitch(self, pitch: str):
+        pass
+
+    @abstractmethod
+    async def set_rate(self, rate: str):
+        pass
+
+    @abstractmethod
+    async def set_volume(self, volume: str):
+        pass
+
+    @abstractmethod
+    async def set_emphasis(self, emphasis: str):
+        pass
+
+    @abstractmethod
+    async def set_style(self, style: str):
+        pass
+
+    @abstractmethod
+    async def set_style_degree(self, style_degree: str):
+        pass
+
+    @abstractmethod
+    async def set_role(self, role: str):
+        pass
+
     # Converts the text to audio.
     @abstractmethod
     async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
@@ -233,6 +273,26 @@ class TTSService(AIService):
                 await self.set_voice(frame.voice)
             if frame.language is not None:
                 await self.set_language(frame.language)
+            if frame.speed is not None:
+                await self.set_speed(frame.speed)
+            if frame.emotion is not None:
+                await self.set_emotion(frame.emotion)
+            if frame.engine is not None:
+                await self.set_engine(frame.engine)
+            if frame.pitch is not None:
+                await self.set_pitch(frame.pitch)
+            if frame.rate is not None:
+                await self.set_rate(frame.rate)
+            if frame.volume is not None:
+                await self.set_volume(frame.volume)
+            if frame.emphasis is not None:
+                await self.set_emphasis(frame.emphasis)
+            if frame.style is not None:
+                await self.set_style(frame.style)
+            if frame.style_degree is not None:
+                await self.set_style_degree(frame.style_degree)
+            if frame.role is not None:
+                await self.set_role(frame.role)
         else:
             await self.push_frame(frame, direction)
 

From 1f77863aef18c1f81d181d05e03924cbdf855e2a Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Mon, 30 Sep 2024 12:45:32 -0400
Subject: [PATCH 100/135] Code review feedback

---
 src/pipecat/services/ai_services.py | 66 ++++++++++++++++-------------
 src/pipecat/services/anthropic.py   | 29 +++++++------
 src/pipecat/services/openai.py      | 33 ++++++++-------
 src/pipecat/services/together.py    | 37 ++++++++--------
 4 files changed, 90 insertions(+), 75 deletions(-)

diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index 1cb91d6a2..ba78b24f8 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -248,6 +248,34 @@ class TTSService(AIService):
             # interrupted, the text is not added to the assistant context.
             await self.push_frame(TextFrame(text))
 
+    async def _update_tts_settings(self, frame: TTSUpdateSettingsFrame):
+        if frame.model is not None:
+            await self.set_model(frame.model)
+        if frame.voice is not None:
+            await self.set_voice(frame.voice)
+        if frame.language is not None:
+            await self.set_language(frame.language)
+        if frame.speed is not None:
+            await self.set_speed(frame.speed)
+        if frame.emotion is not None:
+            await self.set_emotion(frame.emotion)
+        if frame.engine is not None:
+            await self.set_engine(frame.engine)
+        if frame.pitch is not None:
+            await self.set_pitch(frame.pitch)
+        if frame.rate is not None:
+            await self.set_rate(frame.rate)
+        if frame.volume is not None:
+            await self.set_volume(frame.volume)
+        if frame.emphasis is not None:
+            await self.set_emphasis(frame.emphasis)
+        if frame.style is not None:
+            await self.set_style(frame.style)
+        if frame.style_degree is not None:
+            await self.set_style_degree(frame.style_degree)
+        if frame.role is not None:
+            await self.set_role(frame.role)
+
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
@@ -267,32 +295,7 @@ class TTSService(AIService):
         elif isinstance(frame, TTSSpeakFrame):
             await self._push_tts_frames(frame.text)
         elif isinstance(frame, TTSUpdateSettingsFrame):
-            if frame.model is not None:
-                await self.set_model(frame.model)
-            if frame.voice is not None:
-                await self.set_voice(frame.voice)
-            if frame.language is not None:
-                await self.set_language(frame.language)
-            if frame.speed is not None:
-                await self.set_speed(frame.speed)
-            if frame.emotion is not None:
-                await self.set_emotion(frame.emotion)
-            if frame.engine is not None:
-                await self.set_engine(frame.engine)
-            if frame.pitch is not None:
-                await self.set_pitch(frame.pitch)
-            if frame.rate is not None:
-                await self.set_rate(frame.rate)
-            if frame.volume is not None:
-                await self.set_volume(frame.volume)
-            if frame.emphasis is not None:
-                await self.set_emphasis(frame.emphasis)
-            if frame.style is not None:
-                await self.set_style(frame.style)
-            if frame.style_degree is not None:
-                await self.set_style_degree(frame.style_degree)
-            if frame.role is not None:
-                await self.set_role(frame.role)
+            await self._update_tts_settings(frame)
         else:
             await self.push_frame(frame, direction)
 
@@ -454,6 +457,12 @@ class STTService(AIService):
         """Returns transcript as a string"""
         pass
 
+    async def _update_stt_settings(self, frame: STTUpdateSettingsFrame):
+        if frame.model is not None:
+            await self.set_model(frame.model)
+        if frame.language is not None:
+            await self.set_language(frame.language)
+
     async def process_audio_frame(self, frame: AudioRawFrame):
         await self.process_generator(self.run_stt(frame.audio))
 
@@ -466,10 +475,7 @@ class STTService(AIService):
             # push a TextFrame. We don't really want to push audio frames down.
             await self.process_audio_frame(frame)
         elif isinstance(frame, STTUpdateSettingsFrame):
-            if frame.model is not None:
-                await self.set_model(frame.model)
-            if frame.language is not None:
-                await self.set_language(frame.language)
+            await self._update_stt_settings(frame)
         else:
             await self.push_frame(frame, direction)
 
diff --git a/src/pipecat/services/anthropic.py b/src/pipecat/services/anthropic.py
index 1c4cd284e..bc91e4e16 100644
--- a/src/pipecat/services/anthropic.py
+++ b/src/pipecat/services/anthropic.py
@@ -279,6 +279,21 @@ class AnthropicLLMService(LLMService):
                 cache_read_input_tokens=cache_read_input_tokens,
             )
 
+    async def _update_settings(self, frame: LLMUpdateSettingsFrame):
+        if frame.model is not None:
+            logger.debug(f"Switching LLM model to: [{frame.model}]")
+            self.set_model_name(frame.model)
+        if frame.max_tokens is not None:
+            await self.set_max_tokens(frame.max_tokens)
+        if frame.temperature is not None:
+            await self.set_temperature(frame.temperature)
+        if frame.top_k is not None:
+            await self.set_top_k(frame.top_k)
+        if frame.top_p is not None:
+            await self.set_top_p(frame.top_p)
+        if frame.extra:
+            await self.set_extra(frame.extra)
+
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
@@ -294,19 +309,7 @@ class AnthropicLLMService(LLMService):
             # to the context.
             context = AnthropicLLMContext.from_image_frame(frame)
         elif isinstance(frame, LLMUpdateSettingsFrame):
-            if frame.model is not None:
-                logger.debug(f"Switching LLM model to: [{frame.model}]")
-                self.set_model_name(frame.model)
-            if frame.max_tokens is not None:
-                await self.set_max_tokens(frame.max_tokens)
-            if frame.temperature is not None:
-                await self.set_temperature(frame.temperature)
-            if frame.top_k is not None:
-                await self.set_top_k(frame.top_k)
-            if frame.top_p is not None:
-                await self.set_top_p(frame.top_p)
-            if frame.extra:
-                await self.set_extra(frame.extra)
+            await self._update_settings(frame)
         elif isinstance(frame, LLMEnablePromptCachingFrame):
             logger.debug(f"Setting enable prompt caching to: [{frame.enable}]")
             self._enable_prompt_caching_beta = frame.enable
diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py
index a830b65a8..f0892b9ca 100644
--- a/src/pipecat/services/openai.py
+++ b/src/pipecat/services/openai.py
@@ -273,6 +273,23 @@ class BaseOpenAILLMService(LLMService):
             arguments=arguments,
         )
 
+    async def _update_settings(self, frame: LLMUpdateSettingsFrame):
+        if frame.model is not None:
+            logger.debug(f"Switching LLM model to: [{frame.model}]")
+            self.set_model_name(frame.model)
+        if frame.frequency_penalty is not None:
+            await self.set_frequency_penalty(frame.frequency_penalty)
+        if frame.presence_penalty is not None:
+            await self.set_presence_penalty(frame.presence_penalty)
+        if frame.seed is not None:
+            await self.set_seed(frame.seed)
+        if frame.temperature is not None:
+            await self.set_temperature(frame.temperature)
+        if frame.top_p is not None:
+            await self.set_top_p(frame.top_p)
+        if frame.extra:
+            await self.set_extra(frame.extra)
+
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
@@ -284,21 +301,7 @@ class BaseOpenAILLMService(LLMService):
         elif isinstance(frame, VisionImageRawFrame):
             context = OpenAILLMContext.from_image_frame(frame)
         elif isinstance(frame, LLMUpdateSettingsFrame):
-            if frame.model is not None:
-                logger.debug(f"Switching LLM model to: [{frame.model}]")
-                self.set_model_name(frame.model)
-            if frame.frequency_penalty is not None:
-                await self.set_frequency_penalty(frame.frequency_penalty)
-            if frame.presence_penalty is not None:
-                await self.set_presence_penalty(frame.presence_penalty)
-            if frame.seed is not None:
-                await self.set_seed(frame.seed)
-            if frame.temperature is not None:
-                await self.set_temperature(frame.temperature)
-            if frame.top_p is not None:
-                await self.set_top_p(frame.top_p)
-            if frame.extra:
-                await self.set_extra(frame.extra)
+            await self._update_settings(frame)
         else:
             await self.push_frame(frame, direction)
 
diff --git a/src/pipecat/services/together.py b/src/pipecat/services/together.py
index 981aa6de2..e4068ecfc 100644
--- a/src/pipecat/services/together.py
+++ b/src/pipecat/services/together.py
@@ -128,6 +128,25 @@ class TogetherLLMService(LLMService):
         logger.debug(f"Switching LLM extra to: [{extra}]")
         self._extra = extra
 
+    async def _update_settings(self, frame: LLMUpdateSettingsFrame):
+        if frame.model is not None:
+            logger.debug(f"Switching LLM model to: [{frame.model}]")
+            self.set_model_name(frame.model)
+        if frame.frequency_penalty is not None:
+            await self.set_frequency_penalty(frame.frequency_penalty)
+        if frame.max_tokens is not None:
+            await self.set_max_tokens(frame.max_tokens)
+        if frame.presence_penalty is not None:
+            await self.set_presence_penalty(frame.presence_penalty)
+        if frame.temperature is not None:
+            await self.set_temperature(frame.temperature)
+        if frame.top_k is not None:
+            await self.set_top_k(frame.top_k)
+        if frame.top_p is not None:
+            await self.set_top_p(frame.top_p)
+        if frame.extra:
+            await self.set_extra(frame.extra)
+
     async def _process_context(self, context: OpenAILLMContext):
         try:
             await self.push_frame(LLMFullResponseStartFrame())
@@ -206,23 +225,7 @@ class TogetherLLMService(LLMService):
         elif isinstance(frame, LLMMessagesFrame):
             context = TogetherLLMContext.from_messages(frame.messages)
         elif isinstance(frame, LLMUpdateSettingsFrame):
-            if frame.model is not None:
-                logger.debug(f"Switching LLM model to: [{frame.model}]")
-                self.set_model_name(frame.model)
-            if frame.frequency_penalty is not None:
-                await self.set_frequency_penalty(frame.frequency_penalty)
-            if frame.max_tokens is not None:
-                await self.set_max_tokens(frame.max_tokens)
-            if frame.presence_penalty is not None:
-                await self.set_presence_penalty(frame.presence_penalty)
-            if frame.temperature is not None:
-                await self.set_temperature(frame.temperature)
-            if frame.top_k is not None:
-                await self.set_top_k(frame.top_k)
-            if frame.top_p is not None:
-                await self.set_top_p(frame.top_p)
-            if frame.extra:
-                await self.set_extra(frame.extra)
+            await self._update_settings(frame)
         else:
             await self.push_frame(frame, direction)
 

From ed49cebf2c32ec522f2dc9d592ca63e103382ef9 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Mon, 30 Sep 2024 15:16:46 -0400
Subject: [PATCH 101/135] Set Google TTS default language to en-US

---
 src/pipecat/services/google.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/pipecat/services/google.py b/src/pipecat/services/google.py
index 53efd8c17..519f47028 100644
--- a/src/pipecat/services/google.py
+++ b/src/pipecat/services/google.py
@@ -153,7 +153,7 @@ class GoogleTTSService(TTSService):
         rate: Optional[str] = None
         volume: Optional[str] = None
         emphasis: Optional[Literal["strong", "moderate", "reduced", "none"]] = None
-        language: Optional[str] = None
+        language: Optional[str] = "en-US"
         gender: Optional[Literal["male", "female", "neutral"]] = None
         google_style: Optional[Literal["apologetic", "calm", "empathetic", "firm", "lively"]] = None
 

From 6b7f924af606bffd006a7e239af5be281ae9f83d Mon Sep 17 00:00:00 2001
From: Kwindla Hultman Kramer <kwindla@gmail.com>
Date: Mon, 30 Sep 2024 14:33:08 -0700
Subject: [PATCH 102/135] tts sentence aggregation fix

---
 .../07a-interruptible-anthropic.py            | 27 ++++++++-----------
 src/pipecat/services/ai_services.py           | 12 +++++----
 src/pipecat/utils/string.py                   |  6 ++---
 3 files changed, 21 insertions(+), 24 deletions(-)

diff --git a/examples/foundational/07a-interruptible-anthropic.py b/examples/foundational/07a-interruptible-anthropic.py
index 2bded2480..288cb1b31 100644
--- a/examples/foundational/07a-interruptible-anthropic.py
+++ b/examples/foundational/07a-interruptible-anthropic.py
@@ -5,29 +5,24 @@
 #
 
 import asyncio
-import aiohttp
 import os
 import sys
 
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+from runner import configure
+
 from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator,
-    LLMUserResponseAggregator,
-)
-from pipecat.services.cartesia import CartesiaTTSService
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.services.anthropic import AnthropicLLMService
+from pipecat.services.cartesia import CartesiaTTSService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 from pipecat.vad.silero import SileroVADAnalyzer
 
-from runner import configure
-
-from loguru import logger
-
-from dotenv import load_dotenv
-
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -69,17 +64,17 @@ async def main():
             },
         ]
 
-        tma_in = LLMUserResponseAggregator(messages)
-        tma_out = LLMAssistantResponseAggregator(messages)
+        context = OpenAILLMContext(messages)
+        context_aggregator = llm.create_context_aggregator(context)
 
         pipeline = Pipeline(
             [
                 transport.input(),  # Transport user input
-                tma_in,  # User responses
+                context_aggregator.user(),  # User responses
                 llm,  # LLM
                 tts,  # TTS
                 transport.output(),  # Transport bot output
-                tma_out,  # Assistant spoken responses
+                context_aggregator.assistant(),  # Assistant spoken responses
             ]
         )
 
diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index ba78b24f8..8386fccd5 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -228,16 +228,18 @@ class TTSService(AIService):
             text = frame.text
         else:
             self._current_sentence += frame.text
-            if match_endofsentence(self._current_sentence):
-                text = self._current_sentence
-                self._current_sentence = ""
+            eos_end_marker = match_endofsentence(self._current_sentence)
+            if eos_end_marker:
+                text = self._current_sentence[:eos_end_marker]
+                self._current_sentence = self._current_sentence[eos_end_marker:]
 
         if text:
             await self._push_tts_frames(text)
 
     async def _push_tts_frames(self, text: str):
-        text = text.strip()
-        if not text:
+        # Don't send only whitespace. This causes problems for some TTS models. But also don't
+        # strip all whitespace, as whitespace can influence prosody.
+        if not text.strip():
             return
 
         await self.start_processing_metrics()
diff --git a/src/pipecat/utils/string.py b/src/pipecat/utils/string.py
index cf9a22ad8..936764345 100644
--- a/src/pipecat/utils/string.py
+++ b/src/pipecat/utils/string.py
@@ -6,7 +6,6 @@
 
 import re
 
-
 ENDOFSENTENCE_PATTERN_STR = r"""
     (?<![A-Z])       # Negative lookbehind: not preceded by an uppercase letter (e.g., "U.S.A.")
     (?<!\d)          # Negative lookbehind: not preceded by a digit (e.g., "1. Let's start")
@@ -21,5 +20,6 @@ ENDOFSENTENCE_PATTERN_STR = r"""
 ENDOFSENTENCE_PATTERN = re.compile(ENDOFSENTENCE_PATTERN_STR, re.VERBOSE)
 
 
-def match_endofsentence(text: str) -> bool:
-    return ENDOFSENTENCE_PATTERN.search(text.rstrip()) is not None
+def match_endofsentence(text: str) -> int:
+    match = ENDOFSENTENCE_PATTERN.search(text.rstrip())
+    return match.end() if match else 0

From c8995b82e56d3d293057e12a7a46143e4becf71b Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Mon, 30 Sep 2024 10:05:56 -0700
Subject: [PATCH 103/135] all frame processors are asynchrnous

In this commit we make all frame processors asynchronous, that is, they have an
internal queue and they push frames using a task from that queue.
---
 CHANGELOG.md                                  |  22 +--
 .../foundational/05-sync-speech-and-image.py  |  10 +-
 .../05a-local-sync-speech-and-image.py        |   8 +-
 src/pipecat/processors/frame_processor.py     |  22 +--
 src/pipecat/processors/frameworks/rtvi.py     |   2 +-
 .../processors/gstreamer/pipeline_source.py   |   2 +-
 .../processors/idle_frame_processor.py        |   2 +-
 src/pipecat/processors/user_idle_processor.py |   2 +-
 src/pipecat/services/ai_services.py           | 155 ++++++++----------
 src/pipecat/services/cartesia.py              |   4 +-
 src/pipecat/services/elevenlabs.py            |   4 +-
 src/pipecat/services/gladia.py                |   2 +-
 src/pipecat/services/lmnt.py                  |   6 +-
 src/pipecat/transports/base_input.py          |   2 +-
 src/pipecat/transports/base_output.py         |   2 +-
 15 files changed, 113 insertions(+), 132 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 0f489556c..b59ed56c8 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -48,15 +48,10 @@ async def on_connected(processor):
   frames. To achieve that, each frame processor should only output frames from a
   single task.
 
-  In this version we introduce synchronous and asynchronous frame
-  processors. The synchronous processors push output frames from the same task
-  that they receive input frames, and therefore only pushing frames from one
-  task. Asynchronous frame processors can have internal tasks to perform things
-  asynchronously (e.g. receiving data from a websocket) but they also have a
-  single task where they push frames from.
-
-  By default, frame processors are synchronous. To change a frame processor to
-  asynchronous you only need to pass `sync=False` to the base class constructor.
+  In this version all the frame processors have their own task to push
+  frames. That is, when `push_frame()` is called the given frame will be put
+  into an internal queue (with the exception of system frames) and a frame
+  processor task will push it out.
 
 - Added pipeline clocks. A pipeline clock is used by the output transport to
   know when a frame needs to be presented. For that, all frames now have an
@@ -68,9 +63,7 @@ async def on_connected(processor):
   `SystemClock`). This clock will be passed to each frame processor via the
   `StartFrame`.
 
-- Added `CartesiaHttpTTSService`. This is a synchronous frame processor
-  (i.e. given an input text frame it will wait for the whole output before
-  returning).
+- Added `CartesiaHttpTTSService`.
 
 - `DailyTransport` now supports setting the audio bitrate to improve audio
   quality through the `DailyParams.audio_out_bitrate` parameter. The new
@@ -110,8 +103,9 @@ async def on_connected(processor):
   pipelines to be executed concurrently. The difference between a
   `SyncParallelPipeline` and a `ParallelPipeline` is that, given an input frame,
   the `SyncParallelPipeline` will wait for all the internal pipelines to
-  complete. This is achieved by ensuring all the processors in each of the
-  internal pipelines are synchronous.
+  complete. This is achieved by making sure the last processor in each of the
+  pipelines is synchronous (e.g. an HTTP-based service that waits for the
+  response).
 
 - `StartFrame` is back a system frame so we make sure it's processed immediately
   by all processors. `EndFrame` stays a control frame since it needs to be
diff --git a/examples/foundational/05-sync-speech-and-image.py b/examples/foundational/05-sync-speech-and-image.py
index dae860a92..5477d0691 100644
--- a/examples/foundational/05-sync-speech-and-image.py
+++ b/examples/foundational/05-sync-speech-and-image.py
@@ -86,13 +86,13 @@ async def main():
             ),
         )
 
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
+
         tts = CartesiaHttpTTSService(
             api_key=os.getenv("CARTESIA_API_KEY"),
             voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
         )
 
-        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
-
         imagegen = FalImageGenService(
             params=FalImageGenService.InputParams(image_size="square_hd"),
             aiohttp_session=session,
@@ -107,8 +107,10 @@ async def main():
         # that, each pipeline runs concurrently and `SyncParallelPipeline` will
         # wait for the input frame to be processed.
         #
-        # Note that `SyncParallelPipeline` requires all processors in it to be
-        # synchronous (which is the default for most processors).
+        # Note that `SyncParallelPipeline` requires the last processor in each
+        # of the pipelines to be synchronous. In this case, we use
+        # `CartesiaHttpTTSService` and `FalImageGenService` which make HTTP
+        # requests and wait for the response.
         pipeline = Pipeline(
             [
                 llm,  # LLM
diff --git a/examples/foundational/05a-local-sync-speech-and-image.py b/examples/foundational/05a-local-sync-speech-and-image.py
index 27c36f6ce..4a561c073 100644
--- a/examples/foundational/05a-local-sync-speech-and-image.py
+++ b/examples/foundational/05a-local-sync-speech-and-image.py
@@ -82,6 +82,7 @@ async def main():
                         self.frame = OutputAudioRawFrame(
                             bytes(self.audio), frame.sample_rate, frame.num_channels
                         )
+                    await self.push_frame(frame, direction)
 
             class ImageGrabber(FrameProcessor):
                 def __init__(self):
@@ -93,6 +94,7 @@ async def main():
 
                     if isinstance(frame, URLImageRawFrame):
                         self.frame = frame
+                    await self.push_frame(frame, direction)
 
             llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
@@ -121,8 +123,10 @@ async def main():
             # `SyncParallelPipeline` will wait for the input frame to be
             # processed.
             #
-            # Note that `SyncParallelPipeline` requires all processors in it to
-            # be synchronous (which is the default for most processors).
+            # Note that `SyncParallelPipeline` requires the last processor in
+            # each of the pipelines to be synchronous. In this case, we use
+            # `CartesiaHttpTTSService` and `FalImageGenService` which make HTTP
+            # requests and wait for the response.
             pipeline = Pipeline(
                 [
                     llm,  # LLM
diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py
index f71e066d7..f458f43ff 100644
--- a/src/pipecat/processors/frame_processor.py
+++ b/src/pipecat/processors/frame_processor.py
@@ -37,7 +37,6 @@ class FrameProcessor:
         *,
         name: str | None = None,
         metrics: FrameProcessorMetrics | None = None,
-        sync: bool = True,
         loop: asyncio.AbstractEventLoop | None = None,
         **kwargs,
     ):
@@ -47,7 +46,6 @@ class FrameProcessor:
         self._prev: "FrameProcessor" | None = None
         self._next: "FrameProcessor" | None = None
         self._loop: asyncio.AbstractEventLoop = loop or asyncio.get_running_loop()
-        self._sync = sync
 
         self._event_handlers: dict = {}
 
@@ -66,11 +64,8 @@ class FrameProcessor:
 
         # Every processor in Pipecat should only output frames from a single
         # task. This avoid problems like audio overlapping. System frames are
-        # the exception to this rule.
-        #
-        # This create this task.
-        if not self._sync:
-            self.__create_push_task()
+        # the exception to this rule. This create this task.
+        self.__create_push_task()
 
     @property
     def interruptions_allowed(self):
@@ -167,7 +162,7 @@ class FrameProcessor:
         await self.push_frame(error, FrameDirection.UPSTREAM)
 
     async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM):
-        if self._sync or isinstance(frame, SystemFrame):
+        if isinstance(frame, SystemFrame):
             await self.__internal_push_frame(frame, direction)
         else:
             await self.__push_queue.put((frame, direction))
@@ -194,13 +189,12 @@ class FrameProcessor:
     #
 
     async def _start_interruption(self):
-        if not self._sync:
-            # Cancel the task. This will stop pushing frames downstream.
-            self.__push_frame_task.cancel()
-            await self.__push_frame_task
+        # Cancel the task. This will stop pushing frames downstream.
+        self.__push_frame_task.cancel()
+        await self.__push_frame_task
 
-            # Create a new queue and task.
-            self.__create_push_task()
+        # Create a new queue and task.
+        self.__create_push_task()
 
     async def _stop_interruption(self):
         # Nothing to do right now.
diff --git a/src/pipecat/processors/frameworks/rtvi.py b/src/pipecat/processors/frameworks/rtvi.py
index f88660f60..7a6054c3c 100644
--- a/src/pipecat/processors/frameworks/rtvi.py
+++ b/src/pipecat/processors/frameworks/rtvi.py
@@ -516,7 +516,7 @@ class RTVIProcessor(FrameProcessor):
         params: RTVIProcessorParams = RTVIProcessorParams(),
         **kwargs,
     ):
-        super().__init__(sync=False, **kwargs)
+        super().__init__(**kwargs)
         self._config = config
         self._params = params
 
diff --git a/src/pipecat/processors/gstreamer/pipeline_source.py b/src/pipecat/processors/gstreamer/pipeline_source.py
index 9f8471153..426eab50a 100644
--- a/src/pipecat/processors/gstreamer/pipeline_source.py
+++ b/src/pipecat/processors/gstreamer/pipeline_source.py
@@ -44,7 +44,7 @@ class GStreamerPipelineSource(FrameProcessor):
         clock_sync: bool = True
 
     def __init__(self, *, pipeline: str, out_params: OutputParams = OutputParams(), **kwargs):
-        super().__init__(sync=False, **kwargs)
+        super().__init__(**kwargs)
 
         self._out_params = out_params
 
diff --git a/src/pipecat/processors/idle_frame_processor.py b/src/pipecat/processors/idle_frame_processor.py
index 576cb9087..e674b6b84 100644
--- a/src/pipecat/processors/idle_frame_processor.py
+++ b/src/pipecat/processors/idle_frame_processor.py
@@ -26,7 +26,7 @@ class IdleFrameProcessor(FrameProcessor):
         types: List[type] = [],
         **kwargs,
     ):
-        super().__init__(sync=False, **kwargs)
+        super().__init__(**kwargs)
 
         self._callback = callback
         self._timeout = timeout
diff --git a/src/pipecat/processors/user_idle_processor.py b/src/pipecat/processors/user_idle_processor.py
index 31d49cf5a..507dcb495 100644
--- a/src/pipecat/processors/user_idle_processor.py
+++ b/src/pipecat/processors/user_idle_processor.py
@@ -31,7 +31,7 @@ class UserIdleProcessor(FrameProcessor):
         timeout: float,
         **kwargs,
     ):
-        super().__init__(sync=False, **kwargs)
+        super().__init__(**kwargs)
 
         self._callback = callback
         self._timeout = timeout
diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index ba78b24f8..d27a3277d 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -144,6 +144,10 @@ class TTSService(AIService):
         # if True, TTSService will push TextFrames and LLMFullResponseEndFrames,
         # otherwise subclass must do it
         push_text_frames: bool = True,
+        # if True, TTSService will push TTSStoppedFrames, otherwise subclass must do it
+        push_stop_frames: bool = False,
+        # if push_stop_frames is True, wait for this idle period before pushing TTSStoppedFrame
+        stop_frame_timeout_s: float = 1.0,
         # TTS output sample rate
         sample_rate: int = 16000,
         **kwargs,
@@ -151,9 +155,15 @@ class TTSService(AIService):
         super().__init__(**kwargs)
         self._aggregate_sentences: bool = aggregate_sentences
         self._push_text_frames: bool = push_text_frames
-        self._current_sentence: str = ""
+        self._push_stop_frames: bool = push_stop_frames
+        self._stop_frame_timeout_s: float = stop_frame_timeout_s
         self._sample_rate: int = sample_rate
 
+        self._stop_frame_task: Optional[asyncio.Task] = None
+        self._stop_frame_queue: asyncio.Queue = asyncio.Queue()
+
+        self._current_sentence: str = ""
+
     @property
     def sample_rate(self) -> int:
         return self._sample_rate
@@ -210,13 +220,72 @@ class TTSService(AIService):
     async def set_role(self, role: str):
         pass
 
+    @abstractmethod
+    async def flush_audio(self):
+        pass
+
     # Converts the text to audio.
     @abstractmethod
     async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
         pass
 
+    async def start(self, frame: StartFrame):
+        await super().start(frame)
+        if self._push_stop_frames:
+            self._stop_frame_task = self.get_event_loop().create_task(self._stop_frame_handler())
+
+    async def stop(self, frame: EndFrame):
+        await super().stop(frame)
+        if self._stop_frame_task:
+            self._stop_frame_task.cancel()
+            await self._stop_frame_task
+            self._stop_frame_task = None
+
+    async def cancel(self, frame: CancelFrame):
+        await super().cancel(frame)
+        if self._stop_frame_task:
+            self._stop_frame_task.cancel()
+            await self._stop_frame_task
+            self._stop_frame_task = None
+
     async def say(self, text: str):
         await self.process_frame(TextFrame(text=text), FrameDirection.DOWNSTREAM)
+        await self.flush_audio()
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        if isinstance(frame, TextFrame):
+            await self._process_text_frame(frame)
+        elif isinstance(frame, StartInterruptionFrame):
+            await self._handle_interruption(frame, direction)
+        elif isinstance(frame, LLMFullResponseEndFrame) or isinstance(frame, EndFrame):
+            sentence = self._current_sentence
+            self._current_sentence = ""
+            await self._push_tts_frames(sentence)
+            if isinstance(frame, LLMFullResponseEndFrame):
+                if self._push_text_frames:
+                    await self.push_frame(frame, direction)
+            else:
+                await self.push_frame(frame, direction)
+        elif isinstance(frame, TTSSpeakFrame):
+            await self._push_tts_frames(frame.text)
+            await self.flush_audio()
+        elif isinstance(frame, TTSUpdateSettingsFrame):
+            await self._update_tts_settings(frame)
+        else:
+            await self.push_frame(frame, direction)
+
+    async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM):
+        await super().push_frame(frame, direction)
+
+        if self._push_stop_frames and (
+            isinstance(frame, StartInterruptionFrame)
+            or isinstance(frame, TTSStartedFrame)
+            or isinstance(frame, TTSAudioRawFrame)
+            or isinstance(frame, TTSStoppedFrame)
+        ):
+            await self._stop_frame_queue.put(frame)
 
     async def _handle_interruption(self, frame: StartInterruptionFrame, direction: FrameDirection):
         self._current_sentence = ""
@@ -276,88 +345,6 @@ class TTSService(AIService):
         if frame.role is not None:
             await self.set_role(frame.role)
 
-    async def process_frame(self, frame: Frame, direction: FrameDirection):
-        await super().process_frame(frame, direction)
-
-        if isinstance(frame, TextFrame):
-            await self._process_text_frame(frame)
-        elif isinstance(frame, StartInterruptionFrame):
-            await self._handle_interruption(frame, direction)
-        elif isinstance(frame, LLMFullResponseEndFrame) or isinstance(frame, EndFrame):
-            sentence = self._current_sentence
-            self._current_sentence = ""
-            await self._push_tts_frames(sentence)
-            if isinstance(frame, LLMFullResponseEndFrame):
-                if self._push_text_frames:
-                    await self.push_frame(frame, direction)
-            else:
-                await self.push_frame(frame, direction)
-        elif isinstance(frame, TTSSpeakFrame):
-            await self._push_tts_frames(frame.text)
-        elif isinstance(frame, TTSUpdateSettingsFrame):
-            await self._update_tts_settings(frame)
-        else:
-            await self.push_frame(frame, direction)
-
-
-class AsyncTTSService(TTSService):
-    def __init__(
-        self,
-        # if True, TTSService will push TTSStoppedFrames, otherwise subclass must do it
-        push_stop_frames: bool = False,
-        # if push_stop_frames is True, wait for this idle period before pushing TTSStoppedFrame
-        stop_frame_timeout_s: float = 1.0,
-        **kwargs,
-    ):
-        super().__init__(sync=False, **kwargs)
-        self._push_stop_frames: bool = push_stop_frames
-        self._stop_frame_timeout_s: float = stop_frame_timeout_s
-        self._stop_frame_task: Optional[asyncio.Task] = None
-        self._stop_frame_queue: asyncio.Queue = asyncio.Queue()
-
-    @abstractmethod
-    async def flush_audio(self):
-        pass
-
-    async def say(self, text: str):
-        await super().say(text)
-        await self.flush_audio()
-
-    async def start(self, frame: StartFrame):
-        await super().start(frame)
-        if self._push_stop_frames:
-            self._stop_frame_task = self.get_event_loop().create_task(self._stop_frame_handler())
-
-    async def stop(self, frame: EndFrame):
-        await super().stop(frame)
-        if self._stop_frame_task:
-            self._stop_frame_task.cancel()
-            await self._stop_frame_task
-            self._stop_frame_task = None
-
-    async def cancel(self, frame: CancelFrame):
-        await super().cancel(frame)
-        if self._stop_frame_task:
-            self._stop_frame_task.cancel()
-            await self._stop_frame_task
-            self._stop_frame_task = None
-
-    async def process_frame(self, frame: Frame, direction: FrameDirection):
-        await super().process_frame(frame, direction)
-        if isinstance(frame, TTSSpeakFrame):
-            await self.flush_audio()
-
-    async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM):
-        await super().push_frame(frame, direction)
-
-        if self._push_stop_frames and (
-            isinstance(frame, StartInterruptionFrame)
-            or isinstance(frame, TTSStartedFrame)
-            or isinstance(frame, TTSAudioRawFrame)
-            or isinstance(frame, TTSStoppedFrame)
-        ):
-            await self._stop_frame_queue.put(frame)
-
     async def _stop_frame_handler(self):
         try:
             has_started = False
@@ -378,7 +365,7 @@ class AsyncTTSService(TTSService):
             pass
 
 
-class AsyncWordTTSService(AsyncTTSService):
+class WordTTSService(TTSService):
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
         self._initial_word_timestamp = -1
diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index e38d56db3..5f798b1e5 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -26,7 +26,7 @@ from pipecat.frames.frames import (
 )
 from pipecat.processors.frame_processor import FrameDirection
 from pipecat.transcriptions.language import Language
-from pipecat.services.ai_services import AsyncWordTTSService, TTSService
+from pipecat.services.ai_services import WordTTSService, TTSService
 
 from loguru import logger
 
@@ -61,7 +61,7 @@ def language_to_cartesia_language(language: Language) -> str | None:
     return None
 
 
-class CartesiaTTSService(AsyncWordTTSService):
+class CartesiaTTSService(WordTTSService):
     class InputParams(BaseModel):
         encoding: Optional[str] = "pcm_s16le"
         sample_rate: Optional[int] = 16000
diff --git a/src/pipecat/services/elevenlabs.py b/src/pipecat/services/elevenlabs.py
index ca4713f5f..611f2a024 100644
--- a/src/pipecat/services/elevenlabs.py
+++ b/src/pipecat/services/elevenlabs.py
@@ -23,7 +23,7 @@ from pipecat.frames.frames import (
     TTSStoppedFrame,
 )
 from pipecat.processors.frame_processor import FrameDirection
-from pipecat.services.ai_services import AsyncWordTTSService
+from pipecat.services.ai_services import WordTTSService
 
 # See .env.example for ElevenLabs configuration needed
 try:
@@ -70,7 +70,7 @@ def calculate_word_times(
     return word_times
 
 
-class ElevenLabsTTSService(AsyncWordTTSService):
+class ElevenLabsTTSService(WordTTSService):
     class InputParams(BaseModel):
         language: Optional[str] = None
         output_format: Literal["pcm_16000", "pcm_22050", "pcm_24000", "pcm_44100"] = "pcm_16000"
diff --git a/src/pipecat/services/gladia.py b/src/pipecat/services/gladia.py
index 12183adde..a590d73cf 100644
--- a/src/pipecat/services/gladia.py
+++ b/src/pipecat/services/gladia.py
@@ -51,7 +51,7 @@ class GladiaSTTService(STTService):
         params: InputParams = InputParams(),
         **kwargs,
     ):
-        super().__init__(sync=False, **kwargs)
+        super().__init__(**kwargs)
 
         self._api_key = api_key
         self._url = url
diff --git a/src/pipecat/services/lmnt.py b/src/pipecat/services/lmnt.py
index 1ac24d731..8f18002c5 100644
--- a/src/pipecat/services/lmnt.py
+++ b/src/pipecat/services/lmnt.py
@@ -20,7 +20,7 @@ from pipecat.frames.frames import (
     TTSStartedFrame,
     TTSStoppedFrame,
 )
-from pipecat.services.ai_services import AsyncTTSService
+from pipecat.services.ai_services import TTSService
 
 from loguru import logger
 
@@ -35,7 +35,7 @@ except ModuleNotFoundError as e:
     raise Exception(f"Missing module: {e}")
 
