Update AWSNovaSonicLLMService docstrings

src/pipecat/services/aws_nova_sonic/aws.py

@@ -4,6 +4,12 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
+"""AWS Nova Sonic LLM service implementation for Pipecat AI framework.
+
+This module provides a speech-to-speech LLM service using AWS Nova Sonic, which supports
+bidirectional audio streaming, text generation, and function calling capabilities.
+"""
+
 import asyncio
 import base64
 import json
@@ -83,22 +89,37 @@ except ModuleNotFoundError as e:
 
 
 class AWSNovaSonicUnhandledFunctionException(Exception):
+    """Exception raised when the LLM attempts to call an unregistered function."""
+
     pass
 
 
 class ContentType(Enum):
+    """Content types supported by AWS Nova Sonic."""
+
     AUDIO = "AUDIO"
     TEXT = "TEXT"
     TOOL = "TOOL"
 
 
 class TextStage(Enum):
+    """Text generation stages in AWS Nova Sonic responses."""
+
     FINAL = "FINAL"  # what has been said
     SPECULATIVE = "SPECULATIVE"  # what's planned to be said
 
 
 @dataclass
 class CurrentContent:
+    """Represents content currently being received from AWS Nova Sonic.
+
+    Parameters:
+        type: The type of content (audio, text, or tool).
+        role: The role generating the content (user, assistant, etc.).
+        text_stage: The stage of text generation (final or speculative).
+        text_content: The actual text content if applicable.
+    """
+
     type: ContentType
     role: Role
     text_stage: TextStage  # None if not text
@@ -115,6 +136,20 @@ class CurrentContent:
 
 
 class Params(BaseModel):
+    """Configuration parameters for AWS Nova Sonic.
+
+    Attributes:
+        input_sample_rate: Audio input sample rate in Hz.
+        input_sample_size: Audio input sample size in bits.
+        input_channel_count: Number of input audio channels.
+        output_sample_rate: Audio output sample rate in Hz.
+        output_sample_size: Audio output sample size in bits.
+        output_channel_count: Number of output audio channels.
+        max_tokens: Maximum number of tokens to generate.
+        top_p: Nucleus sampling parameter.
+        temperature: Sampling temperature for text generation.
+    """
+
     # Audio input
     input_sample_rate: Optional[int] = Field(default=16000)
     input_sample_size: Optional[int] = Field(default=16)
@@ -132,6 +167,24 @@ class Params(BaseModel):
 
 
 class AWSNovaSonicLLMService(LLMService):
+    """AWS Nova Sonic speech-to-speech LLM service.
+
+    Provides bidirectional audio streaming, real-time transcription, text generation,
+    and function calling capabilities using AWS Nova Sonic model.
+
+    Args:
+        secret_access_key: AWS secret access key for authentication.
+        access_key_id: AWS access key ID for authentication.
+        region: AWS region where the service is hosted.
+        model: Model identifier. Defaults to "amazon.nova-sonic-v1:0".
+        voice_id: Voice ID for speech synthesis. Options: matthew, tiffany, amy.
+        params: Model parameters for audio configuration and inference.
+        system_instruction: System-level instruction for the model.
+        tools: Available tools/functions for the model to use.
+        send_transcription_frames: Whether to emit transcription frames.
+        **kwargs: Additional arguments passed to the parent LLMService.
+    """
+
     # Override the default adapter to use the AWSNovaSonicLLMAdapter one
     adapter_class = AWSNovaSonicLLMAdapter
 
@@ -188,16 +241,31 @@ class AWSNovaSonicLLMService(LLMService):
     #
 
     async def start(self, frame: StartFrame):
+        """Start the service and initiate connection to AWS Nova Sonic.
+
+        Args:
+            frame: The start frame triggering service initialization.
+        """
         await super().start(frame)
         self._wants_connection = True
         await self._start_connecting()
 
     async def stop(self, frame: EndFrame):
+        """Stop the service and close connections.
+
+        Args:
+            frame: The end frame triggering service shutdown.
+        """
         await super().stop(frame)
         self._wants_connection = False
         await self._disconnect()
 
     async def cancel(self, frame: CancelFrame):
+        """Cancel the service and close connections.
+
+        Args:
+            frame: The cancel frame triggering service cancellation.
+        """
         await super().cancel(frame)
         self._wants_connection = False
         await self._disconnect()
@@ -207,6 +275,11 @@ class AWSNovaSonicLLMService(LLMService):
     #
 
     async def reset_conversation(self):
+        """Reset the conversation state while preserving context.
+
+        Handles bot stopped speaking event, disconnects from the service,
+        and reconnects with the preserved context.
+        """
         logger.debug("Resetting conversation")
         await self._handle_bot_stopped_speaking(delay_to_catch_trailing_assistant_text=False)
 
