pipeline: renamed ParallelTask to SyncParallelPipeline

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.

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(
+        tts = CartesiaHttpTTSService(
-            api_key=os.getenv("ELEVENLABS_API_KEY"),
+            api_key=os.getenv("CARTESIA_API_KEY"),
-            voice_id=os.getenv("ELEVENLABS_VOICE_ID"),
+            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
+            SyncParallelPipeline(    # Run pipelines in parallel aggregating the result
-                [month_prepender, tts],                   # Create "Month: sentence" and output audio
+                [month_prepender, tts],  # Create "Month: sentence" and output audio
-                [llm_full_response_aggregator, imagegen]  # Aggregate full LLM response
+                [imagegen]               # Generate image
             ),
-            gated_aggregator,        # Queues everything until an image is available
             transport.output()       # Transport output
         ])
 

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(
+            tts = CartesiaHttpTTSService(
-                api_key=os.getenv("ELEVENLABS_API_KEY"),
+                api_key=os.getenv("CARTESIA_API_KEY"),
-                voice_id=os.getenv("ELEVENLABS_VOICE_ID"))
+                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,
+                llm,                     # LLM
-                aggregator,
+                sentence_aggregator,     # Aggregates LLM output into full sentences
-                description,
+                description,             # Store sentence
-                ParallelPipeline([tts, audio_grabber],
+                SyncParallelPipeline(
-                                 [imagegen, image_grabber])
+                    [tts, audio_grabber],      # Generate and store audio for the given sentence
+                    [imagegen, image_grabber]  # Generate and storeimage for the given sentence
+                )
             ])
 
             task = PipelineTask(pipeline)

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)