 
-class LmntTTSService(AsyncTTSService):
+class LmntTTSService(TTSService):
     def __init__(
         self,
         *,
@@ -47,7 +47,7 @@ class LmntTTSService(AsyncTTSService):
     ):
         # Let TTSService produce TTSStoppedFrames after a short delay of
         # no activity.
-        super().__init__(sync=False, push_stop_frames=True, sample_rate=sample_rate, **kwargs)
+        super().__init__(push_stop_frames=True, sample_rate=sample_rate, **kwargs)
 
         self._api_key = api_key
         self._voice_id = voice_id
diff --git a/src/pipecat/transports/base_input.py b/src/pipecat/transports/base_input.py
index df7babff1..710f8108a 100644
--- a/src/pipecat/transports/base_input.py
+++ b/src/pipecat/transports/base_input.py
@@ -31,7 +31,7 @@ from loguru import logger
 
 class BaseInputTransport(FrameProcessor):
     def __init__(self, params: TransportParams, **kwargs):
-        super().__init__(sync=False, **kwargs)
+        super().__init__(**kwargs)
 
         self._params = params
 
diff --git a/src/pipecat/transports/base_output.py b/src/pipecat/transports/base_output.py
index 941a3505a..c3b9c792b 100644
--- a/src/pipecat/transports/base_output.py
+++ b/src/pipecat/transports/base_output.py
@@ -43,7 +43,7 @@ from pipecat.utils.time import nanoseconds_to_seconds
 
 class BaseOutputTransport(FrameProcessor):
     def __init__(self, params: TransportParams, **kwargs):
-        super().__init__(sync=False, **kwargs)
+        super().__init__(**kwargs)
 
         self._params = params
 

From a90ebdfe7c881d5fe4d3c6850bfc556f9d1a3c04 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Mon, 30 Sep 2024 11:36:59 -0700
Subject: [PATCH 104/135] syncparallelpipeline: fix now that all frames are
 asynchronous

---
 .../pipeline/sync_parallel_pipeline.py        | 66 ++++++++++++++++---
 1 file changed, 56 insertions(+), 10 deletions(-)

diff --git a/src/pipecat/pipeline/sync_parallel_pipeline.py b/src/pipecat/pipeline/sync_parallel_pipeline.py
index 854cea89d..20f4275e4 100644
--- a/src/pipecat/pipeline/sync_parallel_pipeline.py
+++ b/src/pipecat/pipeline/sync_parallel_pipeline.py
@@ -6,17 +6,25 @@
 
 import asyncio
 
+from dataclasses import dataclass
 from itertools import chain
 from typing import List
 
+from pipecat.frames.frames import ControlFrame, EndFrame, Frame, SystemFrame
 from pipecat.pipeline.base_pipeline import BasePipeline
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
-from pipecat.frames.frames import Frame
 
 from loguru import logger
 
 
+@dataclass
+class SyncFrame(ControlFrame):
+    """This frame is used to know when the internal pipelines have finished."""
+
+    pass
+
+
 class Source(FrameProcessor):
     def __init__(self, upstream_queue: asyncio.Queue):
         super().__init__()
@@ -67,13 +75,16 @@ class SyncParallelPipeline(BasePipeline):
                 raise TypeError(f"SyncParallelPipeline argument {processors} is not a list")
 
             # We add a source at the beginning of the pipeline and a sink at the end.
-            source = Source(self._up_queue)
-            sink = Sink(self._down_queue)
+            up_queue = asyncio.Queue()
+            down_queue = asyncio.Queue()
+            source = Source(up_queue)
+            sink = Sink(down_queue)
             processors: List[FrameProcessor] = [source] + processors + [sink]
 
-            # Keep track of sources and sinks.
-            self._sources.append(source)
-            self._sinks.append(sink)
+            # Keep track of sources and sinks. We also keep the output queue of
+            # the source and the sinks so we can use it later.
+            self._sources.append({"processor": source, "queue": down_queue})
+            self._sinks.append({"processor": sink, "queue": up_queue})
 
             # Create pipeline
             pipeline = Pipeline(processors)
@@ -94,17 +105,52 @@ class SyncParallelPipeline(BasePipeline):
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
+        # The last processor of each pipeline needs to be synchronous otherwise
+        # this element won't work. Since, we know it should be synchronous we
+        # push a SyncFrame. Since frames are ordered we know this frame will be
+        # pushed after the synchronous processor has pushed its data allowing us
+        # to synchrnonize all the internal pipelines by waiting for the
+        # SyncFrame in all of them.
+        async def wait_for_sync(
+            obj, main_queue: asyncio.Queue, frame: Frame, direction: FrameDirection
+        ):
+            processor = obj["processor"]
+            queue = obj["queue"]
+
+            await processor.process_frame(frame, direction)
+
+            if isinstance(frame, (SystemFrame, EndFrame)):
+                new_frame = await queue.get()
+                if isinstance(new_frame, (SystemFrame, EndFrame)):
+                    await main_queue.put(new_frame)
+                else:
+                    while not isinstance(new_frame, (SystemFrame, EndFrame)):
+                        await main_queue.put(new_frame)
+                        queue.task_done()
+                        new_frame = await queue.get()
+            else:
+                await processor.process_frame(SyncFrame(), direction)
+                new_frame = await queue.get()
+                while not isinstance(new_frame, SyncFrame):
+                    await main_queue.put(new_frame)
+                    queue.task_done()
+                    new_frame = await queue.get()
+
         if direction == FrameDirection.UPSTREAM:
             # If we get an upstream frame we process it in each sink.
-            await asyncio.gather(*[s.process_frame(frame, direction) for s in self._sinks])
+            await asyncio.gather(
+                *[wait_for_sync(s, self._up_queue, frame, direction) for s in self._sinks]
+            )
         elif direction == FrameDirection.DOWNSTREAM:
             # If we get a downstream frame we process it in each source.
-            await asyncio.gather(*[s.process_frame(frame, direction) for s in self._sources])
+            await asyncio.gather(
+                *[wait_for_sync(s, self._down_queue, frame, direction) for s in self._sources]
+            )
 
         seen_ids = set()
         while not self._up_queue.empty():
             frame = await self._up_queue.get()
-            if frame and frame.id not in seen_ids:
+            if frame.id not in seen_ids:
                 await self.push_frame(frame, FrameDirection.UPSTREAM)
                 seen_ids.add(frame.id)
             self._up_queue.task_done()
@@ -112,7 +158,7 @@ class SyncParallelPipeline(BasePipeline):
         seen_ids = set()
         while not self._down_queue.empty():
             frame = await self._down_queue.get()
-            if frame and frame.id not in seen_ids:
+            if frame.id not in seen_ids:
                 await self.push_frame(frame, FrameDirection.DOWNSTREAM)
                 seen_ids.add(frame.id)
             self._down_queue.task_done()

From d080a31a5ca322364f5645aafa3727d47ea32f64 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Mon, 30 Sep 2024 11:37:26 -0700
Subject: [PATCH 105/135] tests: fix langchanin tests

---
 tests/test_langchain.py | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/tests/test_langchain.py b/tests/test_langchain.py
index fb222205b..d30d213bd 100644
--- a/tests/test_langchain.py
+++ b/tests/test_langchain.py
@@ -7,9 +7,9 @@
 import unittest
 
 from pipecat.frames.frames import (
+    EndFrame,
     LLMFullResponseEndFrame,
     LLMFullResponseStartFrame,
-    StopTaskFrame,
     TextFrame,
     TranscriptionFrame,
     UserStartedSpeakingFrame,
@@ -32,6 +32,7 @@ from langchain_core.language_models import FakeStreamingListLLM
 class TestLangchain(unittest.IsolatedAsyncioTestCase):
     class MockProcessor(FrameProcessor):
         def __init__(self, name):
+            super().__init__()
             self.name = name
             self.token: list[str] = []
             # Start collecting tokens when we see the start frame
@@ -55,13 +56,13 @@ class TestLangchain(unittest.IsolatedAsyncioTestCase):
     def setUp(self):
         self.expected_response = "Hello dear human"
         self.fake_llm = FakeStreamingListLLM(responses=[self.expected_response])
-        self.mock_proc = self.MockProcessor("token_collector")
 
     async def test_langchain(self):
         messages = [("system", "Say hello to {name}"), ("human", "{input}")]
         prompt = ChatPromptTemplate.from_messages(messages).partial(name="Thomas")
         chain = prompt | self.fake_llm
         proc = LangchainProcessor(chain=chain)
+        self.mock_proc = self.MockProcessor("token_collector")
 
         tma_in = LLMUserResponseAggregator(messages)
         tma_out = LLMAssistantResponseAggregator(messages)
@@ -81,7 +82,7 @@ class TestLangchain(unittest.IsolatedAsyncioTestCase):
                 UserStartedSpeakingFrame(),
                 TranscriptionFrame(text="Hi World", user_id="user", timestamp="now"),
                 UserStoppedSpeakingFrame(),
-                StopTaskFrame(),
+                EndFrame(),
             ]
         )
 

From 4d1e370e02b411142ad78bb80743fd2d58efccb7 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Mon, 30 Sep 2024 11:56:59 -0700
Subject: [PATCH 106/135] pipeline(task): since everything is async tasks
 should wait for EndFrame

---
 src/pipecat/pipeline/task.py | 43 ++++++++++++++++++++++++++++--------
 1 file changed, 34 insertions(+), 9 deletions(-)

diff --git a/src/pipecat/pipeline/task.py b/src/pipecat/pipeline/task.py
index f79ff6f39..96845430d 100644
--- a/src/pipecat/pipeline/task.py
+++ b/src/pipecat/pipeline/task.py
@@ -69,6 +69,19 @@ class Source(FrameProcessor):
                 await self._up_queue.put(StopTaskFrame())
 
 
+class Sink(FrameProcessor):
+    def __init__(self, down_queue: asyncio.Queue):
+        super().__init__()
+        self._down_queue = down_queue
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        # We really just want to know when the EndFrame reached the sink.
+        if isinstance(frame, EndFrame):
+            await self._down_queue.put(frame)
+
+
 class PipelineTask:
     def __init__(
         self,
@@ -84,12 +97,16 @@ class PipelineTask:
         self._params = params
         self._finished = False
 
-        self._down_queue = asyncio.Queue()
         self._up_queue = asyncio.Queue()
+        self._down_queue = asyncio.Queue()
+        self._push_queue = asyncio.Queue()
 
         self._source = Source(self._up_queue)
         self._source.link(pipeline)
 
+        self._sink = Sink(self._down_queue)
+        pipeline.link(self._sink)
+
     def has_finished(self):
         return self._finished
 
@@ -103,19 +120,19 @@ class PipelineTask:
         # out-of-band from the main streaming task which is what we want since
         # we want to cancel right away.
         await self._source.push_frame(CancelFrame())
-        self._process_down_task.cancel()
+        self._process_push_task.cancel()
         self._process_up_task.cancel()
-        await self._process_down_task
+        await self._process_push_task
         await self._process_up_task
 
     async def run(self):
         self._process_up_task = asyncio.create_task(self._process_up_queue())
-        self._process_down_task = asyncio.create_task(self._process_down_queue())
-        await asyncio.gather(self._process_up_task, self._process_down_task)
+        self._process_push_task = asyncio.create_task(self._process_push_queue())
+        await asyncio.gather(self._process_up_task, self._process_push_task)
         self._finished = True
 
     async def queue_frame(self, frame: Frame):
-        await self._down_queue.put(frame)
+        await self._push_queue.put(frame)
 
     async def queue_frames(self, frames: Iterable[Frame] | AsyncIterable[Frame]):
         if isinstance(frames, AsyncIterable):
@@ -133,7 +150,7 @@ class PipelineTask:
             data.append(ProcessingMetricsData(processor=p.name, value=0.0))
         return MetricsFrame(data=data)
 
-    async def _process_down_queue(self):
+    async def _process_push_queue(self):
         self._clock.start()
 
         start_frame = StartFrame(
@@ -154,11 +171,13 @@ class PipelineTask:
         should_cleanup = True
         while running:
             try:
-                frame = await self._down_queue.get()
+                frame = await self._push_queue.get()
                 await self._source.process_frame(frame, FrameDirection.DOWNSTREAM)
+                if isinstance(frame, EndFrame):
+                    await self._wait_for_endframe()
                 running = not (isinstance(frame, StopTaskFrame) or isinstance(frame, EndFrame))
                 should_cleanup = not isinstance(frame, StopTaskFrame)
-                self._down_queue.task_done()
+                self._push_queue.task_done()
             except asyncio.CancelledError:
                 break
         # Cleanup only if we need to.
@@ -169,6 +188,12 @@ class PipelineTask:
         self._process_up_task.cancel()
         await self._process_up_task
 
+    async def _wait_for_endframe(self):
+        # NOTE(aleix): the Sink element just pushes EndFrames to the down queue,
+        # so just wait for it. In the future we might do something else here,
+        # but for now this is fine.
+        await self._down_queue.get()
+
     async def _process_up_queue(self):
         while True:
             try:

From f8a75cede901c9f614e83c4d62ce24fc7a97a410 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Mon, 30 Sep 2024 18:22:38 -0400
Subject: [PATCH 107/135] Update daily-python to 0.11.0

---
 pyproject.toml        | 2 +-
 test-requirements.txt | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index e31755d50..a29697bdb 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -38,7 +38,7 @@ anthropic = [ "anthropic~=0.34.0" ]
 aws = [ "boto3~=1.35.27" ]
 azure = [ "azure-cognitiveservices-speech~=1.40.0" ]
 cartesia = [ "cartesia~=1.0.13", "websockets~=12.0" ]
-daily = [ "daily-python~=0.10.1" ]
+daily = [ "daily-python~=0.11.0" ]
 deepgram = [ "deepgram-sdk~=3.5.0" ]
 elevenlabs = [ "websockets~=12.0" ]
 examples = [ "python-dotenv~=1.0.1", "flask~=3.0.3", "flask_cors~=4.0.1" ]
diff --git a/test-requirements.txt b/test-requirements.txt
index 8c7db7377..07ef45054 100644
--- a/test-requirements.txt
+++ b/test-requirements.txt
@@ -2,7 +2,7 @@ aiohttp~=3.10.3
 anthropic~=0.30.0
 azure-cognitiveservices-speech~=1.40.0
 boto3~=1.35.27
-daily-python~=0.10.1
+daily-python~=0.11.0
 deepgram-sdk~=3.5.0
 fal-client~=0.4.1
 fastapi~=0.112.1

From 69c7edd60c8d586bf786f7f442e2217d13d9db42 Mon Sep 17 00:00:00 2001
From: Kwindla Hultman Kramer <kwindla@gmail.com>
Date: Sat, 28 Sep 2024 21:37:03 -0700
Subject: [PATCH 108/135] pushing context frames from assistant aggregators

---
 src/pipecat/services/anthropic.py | 5 ++++-
 src/pipecat/services/openai.py    | 5 ++++-
 src/pipecat/services/together.py  | 5 ++++-
 3 files changed, 12 insertions(+), 3 deletions(-)

diff --git a/src/pipecat/services/anthropic.py b/src/pipecat/services/anthropic.py
index bc91e4e16..6a535ef15 100644
--- a/src/pipecat/services/anthropic.py
+++ b/src/pipecat/services/anthropic.py
@@ -579,7 +579,7 @@ class AnthropicAssistantContextAggregator(LLMAssistantContextAggregator):
         run_llm = False
 
         aggregation = self._aggregation
-        self._aggregation = ""
+        self._reset()
 
         try:
             if self._function_call_result:
@@ -630,5 +630,8 @@ class AnthropicAssistantContextAggregator(LLMAssistantContextAggregator):
             if run_llm:
                 await self._user_context_aggregator.push_context_frame()
 
+            frame = OpenAILLMContextFrame(self._context)
+            await self.push_frame(frame)
+
         except Exception as e:
             logger.error(f"Error processing frame: {e}")
diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py
index f0892b9ca..99d2d7497 100644
--- a/src/pipecat/services/openai.py
+++ b/src/pipecat/services/openai.py
@@ -495,7 +495,7 @@ class OpenAIAssistantContextAggregator(LLMAssistantContextAggregator):
         run_llm = False
 
         aggregation = self._aggregation
-        self._aggregation = ""
+        self._reset()
 
         try:
             if self._function_call_result:
@@ -531,5 +531,8 @@ class OpenAIAssistantContextAggregator(LLMAssistantContextAggregator):
             if run_llm:
                 await self._user_context_aggregator.push_context_frame()
 
+            frame = OpenAILLMContextFrame(self._context)
+            await self.push_frame(frame)
+
         except Exception as e:
             logger.error(f"Error processing frame: {e}")
diff --git a/src/pipecat/services/together.py b/src/pipecat/services/together.py
index e4068ecfc..935f625ad 100644
--- a/src/pipecat/services/together.py
+++ b/src/pipecat/services/together.py
@@ -370,7 +370,7 @@ class TogetherAssistantContextAggregator(LLMAssistantContextAggregator):
         run_llm = False
 
         aggregation = self._aggregation
-        self._aggregation = ""
+        self._reset()
 
         try:
             if self._function_call_result:
@@ -390,5 +390,8 @@ class TogetherAssistantContextAggregator(LLMAssistantContextAggregator):
             if run_llm:
                 await self._user_context_aggregator.push_messages_frame()
 
+            frame = OpenAILLMContextFrame(self._context)
+            await self.push_frame(frame)
+
         except Exception as e:
             logger.error(f"Error processing frame: {e}")

From 37da7e44cdbd7ec3d580926320b4cc5edc9ae450 Mon Sep 17 00:00:00 2001
From: Kwindla Hultman Kramer <kwindla@gmail.com>
Date: Sat, 28 Sep 2024 22:01:40 -0700
Subject: [PATCH 109/135] whitespace fix

---
 .../07l-interruptible-together.py             | 27 +++++++++----------
 .../processors/aggregators/llm_response.py    | 15 +++++------
 2 files changed, 19 insertions(+), 23 deletions(-)

diff --git a/examples/foundational/07l-interruptible-together.py b/examples/foundational/07l-interruptible-together.py
index e2cb55fed..a7086c941 100644
--- a/examples/foundational/07l-interruptible-together.py
+++ b/examples/foundational/07l-interruptible-together.py
@@ -5,29 +5,24 @@
 #
 
 import asyncio
-import aiohttp
 import os
 import sys
 
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+from runner import configure
+
 from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator,
-    LLMUserResponseAggregator,
-)
+from pipecat.services.ai_services import OpenAILLMContext
 from pipecat.services.cartesia import CartesiaTTSService
 from pipecat.services.together import TogetherLLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 from pipecat.vad.silero import SileroVADAnalyzer
 
-from runner import configure
-
-from loguru import logger
-
-from dotenv import load_dotenv
-
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -76,17 +71,19 @@ async def main():
             },
         ]
 
-        tma_in = LLMUserResponseAggregator(messages)
-        tma_out = LLMAssistantResponseAggregator(messages)
+        context = OpenAILLMContext(messages, tools)
+        context_aggregator = llm.create_context_aggregator(context)
+        user_aggregator = context_aggregator.user()
+        assistant_aggregator = context_aggregator.assistant()
 
         pipeline = Pipeline(
             [
                 transport.input(),  # Transport user input
-                tma_in,  # User responses
+                user_aggregator,  # User responses
                 llm,  # LLM
                 tts,  # TTS
                 transport.output(),  # Transport bot output
-                tma_out,  # Assistant spoken responses
+                assistant_aggregator,  # Assistant spoken responses
             ]
         )
 
diff --git a/src/pipecat/processors/aggregators/llm_response.py b/src/pipecat/processors/aggregators/llm_response.py
index 036f5fe47..a3cd63cbd 100644
--- a/src/pipecat/processors/aggregators/llm_response.py
+++ b/src/pipecat/processors/aggregators/llm_response.py
@@ -6,12 +6,6 @@
 
 from typing import List, Type
 
-from pipecat.processors.aggregators.openai_llm_context import (
-    OpenAILLMContextFrame,
-    OpenAILLMContext,
-)
-
-from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.frames.frames import (
     Frame,
     InterimTranscriptionFrame,
@@ -22,11 +16,16 @@ from pipecat.frames.frames import (
     LLMMessagesUpdateFrame,
     LLMSetToolsFrame,
     StartInterruptionFrame,
-    TranscriptionFrame,
     TextFrame,
+    TranscriptionFrame,
     UserStartedSpeakingFrame,
     UserStoppedSpeakingFrame,
 )
+from pipecat.processors.aggregators.openai_llm_context import (
+    OpenAILLMContext,
+    OpenAILLMContextFrame,
+)
+from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 
 
 class LLMResponseAggregator(FrameProcessor):
@@ -111,7 +110,7 @@ class LLMResponseAggregator(FrameProcessor):
             await self.push_frame(frame, direction)
         elif isinstance(frame, self._accumulator_frame):
             if self._aggregating:
-                self._aggregation += f" {frame.text}" if self._aggregation else frame.text
+                self._aggregation += frame.text if self._aggregation else frame.text
                 # We have recevied a complete sentence, so if we have seen the
                 # end frame and we were still aggregating, it means we should
                 # send the aggregation.

From ed607d5c4b30695c3d7a9a669b3ac707ec62647d Mon Sep 17 00:00:00 2001
From: Kwindla Hultman Kramer <kwindla@gmail.com>
Date: Sat, 28 Sep 2024 22:02:33 -0700
Subject: [PATCH 110/135] typo fix

---
 examples/foundational/07l-interruptible-together.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/foundational/07l-interruptible-together.py b/examples/foundational/07l-interruptible-together.py
index a7086c941..ca3386718 100644
--- a/examples/foundational/07l-interruptible-together.py
+++ b/examples/foundational/07l-interruptible-together.py
@@ -71,7 +71,7 @@ async def main():
             },
         ]
 
-        context = OpenAILLMContext(messages, tools)
+        context = OpenAILLMContext(messages)
         context_aggregator = llm.create_context_aggregator(context)
         user_aggregator = context_aggregator.user()
         assistant_aggregator = context_aggregator.assistant()

From fef393dcacf4e1c94d7a819cf3ea35722fbc8a67 Mon Sep 17 00:00:00 2001
From: Kwindla Hultman Kramer <kwindla@gmail.com>
Date: Sun, 29 Sep 2024 14:11:17 -0700
Subject: [PATCH 111/135] assistant aggregator switch for space padding or not

---
 src/pipecat/processors/aggregators/llm_response.py | 10 ++++++++--
 src/pipecat/services/anthropic.py                  | 12 ++++++++----
 src/pipecat/services/openai.py                     | 12 ++++++++----
 src/pipecat/services/together.py                   | 12 ++++++++----
 4 files changed, 32 insertions(+), 14 deletions(-)

diff --git a/src/pipecat/processors/aggregators/llm_response.py b/src/pipecat/processors/aggregators/llm_response.py
index a3cd63cbd..4ea38b89f 100644
--- a/src/pipecat/processors/aggregators/llm_response.py
+++ b/src/pipecat/processors/aggregators/llm_response.py
@@ -39,6 +39,7 @@ class LLMResponseAggregator(FrameProcessor):
         accumulator_frame: Type[TextFrame],
         interim_accumulator_frame: Type[TextFrame] | None = None,
         handle_interruptions: bool = False,
+        expect_stripped_words: bool = True,  # if True, need to add spaces between words
     ):
         super().__init__()
 
@@ -49,6 +50,7 @@ class LLMResponseAggregator(FrameProcessor):
         self._accumulator_frame = accumulator_frame
         self._interim_accumulator_frame = interim_accumulator_frame
         self._handle_interruptions = handle_interruptions
+        self._expect_stripped_words = expect_stripped_words
 
         # Reset our accumulator state.
         self._reset()
@@ -110,7 +112,10 @@ class LLMResponseAggregator(FrameProcessor):
             await self.push_frame(frame, direction)
         elif isinstance(frame, self._accumulator_frame):
             if self._aggregating:
-                self._aggregation += frame.text if self._aggregation else frame.text
+                if self._expect_stripped_words:
+                    self._aggregation += f" {frame.text}" if self._aggregation else frame.text
+                else:
+                    self._aggregation += frame.text if self._aggregation else frame.text
                 # We have recevied a complete sentence, so if we have seen the
                 # end frame and we were still aggregating, it means we should
                 # send the aggregation.
@@ -289,7 +294,7 @@ class LLMContextAggregator(LLMResponseAggregator):
 
 
 class LLMAssistantContextAggregator(LLMContextAggregator):
-    def __init__(self, context: OpenAILLMContext):
+    def __init__(self, context: OpenAILLMContext, *, expect_stripped_words: bool = True):
         super().__init__(
             messages=[],
             context=context,
@@ -298,6 +303,7 @@ class LLMAssistantContextAggregator(LLMContextAggregator):
             end_frame=LLMFullResponseEndFrame,
             accumulator_frame=TextFrame,
             handle_interruptions=True,
+            expect_stripped_words=expect_stripped_words,
         )
 
 
diff --git a/src/pipecat/services/anthropic.py b/src/pipecat/services/anthropic.py
index 6a535ef15..86e1e3726 100644
--- a/src/pipecat/services/anthropic.py
+++ b/src/pipecat/services/anthropic.py
@@ -110,9 +110,13 @@ class AnthropicLLMService(LLMService):
         return self._enable_prompt_caching_beta
 
     @staticmethod
-    def create_context_aggregator(context: OpenAILLMContext) -> AnthropicContextAggregatorPair:
+    def create_context_aggregator(
+        context: OpenAILLMContext, *, assistant_expect_stripped_words: bool = True
+    ) -> AnthropicContextAggregatorPair:
         user = AnthropicUserContextAggregator(context)
-        assistant = AnthropicAssistantContextAggregator(user)
+        assistant = AnthropicAssistantContextAggregator(
+            user, expect_stripped_words=assistant_expect_stripped_words
+        )
         return AnthropicContextAggregatorPair(_user=user, _assistant=assistant)
 
     async def set_enable_prompt_caching_beta(self, enable_prompt_caching_beta: bool):
@@ -541,8 +545,8 @@ class AnthropicUserContextAggregator(LLMUserContextAggregator):
 
 
 class AnthropicAssistantContextAggregator(LLMAssistantContextAggregator):
-    def __init__(self, user_context_aggregator: AnthropicUserContextAggregator):
-        super().__init__(context=user_context_aggregator._context)
+    def __init__(self, user_context_aggregator: AnthropicUserContextAggregator, **kwargs):
+        super().__init__(context=user_context_aggregator._context, **kwargs)
         self._user_context_aggregator = user_context_aggregator
         self._function_call_in_progress = None
         self._function_call_result = None
diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py
index 99d2d7497..c17916f2d 100644
--- a/src/pipecat/services/openai.py
+++ b/src/pipecat/services/openai.py
@@ -336,9 +336,13 @@ class OpenAILLMService(BaseOpenAILLMService):
         super().__init__(model=model, params=params, **kwargs)
 
     @staticmethod
-    def create_context_aggregator(context: OpenAILLMContext) -> OpenAIContextAggregatorPair:
+    def create_context_aggregator(
+        context: OpenAILLMContext, *, assistant_expect_stripped_words: bool = True
+    ) -> OpenAIContextAggregatorPair:
         user = OpenAIUserContextAggregator(context)
-        assistant = OpenAIAssistantContextAggregator(user)
+        assistant = OpenAIAssistantContextAggregator(
+            user, expect_stripped_words=assistant_expect_stripped_words
+        )
         return OpenAIContextAggregatorPair(_user=user, _assistant=assistant)
 
 
@@ -458,8 +462,8 @@ class OpenAIUserContextAggregator(LLMUserContextAggregator):
 
 
 class OpenAIAssistantContextAggregator(LLMAssistantContextAggregator):
-    def __init__(self, user_context_aggregator: OpenAIUserContextAggregator):
-        super().__init__(context=user_context_aggregator._context)
+    def __init__(self, user_context_aggregator: OpenAIUserContextAggregator, **kwargs):
+        super().__init__(context=user_context_aggregator._context, **kwargs)
         self._user_context_aggregator = user_context_aggregator
         self._function_call_in_progress = None
         self._function_call_result = None
diff --git a/src/pipecat/services/together.py b/src/pipecat/services/together.py
index 935f625ad..3f4d97964 100644
--- a/src/pipecat/services/together.py
+++ b/src/pipecat/services/together.py
@@ -95,9 +95,13 @@ class TogetherLLMService(LLMService):
         return True
 
     @staticmethod
-    def create_context_aggregator(context: OpenAILLMContext) -> TogetherContextAggregatorPair:
+    def create_context_aggregator(
+        context: OpenAILLMContext, *, assistant_expect_stripped_words: bool = True
+    ) -> TogetherContextAggregatorPair:
         user = TogetherUserContextAggregator(context)
-        assistant = TogetherAssistantContextAggregator(user)
+        assistant = TogetherAssistantContextAggregator(
+            user, expect_stripped_words=assistant_expect_stripped_words
+        )
         return TogetherContextAggregatorPair(_user=user, _assistant=assistant)
 
     async def set_frequency_penalty(self, frequency_penalty: float):
@@ -331,8 +335,8 @@ class TogetherUserContextAggregator(LLMUserContextAggregator):
 
 
 class TogetherAssistantContextAggregator(LLMAssistantContextAggregator):
-    def __init__(self, user_context_aggregator: TogetherUserContextAggregator):
-        super().__init__(context=user_context_aggregator._context)
+    def __init__(self, user_context_aggregator: TogetherUserContextAggregator, **kwargs):
+        super().__init__(context=user_context_aggregator._context, **kwargs)
         self._user_context_aggregator = user_context_aggregator
         self._function_call_in_progress = None
         self._function_call_result = None

From 539e0b66fb5abb446358c0b21ece7162fab63237 Mon Sep 17 00:00:00 2001
From: Kwindla Hultman Kramer <kwindla@gmail.com>
Date: Mon, 30 Sep 2024 09:26:06 -0700
Subject: [PATCH 112/135] small fix as per aleix

---
 src/pipecat/processors/aggregators/llm_response.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/pipecat/processors/aggregators/llm_response.py b/src/pipecat/processors/aggregators/llm_response.py
index 4ea38b89f..479746471 100644
--- a/src/pipecat/processors/aggregators/llm_response.py
+++ b/src/pipecat/processors/aggregators/llm_response.py
@@ -115,7 +115,7 @@ class LLMResponseAggregator(FrameProcessor):
                 if self._expect_stripped_words:
                     self._aggregation += f" {frame.text}" if self._aggregation else frame.text
                 else:
-                    self._aggregation += frame.text if self._aggregation else frame.text
+                    self._aggregation += frame.text
                 # We have recevied a complete sentence, so if we have seen the
                 # end frame and we were still aggregating, it means we should
                 # send the aggregation.

From def04ac0ce0fe6f90c66e523066c3b4517dbc8d3 Mon Sep 17 00:00:00 2001
From: JeevanReddy <jeevanreddy.narra@transformco.com>
Date: Wed, 7 Aug 2024 13:07:18 +0530
Subject: [PATCH 113/135] openai can give multiple tool calls, current
 implementation assumes only one function call at a time. Fixed this to handle
 multiple function calls.

---
 src/pipecat/services/openai.py | 33 +++++++++++++++++++++++++++------
 1 file changed, 27 insertions(+), 6 deletions(-)

diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py
index c17916f2d..b17dd7397 100644
--- a/src/pipecat/services/openai.py
+++ b/src/pipecat/services/openai.py
@@ -205,6 +205,10 @@ class BaseOpenAILLMService(LLMService):
         return chunks
 
     async def _process_context(self, context: OpenAILLMContext):
+        functions_list = []
+        arguments_list = []
+        tool_id_list = []
+        func_idx = 0
         function_name = ""
         arguments = ""
         tool_call_id = ""
@@ -242,6 +246,14 @@ class BaseOpenAILLMService(LLMService):
                 # yield a frame containing the function name and the arguments.
 
                 tool_call = chunk.choices[0].delta.tool_calls[0]
+                if tool_call.index != func_idx:
+                    functions_list.append(function_name)
+                    arguments_list.append(arguments)
+                    tool_id_list.append(tool_call_id)
+                    function_name = ""
+                    arguments = ""
+                    tool_call_id = ""
+                    func_idx += 1
                 if tool_call.function and tool_call.function.name:
                     function_name += tool_call.function.name
                     tool_call_id = tool_call.id
@@ -257,12 +269,21 @@ class BaseOpenAILLMService(LLMService):
         # the context, and re-prompt to get a chat answer. If we don't have a registered
         # handler, raise an exception.
         if function_name and arguments:
-            if self.has_function(function_name):
-                await self._handle_function_call(context, tool_call_id, function_name, arguments)
-            else:
-                raise OpenAIUnhandledFunctionException(
-                    f"The LLM tried to call a function named '{function_name}', but there isn't a callback registered for that function."
-                )
+            # added to the list as last function name and arguments not added to the list
+            functions_list.append(function_name)
+            arguments_list.append(arguments)
+            tool_id_list.append(tool_call_id)
+            for function_name, arguments, tool_id in zip(
+                functions_list, arguments_list, tool_id_list
+            ):
+                if self.has_function(function_name):
+                    await self._handle_function_call(context, tool_id, function_name, arguments)
+                else:
+                    raise OpenAIUnhandledFunctionException(
+                        f"The LLM tried to call a function named '{function_name}', but there isn't a callback registered for that function."
+                    )
+            # re-prompt to get a human answer after all the functions are called
+            await self._process_context(context)
 
     async def _handle_function_call(self, context, tool_call_id, function_name, arguments):
         arguments = json.loads(arguments)

From a5c73ec829685f302b3fdb8450de2ac75297b72e Mon Sep 17 00:00:00 2001
From: Kwindla Hultman Kramer <kwindla@gmail.com>
Date: Sun, 29 Sep 2024 21:03:59 -0700
Subject: [PATCH 114/135] handle openai multiple function calls

---
 examples/foundational/14-function-calling.py  | 11 ++--
 src/pipecat/frames/frames.py                  |  1 +
 .../aggregators/openai_llm_context.py         |  2 +
 src/pipecat/services/ai_services.py           | 15 +++++-
 src/pipecat/services/openai.py                | 54 +++++++++----------
 5 files changed, 50 insertions(+), 33 deletions(-)

diff --git a/examples/foundational/14-function-calling.py b/examples/foundational/14-function-calling.py
index b5aba449c..9141029ca 100644
--- a/examples/foundational/14-function-calling.py
+++ b/examples/foundational/14-function-calling.py
@@ -34,7 +34,12 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 async def start_fetch_weather(function_name, llm, context):
-    await llm.push_frame(TextFrame("Let me check on that."))
+    # note: we can't push a frame to the LLM here. the bot
+    # can interrupt itself and/or cause audio overlapping glitches.
+    # possible question for Aleix and Chad about what the right way
+    # to trigger speech is, now, with the new queues/async/sync refactors.
+    # await llm.push_frame(TextFrame("Let me check on that."))
+    logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
 
 
 async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
@@ -106,11 +111,11 @@ async def main():
 
         pipeline = Pipeline(
             [
-                fl_in,
+                # fl_in,
                 transport.input(),
                 context_aggregator.user(),
                 llm,
-                fl_out,
+                # fl_out,
                 tts,
                 transport.output(),
                 context_aggregator.assistant(),
diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py
index 8059b904b..f7faa8ef0 100644
--- a/src/pipecat/frames/frames.py
+++ b/src/pipecat/frames/frames.py
@@ -585,6 +585,7 @@ class FunctionCallResultFrame(DataFrame):
     tool_call_id: str
     arguments: str
     result: Any
+    run_llm: bool = True
 
 
 @dataclass
diff --git a/src/pipecat/processors/aggregators/openai_llm_context.py b/src/pipecat/processors/aggregators/openai_llm_context.py
index 83ec3e57f..4bf3f042c 100644
--- a/src/pipecat/processors/aggregators/openai_llm_context.py
+++ b/src/pipecat/processors/aggregators/openai_llm_context.py
@@ -133,6 +133,7 @@ class OpenAILLMContext:
         tool_call_id: str,
         arguments: str,
         llm: FrameProcessor,
+        run_llm: bool = True,
     ) -> None:
         # Push a SystemFrame downstream. This frame will let our assistant context aggregator
         # know that we are in the middle of a function call. Some contexts/aggregators may
@@ -153,6 +154,7 @@ class OpenAILLMContext:
                     tool_call_id=tool_call_id,
                     arguments=arguments,
                     result=result,
+                    run_llm=run_llm,
                 )
             )
 
diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index 5eadb475b..a46ad3fab 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -110,7 +110,13 @@ class LLMService(AIService):
         return function_name in self._callbacks.keys()
 
     async def call_function(
-        self, *, context: OpenAILLMContext, tool_call_id: str, function_name: str, arguments: str
+        self,
+        *,
+        context: OpenAILLMContext,
+        tool_call_id: str,
+        function_name: str,
+        arguments: str,
+        run_llm: bool,
     ) -> None:
         f = None
         if function_name in self._callbacks.keys():
@@ -120,7 +126,12 @@ class LLMService(AIService):
         else:
             return None
         await context.call_function(
-            f, function_name=function_name, tool_call_id=tool_call_id, arguments=arguments, llm=self
+            f,
+            function_name=function_name,
+            tool_call_id=tool_call_id,
+            arguments=arguments,
+            llm=self,
+            run_llm=run_llm,
         )
 
