services: add missing * keyword separator

src/pipecat/processors/async_frame_processor.py

@@ -14,10 +14,11 @@ class AsyncFrameProcessor(FrameProcessor):
 
     def __init__(
             self,
+            *,
             name: str | None = None,
             loop: asyncio.AbstractEventLoop | None = None,
             **kwargs):
-        super().__init__(name, loop, **kwargs)
+        super().__init__(name=name, loop=loop, **kwargs)
 
         self._create_push_task()
 

src/pipecat/processors/frame_processor.py

@@ -66,6 +66,7 @@ class FrameProcessor:
 
     def __init__(
             self,
+            *,
             name: str | None = None,
             loop: asyncio.AbstractEventLoop | None = None,
             **kwargs):

src/pipecat/services/ai_services.py

@@ -118,7 +118,7 @@ class LLMService(AIService):
 
 
 class TTSService(AIService):
-    def __init__(self, aggregate_sentences: bool = True, **kwargs):
+    def __init__(self, *, aggregate_sentences: bool = True, **kwargs):
         super().__init__(**kwargs)
         self._aggregate_sentences: bool = aggregate_sentences
         self._current_sentence: str = ""
@@ -180,6 +180,7 @@ class STTService(AIService):
     """STTService is a base class for speech-to-text services."""
 
     def __init__(self,
+                 *,
                  min_volume: float = 0.6,
                  max_silence_secs: float = 0.3,
                  max_buffer_secs: float = 1.5,

src/pipecat/services/anthropic.py

@@ -41,6 +41,7 @@ class AnthropicLLMService(LLMService):
 
     def __init__(
             self,
+            *,
             api_key: str,
             model: str = "claude-3-opus-20240229",
             max_tokens: int = 1024):

src/pipecat/services/deepgram.py

@@ -5,7 +5,6 @@
 #
 
 import aiohttp
-import asyncio
 import time
 
 from typing import AsyncGenerator
@@ -18,11 +17,10 @@ from pipecat.frames.frames import (
     Frame,
     InterimTranscriptionFrame,
     StartFrame,
-    StartInterruptionFrame,
     SystemFrame,
     TranscriptionFrame)
 from pipecat.processors.frame_processor import FrameDirection
-from pipecat.services.ai_services import AIService, AsyncAIService, TTSService
+from pipecat.services.ai_services import AsyncAIService, TTSService
 
 from loguru import logger
 
@@ -96,6 +94,7 @@ class DeepgramTTSService(TTSService):
 
 class DeepgramSTTService(AsyncAIService):
     def __init__(self,
+                 *,
                  api_key: str,
                  url: str = "",
                  live_options: LiveOptions = LiveOptions(

src/pipecat/services/fireworks.py

@@ -19,6 +19,7 @@ except ModuleNotFoundError as e:
 
 class FireworksLLMService(BaseOpenAILLMService):
     def __init__(self,
+                 *,
                  model: str = "accounts/fireworks/models/firefunction-v1",
                  base_url: str = "https://api.fireworks.ai/inference/v1"):
         super().__init__(model, base_url)

src/pipecat/services/google.py

@@ -42,7 +42,7 @@ class GoogleLLMService(LLMService):
     franca for all LLM services, so that it is easy to switch between different LLMs.
     """
 
-    def __init__(self, api_key: str, model: str = "gemini-1.5-flash-latest", **kwargs):
+    def __init__(self, *, api_key: str, model: str = "gemini-1.5-flash-latest", **kwargs):
         super().__init__(**kwargs)
         gai.configure(api_key=api_key)
         self._client = gai.GenerativeModel(model)

src/pipecat/services/moondream.py

@@ -46,6 +46,7 @@ def detect_device():
 class MoondreamService(VisionService):
     def __init__(
         self,
+            *,
         model="vikhyatk/moondream2",
         revision="2024-04-02",
         use_cpu=False

src/pipecat/services/ollama.py

@@ -9,5 +9,5 @@ from pipecat.services.openai import BaseOpenAILLMService
 
 class OLLamaLLMService(BaseOpenAILLMService):
 
-    def __init__(self, model: str = "llama2", base_url: str = "http://localhost:11434/v1"):
+    def __init__(self, *, model: str = "llama2", base_url: str = "http://localhost:11434/v1"):
         super().__init__(model=model, base_url=base_url, api_key="ollama")

src/pipecat/services/openai.py

@@ -67,7 +67,7 @@ class BaseOpenAILLMService(LLMService):
     calls from the LLM.
     """
 
-    def __init__(self, model: str, api_key=None, base_url=None, **kwargs):
+    def __init__(self, *, model: str, api_key=None, base_url=None, **kwargs):
         super().__init__(**kwargs)
         self._model: str = model
         self._client = self.create_client(api_key=api_key, base_url=base_url, **kwargs)
@@ -236,8 +236,8 @@ class BaseOpenAILLMService(LLMService):
 
 class OpenAILLMService(BaseOpenAILLMService):
 
-    def __init__(self, model="gpt-4o", **kwargs):
-        super().__init__(model, **kwargs)
+    def __init__(self, *, model: str = "gpt-4o", **kwargs):
+        super().__init__(model=model, **kwargs)
 
 
 class OpenAIImageGenService(ImageGenService):

src/pipecat/services/openpipe.py

@@ -25,6 +25,7 @@ class OpenPipeLLMService(BaseOpenAILLMService):
 
     def __init__(
             self,
+            *,
             model: str = "gpt-4o",
             api_key: str | None = None,
             base_url: str | None = None,
@@ -33,9 +34,9 @@ class OpenPipeLLMService(BaseOpenAILLMService):
             tags: Dict[str, str] | None = None,
             **kwargs):
         super().__init__(
-            model,
-            api_key,
-            base_url,
+            model=model,
+            api_key=api_key,
+            base_url=base_url,
             openpipe_api_key=openpipe_api_key,
             openpipe_base_url=openpipe_base_url,
             **kwargs)

src/pipecat/services/whisper.py

@@ -42,7 +42,8 @@ class WhisperSTTService(STTService):
     """Class to transcribe audio with a locally-downloaded Whisper model"""
 
     def __init__(self,
-                 model: Model = Model.DISTIL_MEDIUM_EN,
+                 *,
+                 model: str | Model = Model.DISTIL_MEDIUM_EN,
                  device: str = "auto",
                  compute_type: str = "default",
                  no_speech_prob: float = 0.4,
@@ -51,7 +52,7 @@ class WhisperSTTService(STTService):
         super().__init__(**kwargs)
         self._device: str = device
         self._compute_type = compute_type
-        self._model_name: Model = model
+        self._model_name: str | Model = model
         self._no_speech_prob = no_speech_prob
         self._model: WhisperModel | None = None
         self._load()
@@ -64,7 +65,7 @@ class WhisperSTTService(STTService):
         this model is being run, it will take time to download."""
         logger.debug("Loading Whisper model...")
         self._model = WhisperModel(
-            self._model_name.value,
+            self._model_name.value if isinstance(self._model_name, Enum) else self._model_name,
             device=self._device,
             compute_type=self._compute_type)
         logger.debug("Loaded Whisper model")