     # QUESTION FOR CB: maybe this isn't needed anymore?
diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py
index b17dd7397..73dae4644 100644
--- a/src/pipecat/services/openai.py
+++ b/src/pipecat/services/openai.py
@@ -273,26 +273,21 @@ class BaseOpenAILLMService(LLMService):
             functions_list.append(function_name)
             arguments_list.append(arguments)
             tool_id_list.append(tool_call_id)
-            for function_name, arguments, tool_id in zip(
-                functions_list, arguments_list, tool_id_list
+
+            total_items = len(functions_list)
+            for index, (function_name, arguments, tool_id) in enumerate(
+                zip(functions_list, arguments_list, tool_id_list), start=1
             ):
                 if self.has_function(function_name):
-                    await self._handle_function_call(context, tool_id, function_name, arguments)
-                else:
-                    raise OpenAIUnhandledFunctionException(
-                        f"The LLM tried to call a function named '{function_name}', but there isn't a callback registered for that function."
+                    run_llm = index == total_items
+                    arguments = json.loads(arguments)
+                    await self.call_function(
+                        context=context,
+                        function_name=function_name,
+                        arguments=arguments,
+                        tool_call_id=tool_id,
+                        run_llm=run_llm,
                     )
-            # re-prompt to get a human answer after all the functions are called
-            await self._process_context(context)
-
-    async def _handle_function_call(self, context, tool_call_id, function_name, arguments):
-        arguments = json.loads(arguments)
-        await self.call_function(
-            context=context,
-            tool_call_id=tool_call_id,
-            function_name=function_name,
-            arguments=arguments,
-        )
 
     async def _update_settings(self, frame: LLMUpdateSettingsFrame):
         if frame.model is not None:
@@ -486,31 +481,34 @@ class OpenAIAssistantContextAggregator(LLMAssistantContextAggregator):
     def __init__(self, user_context_aggregator: OpenAIUserContextAggregator, **kwargs):
         super().__init__(context=user_context_aggregator._context, **kwargs)
         self._user_context_aggregator = user_context_aggregator
-        self._function_call_in_progress = None
+        self._function_calls_in_progress = {}
         self._function_call_result = None
 
     async def process_frame(self, frame, direction):
         await super().process_frame(frame, direction)
         # See note above about not calling push_frame() here.
         if isinstance(frame, StartInterruptionFrame):
-            self._function_call_in_progress = None
+            self._function_calls_in_progress.clear()
             self._function_call_finished = None
+            logger.debug("clearing function calls in progress")
         elif isinstance(frame, FunctionCallInProgressFrame):
-            self._function_call_in_progress = frame
+            self._function_calls_in_progress[frame.tool_call_id] = frame
+            logger.debug(
+                f"FunctionCallInProgressFrame: {frame.tool_call_id} {self._function_calls_in_progress}"
+            )
         elif isinstance(frame, FunctionCallResultFrame):
-            if (
-                self._function_call_in_progress
-                and self._function_call_in_progress.tool_call_id == frame.tool_call_id
-            ):
-                self._function_call_in_progress = None
+            logger.debug(
+                f"FunctionCallResultFrame: {frame.tool_call_id} {self._function_calls_in_progress}"
+            )
+            if frame.tool_call_id in self._function_calls_in_progress:
+                del self._function_calls_in_progress[frame.tool_call_id]
                 self._function_call_result = frame
                 # TODO-CB: Kwin wants us to refactor this out of here but I REFUSE
                 await self._push_aggregation()
             else:
                 logger.warning(
-                    "FunctionCallResultFrame tool_call_id does not match FunctionCallInProgressFrame tool_call_id"
+                    "FunctionCallResultFrame tool_call_id does not match any function call in progress"
                 )
-                self._function_call_in_progress = None
                 self._function_call_result = None
 
     async def _push_aggregation(self):
@@ -549,7 +547,7 @@ class OpenAIAssistantContextAggregator(LLMAssistantContextAggregator):
                             "tool_call_id": frame.tool_call_id,
                         }
                     )
-                    run_llm = True
+                    run_llm = frame.run_llm
             else:
                 self._context.add_message({"role": "assistant", "content": aggregation})
 

From 6ad3437fd2b3511b7aef91d4f9785b30ff0dc1ec Mon Sep 17 00:00:00 2001
From: Kwindla Hultman Kramer <kwindla@gmail.com>
Date: Sun, 29 Sep 2024 21:10:21 -0700
Subject: [PATCH 115/135] throw error if the llm tries to call a function
 that's not registered

---
 src/pipecat/services/openai.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py
index 73dae4644..8a032ea40 100644
--- a/src/pipecat/services/openai.py
+++ b/src/pipecat/services/openai.py
@@ -288,6 +288,10 @@ class BaseOpenAILLMService(LLMService):
                         tool_call_id=tool_id,
                         run_llm=run_llm,
                     )
+                else:
+                    raise OpenAIUnhandledFunctionException(
+                        f"The LLM tried to call a function named '{function_name}', but there isn't a callback registered for that function."
+                    )
 
     async def _update_settings(self, frame: LLMUpdateSettingsFrame):
         if frame.model is not None:

From 0499fe41e455c700c2de11a1eebb84cc3f71a573 Mon Sep 17 00:00:00 2001
From: Kwindla Hultman Kramer <kwindla@gmail.com>
Date: Sun, 29 Sep 2024 21:12:09 -0700
Subject: [PATCH 116/135] get rid of some debug log lines used during
 development

---
 src/pipecat/services/openai.py | 7 -------
 1 file changed, 7 deletions(-)

diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py
index 8a032ea40..49fd04371 100644
--- a/src/pipecat/services/openai.py
+++ b/src/pipecat/services/openai.py
@@ -494,16 +494,9 @@ class OpenAIAssistantContextAggregator(LLMAssistantContextAggregator):
         if isinstance(frame, StartInterruptionFrame):
             self._function_calls_in_progress.clear()
             self._function_call_finished = None
-            logger.debug("clearing function calls in progress")
         elif isinstance(frame, FunctionCallInProgressFrame):
             self._function_calls_in_progress[frame.tool_call_id] = frame
-            logger.debug(
-                f"FunctionCallInProgressFrame: {frame.tool_call_id} {self._function_calls_in_progress}"
-            )
         elif isinstance(frame, FunctionCallResultFrame):
-            logger.debug(
-                f"FunctionCallResultFrame: {frame.tool_call_id} {self._function_calls_in_progress}"
-            )
             if frame.tool_call_id in self._function_calls_in_progress:
                 del self._function_calls_in_progress[frame.tool_call_id]
                 self._function_call_result = frame

From 128355add5b80a7694e92472a24e438bbee2c3c5 Mon Sep 17 00:00:00 2001
From: Kwindla Hultman Kramer <kwindla@gmail.com>
Date: Mon, 30 Sep 2024 16:19:31 -0700
Subject: [PATCH 117/135] fix for multi-sentence tts say utterances

---
 src/pipecat/services/ai_services.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index 5eadb475b..3e39b5443 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -249,7 +249,10 @@ class TTSService(AIService):
             self._stop_frame_task = None
 
     async def say(self, text: str):
+        aggregate_sentences = self._aggregate_sentences
+        self._aggregate_sentences = False
         await self.process_frame(TextFrame(text=text), FrameDirection.DOWNSTREAM)
+        self._aggregate_sentences = aggregate_sentences
         await self.flush_audio()
 
     async def process_frame(self, frame: Frame, direction: FrameDirection):

From 0d5cb84531856cb325f26496d60931adf0544bdb Mon Sep 17 00:00:00 2001
From: Kwindla Hultman Kramer <kwindla@gmail.com>
Date: Mon, 30 Sep 2024 20:59:28 -0700
Subject: [PATCH 118/135] function calling testing and improvements

---
 .../07l-interruptible-together.py             |   9 +-
 examples/foundational/14-function-calling.py  |   7 -
 ...c.py => 14a-function-calling-anthropic.py} |   0
 ...> 14b-function-calling-anthropic-video.py} |   0
 .../14c-function-calling-together.py          | 136 ++++++++
 examples/foundational/19c-tools-togetherai.py | 137 --------
 src/pipecat/services/ai_services.py           |   2 +-
 src/pipecat/services/together.py              | 323 ++----------------
 8 files changed, 167 insertions(+), 447 deletions(-)
 rename examples/foundational/{19a-tools-anthropic.py => 14a-function-calling-anthropic.py} (100%)
 rename examples/foundational/{19b-tools-video-anthropic.py => 14b-function-calling-anthropic-video.py} (100%)
 create mode 100644 examples/foundational/14c-function-calling-together.py
 delete mode 100644 examples/foundational/19c-tools-togetherai.py

diff --git a/examples/foundational/07l-interruptible-together.py b/examples/foundational/07l-interruptible-together.py
index ca3386718..a99b07a1a 100644
--- a/examples/foundational/07l-interruptible-together.py
+++ b/examples/foundational/07l-interruptible-together.py
@@ -67,7 +67,7 @@ async def main():
         messages = [
             {
                 "role": "system",
-                "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+                "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond in plain language. Respond to what the user said in a creative and helpful way.",
             },
         ]
 
@@ -87,7 +87,12 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True, enable_metrics=True, enable_usage_metrics=True
+            ),
+        )
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
diff --git a/examples/foundational/14-function-calling.py b/examples/foundational/14-function-calling.py
index 9141029ca..35a02743b 100644
--- a/examples/foundational/14-function-calling.py
+++ b/examples/foundational/14-function-calling.py
@@ -9,11 +9,9 @@ import aiohttp
 import os
 import sys
 
-from pipecat.frames.frames import TextFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
-from pipecat.processors.logger import FrameLogger
 from pipecat.services.cartesia import CartesiaTTSService
 from pipecat.services.openai import OpenAILLMContext, OpenAILLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
@@ -72,9 +70,6 @@ async def main():
         # sent to the same callback with an additional function_name parameter.
         llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
 
-        fl_in = FrameLogger("Inner")
-        fl_out = FrameLogger("Outer")
-
         tools = [
             ChatCompletionToolParam(
                 type="function",
@@ -111,11 +106,9 @@ async def main():
 
         pipeline = Pipeline(
             [
-                # fl_in,
                 transport.input(),
                 context_aggregator.user(),
                 llm,
-                # fl_out,
                 tts,
                 transport.output(),
                 context_aggregator.assistant(),
diff --git a/examples/foundational/19a-tools-anthropic.py b/examples/foundational/14a-function-calling-anthropic.py
similarity index 100%
rename from examples/foundational/19a-tools-anthropic.py
rename to examples/foundational/14a-function-calling-anthropic.py
diff --git a/examples/foundational/19b-tools-video-anthropic.py b/examples/foundational/14b-function-calling-anthropic-video.py
similarity index 100%
rename from examples/foundational/19b-tools-video-anthropic.py
rename to examples/foundational/14b-function-calling-anthropic-video.py
diff --git a/examples/foundational/14c-function-calling-together.py b/examples/foundational/14c-function-calling-together.py
new file mode 100644
index 000000000..ebfc4b5df
--- /dev/null
+++ b/examples/foundational/14c-function-calling-together.py
@@ -0,0 +1,136 @@
+#
+# Copyright (c) 2024, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import aiohttp
+import os
+import sys
+
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineTask
+from pipecat.services.cartesia import CartesiaTTSService
+from pipecat.services.openai import OpenAILLMContext
+from pipecat.services.together import TogetherLLMService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+from pipecat.vad.silero import SileroVADAnalyzer
+
+from openai.types.chat import ChatCompletionToolParam
+
+from runner import configure
+
+from loguru import logger
+
+from dotenv import load_dotenv
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+async def start_fetch_weather(function_name, llm, context):
+    # note: we can't push a frame to the LLM here. the bot
+    # can interrupt itself and/or cause audio overlapping glitches.
+    # possible question for Aleix and Chad about what the right way
+    # to trigger speech is, now, with the new queues/async/sync refactors.
+    # await llm.push_frame(TextFrame("Let me check on that."))
+    logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
+
+
+async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
+    await result_callback({"conditions": "nice", "temperature": "75"})
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, token) = await configure(session)
+
+        transport = DailyTransport(
+            room_url,
+            token,
+            "Respond bot",
+            DailyParams(
+                audio_out_enabled=True,
+                transcription_enabled=True,
+                vad_enabled=True,
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
+        )
+
+        tts = CartesiaTTSService(
+            api_key=os.getenv("CARTESIA_API_KEY"),
+            voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
+        )
+
+        llm = TogetherLLMService(
+            api_key=os.getenv("TOGETHER_API_KEY"),
+            model="meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo",
+        )
+        # Register a function_name of None to get all functions
+        # sent to the same callback with an additional function_name parameter.
+        llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
+
+        tools = [
+            ChatCompletionToolParam(
+                type="function",
+                function={
+                    "name": "get_current_weather",
+                    "description": "Get the current weather",
+                    "parameters": {
+                        "type": "object",
+                        "properties": {
+                            "location": {
+                                "type": "string",
+                                "description": "The city and state, e.g. San Francisco, CA",
+                            },
+                            "format": {
+                                "type": "string",
+                                "enum": ["celsius", "fahrenheit"],
+                                "description": "The temperature unit to use. Infer this from the users location.",
+                            },
+                        },
+                        "required": ["location", "format"],
+                    },
+                },
+            )
+        ]
+        messages = [
+            {
+                "role": "system",
+                "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+            },
+        ]
+
+        context = OpenAILLMContext(messages, tools)
+        context_aggregator = llm.create_context_aggregator(context)
+
+        pipeline = Pipeline(
+            [
+                transport.input(),
+                context_aggregator.user(),
+                llm,
+                tts,
+                transport.output(),
+                context_aggregator.assistant(),
+            ]
+        )
+
+        task = PipelineTask(pipeline)
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            transport.capture_participant_transcription(participant["id"])
+            # Kick off the conversation.
+            # await tts.say("Hi! Ask me about the weather in San Francisco.")
+
+        runner = PipelineRunner()
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
diff --git a/examples/foundational/19c-tools-togetherai.py b/examples/foundational/19c-tools-togetherai.py
deleted file mode 100644
index f8e63ef75..000000000
--- a/examples/foundational/19c-tools-togetherai.py
+++ /dev/null
@@ -1,137 +0,0 @@
-#
-# Copyright (c) 2024, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import asyncio
-import aiohttp
-import os
-import sys
-import json
-
-from pipecat.frames.frames import LLMMessagesFrame
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.services.cartesia import CartesiaTTSService
-from pipecat.services.together import TogetherLLMService
-from pipecat.transports.services.daily import DailyParams, DailyTransport
-from pipecat.vad.silero import SileroVADAnalyzer
-
-from runner import configure
-
-from loguru import logger
-
-from dotenv import load_dotenv
-
-load_dotenv(override=True)
-
-logger.remove(0)
-logger.add(sys.stderr, level="DEBUG")
-
-
-async def get_current_weather(
-    function_name, tool_call_id, arguments, llm, context, result_callback
-):
-    logger.debug("IN get_current_weather")
-    location = arguments["location"]
-    await result_callback(f"The weather in {location} is currently 72 degrees and sunny.")
-
-
-async def main():
-    async with aiohttp.ClientSession() as session:
-        (room_url, token) = await configure(session)
-
-        transport = DailyTransport(
-            room_url,
-            token,
-            "Respond bot",
-            DailyParams(
-                audio_out_enabled=True,
-                transcription_enabled=True,
-                vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer(),
-            ),
-        )
-
-        tts = CartesiaTTSService(
-            api_key=os.getenv("CARTESIA_API_KEY"),
-            voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
-        )
-
-        llm = TogetherLLMService(
-            api_key=os.getenv("TOGETHER_API_KEY"),
-            model=os.getenv("TOGETHER_MODEL"),
-        )
-        llm.register_function("get_current_weather", get_current_weather)
-
-        weatherTool = {
-            "name": "get_current_weather",
-            "description": "Get the current weather in a given location",
-            "parameters": {
-                "type": "object",
-                "properties": {
-                    "location": {
-                        "type": "string",
-                        "description": "The city and state, e.g. San Francisco, CA",
-                    },
-                },
-                "required": ["location"],
-            },
-        }
-
-        system_prompt = f"""\
-You have access to the following functions:
-
-Use the function '{weatherTool["name"]}' to '{weatherTool["description"]}':
-{json.dumps(weatherTool)}
-
-If you choose to call a function ONLY reply in the following format with no prefix or suffix:
-
-<function=example_function_name>{{\"example_name\": \"example_value\"}}</function>
-
-Reminder:
-- Function calls MUST follow the specified format, start with <function= and end with </function>
-- Required parameters MUST be specified
-- Only call one function at a time
-- Put the entire function call reply on one line
-- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls
-
-"""
-
-        messages = [
-            {"role": "system", "content": system_prompt},
-            {"role": "user", "content": "Wait for the user to say something."},
-        ]
-
-        context = OpenAILLMContext(messages)
-        context_aggregator = llm.create_context_aggregator(context)
-
-        pipeline = Pipeline(
-            [
-                transport.input(),  # Transport user input
-                context_aggregator.user(),  # User speech to text
-                llm,  # LLM
-                tts,  # TTS
-                transport.output(),  # Transport bot output
-                context_aggregator.assistant(),  # Assistant spoken responses and tool context
-            ]
-        )
-
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True, enable_metrics=True))
-
-        @transport.event_handler("on_first_participant_joined")
-        async def on_first_participant_joined(transport, participant):
-            transport.capture_participant_transcription(participant["id"])
-            # Kick off the conversation.
-            await task.queue_frames([LLMMessagesFrame(messages)])
-
-        runner = PipelineRunner()
-
-        await runner.run(task)
-
-
-if __name__ == "__main__":
-    asyncio.run(main())
diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index a46ad3fab..ec1d04ec4 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -116,7 +116,7 @@ class LLMService(AIService):
         tool_call_id: str,
         function_name: str,
         arguments: str,
-        run_llm: bool,
+        run_llm: bool = True,
     ) -> None:
         f = None
         if function_name in self._callbacks.keys():
diff --git a/src/pipecat/services/together.py b/src/pipecat/services/together.py
index 3f4d97964..5da470002 100644
--- a/src/pipecat/services/together.py
+++ b/src/pipecat/services/together.py
@@ -4,42 +4,21 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-import json
-import re
-import uuid
-from asyncio import CancelledError
-from dataclasses import dataclass
-from typing import Any, Dict, List, Optional
-
+from typing import Any, Dict, Optional
+import httpx
 from loguru import logger
 from pydantic import BaseModel, Field
 
 from pipecat.frames.frames import (
-    Frame,
-    FunctionCallInProgressFrame,
-    FunctionCallResultFrame,
-    LLMFullResponseEndFrame,
-    LLMFullResponseStartFrame,
-    LLMMessagesFrame,
     LLMUpdateSettingsFrame,
-    StartInterruptionFrame,
-    TextFrame,
-    UserImageRequestFrame,
 )
-from pipecat.metrics.metrics import LLMTokenUsage
-from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantContextAggregator,
-    LLMUserContextAggregator,
-)
-from pipecat.processors.aggregators.openai_llm_context import (
-    OpenAILLMContext,
-    OpenAILLMContextFrame,
-)
-from pipecat.processors.frame_processor import FrameDirection
-from pipecat.services.ai_services import LLMService
+from pipecat.services.openai import OpenAILLMService
+
 
 try:
-    from together import AsyncTogether
+    # Together.ai is recommending OpenAI-compatible function calling, so we've switched over
+    # to using the OpenAI client library here rather than the Together Python client library.
+    from openai import AsyncOpenAI, DefaultAsyncHttpxClient
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
@@ -48,19 +27,7 @@ except ModuleNotFoundError as e:
     raise Exception(f"Missing module: {e}")
 
 
-@dataclass
-class TogetherContextAggregatorPair:
-    _user: "TogetherUserContextAggregator"
-    _assistant: "TogetherAssistantContextAggregator"
-
-    def user(self) -> "TogetherUserContextAggregator":
-        return self._user
-
-    def assistant(self) -> "TogetherAssistantContextAggregator":
-        return self._assistant
-
-
-class TogetherLLMService(LLMService):
+class TogetherLLMService(OpenAILLMService):
     """This class implements inference with Together's Llama 3.1 models"""
 
     class InputParams(BaseModel):
@@ -68,20 +35,23 @@ class TogetherLLMService(LLMService):
         max_tokens: Optional[int] = Field(default=4096, ge=1)
         presence_penalty: Optional[float] = Field(default=None, ge=-2.0, le=2.0)
         temperature: Optional[float] = Field(default=None, ge=0.0, le=1.0)
+        # Note: top_k is currently not supported by the OpenAI client library,
+        # so top_k is ignore right now.
         top_k: Optional[int] = Field(default=None, ge=0)
         top_p: Optional[float] = Field(default=None, ge=0.0, le=1.0)
         extra: Optional[Dict[str, Any]] = Field(default_factory=dict)
+        seed: Optional[int] = Field(default=None)
 
     def __init__(
         self,
         *,
         api_key: str,
+        base_url: str = "https://api.together.xyz/v1",
         model: str = "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo",
         params: InputParams = InputParams(),
         **kwargs,
     ):
-        super().__init__(**kwargs)
-        self._client = AsyncTogether(api_key=api_key)
+        super().__init__(api_key=api_key, base_url=base_url, model=model, params=params, **kwargs)
         self.set_model_name(model)
         self._max_tokens = params.max_tokens
         self._frequency_penalty = params.frequency_penalty
@@ -94,15 +64,17 @@ class TogetherLLMService(LLMService):
     def can_generate_metrics(self) -> bool:
         return True
 
-    @staticmethod
-    def create_context_aggregator(
-        context: OpenAILLMContext, *, assistant_expect_stripped_words: bool = True
-    ) -> TogetherContextAggregatorPair:
-        user = TogetherUserContextAggregator(context)
-        assistant = TogetherAssistantContextAggregator(
-            user, expect_stripped_words=assistant_expect_stripped_words
+    def create_client(self, api_key=None, base_url=None, **kwargs):
+        logger.debug(f"Creating Together.ai client with api {base_url}")
+        return AsyncOpenAI(
+            api_key=api_key,
+            base_url=base_url,
+            http_client=DefaultAsyncHttpxClient(
+                limits=httpx.Limits(
+                    max_keepalive_connections=100, max_connections=1000, keepalive_expiry=None
+                )
+            ),
         )
-        return TogetherContextAggregatorPair(_user=user, _assistant=assistant)
 
     async def set_frequency_penalty(self, frequency_penalty: float):
         logger.debug(f"Switching LLM frequency_penalty to: [{frequency_penalty}]")
@@ -150,252 +122,3 @@ class TogetherLLMService(LLMService):
             await self.set_top_p(frame.top_p)
         if frame.extra:
             await self.set_extra(frame.extra)
-
-    async def _process_context(self, context: OpenAILLMContext):
-        try:
-            await self.push_frame(LLMFullResponseStartFrame())
-            await self.start_processing_metrics()
-
-            logger.debug(f"Generating chat: {context.get_messages_for_logging()}")
-
-            await self.start_ttfb_metrics()
-
-            params = {
-                "messages": context.messages,
-                "model": self.model_name,
-                "max_tokens": self._max_tokens,
-                "stream": True,
-                "frequency_penalty": self._frequency_penalty,
-                "presence_penalty": self._presence_penalty,
-                "temperature": self._temperature,
-                "top_k": self._top_k,
-                "top_p": self._top_p,
-            }
-
-            params.update(self._extra)
-
-            stream = await self._client.chat.completions.create(**params)
-
-            # Function calling
-            got_first_chunk = False
-            accumulating_function_call = False
-            function_call_accumulator = ""
-
-            async for chunk in stream:
-                # logger.debug(f"Together LLM event: {chunk}")
-                if chunk.usage:
-                    tokens = LLMTokenUsage(
-                        prompt_tokens=chunk.usage.prompt_tokens,
-                        completion_tokens=chunk.usage.completion_tokens,
-                        total_tokens=chunk.usage.total_tokens,
-                    )
-                    await self.start_llm_usage_metrics(tokens)
-
-                if len(chunk.choices) == 0:
-                    continue
-
-                if not got_first_chunk:
-                    await self.stop_ttfb_metrics()
-                    if chunk.choices[0].delta.content:
-                        got_first_chunk = True
-                        if chunk.choices[0].delta.content[0] == "<":
-                            accumulating_function_call = True
-
-                if chunk.choices[0].delta.content:
-                    if accumulating_function_call:
-                        function_call_accumulator += chunk.choices[0].delta.content
-                    else:
-                        await self.push_frame(TextFrame(chunk.choices[0].delta.content))
-
-                if chunk.choices[0].finish_reason == "eos" and accumulating_function_call:
-                    await self._extract_function_call(context, function_call_accumulator)
-
-        except CancelledError:
-            # todo: implement token counting estimates for use when the user interrupts a long generation
-            # we do this in the anthropic.py service
-            raise
-        except Exception as e:
-            logger.exception(f"{self} exception: {e}")
-        finally:
-            await self.stop_processing_metrics()
-            await self.push_frame(LLMFullResponseEndFrame())
-
-    async def process_frame(self, frame: Frame, direction: FrameDirection):
-        await super().process_frame(frame, direction)
-
-        context = None
-        if isinstance(frame, OpenAILLMContextFrame):
-            context = frame.context
-        elif isinstance(frame, LLMMessagesFrame):
-            context = TogetherLLMContext.from_messages(frame.messages)
-        elif isinstance(frame, LLMUpdateSettingsFrame):
-            await self._update_settings(frame)
-        else:
-            await self.push_frame(frame, direction)
-
-        if context:
-            await self._process_context(context)
-
-    async def _extract_function_call(self, context, function_call_accumulator):
-        context.add_message({"role": "assistant", "content": function_call_accumulator})
-
-        function_regex = r"<function=(\w+)>(.*?)</function>"
-        match = re.search(function_regex, function_call_accumulator)
-        if match:
-            function_name, args_string = match.groups()
-            try:
-                arguments = json.loads(args_string)
-                await self.call_function(
-                    context=context,
-                    tool_call_id=str(uuid.uuid4()),
-                    function_name=function_name,
-                    arguments=arguments,
-                )
-                return
-            except json.JSONDecodeError as error:
-                # We get here if the LLM returns a function call with invalid JSON arguments. This could happen
-                # because of LLM non-determinism, or maybe more often because of user error in the prompt.
-                # Should we do anything more than log a warning?
-                logger.debug(f"Error parsing function arguments: {error}")
-
-
-class TogetherLLMContext(OpenAILLMContext):
-    def __init__(
-        self,
-        messages: list[dict] | None = None,
-    ):
-        super().__init__(messages=messages)
-
-    @classmethod
-    def from_openai_context(cls, openai_context: OpenAILLMContext):
-        self = cls(
-            messages=openai_context.messages,
-        )
-        return self
-
-    @classmethod
-    def from_messages(cls, messages: List[dict]) -> "TogetherLLMContext":
-        return cls(messages=messages)
-
-    def add_message(self, message):
-        try:
-            self.messages.append(message)
-        except Exception as e:
-            logger.error(f"Error adding message: {e}")
-
-    def get_messages_for_logging(self) -> str:
-        return json.dumps(self.messages)
-
-
-class TogetherUserContextAggregator(LLMUserContextAggregator):
-    def __init__(self, context: OpenAILLMContext | TogetherLLMContext):
-        super().__init__(context=context)
-
-        if isinstance(context, OpenAILLMContext):
-            self._context = TogetherLLMContext.from_openai_context(context)
-
-    async def push_messages_frame(self):
-        frame = OpenAILLMContextFrame(self._context)
-        await self.push_frame(frame)
-
-    async def process_frame(self, frame, direction):
-        await super().process_frame(frame, direction)
-        # Our parent method has already called push_frame(). So we can't interrupt the
-        # flow here and we don't need to call push_frame() ourselves. Possibly something
-        # to talk through (tagging @aleix). At some point we might need to refactor these
-        # context aggregators.
-        try:
-            if isinstance(frame, UserImageRequestFrame):
-                # The LLM sends a UserImageRequestFrame upstream. Cache any context provided with
-                # that frame so we can use it when we assemble the image message in the assistant
-                # context aggregator.
-                if frame.context:
-                    if isinstance(frame.context, str):
-                        self._context._user_image_request_context[frame.user_id] = frame.context
-                    else:
-                        logger.error(
-                            f"Unexpected UserImageRequestFrame context type: {type(frame.context)}"
-                        )
-                        del self._context._user_image_request_context[frame.user_id]
-                else:
-                    if frame.user_id in self._context._user_image_request_context:
-                        del self._context._user_image_request_context[frame.user_id]
-        except Exception as e:
-            logger.error(f"Error processing frame: {e}")
-
-
-#
-# Claude returns a text content block along with a tool use content block. This works quite nicely
-# with streaming. We get the text first, so we can start streaming it right away. Then we get the
-# tool_use block. While the text is streaming to TTS and the transport, we can run the tool call.
-#
-# But Claude is verbose. It would be nice to come up with prompt language that suppresses Claude's
-# chattiness about it's tool thinking.
-#
-
-
-class TogetherAssistantContextAggregator(LLMAssistantContextAggregator):
-    def __init__(self, user_context_aggregator: TogetherUserContextAggregator, **kwargs):
-        super().__init__(context=user_context_aggregator._context, **kwargs)
-        self._user_context_aggregator = user_context_aggregator
-        self._function_call_in_progress = None
-        self._function_call_result = None
-
-    async def process_frame(self, frame, direction):
-        await super().process_frame(frame, direction)
-        # See note above about not calling push_frame() here.
-        if isinstance(frame, StartInterruptionFrame):
-            self._function_call_in_progress = None
-            self._function_call_finished = None
-        elif isinstance(frame, FunctionCallInProgressFrame):
-            self._function_call_in_progress = frame
-        elif isinstance(frame, FunctionCallResultFrame):
-            if (
-                self._function_call_in_progress
-                and self._function_call_in_progress.tool_call_id == frame.tool_call_id
-            ):
-                self._function_call_in_progress = None
-                self._function_call_result = frame
-                await self._push_aggregation()
-            else:
-                logger.warning(
-                    "FunctionCallResultFrame tool_call_id does not match FunctionCallInProgressFrame tool_call_id"
-                )
-                self._function_call_in_progress = None
-                self._function_call_result = None
-
-    def add_message(self, message):
-        self._user_context_aggregator.add_message(message)
-
-    async def _push_aggregation(self):
-        if not (self._aggregation or self._function_call_result):
-            return
-
-        run_llm = False
-
-        aggregation = self._aggregation
-        self._reset()
-
-        try:
-            if self._function_call_result:
-                frame = self._function_call_result
-                self._function_call_result = None
-                self._context.add_message(
-                    {
-                        "role": "tool",
-                        # Together expects the content here to be a string, so stringify it
-                        "content": str(frame.result),
-                    }
-                )
-                run_llm = True
-            else:
-                self._context.add_message({"role": "assistant", "content": aggregation})
-
-            if run_llm:
-                await self._user_context_aggregator.push_messages_frame()
-
-            frame = OpenAILLMContextFrame(self._context)
-            await self.push_frame(frame)
-
-        except Exception as e:
-            logger.error(f"Error processing frame: {e}")

From 92d8b37229741fba217ec456f5dadb06c8e15ca8 Mon Sep 17 00:00:00 2001
From: Kwindla Hultman Kramer <kwindla@gmail.com>
Date: Mon, 30 Sep 2024 21:49:29 -0700
Subject: [PATCH 119/135] implement vision for openai

---
 .../14d-function-calling-video.py             | 167 ++++++++++++++++++
 .../aggregators/openai_llm_context.py         |  31 ++++
 src/pipecat/services/anthropic.py             |   2 +-
 src/pipecat/services/openai.py                |  62 ++++++-
 4 files changed, 259 insertions(+), 3 deletions(-)
 create mode 100644 examples/foundational/14d-function-calling-video.py

diff --git a/examples/foundational/14d-function-calling-video.py b/examples/foundational/14d-function-calling-video.py
new file mode 100644
index 000000000..f42665d5b
--- /dev/null
+++ b/examples/foundational/14d-function-calling-video.py
@@ -0,0 +1,167 @@
+#
+# Copyright (c) 2024, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import aiohttp
+import os
+import sys
+
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineTask
+from pipecat.services.cartesia import CartesiaTTSService
+from pipecat.services.openai import OpenAILLMContext, OpenAILLMService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+from pipecat.vad.silero import SileroVADAnalyzer
+
+from openai.types.chat import ChatCompletionToolParam
+
+from runner import configure
+
+from loguru import logger
+
+from dotenv import load_dotenv
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+video_participant_id = None
+
+
+async def get_weather(function_name, tool_call_id, arguments, llm, context, result_callback):
+    location = arguments["location"]
+    await result_callback(f"The weather in {location} is currently 72 degrees and sunny.")
+
+
+async def get_image(function_name, tool_call_id, arguments, llm, context, result_callback):
+    logger.debug(f"!!! IN get_image {video_participant_id}, {arguments}")
+    question = arguments["question"]
+    await llm.request_image_frame(user_id=video_participant_id, text_content=question)
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, token) = await configure(session)
+
+        transport = DailyTransport(
+            room_url,
+            token,
+            "Respond bot",
+            DailyParams(
+                audio_out_enabled=True,
+                transcription_enabled=True,
+                vad_enabled=True,
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
+        )
+
+        tts = CartesiaTTSService(
+            api_key=os.getenv("CARTESIA_API_KEY"),
+            voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
+        )
+
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
+        llm.register_function("get_weather", get_weather)
+        llm.register_function("get_image", get_image)
+
+        tools = [
+            ChatCompletionToolParam(
+                type="function",
+                function={
+                    "name": "get_weather",
+                    "description": "Get the current weather",
+                    "parameters": {
+                        "type": "object",
+                        "properties": {
+                            "location": {
+                                "type": "string",
+                                "description": "The city and state, e.g. San Francisco, CA",
+                            },
+                            "format": {
+                                "type": "string",
+                                "enum": ["celsius", "fahrenheit"],
+                                "description": "The temperature unit to use. Infer this from the users location.",
+                            },
+                        },
+                        "required": ["location", "format"],
+                    },
+                },
+            ),
+            ChatCompletionToolParam(
+                type="function",
+                function={
+                    "name": "get_image",
+                    "description": "Get an image from the video stream.",
+                    "parameters": {
+                        "type": "object",
+                        "properties": {
+                            "question": {
+                                "type": "string",
+                                "description": "The question to ask the AI to generate an image of",
+                            },
+                        },
+                        "required": ["question"],
+                    },
+                },
+            ),
+        ]
+
+        system_prompt = """\
+You are a helpful assistant who converses with a user and answers questions. Respond concisely to general questions.
+
+Your response will be turned into speech so use only simple words and punctuation.
+
+You have access to two tools: get_weather and get_image.
+
+You can respond to questions about the weather using the get_weather tool.
+
+You can answer questions about the user's video stream using the get_image tool. Some examples of phrases that \
+indicate you should use the get_image tool are:
+  - What do you see?
+  - What's in the video?
+  - Can you describe the video?
+  - Tell me about what you see.
+  - Tell me something interesting about what you see.
+  - What's happening in the video?
+"""
+        messages = [
+            {"role": "system", "content": system_prompt},
+        ]
+
+        context = OpenAILLMContext(messages, tools)
+        context_aggregator = llm.create_context_aggregator(context)
+
+        pipeline = Pipeline(
+            [
+                transport.input(),
+                context_aggregator.user(),
+                llm,
+                tts,
+                transport.output(),
+                context_aggregator.assistant(),
+            ]
+        )
+
+        task = PipelineTask(pipeline)
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            global video_participant_id
+            video_participant_id = participant["id"]
+            transport.capture_participant_transcription(participant["id"])
+            transport.capture_participant_video(video_participant_id, framerate=0)
+            # Kick off the conversation.
+            await tts.say("Hi! Ask me about the weather in San Francisco.")
+
+        runner = PipelineRunner()
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
diff --git a/src/pipecat/processors/aggregators/openai_llm_context.py b/src/pipecat/processors/aggregators/openai_llm_context.py
index 4bf3f042c..c86045fab 100644
--- a/src/pipecat/processors/aggregators/openai_llm_context.py
+++ b/src/pipecat/processors/aggregators/openai_llm_context.py
@@ -4,6 +4,8 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
+import base64
+import copy
 import io
 import json
 
@@ -60,6 +62,7 @@ class OpenAILLMContext:
         self._messages: List[ChatCompletionMessageParam] = messages if messages else []
         self._tool_choice: ChatCompletionToolChoiceOptionParam | NotGiven = tool_choice
         self._tools: List[ChatCompletionToolParam] | NotGiven = tools
+        self._user_image_request_context = {}
 
     @staticmethod
     def from_messages(messages: List[dict]) -> "OpenAILLMContext":
@@ -114,6 +117,19 @@ class OpenAILLMContext:
     def get_messages_json(self) -> str:
         return json.dumps(self._messages, cls=CustomEncoder)
 
+    def get_messages_for_logging(self) -> str:
+        msgs = []
+        for message in self.messages:
+            msg = copy.deepcopy(message)
+            if "content" in msg:
+                if isinstance(msg["content"], list):
+                    for item in msg["content"]:
+                        if item["type"] == "image_url":
+                            if item["image_url"]["url"].startswith("data:image/"):
+                                item["image_url"]["url"] = "data:image/..."
+            msgs.append(msg)
+        return json.dumps(msgs)
+
     def set_tool_choice(self, tool_choice: ChatCompletionToolChoiceOptionParam | NotGiven):
         self._tool_choice = tool_choice
 
@@ -122,6 +138,21 @@ class OpenAILLMContext:
             tools = NOT_GIVEN
         self._tools = tools
 
+    def add_image_frame_message(
+        self, *, format: str, size: tuple[int, int], image: bytes, text: str = None
+    ):
+        buffer = io.BytesIO()
+        Image.frombytes(format, size, image).save(buffer, format="JPEG")
+        encoded_image = base64.b64encode(buffer.getvalue()).decode("utf-8")
+
+        content = [
+            {"type": "text", "text": text},
+            {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{encoded_image}"}},
+        ]
+        if text:
+            content.append({"type": "text", "text": text})
+        self.add_message({"role": "user", "content": content})
+
     async def call_function(
         self,
         f: Callable[
diff --git a/src/pipecat/services/anthropic.py b/src/pipecat/services/anthropic.py
index 86e1e3726..639a922e6 100644
--- a/src/pipecat/services/anthropic.py
+++ b/src/pipecat/services/anthropic.py
@@ -55,6 +55,7 @@ except ModuleNotFoundError as e:
     raise Exception(f"Missing module: {e}")
 
 
+# internal use only -- todo: refactor
 @dataclass
 class AnthropicImageMessageFrame(Frame):
     user_image_raw_frame: UserImageRawFrame
@@ -359,7 +360,6 @@ class AnthropicLLMContext(OpenAILLMContext):
         system: str | NotGiven = NOT_GIVEN,
     ):
         super().__init__(messages=messages, tools=tools, tool_choice=tool_choice)
-        self._user_image_request_context = {}
 
         # For beta prompt caching. This is a counter that tracks the number of turns
         # we've seen above the cache threshold. We reset this when we reset the
diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py
index 49fd04371..9a7cc9023 100644
--- a/src/pipecat/services/openai.py
+++ b/src/pipecat/services/openai.py
@@ -31,6 +31,8 @@ from pipecat.frames.frames import (
     TTSStartedFrame,
     TTSStoppedFrame,
     URLImageRawFrame,
+    UserImageRawFrame,
+    UserImageRequestFrame,
     VisionImageRawFrame,
 )
 from pipecat.metrics.metrics import LLMTokenUsage
@@ -181,7 +183,7 @@ class BaseOpenAILLMService(LLMService):
     async def _stream_chat_completions(
         self, context: OpenAILLMContext
     ) -> AsyncStream[ChatCompletionChunk]:
-        logger.debug(f"Generating chat: {context.get_messages_json()}")
+        logger.debug(f"Generating chat: {context.get_messages_for_logging()}")
 
         messages: List[ChatCompletionMessageParam] = context.get_messages()
 
@@ -476,10 +478,49 @@ class OpenAITTSService(TTSService):
             logger.exception(f"{self} error generating TTS: {e}")
 
 
+# internal use only -- todo: refactor
+@dataclass
+class OpenAIImageMessageFrame(Frame):
+    user_image_raw_frame: UserImageRawFrame
+    text: Optional[str] = None
+
+
 class OpenAIUserContextAggregator(LLMUserContextAggregator):
     def __init__(self, context: OpenAILLMContext):
         super().__init__(context=context)
 
+    async def process_frame(self, frame, direction):
+        await super().process_frame(frame, direction)
+        # Our parent method has already called push_frame(). So we can't interrupt the
+        # flow here and we don't need to call push_frame() ourselves.
+        try:
+            if isinstance(frame, UserImageRequestFrame):
+                # The LLM sends a UserImageRequestFrame upstream. Cache any context provided with
+                # that frame so we can use it when we assemble the image message in the assistant
+                # context aggregator.
+                if frame.context:
+                    if isinstance(frame.context, str):
+                        self._context._user_image_request_context[frame.user_id] = frame.context
+                    else:
+                        logger.error(
+                            f"Unexpected UserImageRequestFrame context type: {type(frame.context)}"
+                        )
+                        del self._context._user_image_request_context[frame.user_id]
+                else:
+                    if frame.user_id in self._context._user_image_request_context:
+                        del self._context._user_image_request_context[frame.user_id]
+            elif isinstance(frame, UserImageRawFrame):
+                # Push a new AnthropicImageMessageFrame with the text context we cached
+                # downstream to be handled by our assistant context aggregator. This is
+                # necessary so that we add the message to the context in the right order.
+                text = self._context._user_image_request_context.get(frame.user_id) or ""
+                if text:
+                    del self._context._user_image_request_context[frame.user_id]
+                frame = OpenAIImageMessageFrame(user_image_raw_frame=frame, text=text)
+                await self.push_frame(frame)
+        except Exception as e:
+            logger.error(f"Error processing frame: {e}")
+
 
 class OpenAIAssistantContextAggregator(LLMAssistantContextAggregator):
     def __init__(self, user_context_aggregator: OpenAIUserContextAggregator, **kwargs):
@@ -487,6 +528,7 @@ class OpenAIAssistantContextAggregator(LLMAssistantContextAggregator):
         self._user_context_aggregator = user_context_aggregator
         self._function_calls_in_progress = {}
         self._function_call_result = None
+        self._pending_image_frame_message = None
 
     async def process_frame(self, frame, direction):
         await super().process_frame(frame, direction)
@@ -507,9 +549,14 @@ class OpenAIAssistantContextAggregator(LLMAssistantContextAggregator):
                     "FunctionCallResultFrame tool_call_id does not match any function call in progress"
                 )
                 self._function_call_result = None
+        elif isinstance(frame, OpenAIImageMessageFrame):
+            self._pending_image_frame_message = frame
+            await self._push_aggregation()
 
     async def _push_aggregation(self):
-        if not (self._aggregation or self._function_call_result):
+        if not (
+            self._aggregation or self._function_call_result or self._pending_image_frame_message
+        ):
             return
 
         run_llm = False
@@ -548,6 +595,17 @@ class OpenAIAssistantContextAggregator(LLMAssistantContextAggregator):
             else:
                 self._context.add_message({"role": "assistant", "content": aggregation})
 
+            if self._pending_image_frame_message:
+                frame = self._pending_image_frame_message
+                self._pending_image_frame_message = None
+                self._context.add_image_frame_message(
+                    format=frame.user_image_raw_frame.format,
+                    size=frame.user_image_raw_frame.size,
+                    image=frame.user_image_raw_frame.image,
+                    text=frame.text,
+                )
+                run_llm = True
+
             if run_llm:
                 await self._user_context_aggregator.push_context_frame()
 

From a397b859fec9e94ec7248cc2469366564e09e9c4 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Mon, 30 Sep 2024 15:47:41 -0400
Subject: [PATCH 120/135] Add support for gender and google_style inputs to
 Google TTS

---
 src/pipecat/frames/frames.py        | 2 ++
 src/pipecat/services/ai_services.py | 8 ++++++++
 src/pipecat/services/google.py      | 2 +-
 3 files changed, 11 insertions(+), 1 deletion(-)

diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py
index f7faa8ef0..584be32db 100644
--- a/src/pipecat/frames/frames.py
+++ b/src/pipecat/frames/frames.py
@@ -558,6 +558,8 @@ class TTSUpdateSettingsFrame(ControlFrame):
     style: Optional[str] = None
     style_degree: Optional[str] = None
     role: Optional[str] = None
+    gender: Optional[str] = None
+    google_style: Optional[str] = None
 
 
 @dataclass
diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index a329239dc..344531de3 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -235,6 +235,14 @@ class TTSService(AIService):
     async def flush_audio(self):
         pass
 
+    @abstractmethod
+    async def set_gender(self, gender: str):
+        pass
+
+    @abstractmethod
+    async def set_google_style(self, google_style: str):
+        pass
+
     # Converts the text to audio.
     @abstractmethod
     async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
diff --git a/src/pipecat/services/google.py b/src/pipecat/services/google.py
index 519f47028..046b465b4 100644
--- a/src/pipecat/services/google.py
+++ b/src/pipecat/services/google.py
@@ -272,7 +272,7 @@ class GoogleTTSService(TTSService):
         logger.debug(f"Switch TTS gender to [{gender}]")
         self._params.gender = gender
 
-    async def google_style(
+    async def set_google_style(
         self, google_style: Literal["apologetic", "calm", "empathetic", "firm", "lively"]
     ) -> None:
         logger.debug(f"Switching TTS google style to: [{google_style}]")

From 88cca7bf68ba742935aeaee6e2e14af3068850a1 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Tue, 1 Oct 2024 10:35:59 -0400
Subject: [PATCH 121/135] Consolidate service UpdateSettingsFrame into a single
 ServiceUpdateSettingsFrame

---
 CHANGELOG.md                        |  4 +-
 src/pipecat/frames/frames.py        | 46 ++-------------
 src/pipecat/services/ai_services.py | 87 ++++++++++++++---------------
 src/pipecat/services/anthropic.py   | 30 +++++-----
 src/pipecat/services/google.py      | 25 +++++++--
 src/pipecat/services/openai.py      | 32 +++++------
 src/pipecat/services/together.py    | 33 ++++-------
 7 files changed, 106 insertions(+), 151 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index b59ed56c8..922a21f21 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -86,8 +86,8 @@ async def on_connected(processor):
 
 ### Changed
 
-- Updated individual update settings frame classes into a single UpdateSettingsFrame
-  class for STT, LLM, and TTS.
+- Updated individual update settings frame classes into a single
+  ServiceUpdateSettingsFrame class.
 
 - We now distinguish between input and output audio and image frames. We
   introduce `InputAudioRawFrame`, `OutputAudioRawFrame`, `InputImageRawFrame`
diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py
index 584be32db..7cb93606d 100644
--- a/src/pipecat/frames/frames.py
+++ b/src/pipecat/frames/frames.py
@@ -5,7 +5,7 @@
 #
 
 from dataclasses import dataclass, field
-from typing import Any, List, Optional, Tuple, Union
+from typing import Any, Dict, List, Optional, Tuple
 
 from pipecat.clocks.base_clock import BaseClock
 from pipecat.metrics.metrics import MetricsData
@@ -527,47 +527,11 @@ class UserImageRequestFrame(ControlFrame):
 
 
 @dataclass
-class LLMUpdateSettingsFrame(ControlFrame):
-    """A control frame containing a request to update LLM settings."""
+class ServiceUpdateSettingsFrame(ControlFrame):
+    """A control frame containing a request to update service settings."""
 
-    model: Optional[str] = None
-    temperature: Optional[float] = None
-    top_k: Optional[int] = None
-    top_p: Optional[float] = None
-    frequency_penalty: Optional[float] = None
-    presence_penalty: Optional[float] = None
-    max_tokens: Optional[int] = None
-    seed: Optional[int] = None
-    extra: dict = field(default_factory=dict)
-
-
-@dataclass
-class TTSUpdateSettingsFrame(ControlFrame):
-    """A control frame containing a request to update TTS settings."""
-
-    model: Optional[str] = None
-    voice: Optional[str] = None
-    language: Optional[Language] = None
-    speed: Optional[Union[str, float]] = None
-    emotion: Optional[List[str]] = None
-    engine: Optional[str] = None
-    pitch: Optional[str] = None
-    rate: Optional[str] = None
-    volume: Optional[str] = None
-    emphasis: Optional[str] = None
-    style: Optional[str] = None
-    style_degree: Optional[str] = None
-    role: Optional[str] = None
-    gender: Optional[str] = None
-    google_style: Optional[str] = None
-
-
-@dataclass
-class STTUpdateSettingsFrame(ControlFrame):
-    """A control frame containing a request to update STT settings."""
-
-    model: Optional[str] = None
-    language: Optional[Language] = None
+    service_type: str
+    settings: Dict[str, Any]
 
 
 @dataclass
diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index 344531de3..6ddc4d426 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -8,7 +8,7 @@ import asyncio
 import io
 import wave
 from abc import abstractmethod
-from typing import AsyncGenerator, List, Optional, Tuple, Union
+from typing import Any, AsyncGenerator, Dict, List, Optional, Tuple, Union
 
 from loguru import logger
 
@@ -19,15 +19,14 @@ from pipecat.frames.frames import (
     ErrorFrame,
     Frame,
     LLMFullResponseEndFrame,
+    ServiceUpdateSettingsFrame,
     StartFrame,
     StartInterruptionFrame,
-    STTUpdateSettingsFrame,
     TextFrame,
     TTSAudioRawFrame,
     TTSSpeakFrame,
     TTSStartedFrame,
     TTSStoppedFrame,
-    TTSUpdateSettingsFrame,
     UserImageRequestFrame,
     VisionImageRawFrame,
 )
@@ -169,6 +168,7 @@ class TTSService(AIService):
         self._push_stop_frames: bool = push_stop_frames
         self._stop_frame_timeout_s: float = stop_frame_timeout_s
         self._sample_rate: int = sample_rate
+        self._settings: Dict[str, Any] = {}
 
         self._stop_frame_task: Optional[asyncio.Task] = None
         self._stop_frame_queue: asyncio.Queue = asyncio.Queue()
@@ -231,10 +231,6 @@ class TTSService(AIService):
     async def set_role(self, role: str):
         pass
 
-    @abstractmethod
-    async def flush_audio(self):
-        pass
-
     @abstractmethod
     async def set_gender(self, gender: str):
         pass
@@ -243,6 +239,10 @@ class TTSService(AIService):
     async def set_google_style(self, google_style: str):
         pass
 
+    @abstractmethod
+    async def flush_audio(self):
+        pass
+
     # Converts the text to audio.
     @abstractmethod
     async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
@@ -267,6 +267,22 @@ class TTSService(AIService):
             await self._stop_frame_task
             self._stop_frame_task = None
 
+    async def _update_settings(self, settings: Dict[str, Any]):
+        for key, value in settings.items():
+            setter = getattr(self, f"set_{key}", None)
+            if setter and callable(setter):
+                try:
+                    if key == "language":
+                        await setter(Language(value))
+                    else:
+                        await setter(value)
+                except Exception as e:
+                    logger.warning(f"Error setting {key}: {e}")
+            else:
+                logger.warning(f"Unknown setting for TTS service: {key}")
+
+        self._settings.update(settings)
+
     async def say(self, text: str):
         aggregate_sentences = self._aggregate_sentences
         self._aggregate_sentences = False
@@ -293,8 +309,8 @@ class TTSService(AIService):
         elif isinstance(frame, TTSSpeakFrame):
             await self._push_tts_frames(frame.text)
             await self.flush_audio()
-        elif isinstance(frame, TTSUpdateSettingsFrame):
-            await self._update_tts_settings(frame)
+        elif isinstance(frame, ServiceUpdateSettingsFrame) and frame.service_type == "tts":
+            await self._update_settings(frame.settings)
         else:
             await self.push_frame(frame, direction)
 
@@ -341,34 +357,6 @@ class TTSService(AIService):
             # interrupted, the text is not added to the assistant context.
             await self.push_frame(TextFrame(text))
 
-    async def _update_tts_settings(self, frame: TTSUpdateSettingsFrame):
-        if frame.model is not None:
-            await self.set_model(frame.model)
-        if frame.voice is not None:
-            await self.set_voice(frame.voice)
-        if frame.language is not None:
-            await self.set_language(frame.language)
-        if frame.speed is not None:
-            await self.set_speed(frame.speed)
-        if frame.emotion is not None:
-            await self.set_emotion(frame.emotion)
-        if frame.engine is not None:
-            await self.set_engine(frame.engine)
-        if frame.pitch is not None:
-            await self.set_pitch(frame.pitch)
-        if frame.rate is not None:
-            await self.set_rate(frame.rate)
-        if frame.volume is not None:
-            await self.set_volume(frame.volume)
-        if frame.emphasis is not None:
-            await self.set_emphasis(frame.emphasis)
-        if frame.style is not None:
-            await self.set_style(frame.style)
-        if frame.style_degree is not None:
-            await self.set_style_degree(frame.style_degree)
-        if frame.role is not None:
-            await self.set_role(frame.role)
-
     async def _stop_frame_handler(self):
         try:
             has_started = False
@@ -454,6 +442,7 @@ class STTService(AIService):
 
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
+        self._settings: Dict[str, Any] = {}
 
     @abstractmethod
     async def set_model(self, model: str):
@@ -468,11 +457,21 @@ class STTService(AIService):
         """Returns transcript as a string"""
         pass
 
-    async def _update_stt_settings(self, frame: STTUpdateSettingsFrame):
-        if frame.model is not None:
-            await self.set_model(frame.model)
-        if frame.language is not None:
-            await self.set_language(frame.language)
+    async def _update_settings(self, settings: Dict[str, Any]):
+        for key, value in settings.items():
+            setter = getattr(self, f"set_{key}", None)
+            if setter and callable(setter):
+                try:
+                    if key == "language":
+                        await setter(Language(value))
+                    else:
+                        await setter(value)
+                except Exception as e:
+                    logger.warning(f"Error setting {key}: {e}")
+            else:
+                logger.warning(f"Unknown setting for STT service: {key}")
+
+        self._settings.update(settings)
 
     async def process_audio_frame(self, frame: AudioRawFrame):
         await self.process_generator(self.run_stt(frame.audio))
@@ -485,8 +484,8 @@ class STTService(AIService):
             # In this service we accumulate audio internally and at the end we
             # push a TextFrame. We don't really want to push audio frames down.
             await self.process_audio_frame(frame)
-        elif isinstance(frame, STTUpdateSettingsFrame):
-            await self._update_stt_settings(frame)
+        elif isinstance(frame, ServiceUpdateSettingsFrame) and frame.service_type == "stt":
+            await self._update_settings(frame.settings)
         else:
             await self.push_frame(frame, direction)
 
diff --git a/src/pipecat/services/anthropic.py b/src/pipecat/services/anthropic.py
index 639a922e6..09d6c5402 100644
--- a/src/pipecat/services/anthropic.py
+++ b/src/pipecat/services/anthropic.py
@@ -25,7 +25,7 @@ from pipecat.frames.frames import (
     LLMFullResponseEndFrame,
     LLMFullResponseStartFrame,
     LLMMessagesFrame,
-    LLMUpdateSettingsFrame,
+    ServiceUpdateSettingsFrame,
     StartInterruptionFrame,
     TextFrame,
     UserImageRawFrame,
@@ -284,20 +284,16 @@ class AnthropicLLMService(LLMService):
                 cache_read_input_tokens=cache_read_input_tokens,
             )
 
-    async def _update_settings(self, frame: LLMUpdateSettingsFrame):
-        if frame.model is not None:
-            logger.debug(f"Switching LLM model to: [{frame.model}]")
-            self.set_model_name(frame.model)
-        if frame.max_tokens is not None:
-            await self.set_max_tokens(frame.max_tokens)
-        if frame.temperature is not None:
-            await self.set_temperature(frame.temperature)
-        if frame.top_k is not None:
-            await self.set_top_k(frame.top_k)
-        if frame.top_p is not None:
-            await self.set_top_p(frame.top_p)
-        if frame.extra:
-            await self.set_extra(frame.extra)
+    async def _update_settings(self, settings: Dict[str, Any]):
+        for key, value in settings.items():
+            setter = getattr(self, f"set_{key}", None)
+            if setter and callable(setter):
+                try:
+                    await setter(value)
+                except Exception as e:
+                    logger.warning(f"Error setting {key}: {e}")
+            else:
+                logger.warning(f"Unknown setting for Anthropic LLM service: {key}")
 
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
@@ -313,8 +309,8 @@ class AnthropicLLMService(LLMService):
             # UserImageRawFrames coming through the pipeline and add them
             # to the context.
             context = AnthropicLLMContext.from_image_frame(frame)
-        elif isinstance(frame, LLMUpdateSettingsFrame):
-            await self._update_settings(frame)
+        elif isinstance(frame, ServiceUpdateSettingsFrame) and frame.service_type == "llm":
+            await self._update_settings(frame.settings)
         elif isinstance(frame, LLMEnablePromptCachingFrame):
             logger.debug(f"Setting enable prompt caching to: [{frame.enable}]")
             self._enable_prompt_caching_beta = frame.enable
diff --git a/src/pipecat/services/google.py b/src/pipecat/services/google.py
index 046b465b4..092b4703e 100644
--- a/src/pipecat/services/google.py
+++ b/src/pipecat/services/google.py
@@ -6,7 +6,7 @@
 
 import asyncio
 import json
-from typing import AsyncGenerator, List, Literal, Optional
+from typing import Any, AsyncGenerator, Dict, List, Literal, Optional
 
 from loguru import logger
 from pydantic import BaseModel
@@ -17,7 +17,7 @@ from pipecat.frames.frames import (
     LLMFullResponseEndFrame,
     LLMFullResponseStartFrame,
     LLMMessagesFrame,
-    LLMUpdateSettingsFrame,
+    ServiceUpdateSettingsFrame,
     TextFrame,
     TTSAudioRawFrame,
     TTSStartedFrame,
@@ -64,6 +64,21 @@ class GoogleLLMService(LLMService):
         self.set_model_name(model)
         self._client = gai.GenerativeModel(model)
 
+    async def set_model(self, model: str):
+        logger.debug(f"Switching LLM model to: [{model}]")
+        self._create_client(model)
+
+    async def _update_settings(self, settings: Dict[str, Any]):
+        for key, value in settings.items():
+            setter = getattr(self, f"set_{key}", None)
+            if setter and callable(setter):
+                try:
+                    await setter(value)
+                except Exception as e:
+                    logger.warning(f"Error setting {key}: {e}")
+            else:
+                logger.warning(f"Unknown setting for Google LLM service: {key}")
+
     def _get_messages_from_openai_context(self, context: OpenAILLMContext) -> List[glm.Content]:
         openai_messages = context.get_messages()
         google_messages = []
@@ -136,10 +151,8 @@ class GoogleLLMService(LLMService):
             context = OpenAILLMContext.from_messages(frame.messages)
         elif isinstance(frame, VisionImageRawFrame):
             context = OpenAILLMContext.from_image_frame(frame)
-        elif isinstance(frame, LLMUpdateSettingsFrame):
-            if frame.model is not None:
-                logger.debug(f"Switching LLM model to: [{frame.model}]")
-                self.set_model_name(frame.model)
+        elif isinstance(frame, ServiceUpdateSettingsFrame) and frame.service_type == "llm":
+            await self._update_settings(frame.settings)
         else:
             await self.push_frame(frame, direction)
 
diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py
index 9a7cc9023..57c1b3399 100644
--- a/src/pipecat/services/openai.py
+++ b/src/pipecat/services/openai.py
@@ -24,7 +24,7 @@ from pipecat.frames.frames import (
     LLMFullResponseEndFrame,
     LLMFullResponseStartFrame,
     LLMMessagesFrame,
-    LLMUpdateSettingsFrame,
+    ServiceUpdateSettingsFrame,
     StartInterruptionFrame,
     TextFrame,
     TTSAudioRawFrame,
@@ -295,22 +295,16 @@ class BaseOpenAILLMService(LLMService):
                         f"The LLM tried to call a function named '{function_name}', but there isn't a callback registered for that function."
                     )
 
-    async def _update_settings(self, frame: LLMUpdateSettingsFrame):
-        if frame.model is not None:
-            logger.debug(f"Switching LLM model to: [{frame.model}]")
-            self.set_model_name(frame.model)
-        if frame.frequency_penalty is not None:
-            await self.set_frequency_penalty(frame.frequency_penalty)
-        if frame.presence_penalty is not None:
-            await self.set_presence_penalty(frame.presence_penalty)
-        if frame.seed is not None:
-            await self.set_seed(frame.seed)
-        if frame.temperature is not None:
-            await self.set_temperature(frame.temperature)
-        if frame.top_p is not None:
-            await self.set_top_p(frame.top_p)
-        if frame.extra:
-            await self.set_extra(frame.extra)
+    async def _update_settings(self, settings: Dict[str, Any]):
+        for key, value in settings.items():
+            setter = getattr(self, f"set_{key}", None)
+            if setter and callable(setter):
+                try:
+                    await setter(value)
+                except Exception as e:
+                    logger.warning(f"Error setting {key}: {e}")
+            else:
+                logger.warning(f"Unknown setting for OpenAI LLM service: {key}")
 
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
@@ -322,8 +316,8 @@ class BaseOpenAILLMService(LLMService):
             context = OpenAILLMContext.from_messages(frame.messages)
         elif isinstance(frame, VisionImageRawFrame):
             context = OpenAILLMContext.from_image_frame(frame)
-        elif isinstance(frame, LLMUpdateSettingsFrame):
-            await self._update_settings(frame)
+        elif isinstance(frame, ServiceUpdateSettingsFrame) and frame.service_type == "llm":
+            await self._update_settings(frame.settings)
         else:
             await self.push_frame(frame, direction)
 
diff --git a/src/pipecat/services/together.py b/src/pipecat/services/together.py
index 5da470002..26a1a99fd 100644
--- a/src/pipecat/services/together.py
+++ b/src/pipecat/services/together.py
@@ -5,16 +5,13 @@
 #
 
 from typing import Any, Dict, Optional
+
 import httpx
 from loguru import logger
 from pydantic import BaseModel, Field
 
-from pipecat.frames.frames import (
-    LLMUpdateSettingsFrame,
-)
 from pipecat.services.openai import OpenAILLMService
 
-
 try:
     # Together.ai is recommending OpenAI-compatible function calling, so we've switched over
     # to using the OpenAI client library here rather than the Together Python client library.
@@ -104,21 +101,13 @@ class TogetherLLMService(OpenAILLMService):
         logger.debug(f"Switching LLM extra to: [{extra}]")
         self._extra = extra
 
-    async def _update_settings(self, frame: LLMUpdateSettingsFrame):
-        if frame.model is not None:
-            logger.debug(f"Switching LLM model to: [{frame.model}]")
-            self.set_model_name(frame.model)
-        if frame.frequency_penalty is not None:
-            await self.set_frequency_penalty(frame.frequency_penalty)
-        if frame.max_tokens is not None:
-            await self.set_max_tokens(frame.max_tokens)
-        if frame.presence_penalty is not None:
-            await self.set_presence_penalty(frame.presence_penalty)
-        if frame.temperature is not None:
-            await self.set_temperature(frame.temperature)
-        if frame.top_k is not None:
-            await self.set_top_k(frame.top_k)
-        if frame.top_p is not None:
-            await self.set_top_p(frame.top_p)
-        if frame.extra:
-            await self.set_extra(frame.extra)
+    async def _update_settings(self, settings: Dict[str, Any]):
+        for key, value in settings.items():
+            setter = getattr(self, f"set_{key}", None)
+            if setter and callable(setter):
+                try:
+                    await setter(value)
+                except Exception as e:
+                    logger.warning(f"Error setting {key}: {e}")
+            else:
+                logger.warning(f"Unknown setting for Together LLM service: {key}")

From 28643b453d78c0d71e040e52011f388e7eaad729 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Tue, 1 Oct 2024 14:37:07 -0400
Subject: [PATCH 122/135] Update to use LLM, STT, TTS subclasses and remove
 setter methods

---
 .../07c-interruptible-deepgram.py             |   2 +-
 .../foundational/07e-interruptible-playht.py  |  16 +-
 .../07g-interruptible-openai-tts.py           |  17 +--
 .../16-gpu-container-local-bot.py             |  14 +-
 src/pipecat/frames/frames.py                  |  16 +-
 src/pipecat/services/ai_services.py           | 120 +++++----------
 src/pipecat/services/anthropic.py             |  69 +++------
 src/pipecat/services/aws.py                   |  70 +++------
 src/pipecat/services/azure.py                 | 124 +++++-----------
 src/pipecat/services/cartesia.py              | 137 +++++++-----------
 src/pipecat/services/deepgram.py              |  43 +++---
 src/pipecat/services/elevenlabs.py            |  87 +++++------
 src/pipecat/services/gladia.py                |  19 ++-
 src/pipecat/services/google.py                | 112 +++++---------
 src/pipecat/services/lmnt.py                  |  32 ++--
 src/pipecat/services/openai.py                |  83 +++--------
 src/pipecat/services/playht.py                |  36 +++--
 src/pipecat/services/together.py              |  55 ++-----
 src/pipecat/services/xtts.py                  |  28 ++--
 19 files changed, 395 insertions(+), 685 deletions(-)

diff --git a/examples/foundational/07c-interruptible-deepgram.py b/examples/foundational/07c-interruptible-deepgram.py
index fc33c246f..f3b4ee246 100644
--- a/examples/foundational/07c-interruptible-deepgram.py
+++ b/examples/foundational/07c-interruptible-deepgram.py
@@ -50,7 +50,7 @@ async def main():
 
         stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
 
-        tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-helios-en")
+        tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice_id="aura-helios-en")
 
         llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
diff --git a/examples/foundational/07e-interruptible-playht.py b/examples/foundational/07e-interruptible-playht.py
index 9c48df93a..58d85ed79 100644
--- a/examples/foundational/07e-interruptible-playht.py
+++ b/examples/foundational/07e-interruptible-playht.py
@@ -4,11 +4,15 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-import aiohttp
 import asyncio
 import os
 import sys
 
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+from runner import configure
+
 from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
@@ -17,17 +21,11 @@ from pipecat.processors.aggregators.llm_response import (
     LLMAssistantResponseAggregator,
     LLMUserResponseAggregator,
 )
-from pipecat.services.playht import PlayHTTTSService
 from pipecat.services.openai import OpenAILLMService
+from pipecat.services.playht import PlayHTTTSService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 from pipecat.vad.silero import SileroVADAnalyzer
 
-from runner import configure
-
-from loguru import logger
-
-from dotenv import load_dotenv
-
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -54,7 +52,7 @@ async def main():
         tts = PlayHTTTSService(
             user_id=os.getenv("PLAYHT_USER_ID"),
             api_key=os.getenv("PLAYHT_API_KEY"),
-            voice_url="s3://voice-cloning-zero-shot/801a663f-efd0-4254-98d0-5c175514c3e8/jennifer/manifest.json",
+            voice_id="s3://voice-cloning-zero-shot/801a663f-efd0-4254-98d0-5c175514c3e8/jennifer/manifest.json",
         )
 
         llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
diff --git a/examples/foundational/07g-interruptible-openai-tts.py b/examples/foundational/07g-interruptible-openai-tts.py
index 70576c97a..b7671c42f 100644
--- a/examples/foundational/07g-interruptible-openai-tts.py
+++ b/examples/foundational/07g-interruptible-openai-tts.py
@@ -4,11 +4,15 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-import aiohttp
 import asyncio
 import os
 import sys
 
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+from runner import configure
+
 from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
@@ -17,17 +21,10 @@ from pipecat.processors.aggregators.llm_response import (
     LLMAssistantResponseAggregator,
     LLMUserResponseAggregator,
 )
-from pipecat.services.openai import OpenAITTSService
-from pipecat.services.openai import OpenAILLMService
+from pipecat.services.openai import OpenAILLMService, OpenAITTSService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 from pipecat.vad.silero import SileroVADAnalyzer
 
-from runner import configure
-
-from loguru import logger
-
-from dotenv import load_dotenv
-
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -51,7 +48,7 @@ async def main():
             ),
         )
 
-        tts = OpenAITTSService(api_key=os.getenv("OPENAI_API_KEY"), voice="alloy")
+        tts = OpenAITTSService(api_key=os.getenv("OPENAI_API_KEY"), voice_id="alloy")
 
         llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
diff --git a/examples/foundational/16-gpu-container-local-bot.py b/examples/foundational/16-gpu-container-local-bot.py
index 06bf45195..b3ae9686e 100644
--- a/examples/foundational/16-gpu-container-local-bot.py
+++ b/examples/foundational/16-gpu-container-local-bot.py
@@ -5,10 +5,14 @@
 #
 
 import asyncio
-import aiohttp
 import os
 import sys
 
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+from runner import configure
+
 from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
@@ -26,12 +30,6 @@ from pipecat.transports.services.daily import (
 )
 from pipecat.vad.silero import SileroVADAnalyzer
 
-from runner import configure
-
-from loguru import logger
-
-from dotenv import load_dotenv
-
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -57,7 +55,7 @@ async def main():
         tts = DeepgramTTSService(
             aiohttp_session=session,
             api_key=os.getenv("DEEPGRAM_API_KEY"),
-            voice="aura-asteria-en",
+            voice_id="aura-asteria-en",
             base_url="http://0.0.0.0:8080/v1/speak",
         )
 
diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py
index 7cb93606d..e2ef78df5 100644
--- a/src/pipecat/frames/frames.py
+++ b/src/pipecat/frames/frames.py
@@ -530,10 +530,24 @@ class UserImageRequestFrame(ControlFrame):
 class ServiceUpdateSettingsFrame(ControlFrame):
     """A control frame containing a request to update service settings."""
 
-    service_type: str
     settings: Dict[str, Any]
 
 
+@dataclass
+class LLMUpdateSettingsFrame(ServiceUpdateSettingsFrame):
+    pass
+
+
+@dataclass
+class TTSUpdateSettingsFrame(ServiceUpdateSettingsFrame):
+    pass
+
+
+@dataclass
+class STTUpdateSettingsFrame(ServiceUpdateSettingsFrame):
+    pass
+
+
 @dataclass
 class FunctionCallInProgressFrame(SystemFrame):
     """A frame signaling that a function call is in progress."""
diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py
index 6ddc4d426..64d79b582 100644
--- a/src/pipecat/services/ai_services.py
+++ b/src/pipecat/services/ai_services.py
@@ -8,7 +8,7 @@ import asyncio
 import io
 import wave
 from abc import abstractmethod
-from typing import Any, AsyncGenerator, Dict, List, Optional, Tuple, Union
+from typing import Any, AsyncGenerator, Dict, List, Optional, Tuple
 
 from loguru import logger
 
@@ -19,14 +19,15 @@ from pipecat.frames.frames import (
     ErrorFrame,
     Frame,
     LLMFullResponseEndFrame,
-    ServiceUpdateSettingsFrame,
     StartFrame,
     StartInterruptionFrame,
+    STTUpdateSettingsFrame,
     TextFrame,
     TTSAudioRawFrame,
     TTSSpeakFrame,
     TTSStartedFrame,
     TTSStoppedFrame,
+    TTSUpdateSettingsFrame,
     UserImageRequestFrame,
     VisionImageRawFrame,
 )
@@ -44,6 +45,7 @@ class AIService(FrameProcessor):
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
         self._model_name: str = ""
+        self._settings: Dict[str, Any] = {}
 
     @property
     def model_name(self) -> str:
@@ -62,6 +64,16 @@ class AIService(FrameProcessor):
     async def cancel(self, frame: CancelFrame):
         pass
 
+    async def _update_settings(self, settings: Dict[str, Any]):
+        for key, value in settings.items():
+            if key in self._settings:
+                logger.debug(f"Updating setting {key} to: [{value}] for {self.name}")
+                self._settings[key] = value
+            elif key == "model":
+                self.set_model_name(value)
+            else:
+                logger.warning(f"Unknown setting for {self.name} service: {key}")
+
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
@@ -168,6 +180,7 @@ class TTSService(AIService):
         self._push_stop_frames: bool = push_stop_frames
         self._stop_frame_timeout_s: float = stop_frame_timeout_s
         self._sample_rate: int = sample_rate
+        self._voice_id: str = ""
         self._settings: Dict[str, Any] = {}
 
         self._stop_frame_task: Optional[asyncio.Task] = None
@@ -184,60 +197,8 @@ class TTSService(AIService):
         self.set_model_name(model)
 
     @abstractmethod
-    async def set_voice(self, voice: str):
-        pass
-
-    @abstractmethod
-    async def set_language(self, language: Language):
-        pass
-
-    @abstractmethod
-    async def set_speed(self, speed: Union[str, float]):
-        pass
-
-    @abstractmethod
-    async def set_emotion(self, emotion: List[str]):
-        pass
-
-    @abstractmethod
-    async def set_engine(self, engine: str):
-        pass
-
-    @abstractmethod
-    async def set_pitch(self, pitch: str):
-        pass
-
-    @abstractmethod
-    async def set_rate(self, rate: str):
-        pass
-
-    @abstractmethod
-    async def set_volume(self, volume: str):
-        pass
-
-    @abstractmethod
-    async def set_emphasis(self, emphasis: str):
-        pass
-
-    @abstractmethod
-    async def set_style(self, style: str):
-        pass
-
-    @abstractmethod
-    async def set_style_degree(self, style_degree: str):
-        pass
-
-    @abstractmethod
-    async def set_role(self, role: str):
-        pass
-
-    @abstractmethod
-    async def set_gender(self, gender: str):
-        pass
-
-    @abstractmethod
-    async def set_google_style(self, google_style: str):
-        pass
+    def set_voice(self, voice: str):
+        self._voice_id = voice
 
     @abstractmethod
     async def flush_audio(self):
@@ -269,20 +230,18 @@ class TTSService(AIService):
 
     async def _update_settings(self, settings: Dict[str, Any]):
         for key, value in settings.items():
-            setter = getattr(self, f"set_{key}", None)
-            if setter and callable(setter):
-                try:
-                    if key == "language":
-                        await setter(Language(value))
-                    else:
-                        await setter(value)
-                except Exception as e:
-                    logger.warning(f"Error setting {key}: {e}")
+            if key in self._settings:
+                logger.debug(f"Updating TTS setting {key} to: [{value}]")
+                self._settings[key] = value
+                if key == "language":
+                    self._settings[key] = Language(value)
+            elif key == "model":
+                self.set_model_name(value)
+            elif key == "voice":
+                self.set_voice(value)
             else:
                 logger.warning(f"Unknown setting for TTS service: {key}")
 
-        self._settings.update(settings)
-
     async def say(self, text: str):
         aggregate_sentences = self._aggregate_sentences
         self._aggregate_sentences = False
@@ -309,7 +268,7 @@ class TTSService(AIService):
         elif isinstance(frame, TTSSpeakFrame):
             await self._push_tts_frames(frame.text)
             await self.flush_audio()
-        elif isinstance(frame, ServiceUpdateSettingsFrame) and frame.service_type == "tts":
+        elif isinstance(frame, TTSUpdateSettingsFrame):
             await self._update_settings(frame.settings)
         else:
             await self.push_frame(frame, direction)
@@ -448,31 +407,24 @@ class STTService(AIService):
     async def set_model(self, model: str):
         self.set_model_name(model)
 
-    @abstractmethod
-    async def set_language(self, language: Language):
-        pass
-
     @abstractmethod
     async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]:
         """Returns transcript as a string"""
         pass
 
     async def _update_settings(self, settings: Dict[str, Any]):
+        logger.debug(f"Updating STT settings: {self._settings}")
         for key, value in settings.items():
-            setter = getattr(self, f"set_{key}", None)
-            if setter and callable(setter):
-                try:
-                    if key == "language":
-                        await setter(Language(value))
-                    else:
-                        await setter(value)
-                except Exception as e:
-                    logger.warning(f"Error setting {key}: {e}")
+            if key in self._settings:
+                logger.debug(f"Updating STT setting {key} to: [{value}]")
+                self._settings[key] = value
+                if key == "language":
+                    self._settings[key] = Language(value)
+            elif key == "model":
+                self.set_model_name(value)
             else:
                 logger.warning(f"Unknown setting for STT service: {key}")
 
-        self._settings.update(settings)
-
     async def process_audio_frame(self, frame: AudioRawFrame):
         await self.process_generator(self.run_stt(frame.audio))
 
@@ -484,7 +436,7 @@ class STTService(AIService):
             # In this service we accumulate audio internally and at the end we
             # push a TextFrame. We don't really want to push audio frames down.
             await self.process_audio_frame(frame)
-        elif isinstance(frame, ServiceUpdateSettingsFrame) and frame.service_type == "stt":
+        elif isinstance(frame, STTUpdateSettingsFrame):
             await self._update_settings(frame.settings)
         else:
             await self.push_frame(frame, direction)
diff --git a/src/pipecat/services/anthropic.py b/src/pipecat/services/anthropic.py
index 09d6c5402..1b7064209 100644
--- a/src/pipecat/services/anthropic.py
+++ b/src/pipecat/services/anthropic.py
@@ -25,7 +25,7 @@ from pipecat.frames.frames import (
     LLMFullResponseEndFrame,
     LLMFullResponseStartFrame,
     LLMMessagesFrame,
-    ServiceUpdateSettingsFrame,
+    LLMUpdateSettingsFrame,
     StartInterruptionFrame,
     TextFrame,
     UserImageRawFrame,
@@ -96,12 +96,14 @@ class AnthropicLLMService(LLMService):
         super().__init__(**kwargs)
         self._client = AsyncAnthropic(api_key=api_key)
         self.set_model_name(model)
-        self._max_tokens = params.max_tokens
-        self._enable_prompt_caching_beta: bool = params.enable_prompt_caching_beta or False
-        self._temperature = params.temperature
-        self._top_k = params.top_k
-        self._top_p = params.top_p
-        self._extra = params.extra if isinstance(params.extra, dict) else {}
+        self._settings = {
+            "max_tokens": params.max_tokens,
+            "enable_prompt_caching_beta": params.enable_prompt_caching_beta or False,
+            "temperature": params.temperature,
+            "top_k": params.top_k,
+            "top_p": params.top_p,
+            "extra": params.extra if isinstance(params.extra, dict) else {},
+        }
 
     def can_generate_metrics(self) -> bool:
         return True
@@ -120,30 +122,6 @@ class AnthropicLLMService(LLMService):
         )
         return AnthropicContextAggregatorPair(_user=user, _assistant=assistant)
 
-    async def set_enable_prompt_caching_beta(self, enable_prompt_caching_beta: bool):
-        logger.debug(f"Switching LLM enable_prompt_caching_beta to: [{enable_prompt_caching_beta}]")
-        self._enable_prompt_caching_beta = enable_prompt_caching_beta
-
-    async def set_max_tokens(self, max_tokens: int):
-        logger.debug(f"Switching LLM max_tokens to: [{max_tokens}]")
-        self._max_tokens = max_tokens
-
-    async def set_temperature(self, temperature: float):
-        logger.debug(f"Switching LLM temperature to: [{temperature}]")
-        self._temperature = temperature
-
-    async def set_top_k(self, top_k: float):
-        logger.debug(f"Switching LLM top_k to: [{top_k}]")
-        self._top_k = top_k
-
-    async def set_top_p(self, top_p: float):
-        logger.debug(f"Switching LLM top_p to: [{top_p}]")
-        self._top_p = top_p
-
-    async def set_extra(self, extra: Dict[str, Any]):
-        logger.debug(f"Switching LLM extra to: [{extra}]")
-        self._extra = extra
-
     async def _process_context(self, context: OpenAILLMContext):
         # Usage tracking. We track the usage reported by Anthropic in prompt_tokens and
         # completion_tokens. We also estimate the completion tokens from output text
@@ -165,11 +143,11 @@ class AnthropicLLMService(LLMService):
             )
 
             messages = context.messages
-            if self._enable_prompt_caching_beta:
+            if self._settings["enable_prompt_caching_beta"]:
                 messages = context.get_messages_with_cache_control_markers()
 
             api_call = self._client.messages.create
-            if self._enable_prompt_caching_beta:
+            if self._settings["enable_prompt_caching_beta"]:
                 api_call = self._client.beta.prompt_caching.messages.create
 
             await self.start_ttfb_metrics()
@@ -179,14 +157,14 @@ class AnthropicLLMService(LLMService):
                 "system": context.system,
                 "messages": messages,
                 "model": self.model_name,
-                "max_tokens": self._max_tokens,
+                "max_tokens": self._settings["max_tokens"],
                 "stream": True,
-                "temperature": self._temperature,
-                "top_k": self._top_k,
-                "top_p": self._top_p,
+                "temperature": self._settings["temperature"],
+                "top_k": self._settings["top_k"],
+                "top_p": self._settings["top_p"],
             }
 
-            params.update(self._extra)
+            params.update(self._settings["extra"])
 
             response = await api_call(**params)
 
@@ -284,17 +262,6 @@ class AnthropicLLMService(LLMService):
                 cache_read_input_tokens=cache_read_input_tokens,
             )
 
-    async def _update_settings(self, settings: Dict[str, Any]):
-        for key, value in settings.items():
-            setter = getattr(self, f"set_{key}", None)
-            if setter and callable(setter):
-                try:
-                    await setter(value)
-                except Exception as e:
-                    logger.warning(f"Error setting {key}: {e}")
-            else:
-                logger.warning(f"Unknown setting for Anthropic LLM service: {key}")
-
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
@@ -309,11 +276,11 @@ class AnthropicLLMService(LLMService):
             # UserImageRawFrames coming through the pipeline and add them
             # to the context.
             context = AnthropicLLMContext.from_image_frame(frame)
-        elif isinstance(frame, ServiceUpdateSettingsFrame) and frame.service_type == "llm":
+        elif isinstance(frame, LLMUpdateSettingsFrame):
             await self._update_settings(frame.settings)
         elif isinstance(frame, LLMEnablePromptCachingFrame):
             logger.debug(f"Setting enable prompt caching to: [{frame.enable}]")
-            self._enable_prompt_caching_beta = frame.enable
+            self._settings["enable_prompt_caching_beta"] = frame.enable
         else:
             await self.push_frame(frame, direction)
 
diff --git a/src/pipecat/services/aws.py b/src/pipecat/services/aws.py
index 80240985f..7004c21f7 100644
--- a/src/pipecat/services/aws.py
+++ b/src/pipecat/services/aws.py
@@ -6,6 +6,7 @@
 
 from typing import AsyncGenerator, Optional
 
+from loguru import logger
 from pydantic import BaseModel
 
 from pipecat.frames.frames import (
@@ -17,8 +18,6 @@ from pipecat.frames.frames import (
 )
 from pipecat.services.ai_services import TTSService
 
-from loguru import logger
-
 try:
     import boto3
     from botocore.exceptions import BotoCoreError, ClientError
@@ -57,9 +56,16 @@ class AWSTTSService(TTSService):
             aws_secret_access_key=api_key,
             region_name=region,
         )
-        self._voice_id = voice_id
-        self._sample_rate = sample_rate
-        self._params = params
+        self._settings = {
+            "sample_rate": sample_rate,
+            "engine": params.engine,
+            "language": params.language,
+            "pitch": params.pitch,
+            "rate": params.rate,
+            "volume": params.volume,
+        }
+
+        self.set_voice(voice_id)
 
     def can_generate_metrics(self) -> bool:
         return True
@@ -67,18 +73,18 @@ class AWSTTSService(TTSService):
     def _construct_ssml(self, text: str) -> str:
         ssml = "<speak>"
 
-        if self._params.language:
-            ssml += f"<lang xml:lang='{self._params.language}'>"
+        if self._settings["language"]:
+            ssml += f"<lang xml:lang='{self._settings["language"]}'>"
 
         prosody_attrs = []
         # Prosody tags are only supported for standard and neural engines
-        if self._params.engine != "generative":
-            if self._params.rate:
-                prosody_attrs.append(f"rate='{self._params.rate}'")
-            if self._params.pitch:
-                prosody_attrs.append(f"pitch='{self._params.pitch}'")
-            if self._params.volume:
-                prosody_attrs.append(f"volume='{self._params.volume}'")
+        if self._settings["engine"] != "generative":
+            if self._settings["rate"]:
+                prosody_attrs.append(f"rate='{self._settings["rate"]}'")
+            if self._settings["pitch"]:
+                prosody_attrs.append(f"pitch='{self._settings["pitch"]}'")
+            if self._settings["volume"]:
+                prosody_attrs.append(f"volume='{self._settings["volume"]}'")
 
             if prosody_attrs:
                 ssml += f"<prosody {' '.join(prosody_attrs)}>"
@@ -90,41 +96,13 @@ class AWSTTSService(TTSService):
         if prosody_attrs:
             ssml += "</prosody>"
 
-        if self._params.language:
+        if self._settings["language"]:
             ssml += "</lang>"
 
         ssml += "</speak>"
 
         return ssml
 
-    async def set_voice(self, voice: str):
-        logger.debug(f"Switching TTS voice to: [{voice}]")
-        self._voice_id = voice
-
-    async def set_engine(self, engine: str):
-        logger.debug(f"Switching TTS engine to: [{engine}]")
-        self._params.engine = engine
-
-    async def set_language(self, language: str):
-        logger.debug(f"Switching TTS language to: [{language}]")
-        self._params.language = language
-
-    async def set_pitch(self, pitch: str):
-        logger.debug(f"Switching TTS pitch to: [{pitch}]")
-        self._params.pitch = pitch
-
-    async def set_rate(self, rate: str):
-        logger.debug(f"Switching TTS rate to: [{rate}]")
-        self._params.rate = rate
-
-    async def set_volume(self, volume: str):
-        logger.debug(f"Switching TTS volume to: [{volume}]")
-        self._params.volume = volume
-
-    async def set_params(self, params: InputParams):
-        logger.debug(f"Switching TTS params to: [{params}]")
-        self._params = params
-
     async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
         logger.debug(f"Generating TTS: [{text}]")
 
@@ -139,8 +117,8 @@ class AWSTTSService(TTSService):
                 "TextType": "ssml",
                 "OutputFormat": "pcm",
                 "VoiceId": self._voice_id,
-                "Engine": self._params.engine,
-                "SampleRate": str(self._sample_rate),
+                "Engine": self._settings["engine"],
+                "SampleRate": str(self._settings["sample_rate"]),
             }
 
             # Filter out None values
@@ -160,7 +138,7 @@ class AWSTTSService(TTSService):
                         chunk = audio_data[i : i + chunk_size]
                         if len(chunk) > 0:
                             await self.stop_ttfb_metrics()
-                            frame = TTSAudioRawFrame(chunk, self._sample_rate, 1)
+                            frame = TTSAudioRawFrame(chunk, self._settings["sample_rate"], 1)
                             yield frame
 
             await self.push_frame(TTSStoppedFrame())
diff --git a/src/pipecat/services/azure.py b/src/pipecat/services/azure.py
index a1349cefe..1b2b9a3f2 100644
--- a/src/pipecat/services/azure.py
+++ b/src/pipecat/services/azure.py
@@ -4,12 +4,13 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-import aiohttp
 import asyncio
 import io
-
 from typing import AsyncGenerator, Optional
 
+import aiohttp
+from loguru import logger
+from PIL import Image
 from pydantic import BaseModel
 
 from pipecat.frames.frames import (
@@ -28,10 +29,6 @@ from pipecat.services.ai_services import ImageGenService, STTService, TTSService
 from pipecat.services.openai import BaseOpenAILLMService
 from pipecat.utils.time import time_now_iso8601
 
-from PIL import Image
-
-from loguru import logger
-
 # See .env.example for Azure configuration needed
 try:
     from azure.cognitiveservices.speech import (
@@ -89,7 +86,7 @@ class AzureTTSService(TTSService):
         *,
         api_key: str,
         region: str,
-        voice="en-US-SaraNeural",
+        voice_id="en-US-SaraNeural",
         sample_rate: int = 16000,
         params: InputParams = InputParams(),
         **kwargs,
@@ -99,114 +96,67 @@ class AzureTTSService(TTSService):
         speech_config = SpeechConfig(subscription=api_key, region=region)
         self._speech_synthesizer = SpeechSynthesizer(speech_config=speech_config, audio_config=None)
 
-        self._voice = voice
-        self._sample_rate = sample_rate
-        self._params = params
+        self._settings = {
+            "sample_rate": sample_rate,
+            "emphasis": params.emphasis,
+            "language": params.language,
+            "pitch": params.pitch,
+            "rate": params.rate,
+            "role": params.role,
+            "style": params.style,
+            "style_degree": params.style_degree,
+            "volume": params.volume,
+        }
+
+        self.set_voice(voice_id)
 
     def can_generate_metrics(self) -> bool:
         return True
 
     def _construct_ssml(self, text: str) -> str:
         ssml = (
-            f"<speak version='1.0' xml:lang='{self._params.language}' "
+            f"<speak version='1.0' xml:lang='{self._settings['language']}' "
             "xmlns='http://www.w3.org/2001/10/synthesis' "
             "xmlns:mstts='http://www.w3.org/2001/mstts'>"
-            f"<voice name='{self._voice}'>"
+            f"<voice name='{self._voice_id}'>"
             "<mstts:silence type='Sentenceboundary' value='20ms' />"
         )
 
-        if self._params.style:
-            ssml += f"<mstts:express-as style='{self._params.style}'"
-            if self._params.style_degree:
-                ssml += f" styledegree='{self._params.style_degree}'"
-            if self._params.role:
-                ssml += f" role='{self._params.role}'"
+        if self._settings["style"]:
+            ssml += f"<mstts:express-as style='{self._settings['style']}'"
+            if self._settings["style_degree"]:
+                ssml += f" styledegree='{self._settings['style_degree']}'"
+            if self._settings["role"]:
+                ssml += f" role='{self._settings['role']}'"
             ssml += ">"
 
         prosody_attrs = []
-        if self._params.rate:
-            prosody_attrs.append(f"rate='{self._params.rate}'")
-        if self._params.pitch:
-            prosody_attrs.append(f"pitch='{self._params.pitch}'")
-        if self._params.volume:
-            prosody_attrs.append(f"volume='{self._params.volume}'")
+        if self._settings["rate"]:
+            prosody_attrs.append(f"rate='{self._settings['rate']}'")
+        if self._settings["pitch"]:
+            prosody_attrs.append(f"pitch='{self._settings['pitch']}'")
+        if self._settings["volume"]:
+            prosody_attrs.append(f"volume='{self._settings['volume']}'")
 
         ssml += f"<prosody {' '.join(prosody_attrs)}>"
 
-        if self._params.emphasis:
-            ssml += f"<emphasis level='{self._params.emphasis}'>"
+        if self._settings["emphasis"]:
+            ssml += f"<emphasis level='{self._settings['emphasis']}'>"
 
         ssml += text
 
-        if self._params.emphasis:
+        if self._settings["emphasis"]:
             ssml += "</emphasis>"
 
         ssml += "</prosody>"
 
-        if self._params.style:
+        if self._settings["style"]:
             ssml += "</mstts:express-as>"
 
         ssml += "</voice></speak>"
 
         return ssml
 
-    async def set_voice(self, voice: str):
-        logger.debug(f"Switching TTS voice to: [{voice}]")
-        self._voice = voice
-
-    async def set_emphasis(self, emphasis: str):
-        logger.debug(f"Setting TTS emphasis to: [{emphasis}]")
-        self._params.emphasis = emphasis
-
-    async def set_language(self, language: str):
-        logger.debug(f"Setting TTS language code to: [{language}]")
-        self._params.language = language
-
-    async def set_pitch(self, pitch: str):
-        logger.debug(f"Setting TTS pitch to: [{pitch}]")
-        self._params.pitch = pitch
-
-    async def set_rate(self, rate: str):
-        logger.debug(f"Setting TTS rate to: [{rate}]")
-        self._params.rate = rate
-
-    async def set_role(self, role: str):
-        logger.debug(f"Setting TTS role to: [{role}]")
-        self._params.role = role
-
-    async def set_style(self, style: str):
-        logger.debug(f"Setting TTS style to: [{style}]")
-        self._params.style = style
-
-    async def set_style_degree(self, style_degree: str):
-        logger.debug(f"Setting TTS style degree to: [{style_degree}]")
-        self._params.style_degree = style_degree
-
-    async def set_volume(self, volume: str):
-        logger.debug(f"Setting TTS volume to: [{volume}]")
-        self._params.volume = volume
-
-    async def set_params(self, **kwargs):
-        valid_params = {
-            "voice": self.set_voice,
-            "emphasis": self.set_emphasis,
-            "language_code": self.set_language,
-            "pitch": self.set_pitch,
-            "rate": self.set_rate,
-            "role": self.set_role,
-            "style": self.set_style,
-            "style_degree": self.set_style_degree,
-            "volume": self.set_volume,
-        }
-
-        for param, value in kwargs.items():
-            if param in valid_params:
-                await valid_params[param](value)
-            else:
-                logger.warning(f"Ignoring unknown parameter: {param}")
-
-        logger.debug(f"Updated TTS parameters: {', '.join(kwargs.keys())}")
-
     async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
         logger.debug(f"Generating TTS: [{text}]")
 
@@ -222,7 +172,9 @@ class AzureTTSService(TTSService):
             await self.push_frame(TTSStartedFrame())
             # Azure always sends a 44-byte header. Strip it off.
             yield TTSAudioRawFrame(
-                audio=result.audio_data[44:], sample_rate=self._sample_rate, num_channels=1
+                audio=result.audio_data[44:],
+                sample_rate=self._settings["sample_rate"],
+                num_channels=1,
             )
             await self.push_frame(TTSStoppedFrame())
         elif result.reason == ResultReason.Canceled:
diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index 5f798b1e5..0817879c4 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -4,36 +4,35 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
+import asyncio
+import base64
 import json
 import uuid
-import base64
-import asyncio
+from typing import AsyncGenerator, List, Optional, Union
 
-from typing import AsyncGenerator, Optional, Union, List
+from loguru import logger
 from pydantic.main import BaseModel
 
 from pipecat.frames.frames import (
     CancelFrame,
+    EndFrame,
     ErrorFrame,
     Frame,
-    StartInterruptionFrame,
+    LLMFullResponseEndFrame,
     StartFrame,
-    EndFrame,
+    StartInterruptionFrame,
     TTSAudioRawFrame,
     TTSStartedFrame,
     TTSStoppedFrame,
-    LLMFullResponseEndFrame,
 )
 from pipecat.processors.frame_processor import FrameDirection
+from pipecat.services.ai_services import TTSService, WordTTSService
 from pipecat.transcriptions.language import Language
-from pipecat.services.ai_services import WordTTSService, TTSService
-
-from loguru import logger
 
 # See .env.example for Cartesia configuration needed
 try:
-    from cartesia import AsyncCartesia
     import websockets
+    from cartesia import AsyncCartesia
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
@@ -66,7 +65,7 @@ class CartesiaTTSService(WordTTSService):
         encoding: Optional[str] = "pcm_s16le"
         sample_rate: Optional[int] = 16000
         container: Optional[str] = "raw"
-        language: Optional[str] = "en"
+        language: Optional[Language] = Language.EN
         speed: Optional[Union[str, float]] = ""
         emotion: Optional[List[str]] = []
 
@@ -77,7 +76,7 @@ class CartesiaTTSService(WordTTSService):
         voice_id: str,
         cartesia_version: str = "2024-06-10",
         url: str = "wss://api.cartesia.ai/tts/websocket",
-        model_id: str = "sonic-english",
+        model: str = "sonic-english",
         params: InputParams = InputParams(),
         **kwargs,
     ):
@@ -101,17 +100,18 @@ class CartesiaTTSService(WordTTSService):
         self._api_key = api_key
         self._cartesia_version = cartesia_version
         self._url = url
-        self._voice_id = voice_id
-        self._model_id = model_id
-        self.set_model_name(model_id)
-        self._output_format = {
-            "container": params.container,
-            "encoding": params.encoding,
-            "sample_rate": params.sample_rate,
+        self._settings = {
+            "output_format": {
+                "container": params.container,
+                "encoding": params.encoding,
+                "sample_rate": params.sample_rate,
+            },
+            "language": language_to_cartesia_language(params.language) if params.language else None,
+            "speed": params.speed,
+            "emotion": params.emotion,
         }
-        self._language = params.language
-        self._speed = params.speed
-        self._emotion = params.emotion
+        self.set_model_name(model)
+        self.set_voice(voice_id)
 
         self._websocket = None
         self._context_id = None
@@ -125,42 +125,28 @@ class CartesiaTTSService(WordTTSService):
         await super().set_model(model)
         logger.debug(f"Switching TTS model to: [{model}]")
 
-    async def set_voice(self, voice: str):
-        logger.debug(f"Switching TTS voice to: [{voice}]")
-        self._voice_id = voice
-
-    async def set_speed(self, speed: str):
-        logger.debug(f"Switching TTS speed to: [{speed}]")
-        self._speed = speed
-
-    async def set_emotion(self, emotion: list[str]):
-        logger.debug(f"Switching TTS emotion to: [{emotion}]")
-        self._emotion = emotion
-
-    async def set_language(self, language: Language):
-        logger.debug(f"Switching TTS language to: [{language}]")
-        self._language = language_to_cartesia_language(language)
-
     def _build_msg(
         self, text: str = "", continue_transcript: bool = True, add_timestamps: bool = True
     ):
-        voice_config = {"mode": "id", "id": self._voice_id}
+        voice_config = {}
+        voice_config["mode"] = "id"
+        voice_config["id"] = self._voice_id
 
-        if self._speed or self._emotion:
+        if self._settings["speed"] or self._settings["emotion"]:
             voice_config["__experimental_controls"] = {}
-            if self._speed:
-                voice_config["__experimental_controls"]["speed"] = self._speed
-            if self._emotion:
-                voice_config["__experimental_controls"]["emotion"] = self._emotion
+            if self._settings["speed"]:
+                voice_config["__experimental_controls"]["speed"] = self._settings["speed"]
+            if self._settings["emotion"]:
+                voice_config["__experimental_controls"]["emotion"] = self._settings["emotion"]
 
         msg = {
             "transcript": text,
             "continue": continue_transcript,
             "context_id": self._context_id,
-            "model_id": self._model_name,
+            "model_id": self.model_name,
             "voice": voice_config,
-            "output_format": self._output_format,
-            "language": self._language,
+            "output_format": self._settings["output_format"],
+            "language": self._settings["language"],
             "add_timestamps": add_timestamps,
         }
         return json.dumps(msg)
@@ -245,7 +231,7 @@ class CartesiaTTSService(WordTTSService):
                     self.start_word_timestamps()
                     frame = TTSAudioRawFrame(
                         audio=base64.b64decode(msg["data"]),
-                        sample_rate=self._output_format["sample_rate"],
+                        sample_rate=self._settings["output_format"]["sample_rate"],
                         num_channels=1,
                     )
                     await self.push_frame(frame)
@@ -303,7 +289,7 @@ class CartesiaHttpTTSService(TTSService):
         *,
         api_key: str,
         voice_id: str,
-        model_id: str = "sonic-english",
+        model: str = "sonic-english",
         base_url: str = "https://api.cartesia.ai",
         params: InputParams = InputParams(),
         **kwargs,
@@ -311,17 +297,18 @@ class CartesiaHttpTTSService(TTSService):
         super().__init__(**kwargs)
 
         self._api_key = api_key
-        self._voice_id = voice_id
-        self._model_id = model_id
-        self.set_model_name(model_id)
-        self._output_format = {
-            "container": params.container,
-            "encoding": params.encoding,
-            "sample_rate": params.sample_rate,
+        self._settings = {
+            "output_format": {
+                "container": params.container,
+                "encoding": params.encoding,
+                "sample_rate": params.sample_rate,
+            },
+            "language": params.language,
+            "speed": params.speed,
+            "emotion": params.emotion,
         }
-        self._language = params.language
-        self._speed = params.speed
-        self._emotion = params.emotion
+        self.set_voice(voice_id)
+        self.set_model_name(model)
 
         self._client = AsyncCartesia(api_key=api_key, base_url=base_url)
 
@@ -333,22 +320,6 @@ class CartesiaHttpTTSService(TTSService):
         self._model_id = model
         await super().set_model(model)
 
-    async def set_voice(self, voice: str):
-        logger.debug(f"Switching TTS voice to: [{voice}]")
-        self._voice_id = voice
-
-    async def set_speed(self, speed: str):
-        logger.debug(f"Switching TTS speed to: [{speed}]")
-        self._speed = speed
-
-    async def set_emotion(self, emotion: list[str]):
-        logger.debug(f"Switching TTS emotion to: [{emotion}]")
-        self._emotion = emotion
-
-    async def set_language(self, language: Language):
-        logger.debug(f"Switching TTS language to: [{language}]")
-        self._language = language_to_cartesia_language(language)
-
     async def stop(self, frame: EndFrame):
         await super().stop(frame)
         await self._client.close()
@@ -365,19 +336,19 @@ class CartesiaHttpTTSService(TTSService):
 
         try:
             voice_controls = None
-            if self._speed or self._emotion:
+            if self._settings["speed"] or self._settings["emotion"]:
                 voice_controls = {}
-                if self._speed:
-                    voice_controls["speed"] = self._speed
-                if self._emotion:
-                    voice_controls["emotion"] = self._emotion
+                if self._settings["speed"]:
+                    voice_controls["speed"] = self._settings["speed"]
+                if self._settings["emotion"]:
+                    voice_controls["emotion"] = self._settings["emotion"]
 
             output = await self._client.tts.sse(
                 model_id=self._model_id,
                 transcript=text,
                 voice_id=self._voice_id,
-                output_format=self._output_format,
-                language=self._language,
+                output_format=self._settings["output_format"],
+                language=self._settings["language"],
                 stream=False,
                 _experimental_voice_controls=voice_controls,
             )
@@ -386,7 +357,7 @@ class CartesiaHttpTTSService(TTSService):
 
             frame = TTSAudioRawFrame(
                 audio=output["audio"],
-                sample_rate=self._output_format["sample_rate"],
+                sample_rate=self._settings["output_format"]["sample_rate"],
                 num_channels=1,
             )
             yield frame
diff --git a/src/pipecat/services/deepgram.py b/src/pipecat/services/deepgram.py
index d109cce3c..40fe0168d 100644
--- a/src/pipecat/services/deepgram.py
+++ b/src/pipecat/services/deepgram.py
@@ -5,9 +5,10 @@
 #
 
 import asyncio
-
 from typing import AsyncGenerator
 
+from loguru import logger
+
 from pipecat.frames.frames import (
     CancelFrame,
     EndFrame,
@@ -24,8 +25,6 @@ from pipecat.services.ai_services import STTService, TTSService
 from pipecat.transcriptions.language import Language
 from pipecat.utils.time import time_now_iso8601
 
-from loguru import logger
-
 # See .env.example for Deepgram configuration needed
 try:
     from deepgram import (
@@ -50,32 +49,30 @@ class DeepgramTTSService(TTSService):
         self,
         *,
         api_key: str,
-        voice: str = "aura-helios-en",
+        voice_id: str = "aura-helios-en",
         sample_rate: int = 16000,
         encoding: str = "linear16",
         **kwargs,
     ):
         super().__init__(**kwargs)
 
-        self._voice = voice
-        self._sample_rate = sample_rate
-        self._encoding = encoding
+        self._settings = {
+            "sample_rate": sample_rate,
+            "encoding": encoding,
+        }
+        self.set_voice(voice_id)
         self._deepgram_client = DeepgramClient(api_key=api_key)
 
     def can_generate_metrics(self) -> bool:
         return True
 
-    async def set_voice(self, voice: str):
-        logger.debug(f"Switching TTS voice to: [{voice}]")
-        self._voice = voice
-
     async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
         logger.debug(f"Generating TTS: [{text}]")
 
         options = SpeakOptions(
-            model=self._voice,
-            encoding=self._encoding,
-            sample_rate=self._sample_rate,
+            model=self._voice_id,
+            encoding=self._settings["encoding"],
+            sample_rate=self._settings["sample_rate"],
             container="none",
         )
 
@@ -103,7 +100,9 @@ class DeepgramTTSService(TTSService):
                 chunk = audio_buffer.read(chunk_size)
                 if not chunk:
                     break
-                frame = TTSAudioRawFrame(audio=chunk, sample_rate=self._sample_rate, num_channels=1)
+                frame = TTSAudioRawFrame(
+                    audio=chunk, sample_rate=self._settings["sample_rate"], num_channels=1
+                )
                 yield frame
 
             await self.push_frame(TTSStoppedFrame())
@@ -135,7 +134,7 @@ class DeepgramSTTService(STTService):
     ):
         super().__init__(**kwargs)
 
-        self._live_options = live_options
+        self._settings = vars(live_options)
 
         self._client = DeepgramClient(
             api_key, config=DeepgramClientOptions(url=url, options={"keepalive": "true"})
@@ -147,7 +146,7 @@ class DeepgramSTTService(STTService):
 
     @property
     def vad_enabled(self):
-        return self._live_options.vad_events
+        return self._settings["vad_events"]
 
     def can_generate_metrics(self) -> bool:
         return self.vad_enabled
@@ -155,13 +154,7 @@ class DeepgramSTTService(STTService):
     async def set_model(self, model: str):
         await super().set_model(model)
         logger.debug(f"Switching STT model to: [{model}]")
-        self._live_options.model = model
-        await self._disconnect()
-        await self._connect()
-
-    async def set_language(self, language: Language):
-        logger.debug(f"Switching STT language to: [{language}]")
-        self._live_options.language = language
+        self._settings["model"] = model
         await self._disconnect()
         await self._connect()
 
@@ -182,7 +175,7 @@ class DeepgramSTTService(STTService):
         yield None
 
     async def _connect(self):
-        if await self._connection.start(self._live_options):
+        if await self._connection.start(self._settings):
             logger.debug(f"{self}: Connected to Deepgram")
         else:
             logger.error(f"{self}: Unable to connect to Deepgram")
diff --git a/src/pipecat/services/elevenlabs.py b/src/pipecat/services/elevenlabs.py
index 611f2a024..871b3eec6 100644
--- a/src/pipecat/services/elevenlabs.py
+++ b/src/pipecat/services/elevenlabs.py
@@ -24,6 +24,7 @@ from pipecat.frames.frames import (
 )
 from pipecat.processors.frame_processor import FrameDirection
 from pipecat.services.ai_services import WordTTSService
+from pipecat.transcriptions.language import Language
 
 # See .env.example for ElevenLabs configuration needed
 try:
@@ -72,7 +73,7 @@ def calculate_word_times(
 
 class ElevenLabsTTSService(WordTTSService):
     class InputParams(BaseModel):
-        language: Optional[str] = None
+        language: Optional[Language] = Language.EN
         output_format: Literal["pcm_16000", "pcm_22050", "pcm_24000", "pcm_44100"] = "pcm_16000"
         optimize_streaming_latency: Optional[str] = None
         stability: Optional[float] = None
@@ -124,10 +125,19 @@ class ElevenLabsTTSService(WordTTSService):
         )
 
         self._api_key = api_key
-        self._voice_id = voice_id
-        self.set_model_name(model)
         self._url = url
-        self._params = params
+        self._settings = {
+            "sample_rate": sample_rate_from_output_format(params.output_format),
+            "language": params.language,
+            "output_format": params.output_format,
+            "optimize_streaming_latency": params.optimize_streaming_latency,
+            "stability": params.stability,
+            "similarity_boost": params.similarity_boost,
+            "style": params.style,
+            "use_speaker_boost": params.use_speaker_boost,
+        }
+        self.set_model_name(model)
+        self.set_voice(voice_id)
         self._voice_settings = self._set_voice_settings()
 
         # Websocket connection to ElevenLabs.
@@ -142,19 +152,22 @@ class ElevenLabsTTSService(WordTTSService):
 
     def _set_voice_settings(self):
         voice_settings = {}
-        if self._params.stability is not None and self._params.similarity_boost is not None:
-            voice_settings["stability"] = self._params.stability
-            voice_settings["similarity_boost"] = self._params.similarity_boost
-            if self._params.style is not None:
-                voice_settings["style"] = self._params.style
-            if self._params.use_speaker_boost is not None:
-                voice_settings["use_speaker_boost"] = self._params.use_speaker_boost
+        if (
+            self._settings["stability"] is not None
+            and self._settings["similarity_boost"] is not None
+        ):
+            voice_settings["stability"] = self._settings["stability"]
+            voice_settings["similarity_boost"] = self._settings["similarity_boost"]
+            if self._settings["style"] is not None:
+                voice_settings["style"] = self._settings["style"]
+            if self._settings["use_speaker_boost"] is not None:
+                voice_settings["use_speaker_boost"] = self._settings["use_speaker_boost"]
         else:
-            if self._params.style is not None:
+            if self._settings["style"] is not None:
                 logger.warning(
                     "'style' is set but will not be applied because 'stability' and 'similarity_boost' are not both set."
                 )
-            if self._params.use_speaker_boost is not None:
+            if self._settings["use_speaker_boost"] is not None:
                 logger.warning(
                     "'use_speaker_boost' is set but will not be applied because 'stability' and 'similarity_boost' are not both set."
                 )
@@ -167,33 +180,13 @@ class ElevenLabsTTSService(WordTTSService):
         await self._disconnect()
         await self._connect()
 
-    async def set_voice(self, voice: str):
-        logger.debug(f"Switching TTS voice to: [{voice}]")
-        self._voice_id = voice
-        await self._disconnect()
-        await self._connect()
-
-    async def set_voice_settings(
-        self,
-        stability: Optional[float] = None,
-        similarity_boost: Optional[float] = None,
-        style: Optional[float] = None,
-        use_speaker_boost: Optional[bool] = None,
-    ):
-        self._params.stability = stability if stability is not None else self._params.stability
-        self._params.similarity_boost = (
-            similarity_boost if similarity_boost is not None else self._params.similarity_boost
-        )
-        self._params.style = style if style is not None else self._params.style
-        self._params.use_speaker_boost = (
-            use_speaker_boost if use_speaker_boost is not None else self._params.use_speaker_boost
-        )
-
-        self._set_voice_settings()
-
-        if self._websocket:
-            msg = {"voice_settings": self._voice_settings}
-            await self._websocket.send(json.dumps(msg))
+    async def _update_settings(self, settings: Dict[str, Any]):
+        prev_voice = self._voice_id
+        await super()._update_settings(settings)
+        if not prev_voice == self._voice_id:
+            await self._disconnect()
+            await self._connect()
+            logger.debug(f"Switching TTS voice to: [{self._voice_id}]")
 
     async def start(self, frame: StartFrame):
         await super().start(frame)
@@ -223,19 +216,19 @@ class ElevenLabsTTSService(WordTTSService):
         try:
             voice_id = self._voice_id
             model = self.model_name
-            output_format = self._params.output_format
+            output_format = self._settings["output_format"]
             url = f"{self._url}/v1/text-to-speech/{voice_id}/stream-input?model_id={model}&output_format={output_format}"
 
-            if self._params.optimize_streaming_latency:
-                url += f"&optimize_streaming_latency={self._params.optimize_streaming_latency}"
+            if self._settings["optimize_streaming_latency"]:
+                url += f"&optimize_streaming_latency={self._settings["optimize_streaming_latency"]}"
 
             # language can only be used with the 'eleven_turbo_v2_5' model
-            if self._params.language:
+            if self._settings["language"]:
                 if model == "eleven_turbo_v2_5":
-                    url += f"&language_code={self._params.language}"
+                    url += f"&language_code={self._settings["language"]}"
                 else:
                     logger.debug(
-                        f"Language code [{self._params.language}] not applied. Language codes can only be used with the 'eleven_turbo_v2_5' model."
+                        f"Language code [{self._settings["language"]}] not applied. Language codes can only be used with the 'eleven_turbo_v2_5' model."
                     )
 
             self._websocket = await websockets.connect(url)
@@ -286,7 +279,7 @@ class ElevenLabsTTSService(WordTTSService):
                     self.start_word_timestamps()
 
                     audio = base64.b64decode(msg["audio"])
-                    frame = TTSAudioRawFrame(audio, self.sample_rate, 1)
+                    frame = TTSAudioRawFrame(audio, self._settings["sample_rate"], 1)
                     await self.push_frame(frame)
 
                 if msg.get("alignment"):
diff --git a/src/pipecat/services/gladia.py b/src/pipecat/services/gladia.py
index a590d73cf..16f3dab97 100644
--- a/src/pipecat/services/gladia.py
+++ b/src/pipecat/services/gladia.py
@@ -6,8 +6,9 @@
 
 import base64
 import json
-
 from typing import AsyncGenerator, Optional
+
+from loguru import logger
 from pydantic.main import BaseModel
 
 from pipecat.frames.frames import (
@@ -21,8 +22,6 @@ from pipecat.frames.frames import (
 from pipecat.services.ai_services import STTService
 from pipecat.utils.time import time_now_iso8601
 
-from loguru import logger
-
 # See .env.example for Gladia configuration needed
 try:
     import websockets
@@ -55,7 +54,13 @@ class GladiaSTTService(STTService):
 
         self._api_key = api_key
         self._url = url
-        self._params = params
+        self._settings = {
+            "sample_rate": params.sample_rate,
+            "language": params.language,
+            "transcription_hint": params.transcription_hint,
+            "endpointing": params.endpointing,
+            "prosody": params.prosody,
+        }
         self._confidence = confidence
 
     async def start(self, frame: StartFrame):
@@ -84,7 +89,11 @@ class GladiaSTTService(STTService):
             "encoding": "WAV/PCM",
             "model_type": "fast",
             "language_behaviour": "manual",
-            **self._params.model_dump(exclude_none=True),
+            "sample_rate": self._settings["sample_rate"],
+            "language": self._settings["language"],
+            "transcription_hint": self._settings["transcription_hint"],
+            "endpointing": self._settings["endpointing"],
+            "prosody": self._settings["prosody"],
         }
 
         await self._websocket.send(json.dumps(configuration))
diff --git a/src/pipecat/services/google.py b/src/pipecat/services/google.py
index 092b4703e..05fff2056 100644
--- a/src/pipecat/services/google.py
+++ b/src/pipecat/services/google.py
@@ -6,7 +6,7 @@
 
 import asyncio
 import json
-from typing import Any, AsyncGenerator, Dict, List, Literal, Optional
+from typing import AsyncGenerator, List, Literal, Optional
 
 from loguru import logger
 from pydantic import BaseModel
@@ -17,7 +17,7 @@ from pipecat.frames.frames import (
     LLMFullResponseEndFrame,
     LLMFullResponseStartFrame,
     LLMMessagesFrame,
-    ServiceUpdateSettingsFrame,
+    LLMUpdateSettingsFrame,
     TextFrame,
     TTSAudioRawFrame,
     TTSStartedFrame,
@@ -64,21 +64,6 @@ class GoogleLLMService(LLMService):
         self.set_model_name(model)
         self._client = gai.GenerativeModel(model)
 
-    async def set_model(self, model: str):
-        logger.debug(f"Switching LLM model to: [{model}]")
-        self._create_client(model)
-
-    async def _update_settings(self, settings: Dict[str, Any]):
-        for key, value in settings.items():
-            setter = getattr(self, f"set_{key}", None)
-            if setter and callable(setter):
-                try:
-                    await setter(value)
-                except Exception as e:
-                    logger.warning(f"Error setting {key}: {e}")
-            else:
-                logger.warning(f"Unknown setting for Google LLM service: {key}")
-
     def _get_messages_from_openai_context(self, context: OpenAILLMContext) -> List[glm.Content]:
         openai_messages = context.get_messages()
         google_messages = []
@@ -151,7 +136,7 @@ class GoogleLLMService(LLMService):
             context = OpenAILLMContext.from_messages(frame.messages)
         elif isinstance(frame, VisionImageRawFrame):
             context = OpenAILLMContext.from_image_frame(frame)
-        elif isinstance(frame, ServiceUpdateSettingsFrame) and frame.service_type == "llm":
+        elif isinstance(frame, LLMUpdateSettingsFrame):
             await self._update_settings(frame.settings)
         else:
             await self.push_frame(frame, direction)
@@ -182,8 +167,17 @@ class GoogleTTSService(TTSService):
     ):
         super().__init__(sample_rate=sample_rate, **kwargs)
 
-        self._voice_id: str = voice_id
-        self._params = params
+        self._settings = {
+            "sample_rate": sample_rate,
+            "pitch": params.pitch,
+            "rate": params.rate,
+            "volume": params.volume,
+            "emphasis": params.emphasis,
+            "language": params.language,
+            "gender": params.gender,
+            "google_style": params.google_style,
+        }
+        self.set_voice(voice_id)
         self._client: texttospeech_v1.TextToSpeechAsyncClient = self._create_client(
             credentials, credentials_path
         )
@@ -216,38 +210,38 @@ class GoogleTTSService(TTSService):
 
         # Voice tag
         voice_attrs = [f"name='{self._voice_id}'"]
-        if self._params.language:
-            voice_attrs.append(f"language='{self._params.language}'")
-        if self._params.gender:
-            voice_attrs.append(f"gender='{self._params.gender}'")
+        if self._settings["language"]:
+            voice_attrs.append(f"language='{self._settings['language']}'")
+        if self._settings["gender"]:
+            voice_attrs.append(f"gender='{self._settings['gender']}'")
         ssml += f"<voice {' '.join(voice_attrs)}>"
 
         # Prosody tag
         prosody_attrs = []
-        if self._params.pitch:
-            prosody_attrs.append(f"pitch='{self._params.pitch}'")
-        if self._params.rate:
-            prosody_attrs.append(f"rate='{self._params.rate}'")
-        if self._params.volume:
-            prosody_attrs.append(f"volume='{self._params.volume}'")
+        if self._settings["pitch"]:
+            prosody_attrs.append(f"pitch='{self._settings['pitch']}'")
+        if self._settings["rate"]:
+            prosody_attrs.append(f"rate='{self._settings['rate']}'")
+        if self._settings["volume"]:
+            prosody_attrs.append(f"volume='{self._settings['volume']}'")
 
         if prosody_attrs:
             ssml += f"<prosody {' '.join(prosody_attrs)}>"
 
         # Emphasis tag
-        if self._params.emphasis:
-            ssml += f"<emphasis level='{self._params.emphasis}'>"
+        if self._settings["emphasis"]:
+            ssml += f"<emphasis level='{self._settings['emphasis']}'>"
 
         # Google style tag
-        if self._params.google_style:
-            ssml += f"<google:style name='{self._params.google_style}'>"
+        if self._settings["google_style"]:
+            ssml += f"<google:style name='{self._settings['google_style']}'>"
 
         ssml += text
 
         # Close tags
-        if self._params.google_style:
+        if self._settings["google_style"]:
             ssml += "</google:style>"
-        if self._params.emphasis:
+        if self._settings["emphasis"]:
             ssml += "</emphasis>"
         if prosody_attrs:
             ssml += "</prosody>"
@@ -255,46 +249,6 @@ class GoogleTTSService(TTSService):
 
         return ssml
 
-    async def set_voice(self, voice: str) -> None:
-        logger.debug(f"Switching TTS voice to: [{voice}]")
-        self._voice_id = voice
-
-    async def set_language(self, language: str) -> None:
-        logger.debug(f"Switching TTS language to: [{language}]")
-        self._params.language = language
-
-    async def set_pitch(self, pitch: str) -> None:
-        logger.debug(f"Switching TTS pitch to: [{pitch}]")
-        self._params.pitch = pitch
-
-    async def set_rate(self, rate: str) -> None:
-        logger.debug(f"Switching TTS rate to: [{rate}]")
-        self._params.rate = rate
-
-    async def set_volume(self, volume: str) -> None:
-        logger.debug(f"Switching TTS volume to: [{volume}]")
-        self._params.volume = volume
-
-    async def set_emphasis(
-        self, emphasis: Literal["strong", "moderate", "reduced", "none"]
-    ) -> None:
-        logger.debug(f"Switching TTS emphasis to: [{emphasis}]")
-        self._params.emphasis = emphasis
-
-    async def set_gender(self, gender: Literal["male", "female", "neutral"]) -> None:
-        logger.debug(f"Switch TTS gender to [{gender}]")
-        self._params.gender = gender
-
-    async def set_google_style(
-        self, google_style: Literal["apologetic", "calm", "empathetic", "firm", "lively"]
-    ) -> None:
-        logger.debug(f"Switching TTS google style to: [{google_style}]")
-        self._params.google_style = google_style
-
-    async def set_params(self, params: InputParams) -> None:
-        logger.debug(f"Switching TTS params to: [{params}]")
-        self._params = params
-
     async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
         logger.debug(f"Generating TTS: [{text}]")
 
@@ -304,11 +258,11 @@ class GoogleTTSService(TTSService):
             ssml = self._construct_ssml(text)
             synthesis_input = texttospeech_v1.SynthesisInput(ssml=ssml)
             voice = texttospeech_v1.VoiceSelectionParams(
-                language_code=self._params.language, name=self._voice_id
+                language_code=self._settings["language"], name=self._voice_id
             )
             audio_config = texttospeech_v1.AudioConfig(
                 audio_encoding=texttospeech_v1.AudioEncoding.LINEAR16,
-                sample_rate_hertz=self.sample_rate,
+                sample_rate_hertz=self._settings["sample_rate"],
             )
 
             request = texttospeech_v1.SynthesizeSpeechRequest(
@@ -331,7 +285,7 @@ class GoogleTTSService(TTSService):
                 if not chunk:
                     break
                 await self.stop_ttfb_metrics()
-                frame = TTSAudioRawFrame(chunk, self.sample_rate, 1)
+                frame = TTSAudioRawFrame(chunk, self._settings["sample_rate"], 1)
                 yield frame
                 await asyncio.sleep(0)  # Allow other tasks to run
 
diff --git a/src/pipecat/services/lmnt.py b/src/pipecat/services/lmnt.py
index 8f18002c5..c828e7a7a 100644
--- a/src/pipecat/services/lmnt.py
+++ b/src/pipecat/services/lmnt.py
@@ -5,10 +5,10 @@
 #
 
 import asyncio
-
 from typing import AsyncGenerator
 
-from pipecat.processors.frame_processor import FrameDirection
+from loguru import logger
+
 from pipecat.frames.frames import (
     CancelFrame,
     EndFrame,
@@ -20,10 +20,9 @@ from pipecat.frames.frames import (
     TTSStartedFrame,
     TTSStoppedFrame,
 )
+from pipecat.processors.frame_processor import FrameDirection
 from pipecat.services.ai_services import TTSService
 
-from loguru import logger
-
 # See .env.example for LMNT configuration needed
 try:
     from lmnt.api import Speech
@@ -50,13 +49,16 @@ class LmntTTSService(TTSService):
         super().__init__(push_stop_frames=True, sample_rate=sample_rate, **kwargs)
 
         self._api_key = api_key
-        self._voice_id = voice_id
-        self._output_format = {
-            "container": "raw",
-            "encoding": "pcm_s16le",
-            "sample_rate": sample_rate,
+        self._settings = {
+            "output_format": {
+                "container": "raw",
+                "encoding": "pcm_s16le",
+                "sample_rate": sample_rate,
+            },
+            "language": language,
         }
-        self._language = language
+
+        self.set_voice(voice_id)
 
         self._speech = None
         self._connection = None
@@ -68,10 +70,6 @@ class LmntTTSService(TTSService):
     def can_generate_metrics(self) -> bool:
         return True
 
-    async def set_voice(self, voice: str):
-        logger.debug(f"Switching TTS voice to: [{voice}]")
-        self._voice_id = voice
-
     async def start(self, frame: StartFrame):
         await super().start(frame)
         await self._connect()
@@ -93,7 +91,9 @@ class LmntTTSService(TTSService):
         try:
             self._speech = Speech()
             self._connection = await self._speech.synthesize_streaming(
-                self._voice_id, format="raw", sample_rate=self._output_format["sample_rate"]
+                self._voice_id,
+                format="raw",
+                sample_rate=self._settings["output_format"]["sample_rate"],
             )
             self._receive_task = self.get_event_loop().create_task(self._receive_task_handler())
         except Exception as e:
@@ -130,7 +130,7 @@ class LmntTTSService(TTSService):
                     await self.stop_ttfb_metrics()
                     frame = TTSAudioRawFrame(
                         audio=msg["audio"],
-                        sample_rate=self._output_format["sample_rate"],
+                        sample_rate=self._settings["output_format"]["sample_rate"],
                         num_channels=1,
                     )
                     await self.push_frame(frame)
diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py
index 57c1b3399..68b7fa4de 100644
--- a/src/pipecat/services/openai.py
+++ b/src/pipecat/services/openai.py
@@ -24,7 +24,7 @@ from pipecat.frames.frames import (
     LLMFullResponseEndFrame,
     LLMFullResponseStartFrame,
     LLMMessagesFrame,
-    ServiceUpdateSettingsFrame,
+    LLMUpdateSettingsFrame,
     StartInterruptionFrame,
     TextFrame,
     TTSAudioRawFrame,
@@ -111,14 +111,16 @@ class BaseOpenAILLMService(LLMService):
         **kwargs,
     ):
         super().__init__(**kwargs)
+        self._settings = {
+            "frequency_penalty": params.frequency_penalty,
+            "presence_penalty": params.presence_penalty,
+            "seed": params.seed,
+            "temperature": params.temperature,
+            "top_p": params.top_p,
+            "extra": params.extra if isinstance(params.extra, dict) else {},
+        }
         self.set_model_name(model)
         self._client = self.create_client(api_key=api_key, base_url=base_url, **kwargs)
-        self._frequency_penalty = params.frequency_penalty
-        self._presence_penalty = params.presence_penalty
-        self._seed = params.seed
-        self._temperature = params.temperature
-        self._top_p = params.top_p
-        self._extra = params.extra if isinstance(params.extra, dict) else {}
 
     def create_client(self, api_key=None, base_url=None, **kwargs):
         return AsyncOpenAI(
@@ -134,30 +136,6 @@ class BaseOpenAILLMService(LLMService):
     def can_generate_metrics(self) -> bool:
         return True
 
-    async def set_frequency_penalty(self, frequency_penalty: float):
-        logger.debug(f"Switching LLM frequency_penalty to: [{frequency_penalty}]")
-        self._frequency_penalty = frequency_penalty
-
-    async def set_presence_penalty(self, presence_penalty: float):
-        logger.debug(f"Switching LLM presence_penalty to: [{presence_penalty}]")
-        self._presence_penalty = presence_penalty
-
-    async def set_seed(self, seed: int):
-        logger.debug(f"Switching LLM seed to: [{seed}]")
-        self._seed = seed
-
-    async def set_temperature(self, temperature: float):
-        logger.debug(f"Switching LLM temperature to: [{temperature}]")
-        self._temperature = temperature
-
-    async def set_top_p(self, top_p: float):
-        logger.debug(f"Switching LLM top_p to: [{top_p}]")
-        self._top_p = top_p
-
-    async def set_extra(self, extra: Dict[str, Any]):
-        logger.debug(f"Switching LLM extra to: [{extra}]")
-        self._extra = extra
-
     async def get_chat_completions(
         self, context: OpenAILLMContext, messages: List[ChatCompletionMessageParam]
     ) -> AsyncStream[ChatCompletionChunk]:
@@ -168,14 +146,14 @@ class BaseOpenAILLMService(LLMService):
             "tools": context.tools,
             "tool_choice": context.tool_choice,
             "stream_options": {"include_usage": True},
-            "frequency_penalty": self._frequency_penalty,
-            "presence_penalty": self._presence_penalty,
-            "seed": self._seed,
-            "temperature": self._temperature,
-            "top_p": self._top_p,
+            "frequency_penalty": self._settings["frequency_penalty"],
+            "presence_penalty": self._settings["presence_penalty"],
+            "seed": self._settings["seed"],
+            "temperature": self._settings["temperature"],
+            "top_p": self._settings["top_p"],
         }
 
-        params.update(self._extra)
+        params.update(self._settings["extra"])
 
         chunks = await self._client.chat.completions.create(**params)
         return chunks
@@ -295,17 +273,6 @@ class BaseOpenAILLMService(LLMService):
                         f"The LLM tried to call a function named '{function_name}', but there isn't a callback registered for that function."
                     )
 
-    async def _update_settings(self, settings: Dict[str, Any]):
-        for key, value in settings.items():
-            setter = getattr(self, f"set_{key}", None)
-            if setter and callable(setter):
-                try:
-                    await setter(value)
-                except Exception as e:
-                    logger.warning(f"Error setting {key}: {e}")
-            else:
-                logger.warning(f"Unknown setting for OpenAI LLM service: {key}")
-
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
@@ -316,7 +283,7 @@ class BaseOpenAILLMService(LLMService):
             context = OpenAILLMContext.from_messages(frame.messages)
         elif isinstance(frame, VisionImageRawFrame):
             context = OpenAILLMContext.from_image_frame(frame)
-        elif isinstance(frame, ServiceUpdateSettingsFrame) and frame.service_type == "llm":
+        elif isinstance(frame, LLMUpdateSettingsFrame):
             await self._update_settings(frame.settings)
         else:
             await self.push_frame(frame, direction)
@@ -414,29 +381,27 @@ class OpenAITTSService(TTSService):
         self,
         *,
         api_key: str | None = None,
-        voice: str = "alloy",
+        voice_id: str = "alloy",
         model: Literal["tts-1", "tts-1-hd"] = "tts-1",
         sample_rate: int = 24000,
         **kwargs,
     ):
         super().__init__(sample_rate=sample_rate, **kwargs)
 
-        self._voice: ValidVoice = VALID_VOICES.get(voice, "alloy")
+        self._settings = {
+            "sample_rate": sample_rate,
+        }
         self.set_model_name(model)
-        self._sample_rate = sample_rate
+        self.set_voice(voice_id)
 
         self._client = AsyncOpenAI(api_key=api_key)
 
     def can_generate_metrics(self) -> bool:
         return True
 
-    async def set_voice(self, voice: str):
-        logger.debug(f"Switching TTS voice to: [{voice}]")
-        self._voice = VALID_VOICES.get(voice, self._voice)
-
     async def set_model(self, model: str):
         logger.debug(f"Switching TTS model to: [{model}]")
-        self._model = model
+        self.set_model_name(model)
 
     async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
         logger.debug(f"Generating TTS: [{text}]")
@@ -446,7 +411,7 @@ class OpenAITTSService(TTSService):
             async with self._client.audio.speech.with_streaming_response.create(
                 input=text,
                 model=self.model_name,
-                voice=self._voice,
+                voice=VALID_VOICES[self._voice_id],
                 response_format="pcm",
             ) as r:
                 if r.status_code != 200:
@@ -465,7 +430,7 @@ class OpenAITTSService(TTSService):
                 async for chunk in r.iter_bytes(8192):
                     if len(chunk) > 0:
                         await self.stop_ttfb_metrics()
-                        frame = TTSAudioRawFrame(chunk, self.sample_rate, 1)
+                        frame = TTSAudioRawFrame(chunk, self._settings["sample_rate"], 1)
                         yield frame
                 await self.push_frame(TTSStoppedFrame())
         except BadRequestError as e:
diff --git a/src/pipecat/services/playht.py b/src/pipecat/services/playht.py
index 2ffa3a419..aea5d8d92 100644
--- a/src/pipecat/services/playht.py
+++ b/src/pipecat/services/playht.py
@@ -6,17 +6,21 @@
 
 import io
 import struct
-
 from typing import AsyncGenerator
 
-from pipecat.frames.frames import Frame, TTSAudioRawFrame, TTSStartedFrame, TTSStoppedFrame
-from pipecat.services.ai_services import TTSService
-
 from loguru import logger
 
+from pipecat.frames.frames import (
+    Frame,
+    TTSAudioRawFrame,
+    TTSStartedFrame,
+    TTSStoppedFrame,
+)
+from pipecat.services.ai_services import TTSService
+
 try:
-    from pyht.client import TTSOptions
     from pyht.async_client import AsyncClient
+    from pyht.client import TTSOptions
     from pyht.protos.api_pb2 import Format
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
@@ -28,7 +32,7 @@ except ModuleNotFoundError as e:
 
 class PlayHTTTSService(TTSService):
     def __init__(
-        self, *, api_key: str, user_id: str, voice_url: str, sample_rate: int = 16000, **kwargs
+        self, *, api_key: str, user_id: str, voice_id: str, sample_rate: int = 16000, **kwargs
     ):
         super().__init__(sample_rate=sample_rate, **kwargs)
 
@@ -39,17 +43,23 @@ class PlayHTTTSService(TTSService):
             user_id=self._user_id,
             api_key=self._speech_key,
         )
+        self._settings = {
+            "sample_rate": sample_rate,
+            "quality": "higher",
+            "format": Format.FORMAT_WAV,
+            "voice_engine": "PlayHT2.0-turbo",
+        }
+        self.set_voice(voice_id)
         self._options = TTSOptions(
-            voice=voice_url, sample_rate=sample_rate, quality="higher", format=Format.FORMAT_WAV
+            voice=self._voice_id,
+            sample_rate=self._settings["sample_rate"],
+            quality=self._settings["quality"],
+            format=self._settings["format"],
         )
 
     def can_generate_metrics(self) -> bool:
         return True
 
-    async def set_voice(self, voice: str):
-        logger.debug(f"Switching TTS voice to: [{voice}]")
-        self._options.voice = voice
-
     async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
         logger.debug(f"Generating TTS: [{text}]")
 
@@ -60,7 +70,7 @@ class PlayHTTTSService(TTSService):
             await self.start_ttfb_metrics()
 
             playht_gen = self._client.tts(
-                text, voice_engine="PlayHT2.0-turbo", options=self._options
+                text, voice_engine=self._settings["voice_engine"], options=self._options
             )
 
             await self.start_tts_usage_metrics(text)
@@ -83,7 +93,7 @@ class PlayHTTTSService(TTSService):
                 else:
                     if len(chunk):
                         await self.stop_ttfb_metrics()
-                        frame = TTSAudioRawFrame(chunk, 16000, 1)
+                        frame = TTSAudioRawFrame(chunk, self._settings["sample_rate"], 1)
                         yield frame
             await self.push_frame(TTSStoppedFrame())
         except Exception as e:
diff --git a/src/pipecat/services/together.py b/src/pipecat/services/together.py
index 26a1a99fd..1bf74e508 100644
--- a/src/pipecat/services/together.py
+++ b/src/pipecat/services/together.py
@@ -50,13 +50,15 @@ class TogetherLLMService(OpenAILLMService):
     ):
         super().__init__(api_key=api_key, base_url=base_url, model=model, params=params, **kwargs)
         self.set_model_name(model)
-        self._max_tokens = params.max_tokens
-        self._frequency_penalty = params.frequency_penalty
-        self._presence_penalty = params.presence_penalty
-        self._temperature = params.temperature
-        self._top_k = params.top_k
-        self._top_p = params.top_p
-        self._extra = params.extra if isinstance(params.extra, dict) else {}
+        self._settings = {
+            "max_tokens": params.max_tokens,
+            "frequency_penalty": params.frequency_penalty,
+            "presence_penalty": params.presence_penalty,
+            "seed": params.seed,
+            "temperature": params.temperature,
+            "top_p": params.top_p,
+            "extra": params.extra if isinstance(params.extra, dict) else {},
+        }
 
     def can_generate_metrics(self) -> bool:
         return True
@@ -72,42 +74,3 @@ class TogetherLLMService(OpenAILLMService):
                 )
             ),
         )
-
-    async def set_frequency_penalty(self, frequency_penalty: float):
-        logger.debug(f"Switching LLM frequency_penalty to: [{frequency_penalty}]")
-        self._frequency_penalty = frequency_penalty
-
-    async def set_max_tokens(self, max_tokens: int):
-        logger.debug(f"Switching LLM max_tokens to: [{max_tokens}]")
-        self._max_tokens = max_tokens
-
-    async def set_presence_penalty(self, presence_penalty: float):
-        logger.debug(f"Switching LLM presence_penalty to: [{presence_penalty}]")
-        self._presence_penalty = presence_penalty
-
-    async def set_temperature(self, temperature: float):
-        logger.debug(f"Switching LLM temperature to: [{temperature}]")
-        self._temperature = temperature
-
-    async def set_top_k(self, top_k: float):
-        logger.debug(f"Switching LLM top_k to: [{top_k}]")
-        self._top_k = top_k
-
-    async def set_top_p(self, top_p: float):
-        logger.debug(f"Switching LLM top_p to: [{top_p}]")
-        self._top_p = top_p
-
-    async def set_extra(self, extra: Dict[str, Any]):
-        logger.debug(f"Switching LLM extra to: [{extra}]")
-        self._extra = extra
-
-    async def _update_settings(self, settings: Dict[str, Any]):
-        for key, value in settings.items():
-            setter = getattr(self, f"set_{key}", None)
-            if setter and callable(setter):
-                try:
-                    await setter(value)
-                except Exception as e:
-                    logger.warning(f"Error setting {key}: {e}")
-            else:
-                logger.warning(f"Unknown setting for Together LLM service: {key}")
diff --git a/src/pipecat/services/xtts.py b/src/pipecat/services/xtts.py
index 2c47d59e8..7826cfcd8 100644
--- a/src/pipecat/services/xtts.py
+++ b/src/pipecat/services/xtts.py
@@ -4,10 +4,12 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-import aiohttp
-
 from typing import Any, AsyncGenerator, Dict
 
+import aiohttp
+import numpy as np
+from loguru import logger
+
 from pipecat.frames.frames import (
     ErrorFrame,
     Frame,
@@ -18,10 +20,6 @@ from pipecat.frames.frames import (
 )
 from pipecat.services.ai_services import TTSService
 
-import numpy as np
-
-from loguru import logger
-
 try:
     import resampy
 except ModuleNotFoundError as e:
@@ -50,9 +48,11 @@ class XTTSService(TTSService):
     ):
         super().__init__(**kwargs)
 
-        self._voice_id = voice_id
-        self._language = language
-        self._base_url = base_url
+        self._settings = {
+            "language": language,
+            "base_url": base_url,
+        }
+        self.set_voice(voice_id)
         self._studio_speakers: Dict[str, Any] | None = None
         self._aiohttp_session = aiohttp_session
 
@@ -61,7 +61,7 @@ class XTTSService(TTSService):
 
     async def start(self, frame: StartFrame):
         await super().start(frame)
-        async with self._aiohttp_session.get(self._base_url + "/studio_speakers") as r:
+        async with self._aiohttp_session.get(self._settings["base_url"] + "/studio_speakers") as r:
             if r.status != 200:
                 text = await r.text()
                 logger.error(
@@ -75,10 +75,6 @@ class XTTSService(TTSService):
                 return
             self._studio_speakers = await r.json()
 
-    async def set_voice(self, voice: str):
-        logger.debug(f"Switching TTS voice to: [{voice}]")
-        self._voice_id = voice
-
     async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
         logger.debug(f"Generating TTS: [{text}]")
 
@@ -88,11 +84,11 @@ class XTTSService(TTSService):
 
         embeddings = self._studio_speakers[self._voice_id]
 
-        url = self._base_url + "/tts_stream"
+        url = self._settings["base_url"] + "/tts_stream"
 
         payload = {
             "text": text.replace(".", "").replace("*", ""),
-            "language": self._language,
+            "language": self._settings["language"],
             "speaker_embedding": embeddings["speaker_embedding"],
             "gpt_cond_latent": embeddings["gpt_cond_latent"],
             "add_wav_header": False,

From d75a02dc51d780ea6b95d4d548db59836a3dc140 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Tue, 1 Oct 2024 21:01:44 -0400
Subject: [PATCH 123/135] Use Language enum and set languages accordingly

---
 src/pipecat/services/aws.py        | 66 +++++++++++++++++++-
 src/pipecat/services/azure.py      | 96 +++++++++++++++++++++++++++++-
 src/pipecat/services/cartesia.py   |  6 +-
 src/pipecat/services/deepgram.py   |  2 +-
 src/pipecat/services/elevenlabs.py | 74 ++++++++++++++++++++++-
 src/pipecat/services/gladia.py     | 83 +++++++++++++++++++++++++-
 src/pipecat/services/google.py     | 94 ++++++++++++++++++++++++++++-
 src/pipecat/services/lmnt.py       | 31 +++++++++-
 src/pipecat/services/xtts.py       | 49 ++++++++++++++-
 9 files changed, 484 insertions(+), 17 deletions(-)

diff --git a/src/pipecat/services/aws.py b/src/pipecat/services/aws.py
index 7004c21f7..210e0e700 100644
--- a/src/pipecat/services/aws.py
+++ b/src/pipecat/services/aws.py
@@ -17,6 +17,7 @@ from pipecat.frames.frames import (
     TTSStoppedFrame,
 )
 from pipecat.services.ai_services import TTSService
+from pipecat.transcriptions.language import Language
 
 try:
     import boto3
@@ -29,10 +30,71 @@ except ModuleNotFoundError as e:
     raise Exception(f"Missing module: {e}")
 
 
+def language_to_aws_language(language: Language) -> str | None:
+    match language:
+        case Language.CA:
+            return "ca-ES"
+        case Language.ZH:
+            return "cmn-CN"
+        case Language.DA:
+            return "da-DK"
+        case Language.NL:
+            return "nl-NL"
+        case Language.NL_BE:
+            return "nl-BE"
+        case Language.EN:
+            return "en-US"
+        case Language.EN_US:
+            return "en-US"
+        case Language.EN_AU:
+            return "en-AU"
+        case Language.EN_GB:
+            return "en-GB"
+        case Language.EN_NZ:
+            return "en-NZ"
+        case Language.EN_IN:
+            return "en-IN"
+        case Language.FI:
+            return "fi-FI"
+        case Language.FR:
+            return "fr-FR"
+        case Language.FR_CA:
+            return "fr-CA"
+        case Language.DE:
+            return "de-DE"
+        case Language.HI:
+            return "hi-IN"
+        case Language.IT:
+            return "it-IT"
+        case Language.JA:
+            return "ja-JP"
+        case Language.KO:
+            return "ko-KR"
+        case Language.NO:
+            return "nb-NO"
+        case Language.PL:
+            return "pl-PL"
+        case Language.PT:
+            return "pt-PT"
+        case Language.PT_BR:
+            return "pt-BR"
+        case Language.RO:
+            return "ro-RO"
+        case Language.RU:
+            return "ru-RU"
+        case Language.ES:
+            return "es-ES"
+        case Language.SV:
+            return "sv-SE"
+        case Language.TR:
+            return "tr-TR"
+    return None
+
+
 class AWSTTSService(TTSService):
     class InputParams(BaseModel):
         engine: Optional[str] = None
-        language: Optional[str] = None
+        language: Optional[Language] = Language.EN
         pitch: Optional[str] = None
         rate: Optional[str] = None
         volume: Optional[str] = None
@@ -59,7 +121,7 @@ class AWSTTSService(TTSService):
         self._settings = {
             "sample_rate": sample_rate,
             "engine": params.engine,
-            "language": params.language,
+            "language": language_to_aws_language(params.language) if params.language else "en-US",
             "pitch": params.pitch,
             "rate": params.rate,
             "volume": params.volume,
diff --git a/src/pipecat/services/azure.py b/src/pipecat/services/azure.py
index 1b2b9a3f2..078b7df6b 100644
--- a/src/pipecat/services/azure.py
+++ b/src/pipecat/services/azure.py
@@ -27,6 +27,7 @@ from pipecat.frames.frames import (
 )
 from pipecat.services.ai_services import ImageGenService, STTService, TTSService
 from pipecat.services.openai import BaseOpenAILLMService
+from pipecat.transcriptions.language import Language
 from pipecat.utils.time import time_now_iso8601
 
 # See .env.example for Azure configuration needed
@@ -70,10 +71,101 @@ class AzureLLMService(BaseOpenAILLMService):
         )
 
 
+def language_to_azure_language(language: Language) -> str | None:
+    match language:
+        case Language.BG:
+            return "bg-BG"
+        case Language.CA:
+            return "ca-ES"
+        case Language.ZH:
+            return "zh-CN"
+        case Language.ZH_TW:
+            return "zh-TW"
+        case Language.CS:
+            return "cs-CZ"
+        case Language.DA:
+            return "da-DK"
+        case Language.NL:
+            return "nl-NL"
+        case Language.EN:
+            return "en-US"
+        case Language.EN_US:
+            return "en-US"
+        case Language.EN_AU:
+            return "en-AU"
+        case Language.EN_GB:
+            return "en-GB"
+        case Language.EN_NZ:
+            return "en-NZ"
+        case Language.EN_IN:
+            return "en-IN"
+        case Language.ET:
+            return "et-EE"
+        case Language.FI:
+            return "fi-FI"
+        case Language.NL_BE:
+            return "nl-BE"
+        case Language.FR:
+            return "fr-FR"
+        case Language.FR_CA:
+            return "fr-CA"
+        case Language.DE:
+            return "de-DE"
+        case Language.DE_CH:
+            return "de-CH"
+        case Language.EL:
+            return "el-GR"
+        case Language.HI:
+            return "hi-IN"
+        case Language.HU:
+            return "hu-HU"
+        case Language.ID:
+            return "id-ID"
+        case Language.IT:
+            return "it-IT"
+        case Language.JA:
+            return "ja-JP"
+        case Language.KO:
+            return "ko-KR"
+        case Language.LV:
+            return "lv-LV"
+        case Language.LT:
+            return "lt-LT"
+        case Language.MS:
+            return "ms-MY"
+        case Language.NO:
+            return "nb-NO"
+        case Language.PL:
+            return "pl-PL"
+        case Language.PT:
+            return "pt-PT"
+        case Language.PT_BR:
+            return "pt-BR"
+        case Language.RO:
+            return "ro-RO"
+        case Language.RU:
+            return "ru-RU"
+        case Language.SK:
+            return "sk-SK"
+        case Language.ES:
+            return "es-ES"
+        case Language.SV:
+            return "sv-SE"
+        case Language.TH:
+            return "th-TH"
+        case Language.TR:
+            return "tr-TR"
+        case Language.UK:
+            return "uk-UA"
+        case Language.VI:
+            return "vi-VN"
+    return None
+
+
 class AzureTTSService(TTSService):
     class InputParams(BaseModel):
         emphasis: Optional[str] = None
-        language: Optional[str] = "en-US"
+        language: Optional[Language] = Language.EN
         pitch: Optional[str] = None
         rate: Optional[str] = "1.05"
         role: Optional[str] = None
@@ -99,7 +191,7 @@ class AzureTTSService(TTSService):
         self._settings = {
             "sample_rate": sample_rate,
             "emphasis": params.emphasis,
-            "language": params.language,
+            "language": language_to_azure_language(params.language) if params.language else "en-US",
             "pitch": params.pitch,
             "rate": params.rate,
             "role": params.role,
diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index 0817879c4..22e09cb2b 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -106,7 +106,7 @@ class CartesiaTTSService(WordTTSService):
                 "encoding": params.encoding,
                 "sample_rate": params.sample_rate,
             },
-            "language": language_to_cartesia_language(params.language) if params.language else None,
+            "language": language_to_cartesia_language(params.language) if params.language else "en",
             "speed": params.speed,
             "emotion": params.emotion,
         }
@@ -280,7 +280,7 @@ class CartesiaHttpTTSService(TTSService):
         encoding: Optional[str] = "pcm_s16le"
         sample_rate: Optional[int] = 16000
         container: Optional[str] = "raw"
-        language: Optional[str] = "en"
+        language: Optional[Language] = Language.EN
         speed: Optional[Union[str, float]] = ""
         emotion: Optional[List[str]] = []
 
@@ -303,7 +303,7 @@ class CartesiaHttpTTSService(TTSService):
                 "encoding": params.encoding,
                 "sample_rate": params.sample_rate,
             },
-            "language": params.language,
+            "language": language_to_cartesia_language(params.language) if params.language else None,
             "speed": params.speed,
             "emotion": params.emotion,
         }
diff --git a/src/pipecat/services/deepgram.py b/src/pipecat/services/deepgram.py
index 40fe0168d..55a3ba68e 100644
--- a/src/pipecat/services/deepgram.py
+++ b/src/pipecat/services/deepgram.py
@@ -120,7 +120,7 @@ class DeepgramSTTService(STTService):
         url: str = "",
         live_options: LiveOptions = LiveOptions(
             encoding="linear16",
-            language="en-US",
+            language=Language.EN,
             model="nova-2-conversationalai",
             sample_rate=16000,
             channels=1,
diff --git a/src/pipecat/services/elevenlabs.py b/src/pipecat/services/elevenlabs.py
index 871b3eec6..695988b03 100644
--- a/src/pipecat/services/elevenlabs.py
+++ b/src/pipecat/services/elevenlabs.py
@@ -50,6 +50,76 @@ def sample_rate_from_output_format(output_format: str) -> int:
     return 16000
 
 
+def language_to_elevenlabs_language(language: Language) -> str | None:
+    match language:
+        case Language.BG:
+            return "bg"
+        case Language.ZH:
+            return "zh"
+        case Language.CS:
+            return "cs"
+        case Language.DA:
+            return "da"
+        case Language.NL:
+            return "nl"
+        case (
+            Language.EN
+            | Language.EN_US
+            | Language.EN_AU
+            | Language.EN_GB
+            | Language.EN_NZ
+            | Language.EN_IN
+        ):
+            return "en"
+        case Language.FI:
+            return "fi"
+        case Language.FR | Language.FR_CA:
+            return "fr"
+        case Language.DE | Language.DE_CH:
+            return "de"
+        case Language.EL:
+            return "el"
+        case Language.HI:
+            return "hi"
+        case Language.HU:
+            return "hu"
+        case Language.ID:
+            return "id"
+        case Language.IT:
+            return "it"
+        case Language.JA:
+            return "ja"
+        case Language.KO:
+            return "ko"
+        case Language.MS:
+            return "ms"
+        case Language.NO:
+            return "no"
+        case Language.PL:
+            return "pl"
+        case Language.PT:
+            return "pt-PT"
+        case Language.PT_BR:
+            return "pt-BR"
+        case Language.RO:
+            return "ro"
+        case Language.RU:
+            return "ru"
+        case Language.SK:
+            return "sk"
+        case Language.ES:
+            return "es"
+        case Language.SV:
+            return "sv"
+        case Language.TR:
+            return "tr"
+        case Language.UK:
+            return "uk"
+        case Language.VI:
+            return "vi"
+    return None
+
+
 def calculate_word_times(
     alignment_info: Mapping[str, Any], cumulative_time: float
 ) -> List[Tuple[str, float]]:
@@ -128,7 +198,9 @@ class ElevenLabsTTSService(WordTTSService):
         self._url = url
         self._settings = {
             "sample_rate": sample_rate_from_output_format(params.output_format),
-            "language": params.language,
+            "language": language_to_elevenlabs_language(params.language)
+            if params.language
+            else "en",
             "output_format": params.output_format,
             "optimize_streaming_latency": params.optimize_streaming_latency,
             "stability": params.stability,
diff --git a/src/pipecat/services/gladia.py b/src/pipecat/services/gladia.py
index 16f3dab97..0938a1cee 100644
--- a/src/pipecat/services/gladia.py
+++ b/src/pipecat/services/gladia.py
@@ -20,6 +20,7 @@ from pipecat.frames.frames import (
     TranscriptionFrame,
 )
 from pipecat.services.ai_services import STTService
+from pipecat.transcriptions.language import Language
 from pipecat.utils.time import time_now_iso8601
 
 # See .env.example for Gladia configuration needed
@@ -33,10 +34,88 @@ except ModuleNotFoundError as e:
     raise Exception(f"Missing module: {e}")
 
 
+def language_to_gladia_language(language: Language) -> str | None:
+    match language:
+        case Language.BG:
+            return "bg"
+        case Language.CA:
+            return "ca"
+        case Language.ZH:
+            return "zh"
+        case Language.CS:
+            return "cs"
+        case Language.DA:
+            return "da"
+        case Language.NL:
+            return "nl"
+        case (
+            Language.EN
+            | Language.EN_US
+            | Language.EN_AU
+            | Language.EN_GB
+            | Language.EN_NZ
+            | Language.EN_IN
+        ):
+            return "en"
+        case Language.ET:
+            return "et"
+        case Language.FI:
+            return "fi"
+        case Language.FR | Language.FR_CA:
+            return "fr"
+        case Language.DE | Language.DE_CH:
+            return "de"
+        case Language.EL:
+            return "el"
+        case Language.HI:
+            return "hi"
+        case Language.HU:
+            return "hu"
+        case Language.ID:
+            return "id"
+        case Language.IT:
+            return "it"
+        case Language.JA:
+            return "ja"
+        case Language.KO:
+            return "ko"
+        case Language.LV:
+            return "lv"
+        case Language.LT:
+            return "lt"
+        case Language.MS:
+            return "ms"
+        case Language.NO:
+            return "no"
+        case Language.PL:
+            return "pl"
+        case Language.PT | Language.PT_BR:
+            return "pt"
+        case Language.RO:
+            return "ro"
+        case Language.RU:
+            return "ru"
+        case Language.SK:
+            return "sk"
+        case Language.ES:
+            return "es"
+        case Language.SV:
+            return "sv"
+        case Language.TH:
+            return "th"
+        case Language.TR:
+            return "tr"
+        case Language.UK:
+            return "uk"
+        case Language.VI:
+            return "vi"
+    return None
+
+
 class GladiaSTTService(STTService):
     class InputParams(BaseModel):
         sample_rate: Optional[int] = 16000
-        language: Optional[str] = "english"
+        language: Optional[Language] = Language.EN
         transcription_hint: Optional[str] = None
         endpointing: Optional[int] = 200
         prosody: Optional[bool] = None
@@ -56,7 +135,7 @@ class GladiaSTTService(STTService):
         self._url = url
         self._settings = {
             "sample_rate": params.sample_rate,
-            "language": params.language,
+            "language": language_to_gladia_language(params.language) if params.language else "en",
             "transcription_hint": params.transcription_hint,
             "endpointing": params.endpointing,
             "prosody": params.prosody,
diff --git a/src/pipecat/services/google.py b/src/pipecat/services/google.py
index 05fff2056..55a2576d2 100644
--- a/src/pipecat/services/google.py
+++ b/src/pipecat/services/google.py
@@ -30,6 +30,7 @@ from pipecat.processors.aggregators.openai_llm_context import (
 )
 from pipecat.processors.frame_processor import FrameDirection
 from pipecat.services.ai_services import LLMService, TTSService
+from pipecat.transcriptions.language import Language
 
 try:
     import google.ai.generativelanguage as glm
@@ -145,13 +146,100 @@ class GoogleLLMService(LLMService):
             await self._process_context(context)
 
 
+def language_to_google_language(language: Language) -> str | None:
+    match language:
+        case Language.BG:
+            return "bg-BG"
+        case Language.CA:
+            return "ca-ES"
+        case Language.ZH:
+            return "cmn-CN"
+        case Language.ZH_TW:
+            return "cmn-TW"
+        case Language.CS:
+            return "cs-CZ"
+        case Language.DA:
+            return "da-DK"
+        case Language.NL:
+            return "nl-NL"
+        case Language.EN:
+            return "en-US"
+        case Language.EN_US:
+            return "en-US"
+        case Language.EN_AU:
+            return "en-AU"
+        case Language.EN_GB:
+            return "en-GB"
+        case Language.EN_IN:
+            return "en-IN"
+        case Language.ET:
+            return "et-EE"
+        case Language.FI:
+            return "fi-FI"
+        case Language.NL_BE:
+            return "nl-BE"
+        case Language.FR:
+            return "fr-FR"
+        case Language.FR_CA:
+            return "fr-CA"
+        case Language.DE:
+            return "de-DE"
+        case Language.EL:
+            return "el-GR"
+        case Language.HI:
+            return "hi-IN"
+        case Language.HU:
+            return "hu-HU"
+        case Language.ID:
+            return "id-ID"
+        case Language.IT:
+            return "it-IT"
+        case Language.JA:
+            return "ja-JP"
+        case Language.KO:
+            return "ko-KR"
+        case Language.LV:
+            return "lv-LV"
+        case Language.LT:
+            return "lt-LT"
+        case Language.MS:
+            return "ms-MY"
+        case Language.NO:
+            return "nb-NO"
+        case Language.PL:
+            return "pl-PL"
+        case Language.PT:
+            return "pt-PT"
+        case Language.PT_BR:
+            return "pt-BR"
+        case Language.RO:
+            return "ro-RO"
+        case Language.RU:
+            return "ru-RU"
+        case Language.SK:
+            return "sk-SK"
+        case Language.ES:
+            return "es-ES"
+        case Language.SV:
+            return "sv-SE"
+        case Language.TH:
+            return "th-TH"
+        case Language.TR:
+            return "tr-TR"
+        case Language.UK:
+            return "uk-UA"
+        case Language.VI:
+            return "vi-VN"
+    return None
+
+
 class GoogleTTSService(TTSService):
     class InputParams(BaseModel):
         pitch: Optional[str] = None
         rate: Optional[str] = None
         volume: Optional[str] = None
         emphasis: Optional[Literal["strong", "moderate", "reduced", "none"]] = None
-        language: Optional[str] = "en-US"
+        language: Optional[Language] = Language.EN
         gender: Optional[Literal["male", "female", "neutral"]] = None
         google_style: Optional[Literal["apologetic", "calm", "empathetic", "firm", "lively"]] = None
 
@@ -173,7 +261,9 @@ class GoogleTTSService(TTSService):
             "rate": params.rate,
             "volume": params.volume,
             "emphasis": params.emphasis,
-            "language": params.language,
+            "language": language_to_google_language(params.language)
+            if params.language
+            else "en-US",
             "gender": params.gender,
             "google_style": params.google_style,
         }
diff --git a/src/pipecat/services/lmnt.py b/src/pipecat/services/lmnt.py
index c828e7a7a..1ea3f1e62 100644
--- a/src/pipecat/services/lmnt.py
+++ b/src/pipecat/services/lmnt.py
@@ -22,6 +22,7 @@ from pipecat.frames.frames import (
 )
 from pipecat.processors.frame_processor import FrameDirection
 from pipecat.services.ai_services import TTSService
+from pipecat.transcriptions.language import Language
 
 # See .env.example for LMNT configuration needed
 try:
@@ -34,6 +35,32 @@ except ModuleNotFoundError as e:
     raise Exception(f"Missing module: {e}")
 
 
+def language_to_lmnt_language(language: Language) -> str | None:
+    match language:
+        case Language.DE:
+            return "de"
+        case (
+            Language.EN
+            | Language.EN_US
+            | Language.EN_AU
+            | Language.EN_GB
+            | Language.EN_NZ
+            | Language.EN_IN
+        ):
+            return "en"
+        case Language.ES:
+            return "es"
+        case Language.FR | Language.FR_CA:
+            return "fr"
+        case Language.PT | Language.PT_BR:
+            return "pt"
+        case Language.ZH | Language.ZH_TW:
+            return "zh"
+        case Language.KO:
+            return "ko"
+    return None
+
+
 class LmntTTSService(TTSService):
     def __init__(
         self,
@@ -41,7 +68,7 @@ class LmntTTSService(TTSService):
         api_key: str,
         voice_id: str,
         sample_rate: int = 24000,
-        language: str = "en",
+        language: Language = Language.EN,
         **kwargs,
     ):
         # Let TTSService produce TTSStoppedFrames after a short delay of
@@ -55,7 +82,7 @@ class LmntTTSService(TTSService):
                 "encoding": "pcm_s16le",
                 "sample_rate": sample_rate,
             },
-            "language": language,
+            "language": language_to_lmnt_language(language) if language else "en",
         }
 
         self.set_voice(voice_id)
diff --git a/src/pipecat/services/xtts.py b/src/pipecat/services/xtts.py
index 7826cfcd8..eb20d5f3c 100644
--- a/src/pipecat/services/xtts.py
+++ b/src/pipecat/services/xtts.py
@@ -19,6 +19,7 @@ from pipecat.frames.frames import (
     TTSStoppedFrame,
 )
 from pipecat.services.ai_services import TTSService
+from pipecat.transcriptions.language import Language
 
 try:
     import resampy
@@ -36,12 +37,56 @@ except ModuleNotFoundError as e:
 # https://github.com/coqui-ai/xtts-streaming-server
 
 
+def language_to_xtts_language(language: Language) -> str | None:
+    match language:
+        case Language.CS:
+            return "cs"
+        case Language.DE:
+            return "de"
+        case (
+            Language.EN
+            | Language.EN_US
+            | Language.EN_AU
+            | Language.EN_GB
+            | Language.EN_NZ
+            | Language.EN_IN
+        ):
+            return "en"
+        case Language.ES:
+            return "es"
+        case Language.FR:
+            return "fr"
+        case Language.HI:
+            return "hi"
+        case Language.HU:
+            return "hu"
+        case Language.IT:
+            return "it"
+        case Language.JA:
+            return "ja"
+        case Language.KO:
+            return "ko"
+        case Language.NL:
+            return "nl"
+        case Language.PL:
+            return "pl"
+        case Language.PT | Language.PT_BR:
+            return "pt"
+        case Language.RU:
+            return "ru"
+        case Language.TR:
+            return "tr"
+        case Language.ZH:
+            return "zh-cn"
+    return None
+
+
 class XTTSService(TTSService):
     def __init__(
         self,
         *,
         voice_id: str,
-        language: str,
+        language: Language,
         base_url: str,
         aiohttp_session: aiohttp.ClientSession,
         **kwargs,
@@ -49,7 +94,7 @@ class XTTSService(TTSService):
         super().__init__(**kwargs)
 
         self._settings = {
-            "language": language,
+            "language": language_to_xtts_language(language) if language else "en",
             "base_url": base_url,
         }
         self.set_voice(voice_id)

From 3d642df2b049eb5f57fc4909f649b96fbef0b43f Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Wed, 2 Oct 2024 11:07:48 -0400
Subject: [PATCH 124/135] Revert aligning voice_id name in TTS service
 constructor

---
 examples/foundational/07c-interruptible-deepgram.py   | 2 +-
 examples/foundational/07e-interruptible-playht.py     | 2 +-
 examples/foundational/07g-interruptible-openai-tts.py | 2 +-
 examples/foundational/16-gpu-container-local-bot.py   | 2 +-
 src/pipecat/services/azure.py                         | 4 ++--
 src/pipecat/services/deepgram.py                      | 4 ++--
 src/pipecat/services/openai.py                        | 4 ++--
 src/pipecat/services/playht.py                        | 4 ++--
 8 files changed, 12 insertions(+), 12 deletions(-)

diff --git a/examples/foundational/07c-interruptible-deepgram.py b/examples/foundational/07c-interruptible-deepgram.py
index f3b4ee246..fc33c246f 100644
--- a/examples/foundational/07c-interruptible-deepgram.py
+++ b/examples/foundational/07c-interruptible-deepgram.py
@@ -50,7 +50,7 @@ async def main():
 
         stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
 
-        tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice_id="aura-helios-en")
+        tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-helios-en")
 
         llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
diff --git a/examples/foundational/07e-interruptible-playht.py b/examples/foundational/07e-interruptible-playht.py
index 58d85ed79..b05c0d9fd 100644
--- a/examples/foundational/07e-interruptible-playht.py
+++ b/examples/foundational/07e-interruptible-playht.py
@@ -52,7 +52,7 @@ async def main():
         tts = PlayHTTTSService(
             user_id=os.getenv("PLAYHT_USER_ID"),
             api_key=os.getenv("PLAYHT_API_KEY"),
-            voice_id="s3://voice-cloning-zero-shot/801a663f-efd0-4254-98d0-5c175514c3e8/jennifer/manifest.json",
+            voice_url="s3://voice-cloning-zero-shot/801a663f-efd0-4254-98d0-5c175514c3e8/jennifer/manifest.json",
         )
 
         llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
diff --git a/examples/foundational/07g-interruptible-openai-tts.py b/examples/foundational/07g-interruptible-openai-tts.py
index b7671c42f..cabf1245e 100644
--- a/examples/foundational/07g-interruptible-openai-tts.py
+++ b/examples/foundational/07g-interruptible-openai-tts.py
@@ -48,7 +48,7 @@ async def main():
             ),
         )
 
-        tts = OpenAITTSService(api_key=os.getenv("OPENAI_API_KEY"), voice_id="alloy")
+        tts = OpenAITTSService(api_key=os.getenv("OPENAI_API_KEY"), voice="alloy")
 
         llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
diff --git a/examples/foundational/16-gpu-container-local-bot.py b/examples/foundational/16-gpu-container-local-bot.py
index b3ae9686e..55286eed5 100644
--- a/examples/foundational/16-gpu-container-local-bot.py
+++ b/examples/foundational/16-gpu-container-local-bot.py
@@ -55,7 +55,7 @@ async def main():
         tts = DeepgramTTSService(
             aiohttp_session=session,
             api_key=os.getenv("DEEPGRAM_API_KEY"),
-            voice_id="aura-asteria-en",
+            voice="aura-asteria-en",
             base_url="http://0.0.0.0:8080/v1/speak",
         )
 
diff --git a/src/pipecat/services/azure.py b/src/pipecat/services/azure.py
index 078b7df6b..32af1b3f4 100644
--- a/src/pipecat/services/azure.py
+++ b/src/pipecat/services/azure.py
@@ -178,7 +178,7 @@ class AzureTTSService(TTSService):
         *,
         api_key: str,
         region: str,
-        voice_id="en-US-SaraNeural",
+        voice="en-US-SaraNeural",
         sample_rate: int = 16000,
         params: InputParams = InputParams(),
         **kwargs,
@@ -200,7 +200,7 @@ class AzureTTSService(TTSService):
             "volume": params.volume,
         }
 
-        self.set_voice(voice_id)
+        self.set_voice(voice)
 
     def can_generate_metrics(self) -> bool:
         return True
diff --git a/src/pipecat/services/deepgram.py b/src/pipecat/services/deepgram.py
index 55a3ba68e..433e08172 100644
--- a/src/pipecat/services/deepgram.py
+++ b/src/pipecat/services/deepgram.py
@@ -49,7 +49,7 @@ class DeepgramTTSService(TTSService):
         self,
         *,
         api_key: str,
-        voice_id: str = "aura-helios-en",
+        voice: str = "aura-helios-en",
         sample_rate: int = 16000,
         encoding: str = "linear16",
         **kwargs,
@@ -60,7 +60,7 @@ class DeepgramTTSService(TTSService):
             "sample_rate": sample_rate,
             "encoding": encoding,
         }
-        self.set_voice(voice_id)
+        self.set_voice(voice)
         self._deepgram_client = DeepgramClient(api_key=api_key)
 
     def can_generate_metrics(self) -> bool:
diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py
index 68b7fa4de..24d673234 100644
--- a/src/pipecat/services/openai.py
+++ b/src/pipecat/services/openai.py
@@ -381,7 +381,7 @@ class OpenAITTSService(TTSService):
         self,
         *,
         api_key: str | None = None,
-        voice_id: str = "alloy",
+        voice: str = "alloy",
         model: Literal["tts-1", "tts-1-hd"] = "tts-1",
         sample_rate: int = 24000,
         **kwargs,
@@ -392,7 +392,7 @@ class OpenAITTSService(TTSService):
             "sample_rate": sample_rate,
         }
         self.set_model_name(model)
-        self.set_voice(voice_id)
+        self.set_voice(voice)
 
         self._client = AsyncOpenAI(api_key=api_key)
 
diff --git a/src/pipecat/services/playht.py b/src/pipecat/services/playht.py
index aea5d8d92..fe5feba3a 100644
--- a/src/pipecat/services/playht.py
+++ b/src/pipecat/services/playht.py
@@ -32,7 +32,7 @@ except ModuleNotFoundError as e:
 
 class PlayHTTTSService(TTSService):
     def __init__(
-        self, *, api_key: str, user_id: str, voice_id: str, sample_rate: int = 16000, **kwargs
+        self, *, api_key: str, user_id: str, voice_url: str, sample_rate: int = 16000, **kwargs
     ):
         super().__init__(sample_rate=sample_rate, **kwargs)
 
@@ -49,7 +49,7 @@ class PlayHTTTSService(TTSService):
             "format": Format.FORMAT_WAV,
             "voice_engine": "PlayHT2.0-turbo",
         }
-        self.set_voice(voice_id)
+        self.set_voice(voice_url)
         self._options = TTSOptions(
             voice=self._voice_id,
             sample_rate=self._settings["sample_rate"],

From 6c1851eef85ff5e03da88dfa9f9f79ce9ffb7bdf Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Tue, 1 Oct 2024 14:22:35 -0700
Subject: [PATCH 125/135] update CHANGELOG for 0.0.42

---
 CHANGELOG.md | 36 +++++++++++++++++++++++++++++-------
 1 file changed, 29 insertions(+), 7 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 922a21f21..21c06e6f6 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,20 +1,29 @@
 # Changelog
 
-All notable changes to **pipecat** will be documented in this file.
+All notable changes to **Pipecat** will be documented in this file.
 
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
-## [Unreleased]
+## [0.0.42] - 2024-10-02
 
 ### Added
 
-- Added Google TTS service and corresponding foundational example `07n-interruptible-google.py`
+- `SentryMetrics` has been added to report frame processor metrics to
+  Sentry. This is now possible because `FrameProcessorMetrics` can now be passed
+  to `FrameProcessor`.
+
+- Added Google TTS service and corresponding foundational example
+  `07n-interruptible-google.py`
 
 - Added AWS Polly TTS support and `07m-interruptible-aws.py` as an example.
 
 - Added InputParams to Azure TTS service.
 
+- Added `LivekitTransport` (audio-only for now).
+
+- RTVI 0.2.0 is now supported.
+
 - All `FrameProcessors` can now register event handlers.
 
 ```
@@ -86,8 +95,12 @@ async def on_connected(processor):
 
 ### Changed
 
+- Context frames are now pushed downstream from assistant context aggregators.
+
+- Removed Silero VAD torch dependency.
+
 - Updated individual update settings frame classes into a single
-  ServiceUpdateSettingsFrame class.
+  `ServiceUpdateSettingsFrame` class.
 
 - We now distinguish between input and output audio and image frames. We
   introduce `InputAudioRawFrame`, `OutputAudioRawFrame`, `InputImageRawFrame`
@@ -107,9 +120,9 @@ async def on_connected(processor):
   pipelines is synchronous (e.g. an HTTP-based service that waits for the
   response).
 
-- `StartFrame` is back a system frame so we make sure it's processed immediately
-  by all processors. `EndFrame` stays a control frame since it needs to be
-  ordered allowing the frames in the pipeline to be processed.
+- `StartFrame` is back a system frame to make sure it's processed immediately by
+  all processors. `EndFrame` stays a control frame since it needs to be ordered
+  allowing the frames in the pipeline to be processed.
 
 - Updated `MoondreamService` revision to `2024-08-26`.
 
@@ -133,6 +146,11 @@ async def on_connected(processor):
 
 ### Fixed
 
+- Fixed OpenAI multiple function calls.
+
+- Fixed a Cartesia TTS issue that would cause audio to be truncated in some
+  cases.
+
 - Fixed a `BaseOutputTransport` issue that would stop audio and video rendering
   tasks (after receiving and `EndFrame`) before the internal queue was emptied,
   causing the pipeline to finish prematurely.
@@ -146,6 +164,10 @@ async def on_connected(processor):
 - `obj_id()` and `obj_count()` now use `itertools.count` avoiding the need of
   `threading.Lock`.
 
+### Other
+
+- Pipecat now uses Ruff as its formatter (https://github.com/astral-sh/ruff).
+
 ## [0.0.41] - 2024-08-22
 
 ### Added

From cd2e29f285d44d683135f009b157a3d9c14cb399 Mon Sep 17 00:00:00 2001
From: Mark Backman <mark@daily.co>
Date: Wed, 2 Oct 2024 12:26:30 -0400
Subject: [PATCH 126/135] Fix nested strings issue

---
 src/pipecat/services/aws.py        | 8 ++++----
 src/pipecat/services/elevenlabs.py | 6 +++---
 2 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/src/pipecat/services/aws.py b/src/pipecat/services/aws.py
index 210e0e700..cb0af1e30 100644
--- a/src/pipecat/services/aws.py
+++ b/src/pipecat/services/aws.py
@@ -136,17 +136,17 @@ class AWSTTSService(TTSService):
         ssml = "<speak>"
 
         if self._settings["language"]:
-            ssml += f"<lang xml:lang='{self._settings["language"]}'>"
+            ssml += f"<lang xml:lang='{self._settings['language']}'>"
 
         prosody_attrs = []
         # Prosody tags are only supported for standard and neural engines
         if self._settings["engine"] != "generative":
             if self._settings["rate"]:
-                prosody_attrs.append(f"rate='{self._settings["rate"]}'")
+                prosody_attrs.append(f"rate='{self._settings['rate']}'")
             if self._settings["pitch"]:
-                prosody_attrs.append(f"pitch='{self._settings["pitch"]}'")
+                prosody_attrs.append(f"pitch='{self._settings['pitch']}'")
             if self._settings["volume"]:
-                prosody_attrs.append(f"volume='{self._settings["volume"]}'")
+                prosody_attrs.append(f"volume='{self._settings['volume']}'")
 
             if prosody_attrs:
                 ssml += f"<prosody {' '.join(prosody_attrs)}>"
diff --git a/src/pipecat/services/elevenlabs.py b/src/pipecat/services/elevenlabs.py
index 695988b03..a2e25cf8a 100644
--- a/src/pipecat/services/elevenlabs.py
+++ b/src/pipecat/services/elevenlabs.py
@@ -292,15 +292,15 @@ class ElevenLabsTTSService(WordTTSService):
             url = f"{self._url}/v1/text-to-speech/{voice_id}/stream-input?model_id={model}&output_format={output_format}"
 
             if self._settings["optimize_streaming_latency"]:
-                url += f"&optimize_streaming_latency={self._settings["optimize_streaming_latency"]}"
+                url += f"&optimize_streaming_latency={self._settings['optimize_streaming_latency']}"
 
             # language can only be used with the 'eleven_turbo_v2_5' model
             if self._settings["language"]:
                 if model == "eleven_turbo_v2_5":
-                    url += f"&language_code={self._settings["language"]}"
+                    url += f"&language_code={self._settings['language']}"
                 else:
                     logger.debug(
-                        f"Language code [{self._settings["language"]}] not applied. Language codes can only be used with the 'eleven_turbo_v2_5' model."
+                        f"Language code [{self._settings['language']}] not applied. Language codes can only be used with the 'eleven_turbo_v2_5' model."
                     )
 
             self._websocket = await websockets.connect(url)

From 70c3ff31fd98bc4bacf70c83e3173f9ab5176e01 Mon Sep 17 00:00:00 2001
From: Allenmylath <155647926+Allenmylath@users.noreply.github.com>
Date: Wed, 2 Oct 2024 21:59:51 +0530
Subject: [PATCH 127/135] Update env.example

elevenlabs is not used in code instead cartesian is used hence changed
---
 examples/patient-intake/env.example | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/patient-intake/env.example b/examples/patient-intake/env.example
index d368ae510..571ebb8b4 100644
--- a/examples/patient-intake/env.example
+++ b/examples/patient-intake/env.example
@@ -1,4 +1,4 @@
 DAILY_SAMPLE_ROOM_URL=https://yourdomain.daily.co/yourroom # (for joining the bot to the same room repeatedly for local dev)
 DAILY_API_KEY=7df...
 OPENAI_API_KEY=sk-PL...
-ELEVENLABS_API_KEY=aeb...
\ No newline at end of file
+CARTESIA_API_KEY=your_cartesia_api_key_here

From 8c01a900cdd7c9729ba1ff4402f643546fcb68e6 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Wed, 2 Oct 2024 11:56:01 -0700
Subject: [PATCH 128/135] google: allow using GOOGLE_APPLICATION_CREDENTIALS

---
 examples/foundational/07n-interruptible-google.py | 1 -
 src/pipecat/services/google.py                    | 4 +---
 2 files changed, 1 insertion(+), 4 deletions(-)

diff --git a/examples/foundational/07n-interruptible-google.py b/examples/foundational/07n-interruptible-google.py
index 713b3dce3..55c931cf6 100644
--- a/examples/foundational/07n-interruptible-google.py
+++ b/examples/foundational/07n-interruptible-google.py
@@ -53,7 +53,6 @@ async def main():
         stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
 
         tts = GoogleTTSService(
-            credentials=os.getenv("GOOGLE_CREDENTIALS"),
             voice_id="en-US-Neural2-J",
             params=GoogleTTSService.InputParams(language="en-US", rate="1.05"),
         )
diff --git a/src/pipecat/services/google.py b/src/pipecat/services/google.py
index 55a2576d2..a02471040 100644
--- a/src/pipecat/services/google.py
+++ b/src/pipecat/services/google.py
@@ -40,7 +40,7 @@ try:
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
-        "In order to use Google AI, you need to `pip install pipecat-ai[google]`. Also, set `GOOGLE_API_KEY` environment variable."
+        "In order to use Google AI, you need to `pip install pipecat-ai[google]`. Also, set `GOOGLE_APPLICATION_CREDENTIALS` environment variable."
     )
     raise Exception(f"Missing module: {e}")
 
@@ -287,8 +287,6 @@ class GoogleTTSService(TTSService):
         elif credentials_path:
             # Use service account JSON file if provided
             creds = service_account.Credentials.from_service_account_file(credentials_path)
-        else:
-            raise ValueError("Either 'credentials' or 'credentials_path' must be provided.")
 
         return texttospeech_v1.TextToSpeechAsyncClient(credentials=creds)
 

From 8bcb5d7fd226778648fd7cb3e8f226c80d002b8a Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Wed, 2 Oct 2024 11:57:08 -0700
Subject: [PATCH 129/135] services: async generators should yield frames

---
 src/pipecat/services/aws.py        | 6 +++---
 src/pipecat/services/azure.py      | 4 ++--
 src/pipecat/services/cartesia.py   | 8 ++++----
 src/pipecat/services/deepgram.py   | 4 ++--
 src/pipecat/services/elevenlabs.py | 4 ++--
 src/pipecat/services/google.py     | 6 +++---
 src/pipecat/services/lmnt.py       | 4 ++--
 src/pipecat/services/openai.py     | 4 ++--
 src/pipecat/services/playht.py     | 4 ++--
 src/pipecat/services/xtts.py       | 4 ++--
 10 files changed, 24 insertions(+), 24 deletions(-)

diff --git a/src/pipecat/services/aws.py b/src/pipecat/services/aws.py
index cb0af1e30..4a2eceab6 100644
--- a/src/pipecat/services/aws.py
+++ b/src/pipecat/services/aws.py
@@ -190,7 +190,7 @@ class AWSTTSService(TTSService):
 
             await self.start_tts_usage_metrics(text)
 
-            await self.push_frame(TTSStartedFrame())
+            yield TTSStartedFrame()
 
             if "AudioStream" in response:
                 with response["AudioStream"] as stream:
@@ -203,7 +203,7 @@ class AWSTTSService(TTSService):
                             frame = TTSAudioRawFrame(chunk, self._settings["sample_rate"], 1)
                             yield frame
 
-            await self.push_frame(TTSStoppedFrame())
+            yield TTSStoppedFrame()
 
         except (BotoCoreError, ClientError) as error:
             logger.exception(f"{self} error generating TTS: {error}")
@@ -211,4 +211,4 @@ class AWSTTSService(TTSService):
             yield ErrorFrame(error=error_message)
 
         finally:
-            await self.push_frame(TTSStoppedFrame())
+            yield TTSStoppedFrame()
diff --git a/src/pipecat/services/azure.py b/src/pipecat/services/azure.py
index 32af1b3f4..eff5d333f 100644
--- a/src/pipecat/services/azure.py
+++ b/src/pipecat/services/azure.py
@@ -261,14 +261,14 @@ class AzureTTSService(TTSService):
         if result.reason == ResultReason.SynthesizingAudioCompleted:
             await self.start_tts_usage_metrics(text)
             await self.stop_ttfb_metrics()
-            await self.push_frame(TTSStartedFrame())
+            yield TTSStartedFrame()
             # Azure always sends a 44-byte header. Strip it off.
             yield TTSAudioRawFrame(
                 audio=result.audio_data[44:],
                 sample_rate=self._settings["sample_rate"],
                 num_channels=1,
             )
-            await self.push_frame(TTSStoppedFrame())
+            yield TTSStoppedFrame()
         elif result.reason == ResultReason.Canceled:
             cancellation_details = result.cancellation_details
             logger.warning(f"Speech synthesis canceled: {cancellation_details.reason}")
diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index 22e09cb2b..c23e96df9 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -255,8 +255,8 @@ class CartesiaTTSService(WordTTSService):
                 await self._connect()
 
             if not self._context_id:
-                await self.push_frame(TTSStartedFrame())
                 await self.start_ttfb_metrics()
+                yield TTSStartedFrame()
                 self._context_id = str(uuid.uuid4())
 
             msg = self._build_msg(text=text)
@@ -266,7 +266,7 @@ class CartesiaTTSService(WordTTSService):
                 await self.start_tts_usage_metrics(text)
             except Exception as e:
                 logger.error(f"{self} error sending message: {e}")
-                await self.push_frame(TTSStoppedFrame())
+                yield TTSStoppedFrame()
                 await self._disconnect()
                 await self._connect()
                 return
@@ -331,8 +331,8 @@ class CartesiaHttpTTSService(TTSService):
     async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
         logger.debug(f"Generating TTS: [{text}]")
 
-        await self.push_frame(TTSStartedFrame())
         await self.start_ttfb_metrics()
+        yield TTSStartedFrame()
 
         try:
             voice_controls = None
@@ -365,4 +365,4 @@ class CartesiaHttpTTSService(TTSService):
             logger.error(f"{self} exception: {e}")
 
         await self.start_tts_usage_metrics(text)
-        await self.push_frame(TTSStoppedFrame())
+        yield TTSStoppedFrame()
diff --git a/src/pipecat/services/deepgram.py b/src/pipecat/services/deepgram.py
index 433e08172..248efe3fc 100644
--- a/src/pipecat/services/deepgram.py
+++ b/src/pipecat/services/deepgram.py
@@ -84,7 +84,7 @@ class DeepgramTTSService(TTSService):
             )
 
             await self.start_tts_usage_metrics(text)
-            await self.push_frame(TTSStartedFrame())
+            yield TTSStartedFrame()
 
             # The response.stream_memory is already a BytesIO object
             audio_buffer = response.stream_memory
@@ -105,7 +105,7 @@ class DeepgramTTSService(TTSService):
                 )
                 yield frame
 
-            await self.push_frame(TTSStoppedFrame())
+                yield TTSStoppedFrame()
 
         except Exception as e:
             logger.exception(f"{self} exception: {e}")
diff --git a/src/pipecat/services/elevenlabs.py b/src/pipecat/services/elevenlabs.py
index a2e25cf8a..723e2f854 100644
--- a/src/pipecat/services/elevenlabs.py
+++ b/src/pipecat/services/elevenlabs.py
@@ -387,8 +387,8 @@ class ElevenLabsTTSService(WordTTSService):
 
             try:
                 if not self._started:
-                    await self.push_frame(TTSStartedFrame())
                     await self.start_ttfb_metrics()
+                    yield TTSStartedFrame()
                     self._started = True
                     self._cumulative_time = 0
 
@@ -396,7 +396,7 @@ class ElevenLabsTTSService(WordTTSService):
                 await self.start_tts_usage_metrics(text)
             except Exception as e:
                 logger.error(f"{self} error sending message: {e}")
-                await self.push_frame(TTSStoppedFrame())
+                yield TTSStoppedFrame()
                 await self._disconnect()
                 await self._connect()
                 return
diff --git a/src/pipecat/services/google.py b/src/pipecat/services/google.py
index a02471040..a8187366a 100644
--- a/src/pipecat/services/google.py
+++ b/src/pipecat/services/google.py
@@ -361,7 +361,7 @@ class GoogleTTSService(TTSService):
 
             await self.start_tts_usage_metrics(text)
 
-            await self.push_frame(TTSStartedFrame())
+            yield TTSStartedFrame()
 
             # Skip the first 44 bytes to remove the WAV header
             audio_content = response.audio_content[44:]
@@ -377,11 +377,11 @@ class GoogleTTSService(TTSService):
                 yield frame
                 await asyncio.sleep(0)  # Allow other tasks to run
 
-            await self.push_frame(TTSStoppedFrame())
+            yield TTSStoppedFrame()
 
         except Exception as e:
             logger.exception(f"{self} error generating TTS: {e}")
             error_message = f"TTS generation error: {str(e)}"
             yield ErrorFrame(error=error_message)
         finally:
-            await self.push_frame(TTSStoppedFrame())
+            yield TTSStoppedFrame()
diff --git a/src/pipecat/services/lmnt.py b/src/pipecat/services/lmnt.py
index 1ea3f1e62..eea4fd9db 100644
--- a/src/pipecat/services/lmnt.py
+++ b/src/pipecat/services/lmnt.py
@@ -176,8 +176,8 @@ class LmntTTSService(TTSService):
                 await self._connect()
 
             if not self._started:
-                await self.push_frame(TTSStartedFrame())
                 await self.start_ttfb_metrics()
+                yield TTSStartedFrame()
                 self._started = True
 
             try:
@@ -186,7 +186,7 @@ class LmntTTSService(TTSService):
                 await self.start_tts_usage_metrics(text)
             except Exception as e:
                 logger.error(f"{self} error sending message: {e}")
-                await self.push_frame(TTSStoppedFrame())
+                yield TTSStoppedFrame()
                 await self._disconnect()
                 await self._connect()
                 return
diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py
index 24d673234..2f98a7e10 100644
--- a/src/pipecat/services/openai.py
+++ b/src/pipecat/services/openai.py
@@ -426,13 +426,13 @@ class OpenAITTSService(TTSService):
 
                 await self.start_tts_usage_metrics(text)
 
-                await self.push_frame(TTSStartedFrame())
+                yield TTSStartedFrame()
                 async for chunk in r.iter_bytes(8192):
                     if len(chunk) > 0:
                         await self.stop_ttfb_metrics()
                         frame = TTSAudioRawFrame(chunk, self._settings["sample_rate"], 1)
                         yield frame
-                await self.push_frame(TTSStoppedFrame())
+                yield TTSStoppedFrame()
         except BadRequestError as e:
             logger.exception(f"{self} error generating TTS: {e}")
 
diff --git a/src/pipecat/services/playht.py b/src/pipecat/services/playht.py
index fe5feba3a..26c666d61 100644
--- a/src/pipecat/services/playht.py
+++ b/src/pipecat/services/playht.py
@@ -75,7 +75,7 @@ class PlayHTTTSService(TTSService):
 
             await self.start_tts_usage_metrics(text)
 
-            await self.push_frame(TTSStartedFrame())
+            yield TTSStartedFrame()
             async for chunk in playht_gen:
                 # skip the RIFF header.
                 if in_header:
@@ -95,6 +95,6 @@ class PlayHTTTSService(TTSService):
                         await self.stop_ttfb_metrics()
                         frame = TTSAudioRawFrame(chunk, self._settings["sample_rate"], 1)
                         yield frame
-            await self.push_frame(TTSStoppedFrame())
+            yield TTSStoppedFrame()
         except Exception as e:
             logger.exception(f"{self} error generating TTS: {e}")
diff --git a/src/pipecat/services/xtts.py b/src/pipecat/services/xtts.py
index eb20d5f3c..d3cea254a 100644
--- a/src/pipecat/services/xtts.py
+++ b/src/pipecat/services/xtts.py
@@ -151,7 +151,7 @@ class XTTSService(TTSService):
 
             await self.start_tts_usage_metrics(text)
 
-            await self.push_frame(TTSStartedFrame())
+            yield TTSStartedFrame()
 
             buffer = bytearray()
             async for chunk in r.content.iter_chunked(1024):
@@ -187,4 +187,4 @@ class XTTSService(TTSService):
                 frame = TTSAudioRawFrame(resampled_audio_bytes, 16000, 1)
                 yield frame
 
-            await self.push_frame(TTSStoppedFrame())
+            yield TTSStoppedFrame()

From 3648874301c06198f286bbfeebac5f3e4afcd352 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Wed, 2 Oct 2024 11:57:25 -0700
Subject: [PATCH 130/135] gladia: fix languages

---
 src/pipecat/services/gladia.py | 66 +++++++++++++++++-----------------
 1 file changed, 33 insertions(+), 33 deletions(-)

diff --git a/src/pipecat/services/gladia.py b/src/pipecat/services/gladia.py
index 0938a1cee..8f270195b 100644
--- a/src/pipecat/services/gladia.py
+++ b/src/pipecat/services/gladia.py
@@ -37,17 +37,17 @@ except ModuleNotFoundError as e:
 def language_to_gladia_language(language: Language) -> str | None:
     match language:
         case Language.BG:
-            return "bg"
+            return "bulgarian"
         case Language.CA:
-            return "ca"
+            return "catalan"
         case Language.ZH:
-            return "zh"
+            return "chinese"
         case Language.CS:
-            return "cs"
+            return "czech"
         case Language.DA:
-            return "da"
+            return "danish"
         case Language.NL:
-            return "nl"
+            return "dutch"
         case (
             Language.EN
             | Language.EN_US
@@ -56,59 +56,59 @@ def language_to_gladia_language(language: Language) -> str | None:
             | Language.EN_NZ
             | Language.EN_IN
         ):
-            return "en"
+            return "english"
         case Language.ET:
-            return "et"
+            return "estonian"
         case Language.FI:
-            return "fi"
+            return "finnish"
         case Language.FR | Language.FR_CA:
-            return "fr"
+            return "french"
         case Language.DE | Language.DE_CH:
-            return "de"
+            return "german"
         case Language.EL:
-            return "el"
+            return "greek"
         case Language.HI:
-            return "hi"
+            return "hindi"
         case Language.HU:
-            return "hu"
+            return "hungarian"
         case Language.ID:
-            return "id"
+            return "indonesian"
         case Language.IT:
-            return "it"
+            return "italian"
         case Language.JA:
-            return "ja"
+            return "japanese"
         case Language.KO:
-            return "ko"
+            return "korean"
         case Language.LV:
-            return "lv"
+            return "latvian"
         case Language.LT:
-            return "lt"
+            return "lithuanian"
         case Language.MS:
-            return "ms"
+            return "malay"
         case Language.NO:
-            return "no"
+            return "norwegian"
         case Language.PL:
-            return "pl"
+            return "polish"
         case Language.PT | Language.PT_BR:
-            return "pt"
+            return "portuguese"
         case Language.RO:
-            return "ro"
+            return "romanian"
         case Language.RU:
-            return "ru"
+            return "russian"
         case Language.SK:
-            return "sk"
+            return "slovak"
         case Language.ES:
-            return "es"
+            return "spanish"
         case Language.SV:
-            return "sv"
+            return "slovenian"
         case Language.TH:
-            return "th"
+            return "thai"
         case Language.TR:
-            return "tr"
+            return "turkish"
         case Language.UK:
-            return "uk"
+            return "ukrainian"
         case Language.VI:
-            return "vi"
+            return "vietnamese"
     return None
 
 

From 6db65f4335ca74dce7b532a20322be2efa7a6150 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Wed, 2 Oct 2024 11:57:36 -0700
Subject: [PATCH 131/135] cartesia: use model_name instead of model_id

---
 src/pipecat/services/cartesia.py | 7 +------
 1 file changed, 1 insertion(+), 6 deletions(-)

diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index c23e96df9..464c2d979 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -315,11 +315,6 @@ class CartesiaHttpTTSService(TTSService):
     def can_generate_metrics(self) -> bool:
         return True
 
-    async def set_model(self, model: str):
-        logger.debug(f"Switching TTS model to: [{model}]")
-        self._model_id = model
-        await super().set_model(model)
-
     async def stop(self, frame: EndFrame):
         await super().stop(frame)
         await self._client.close()
@@ -344,7 +339,7 @@ class CartesiaHttpTTSService(TTSService):
                     voice_controls["emotion"] = self._settings["emotion"]
 
             output = await self._client.tts.sse(
-                model_id=self._model_id,
+                model_id=self._model_name,
                 transcript=text,
                 voice_id=self._voice_id,
                 output_format=self._settings["output_format"],

From 0a37caf4b496dccc33df1afff4892c4dda7254a2 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Wed, 2 Oct 2024 11:57:50 -0700
Subject: [PATCH 132/135] openai: fix image json logging

---
 src/pipecat/processors/aggregators/openai_llm_context.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/src/pipecat/processors/aggregators/openai_llm_context.py b/src/pipecat/processors/aggregators/openai_llm_context.py
index c86045fab..f099c372d 100644
--- a/src/pipecat/processors/aggregators/openai_llm_context.py
+++ b/src/pipecat/processors/aggregators/openai_llm_context.py
@@ -127,6 +127,8 @@ class OpenAILLMContext:
                         if item["type"] == "image_url":
                             if item["image_url"]["url"].startswith("data:image/"):
                                 item["image_url"]["url"] = "data:image/..."
+            if "mime_type" in msg and msg["mime_type"].startswith("image/"):
+                msg["data"] = "..."
             msgs.append(msg)
         return json.dumps(msgs)
 

From 75d27aeb9f036fba0c5c526cd7e6e124db27f8bb Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Wed, 2 Oct 2024 12:00:00 -0700
Subject: [PATCH 133/135] examples(storytelling): update packages

---
 .../frontend/package-lock.json                | 2497 ++++++-------
 .../frontend/package.json                     |   32 +-
 .../storytelling-chatbot/frontend/yarn.lock   | 3208 -----------------
 examples/storytelling-chatbot/src/bot.py      |    2 +-
 4 files changed, 1117 insertions(+), 4622 deletions(-)
 delete mode 100644 examples/storytelling-chatbot/frontend/yarn.lock

diff --git a/examples/storytelling-chatbot/frontend/package-lock.json b/examples/storytelling-chatbot/frontend/package-lock.json
index beedc2006..614315448 100644
--- a/examples/storytelling-chatbot/frontend/package-lock.json
+++ b/examples/storytelling-chatbot/frontend/package-lock.json
@@ -10,46 +10,35 @@
       "dependencies": {
         "@daily-co/daily-js": "^0.62.0",
         "@daily-co/daily-react": "^0.18.0",
-        "@radix-ui/react-select": "^2.0.0",
+        "@radix-ui/react-select": "^2.1.2",
         "@radix-ui/react-slot": "^1.0.2",
-        "@tabler/icons-react": "^3.1.0",
+        "@tabler/icons-react": "^3.19.0",
         "class-variance-authority": "^0.7.0",
-        "clsx": "^2.1.0",
-        "framer-motion": "^11.0.27",
-        "next": "14.1.4",
-        "react": "^18",
-        "react-dom": "^18",
+        "clsx": "^2.1.1",
+        "framer-motion": "^11.9.0",
+        "next": "^14.2.14",
+        "react": "^18.3.1",
+        "react-dom": "^18.3.1",
         "recoil": "^0.7.7",
-        "tailwind-merge": "^2.2.2",
+        "tailwind-merge": "^2.5.2",
         "tailwindcss-animate": "^1.0.7"
       },
       "devDependencies": {
-        "@types/node": "^20",
-        "@types/react": "^18",
-        "@types/react-dom": "^18",
-        "autoprefixer": "^10.0.1",
-        "eslint": "^8",
+        "@types/node": "^20.16.10",
+        "@types/react": "^18.3.11",
+        "@types/react-dom": "^18.3.0",
+        "autoprefixer": "^10.4.20",
+        "eslint": "^8.57.1",
         "eslint-config-next": "14.1.4",
-        "postcss": "^8",
-        "tailwindcss": "^3.4.3",
-        "typescript": "^5"
-      }
-    },
-    "node_modules/@aashutoshrathi/word-wrap": {
-      "version": "1.2.6",
-      "resolved": "https://registry.npmjs.org/@aashutoshrathi/word-wrap/-/word-wrap-1.2.6.tgz",
-      "integrity": "sha512-1Yjs2SvM8TflER/OD3cOjhWWOZb58A2t7wpE2S9XfBYTiIl+XFhQG2bjy4Pu1I+EAlCNUzRDYDdFwFYUKvXcIA==",
-      "dev": true,
-      "license": "MIT",
-      "engines": {
-        "node": ">=0.10.0"
+        "postcss": "^8.4.47",
+        "tailwindcss": "^3.4.13",
+        "typescript": "^5.6.2"
       }
     },
     "node_modules/@alloc/quick-lru": {
       "version": "5.2.0",
       "resolved": "https://registry.npmjs.org/@alloc/quick-lru/-/quick-lru-5.2.0.tgz",
       "integrity": "sha512-UrcABB+4bUrFABwbluTIBErXwvbsU/V7TZWfmbgJfbkwiBuziS9gxdODUyuiecfdGQ85jglMW6juS3+z5TsKLw==",
-      "license": "MIT",
       "engines": {
         "node": ">=10"
       },
@@ -58,10 +47,9 @@
       }
     },
     "node_modules/@babel/runtime": {
-      "version": "7.24.4",
-      "resolved": "https://registry.npmjs.org/@babel/runtime/-/runtime-7.24.4.tgz",
-      "integrity": "sha512-dkxf7+hn8mFBwKjs9bvBlArzLVxVbS8usaPUDd5p2a9JCL9tB8OaOVN1isD4+Xyk4ns89/xeOmbQvgdK7IIVdA==",
-      "license": "MIT",
+      "version": "7.25.7",
+      "resolved": "https://registry.npmjs.org/@babel/runtime/-/runtime-7.25.7.tgz",
+      "integrity": "sha512-FjoyLe754PMiYsFaN5C94ttGiOmBNYTf6pLr4xXHAT5uctHb092PBszndLDR5XA/jghQvn4n7JMHl7dmTgbm9w==",
       "dependencies": {
         "regenerator-runtime": "^0.14.0"
       },
@@ -73,7 +61,6 @@
       "version": "0.62.0",
       "resolved": "https://registry.npmjs.org/@daily-co/daily-js/-/daily-js-0.62.0.tgz",
       "integrity": "sha512-OskaskD0DU44bfoAaW+El5TPnJNTG0FdKx+pjRfgyqkXt4sOuLdo0DoUmUVDkls2iKHTbpTRJUOR8MeW/OdccQ==",
-      "license": "BSD-2-Clause",
       "dependencies": {
         "@babel/runtime": "^7.12.5",
         "@sentry/browser": "^7.60.1",
@@ -89,7 +76,6 @@
       "version": "0.18.0",
       "resolved": "https://registry.npmjs.org/@daily-co/daily-react/-/daily-react-0.18.0.tgz",
       "integrity": "sha512-qjoVkBLLEpE51NbctXPpi6n3f645L8tuwlPLVnELFKTUiGuDPcEX7x9oUtRjk0qOrMdineCg9QtcB5Dk6tgmJw==",
-      "license": "BSD-2-Clause",
       "dependencies": {
         "fast-deep-equal": "^3.1.3",
         "lodash.throttle": "^4.1.1"
@@ -108,7 +94,6 @@
       "resolved": "https://registry.npmjs.org/@eslint-community/eslint-utils/-/eslint-utils-4.4.0.tgz",
       "integrity": "sha512-1/sA4dwrzBAyeUoQ6oxahHKmrZvsnLCg4RfxW3ZFGGmQkSNQPFNLV9CUEFQP1x9EYXHTo5p6xdhZM1Ne9p/AfA==",
       "dev": true,
-      "license": "MIT",
       "dependencies": {
         "eslint-visitor-keys": "^3.3.0"
       },
@@ -120,11 +105,10 @@
       }
     },
     "node_modules/@eslint-community/regexpp": {
-      "version": "4.10.0",
-      "resolved": "https://registry.npmjs.org/@eslint-community/regexpp/-/regexpp-4.10.0.tgz",
-      "integrity": "sha512-Cu96Sd2By9mCNTx2iyKOmq10v22jUVQv0lQnlGNy16oE9589yE+QADPbrMGCkA51cKZSg3Pu/aTJVTGfL/qjUA==",
+      "version": "4.11.1",
+      "resolved": "https://registry.npmjs.org/@eslint-community/regexpp/-/regexpp-4.11.1.tgz",
+      "integrity": "sha512-m4DVN9ZqskZoLU5GlWZadwDnYo3vAEydiUayB9widCl9ffWx2IvPnp6n3on5rJmziJSw9Bv+Z3ChDVdMwXCY8Q==",
       "dev": true,
-      "license": "MIT",
       "engines": {
         "node": "^12.0.0 || ^14.0.0 || >=16.0.0"
       }
@@ -134,7 +118,6 @@
       "resolved": "https://registry.npmjs.org/@eslint/eslintrc/-/eslintrc-2.1.4.tgz",
       "integrity": "sha512-269Z39MS6wVJtsoUl10L60WdkhJVdPG24Q4eZTH3nnF6lpvSShEK3wQjDX9JRWAUPvPh7COouPpU9IrqaZFvtQ==",
       "dev": true,
-      "license": "MIT",
       "dependencies": {
         "ajv": "^6.12.4",
         "debug": "^4.3.2",
@@ -154,41 +137,37 @@
       }
     },
     "node_modules/@eslint/js": {
-      "version": "8.57.0",
-      "resolved": "https://registry.npmjs.org/@eslint/js/-/js-8.57.0.tgz",
-      "integrity": "sha512-Ys+3g2TaW7gADOJzPt83SJtCDhMjndcDMFVQ/Tj9iA1BfJzFKD9mAUXT3OenpuPHbI6P/myECxRJrofUsDx/5g==",
+      "version": "8.57.1",
+      "resolved": "https://registry.npmjs.org/@eslint/js/-/js-8.57.1.tgz",
+      "integrity": "sha512-d9zaMRSTIKDLhctzH12MtXvJKSSUhaHcjV+2Z+GK+EEY7XKpP5yR4x+N3TAcHTcu963nIr+TMcCb4DBCYX1z6Q==",
       "dev": true,
-      "license": "MIT",
       "engines": {
         "node": "^12.22.0 || ^14.17.0 || >=16.0.0"
       }
     },
     "node_modules/@floating-ui/core": {
-      "version": "1.6.0",
-      "resolved": "https://registry.npmjs.org/@floating-ui/core/-/core-1.6.0.tgz",
-      "integrity": "sha512-PcF++MykgmTj3CIyOQbKA/hDzOAiqI3mhuoN44WRCopIs1sgoDoU4oty4Jtqaj/y3oDU6fnVSm4QG0a3t5i0+g==",
-      "license": "MIT",
+      "version": "1.6.8",
+      "resolved": "https://registry.npmjs.org/@floating-ui/core/-/core-1.6.8.tgz",
+      "integrity": "sha512-7XJ9cPU+yI2QeLS+FCSlqNFZJq8arvswefkZrYI1yQBbftw6FyrZOxYSh+9S7z7TpeWlRt9zJ5IhM1WIL334jA==",
       "dependencies": {
-        "@floating-ui/utils": "^0.2.1"
+        "@floating-ui/utils": "^0.2.8"
       }
     },
     "node_modules/@floating-ui/dom": {
-      "version": "1.6.3",
-      "resolved": "https://registry.npmjs.org/@floating-ui/dom/-/dom-1.6.3.tgz",
-      "integrity": "sha512-RnDthu3mzPlQ31Ss/BTwQ1zjzIhr3lk1gZB1OC56h/1vEtaXkESrOqL5fQVMfXpwGtRwX+YsZBdyHtJMQnkArw==",
-      "license": "MIT",
+      "version": "1.6.11",
+      "resolved": "https://registry.npmjs.org/@floating-ui/dom/-/dom-1.6.11.tgz",
+      "integrity": "sha512-qkMCxSR24v2vGkhYDo/UzxfJN3D4syqSjyuTFz6C7XcpU1pASPRieNI0Kj5VP3/503mOfYiGY891ugBX1GlABQ==",
       "dependencies": {
-        "@floating-ui/core": "^1.0.0",
-        "@floating-ui/utils": "^0.2.0"
+        "@floating-ui/core": "^1.6.0",
+        "@floating-ui/utils": "^0.2.8"
       }
     },
     "node_modules/@floating-ui/react-dom": {
-      "version": "2.0.8",
-      "resolved": "https://registry.npmjs.org/@floating-ui/react-dom/-/react-dom-2.0.8.tgz",
-      "integrity": "sha512-HOdqOt3R3OGeTKidaLvJKcgg75S6tibQ3Tif4eyd91QnIJWr0NLvoXFpJA/j8HqkFSL68GDca9AuyWEHlhyClw==",
-      "license": "MIT",
+      "version": "2.1.2",
+      "resolved": "https://registry.npmjs.org/@floating-ui/react-dom/-/react-dom-2.1.2.tgz",
+      "integrity": "sha512-06okr5cgPzMNBy+Ycse2A6udMi4bqwW/zgBF/rwjcNqWkyr82Mcg8b0vjX8OJpZFy/FKjJmw6wV7t44kK6kW7A==",
       "dependencies": {
-        "@floating-ui/dom": "^1.6.1"
+        "@floating-ui/dom": "^1.0.0"
       },
       "peerDependencies": {
         "react": ">=16.8.0",
@@ -196,19 +175,18 @@
       }
     },
     "node_modules/@floating-ui/utils": {
-      "version": "0.2.1",
-      "resolved": "https://registry.npmjs.org/@floating-ui/utils/-/utils-0.2.1.tgz",
-      "integrity": "sha512-9TANp6GPoMtYzQdt54kfAyMmz1+osLlXdg2ENroU7zzrtflTLrrC/lgrIfaSe+Wu0b89GKccT7vxXA0MoAIO+Q==",
-      "license": "MIT"
+      "version": "0.2.8",
+      "resolved": "https://registry.npmjs.org/@floating-ui/utils/-/utils-0.2.8.tgz",
+      "integrity": "sha512-kym7SodPp8/wloecOpcmSnWJsK7M0E5Wg8UcFA+uO4B9s5d0ywXOEro/8HM9x0rW+TljRzul/14UYz3TleT3ig=="
     },
     "node_modules/@humanwhocodes/config-array": {
-      "version": "0.11.14",
-      "resolved": "https://registry.npmjs.org/@humanwhocodes/config-array/-/config-array-0.11.14.tgz",
-      "integrity": "sha512-3T8LkOmg45BV5FICb15QQMsyUSWrQ8AygVfC7ZG32zOalnqrilm018ZVCw0eapXux8FtA33q8PSRSstjee3jSg==",
+      "version": "0.13.0",
+      "resolved": "https://registry.npmjs.org/@humanwhocodes/config-array/-/config-array-0.13.0.tgz",
+      "integrity": "sha512-DZLEEqFWQFiyK6h5YIeynKx7JlvCYWL0cImfSRXZ9l4Sg2efkFGTuFf6vzXjK1cq6IYkU+Eg/JizXw+TD2vRNw==",
+      "deprecated": "Use @eslint/config-array instead",
       "dev": true,
-      "license": "Apache-2.0",
       "dependencies": {
-        "@humanwhocodes/object-schema": "^2.0.2",
+        "@humanwhocodes/object-schema": "^2.0.3",
         "debug": "^4.3.1",
         "minimatch": "^3.0.5"
       },
@@ -221,7 +199,6 @@
       "resolved": "https://registry.npmjs.org/@humanwhocodes/module-importer/-/module-importer-1.0.1.tgz",
       "integrity": "sha512-bxveV4V8v5Yb4ncFTT3rPSgZBOpCkjfK0y4oVVVJwIuDVBRMDXrPyXRL988i5ap9m9bnyEEjWfm5WkBmtffLfA==",
       "dev": true,
-      "license": "Apache-2.0",
       "engines": {
         "node": ">=12.22"
       },
@@ -234,14 +211,13 @@
       "version": "2.0.3",
       "resolved": "https://registry.npmjs.org/@humanwhocodes/object-schema/-/object-schema-2.0.3.tgz",
       "integrity": "sha512-93zYdMES/c1D69yZiKDBj0V24vqNzB/koF26KPaagAfd3P/4gUlh3Dys5ogAK+Exi9QyzlD8x/08Zt7wIKcDcA==",
-      "dev": true,
-      "license": "BSD-3-Clause"
+      "deprecated": "Use @eslint/object-schema instead",
+      "dev": true
     },
     "node_modules/@isaacs/cliui": {
       "version": "8.0.2",
       "resolved": "https://registry.npmjs.org/@isaacs/cliui/-/cliui-8.0.2.tgz",
       "integrity": "sha512-O8jcjabXaleOG9DQ0+ARXWZBTfnP4WNAqzuiJK7ll44AmxGKv/J2M4TPjxjY3znBCfvBXFzucm1twdyFybFqEA==",
-      "license": "ISC",
       "dependencies": {
         "string-width": "^5.1.2",
         "string-width-cjs": "npm:string-width@^4.2.0",
@@ -255,10 +231,9 @@
       }
     },
     "node_modules/@isaacs/cliui/node_modules/ansi-regex": {
-      "version": "6.0.1",
-      "resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-6.0.1.tgz",
-      "integrity": "sha512-n5M855fKb2SsfMIiFFoVrABHJC8QtHwVx+mHWP3QcEqBHYienj5dHSgjbxtC0WEZXYt4wcD6zrQElDPhFuZgfA==",
-      "license": "MIT",
+      "version": "6.1.0",
+      "resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-6.1.0.tgz",
+      "integrity": "sha512-7HSX4QQb4CspciLpVFwyRe79O3xsIZDDLER21kERQ71oaPodF8jL725AgJMFAYbooIqolJoRLuM81SpeUkpkvA==",
       "engines": {
         "node": ">=12"
       },
@@ -270,7 +245,6 @@
       "version": "7.1.0",
       "resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-7.1.0.tgz",
       "integrity": "sha512-iq6eVVI64nQQTRYq2KtEg2d2uU7LElhTJwsH4YzIHZshxlgZms/wIc4VoDQTlG/IvVIrBKG06CrZnp0qv7hkcQ==",
-      "license": "MIT",
       "dependencies": {
         "ansi-regex": "^6.0.1"
       },
@@ -285,7 +259,6 @@
       "version": "0.3.5",
       "resolved": "https://registry.npmjs.org/@jridgewell/gen-mapping/-/gen-mapping-0.3.5.tgz",
       "integrity": "sha512-IzL8ZoEDIBRWEzlCcRhOaCupYyN5gdIK+Q6fbFdPDg6HqX6jpkItn7DFIpW9LQzXG6Df9sA7+OKnq0qlz/GaQg==",
-      "license": "MIT",
       "dependencies": {
         "@jridgewell/set-array": "^1.2.1",
         "@jridgewell/sourcemap-codec": "^1.4.10",
@@ -299,7 +272,6 @@
       "version": "3.1.2",
       "resolved": "https://registry.npmjs.org/@jridgewell/resolve-uri/-/resolve-uri-3.1.2.tgz",
       "integrity": "sha512-bRISgCIjP20/tbWSPWMEi54QVPRZExkuD9lJL+UIxUKtwVJA8wW1Trb1jMs1RFXo1CBTNZ/5hpC9QvmKWdopKw==",
-      "license": "MIT",
       "engines": {
         "node": ">=6.0.0"
       }
@@ -308,51 +280,105 @@
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diff --git a/examples/storytelling-chatbot/frontend/package.json b/examples/storytelling-chatbot/frontend/package.json
index 10edbb29a..358bc3dd5 100644
--- a/examples/storytelling-chatbot/frontend/package.json
+++ b/examples/storytelling-chatbot/frontend/package.json
@@ -11,28 +11,28 @@
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+    "tailwindcss": "^3.4.13",
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 }
diff --git a/examples/storytelling-chatbot/frontend/yarn.lock b/examples/storytelling-chatbot/frontend/yarn.lock
deleted file mode 100644
index c98b07368..000000000
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-  dependencies:
-    ansi-styles "^6.1.0"
-    string-width "^5.0.1"
-    strip-ansi "^7.0.1"
-
-wrappy@1:
-  version "1.0.2"
-  resolved "https://registry.npmjs.org/wrappy/-/wrappy-1.0.2.tgz"
-  integrity sha512-l4Sp/DRseor9wL6EvV2+TuQn63dMkPjZ/sp9XkghTEbV9KlPS1xUsZ3u7/IQO4wxtcFB4bgpQPRcR3QCvezPcQ==
-
-yallist@^4.0.0:
-  version "4.0.0"
-  resolved "https://registry.npmjs.org/yallist/-/yallist-4.0.0.tgz"
-  integrity sha512-3wdGidZyq5PB084XLES5TpOSRA3wjXAlIWMhum2kRcv/41Sn2emQ0dycQW4uZXLejwKvg6EsvbdlVL+FYEct7A==
-
-yaml@^2.3.4:
-  version "2.4.1"
-  resolved "https://registry.npmjs.org/yaml/-/yaml-2.4.1.tgz"
-  integrity sha512-pIXzoImaqmfOrL7teGUBt/T7ZDnyeGBWyXQBvOVhLkWLN37GXv8NMLK406UY6dS51JfcQHsmcW5cJ441bHg6Lg==
-
-yocto-queue@^0.1.0:
-  version "0.1.0"
-  resolved "https://registry.npmjs.org/yocto-queue/-/yocto-queue-0.1.0.tgz"
-  integrity sha512-rVksvsnNCdJ/ohGc6xgPwyN8eheCxsiLM8mxuE/t/mOVqJewPuO1miLpTHQiRgTKCLexL4MeAFVagts7HmNZ2Q==
diff --git a/examples/storytelling-chatbot/src/bot.py b/examples/storytelling-chatbot/src/bot.py
index e67af8d7d..63e727131 100644
--- a/examples/storytelling-chatbot/src/bot.py
+++ b/examples/storytelling-chatbot/src/bot.py
@@ -143,7 +143,7 @@ async def main(room_url, token=None):
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            intro_task.queue_frame(EndFrame())
+            await intro_task.queue_frame(EndFrame())
             await main_task.queue_frame(EndFrame())
 
         @transport.event_handler("on_call_state_updated")

From b1bf6f773398a9eb88c272d2453ba8dc1369ea02 Mon Sep 17 00:00:00 2001
From: Chad Bailey <chadbailey@gmail.com>
Date: Wed, 2 Oct 2024 19:43:51 +0000
Subject: [PATCH 134/135] fixed botinterruptionframe

---
 src/pipecat/transports/base_input.py | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/src/pipecat/transports/base_input.py b/src/pipecat/transports/base_input.py
index 710f8108a..ad95d1139 100644
--- a/src/pipecat/transports/base_input.py
+++ b/src/pipecat/transports/base_input.py
@@ -5,17 +5,17 @@
 #
 
 import asyncio
-
 from concurrent.futures import ThreadPoolExecutor
 
-from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
+from loguru import logger
+
 from pipecat.frames.frames import (
     BotInterruptionFrame,
     CancelFrame,
-    InputAudioRawFrame,
-    StartFrame,
     EndFrame,
     Frame,
+    InputAudioRawFrame,
+    StartFrame,
     StartInterruptionFrame,
     StopInterruptionFrame,
     SystemFrame,
@@ -23,11 +23,10 @@ from pipecat.frames.frames import (
     UserStoppedSpeakingFrame,
     VADParamsUpdateFrame,
 )
+from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.transports.base_transport import TransportParams
 from pipecat.vad.vad_analyzer import VADAnalyzer, VADState
 
-from loguru import logger
-
 
 class BaseInputTransport(FrameProcessor):
     def __init__(self, params: TransportParams, **kwargs):
@@ -87,6 +86,7 @@ class BaseInputTransport(FrameProcessor):
         elif isinstance(frame, BotInterruptionFrame):
             logger.debug("Bot interruption")
             await self._start_interruption()
+            await self.push_frame(StartInterruptionFrame())
         # All other system frames
         elif isinstance(frame, SystemFrame):
             await self.push_frame(frame, direction)

From 598936bc539856290a7743d3c16aff68bda774fe Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aleix=20Conchillo=20Flaqu=C3=A9?= <aleix@daily.co>
Date: Wed, 2 Oct 2024 13:30:01 -0700
Subject: [PATCH 135/135] services: apply service language code before using
 service

---
 src/pipecat/services/aws.py        |  9 ++++-----
 src/pipecat/services/azure.py      |  6 ++++--
 src/pipecat/services/cartesia.py   |  8 ++++----
 src/pipecat/services/elevenlabs.py | 20 +++++++++-----------
 src/pipecat/services/gladia.py     |  4 ++--
 src/pipecat/services/google.py     | 12 ++++++------
 src/pipecat/services/lmnt.py       |  2 +-
 src/pipecat/services/xtts.py       |  6 ++++--
 8 files changed, 34 insertions(+), 33 deletions(-)

diff --git a/src/pipecat/services/aws.py b/src/pipecat/services/aws.py
index 4a2eceab6..0ae72b968 100644
--- a/src/pipecat/services/aws.py
+++ b/src/pipecat/services/aws.py
@@ -121,7 +121,7 @@ class AWSTTSService(TTSService):
         self._settings = {
             "sample_rate": sample_rate,
             "engine": params.engine,
-            "language": language_to_aws_language(params.language) if params.language else "en-US",
+            "language": params.language if params.language else Language.EN,
             "pitch": params.pitch,
             "rate": params.rate,
             "volume": params.volume,
@@ -135,8 +135,8 @@ class AWSTTSService(TTSService):
     def _construct_ssml(self, text: str) -> str:
         ssml = "<speak>"
 
-        if self._settings["language"]:
-            ssml += f"<lang xml:lang='{self._settings['language']}'>"
+        language = language_to_aws_language(self._settings["language"])
+        ssml += f"<lang xml:lang='{language}'>"
 
         prosody_attrs = []
         # Prosody tags are only supported for standard and neural engines
@@ -158,8 +158,7 @@ class AWSTTSService(TTSService):
         if prosody_attrs:
             ssml += "</prosody>"
 
-        if self._settings["language"]:
-            ssml += "</lang>"
+        ssml += "</lang>"
 
         ssml += "</speak>"
 
diff --git a/src/pipecat/services/azure.py b/src/pipecat/services/azure.py
index eff5d333f..190a297a0 100644
--- a/src/pipecat/services/azure.py
+++ b/src/pipecat/services/azure.py
@@ -27,6 +27,7 @@ from pipecat.frames.frames import (
 )
 from pipecat.services.ai_services import ImageGenService, STTService, TTSService
 from pipecat.services.openai import BaseOpenAILLMService
+from pipecat.transcriptions import language
 from pipecat.transcriptions.language import Language
 from pipecat.utils.time import time_now_iso8601
 
@@ -191,7 +192,7 @@ class AzureTTSService(TTSService):
         self._settings = {
             "sample_rate": sample_rate,
             "emphasis": params.emphasis,
-            "language": language_to_azure_language(params.language) if params.language else "en-US",
+            "language": params.language if params.language else Language.EN,
             "pitch": params.pitch,
             "rate": params.rate,
             "role": params.role,
@@ -206,8 +207,9 @@ class AzureTTSService(TTSService):
         return True
 
     def _construct_ssml(self, text: str) -> str:
+        language = language_to_azure_language(self._settings["language"])
         ssml = (
-            f"<speak version='1.0' xml:lang='{self._settings['language']}' "
+            f"<speak version='1.0' xml:lang='{language}' "
             "xmlns='http://www.w3.org/2001/10/synthesis' "
             "xmlns:mstts='http://www.w3.org/2001/mstts'>"
             f"<voice name='{self._voice_id}'>"
diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py
index 464c2d979..b8aab1161 100644
--- a/src/pipecat/services/cartesia.py
+++ b/src/pipecat/services/cartesia.py
@@ -106,7 +106,7 @@ class CartesiaTTSService(WordTTSService):
                 "encoding": params.encoding,
                 "sample_rate": params.sample_rate,
             },
-            "language": language_to_cartesia_language(params.language) if params.language else "en",
+            "language": params.language if params.language else Language.EN,
             "speed": params.speed,
             "emotion": params.emotion,
         }
@@ -146,7 +146,7 @@ class CartesiaTTSService(WordTTSService):
             "model_id": self.model_name,
             "voice": voice_config,
             "output_format": self._settings["output_format"],
-            "language": self._settings["language"],
+            "language": language_to_cartesia_language(self._settings["language"]),
             "add_timestamps": add_timestamps,
         }
         return json.dumps(msg)
@@ -303,7 +303,7 @@ class CartesiaHttpTTSService(TTSService):
                 "encoding": params.encoding,
                 "sample_rate": params.sample_rate,
             },
-            "language": language_to_cartesia_language(params.language) if params.language else None,
+            "language": params.language if params.language else Language.EN,
             "speed": params.speed,
             "emotion": params.emotion,
         }
@@ -343,7 +343,7 @@ class CartesiaHttpTTSService(TTSService):
                 transcript=text,
                 voice_id=self._voice_id,
                 output_format=self._settings["output_format"],
-                language=self._settings["language"],
+                language=language_to_cartesia_language(self._settings["language"]),
                 stream=False,
                 _experimental_voice_controls=voice_controls,
             )
diff --git a/src/pipecat/services/elevenlabs.py b/src/pipecat/services/elevenlabs.py
index 723e2f854..95ac5c1f1 100644
--- a/src/pipecat/services/elevenlabs.py
+++ b/src/pipecat/services/elevenlabs.py
@@ -198,9 +198,7 @@ class ElevenLabsTTSService(WordTTSService):
         self._url = url
         self._settings = {
             "sample_rate": sample_rate_from_output_format(params.output_format),
-            "language": language_to_elevenlabs_language(params.language)
-            if params.language
-            else "en",
+            "language": params.language if params.language else Language.EN,
             "output_format": params.output_format,
             "optimize_streaming_latency": params.optimize_streaming_latency,
             "stability": params.stability,
@@ -294,14 +292,14 @@ class ElevenLabsTTSService(WordTTSService):
             if self._settings["optimize_streaming_latency"]:
                 url += f"&optimize_streaming_latency={self._settings['optimize_streaming_latency']}"
 
-            # language can only be used with the 'eleven_turbo_v2_5' model
-            if self._settings["language"]:
-                if model == "eleven_turbo_v2_5":
-                    url += f"&language_code={self._settings['language']}"
-                else:
-                    logger.debug(
-                        f"Language code [{self._settings['language']}] not applied. Language codes can only be used with the 'eleven_turbo_v2_5' model."
-                    )
+            # Language can only be used with the 'eleven_turbo_v2_5' model
+            language = language_to_elevenlabs_language(self._settings["language"])
+            if model == "eleven_turbo_v2_5":
+                url += f"&language_code={language}"
+            else:
+                logger.debug(
+                    f"Language code [{language}] not applied. Language codes can only be used with the 'eleven_turbo_v2_5' model."
+                )
 
             self._websocket = await websockets.connect(url)
             self._receive_task = self.get_event_loop().create_task(self._receive_task_handler())
diff --git a/src/pipecat/services/gladia.py b/src/pipecat/services/gladia.py
index 8f270195b..e95329040 100644
--- a/src/pipecat/services/gladia.py
+++ b/src/pipecat/services/gladia.py
@@ -135,7 +135,7 @@ class GladiaSTTService(STTService):
         self._url = url
         self._settings = {
             "sample_rate": params.sample_rate,
-            "language": language_to_gladia_language(params.language) if params.language else "en",
+            "language": params.language if params.language else Language.EN,
             "transcription_hint": params.transcription_hint,
             "endpointing": params.endpointing,
             "prosody": params.prosody,
@@ -169,7 +169,7 @@ class GladiaSTTService(STTService):
             "model_type": "fast",
             "language_behaviour": "manual",
             "sample_rate": self._settings["sample_rate"],
-            "language": self._settings["language"],
+            "language": language_to_gladia_language(self._settings["language"]),
             "transcription_hint": self._settings["transcription_hint"],
             "endpointing": self._settings["endpointing"],
             "prosody": self._settings["prosody"],
diff --git a/src/pipecat/services/google.py b/src/pipecat/services/google.py
index a8187366a..93c2f2d62 100644
--- a/src/pipecat/services/google.py
+++ b/src/pipecat/services/google.py
@@ -40,7 +40,7 @@ try:
 except ModuleNotFoundError as e:
     logger.error(f"Exception: {e}")
     logger.error(
-        "In order to use Google AI, you need to `pip install pipecat-ai[google]`. Also, set `GOOGLE_APPLICATION_CREDENTIALS` environment variable."
+        "In order to use Google AI, you need to `pip install pipecat-ai[google]`. Also, set the environment variable GOOGLE_API_KEY for the GoogleLLMService and GOOGLE_APPLICATION_CREDENTIALS for the GoogleTTSService`."
     )
     raise Exception(f"Missing module: {e}")
 
@@ -261,9 +261,7 @@ class GoogleTTSService(TTSService):
             "rate": params.rate,
             "volume": params.volume,
             "emphasis": params.emphasis,
-            "language": language_to_google_language(params.language)
-            if params.language
-            else "en-US",
+            "language": params.language if params.language else Language.EN,
             "gender": params.gender,
             "google_style": params.google_style,
         }
@@ -298,8 +296,10 @@ class GoogleTTSService(TTSService):
 
         # Voice tag
         voice_attrs = [f"name='{self._voice_id}'"]
-        if self._settings["language"]:
-            voice_attrs.append(f"language='{self._settings['language']}'")
+
+        language = language_to_google_language(self._settings["language"])
+        voice_attrs.append(f"language='{language}'")
+
         if self._settings["gender"]:
             voice_attrs.append(f"gender='{self._settings['gender']}'")
         ssml += f"<voice {' '.join(voice_attrs)}>"
diff --git a/src/pipecat/services/lmnt.py b/src/pipecat/services/lmnt.py
index eea4fd9db..8f7fe6528 100644
--- a/src/pipecat/services/lmnt.py
+++ b/src/pipecat/services/lmnt.py
@@ -82,7 +82,7 @@ class LmntTTSService(TTSService):
                 "encoding": "pcm_s16le",
                 "sample_rate": sample_rate,
             },
-            "language": language_to_lmnt_language(language) if language else "en",
+            "language": language,
         }
 
         self.set_voice(voice_id)
diff --git a/src/pipecat/services/xtts.py b/src/pipecat/services/xtts.py
index d3cea254a..2f842c896 100644
--- a/src/pipecat/services/xtts.py
+++ b/src/pipecat/services/xtts.py
@@ -94,7 +94,7 @@ class XTTSService(TTSService):
         super().__init__(**kwargs)
 
         self._settings = {
-            "language": language_to_xtts_language(language) if language else "en",
+            "language": language,
             "base_url": base_url,
         }
         self.set_voice(voice_id)
@@ -131,9 +131,11 @@ class XTTSService(TTSService):
 
         url = self._settings["base_url"] + "/tts_stream"
 
+        language = language_to_xtts_language(self._settings["language"])
+
         payload = {
             "text": text.replace(".", "").replace("*", ""),
-            "language": self._settings["language"],
+            "language": language,
             "speaker_embedding": embeddings["speaker_embedding"],
             "gpt_cond_latent": embeddings["gpt_cond_latent"],
             "add_wav_header": False,