@@ -222,6 +295,12 @@ class AWSNovaSonicLLMService(LLMService):
     #
 
     async def process_frame(self, frame: Frame, direction: FrameDirection):
+        """Process incoming frames and handle service-specific logic.
+
+        Args:
+            frame: The frame to process.
+            direction: The direction the frame is traveling.
+        """
         await super().process_frame(frame, direction)
 
         if isinstance(frame, OpenAILLMContextFrame):
@@ -960,6 +1039,16 @@ class AWSNovaSonicLLMService(LLMService):
         user_params: LLMUserAggregatorParams = LLMUserAggregatorParams(),
         assistant_params: LLMAssistantAggregatorParams = LLMAssistantAggregatorParams(),
     ) -> AWSNovaSonicContextAggregatorPair:
+        """Create context aggregator pair for managing conversation context.
+
+        Args:
+            context: The OpenAI LLM context to upgrade.
+            user_params: Parameters for the user context aggregator.
+            assistant_params: Parameters for the assistant context aggregator.
+
+        Returns:
+            A pair of user and assistant context aggregators.
+        """
         context.set_llm_adapter(self.get_llm_adapter())
 
         user = AWSNovaSonicUserContextAggregator(context=context, params=user_params)
@@ -978,6 +1067,14 @@ class AWSNovaSonicLLMService(LLMService):
     )
 
     async def trigger_assistant_response(self):
+        """Trigger an assistant response by sending audio cue.
+
+        Sends a pre-recorded "ready" audio trigger to prompt the assistant
+        to start speaking. This is useful for controlling conversation flow.
+
+        Returns:
+            False if already triggering a response, True otherwise.
+        """
         if self._triggering_assistant_response:
             return False
 

src/pipecat/services/aws_nova_sonic/context.py

@@ -4,6 +4,12 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
+"""Context management for AWS Nova Sonic LLM service.
+
+This module provides specialized context aggregators and message handling for AWS Nova Sonic,
+including conversation history management and role-specific message processing.
+"""
+
 import copy
 from dataclasses import dataclass, field
 from enum import Enum
@@ -35,6 +41,8 @@ from pipecat.services.openai.llm import (
 
 
 class Role(Enum):
+    """Roles supported in AWS Nova Sonic conversations."""
+
     SYSTEM = "SYSTEM"
     USER = "USER"
     ASSISTANT = "ASSISTANT"
@@ -43,17 +51,42 @@ class Role(Enum):
 
 @dataclass
 class AWSNovaSonicConversationHistoryMessage:
+    """A single message in AWS Nova Sonic conversation history.
+
+    Parameters:
+        role: The role of the message sender (USER or ASSISTANT only).
+        text: The text content of the message.
+    """
+
     role: Role  # only USER and ASSISTANT
     text: str
 
 
 @dataclass
 class AWSNovaSonicConversationHistory:
+    """Complete conversation history for AWS Nova Sonic initialization.
+
+    Parameters:
+        system_instruction: System-level instruction for the conversation.
+        messages: List of conversation messages between user and assistant.
+    """
+
     system_instruction: str = None
     messages: list[AWSNovaSonicConversationHistoryMessage] = field(default_factory=list)
 
 
 class AWSNovaSonicLLMContext(OpenAILLMContext):
+    """Specialized LLM context for AWS Nova Sonic service.
+
+    Extends OpenAI context with Nova Sonic-specific message handling,
+    conversation history management, and text buffering capabilities.
+
+    Args:
+        messages: Initial messages for the context.
+        tools: Available tools for the context.
+        **kwargs: Additional arguments passed to parent class.
+    """
+
     def __init__(self, messages=None, tools=None, **kwargs):
         super().__init__(messages=messages, tools=tools, **kwargs)
         self.__setup_local()
@@ -67,6 +100,15 @@ class AWSNovaSonicLLMContext(OpenAILLMContext):
     def upgrade_to_nova_sonic(
         obj: OpenAILLMContext, system_instruction: str
     ) -> "AWSNovaSonicLLMContext":
+        """Upgrade an OpenAI context to AWS Nova Sonic context.
+
+        Args:
+            obj: The OpenAI context to upgrade.
+            system_instruction: System instruction for the context.
+
+        Returns:
+            The upgraded AWS Nova Sonic context.
+        """
         if isinstance(obj, OpenAILLMContext) and not isinstance(obj, AWSNovaSonicLLMContext):
             obj.__class__ = AWSNovaSonicLLMContext
             obj.__setup_local(system_instruction)
@@ -74,6 +116,14 @@ class AWSNovaSonicLLMContext(OpenAILLMContext):
 
     # NOTE: this method has the side-effect of updating _system_instruction from messages
     def get_messages_for_initializing_history(self) -> AWSNovaSonicConversationHistory:
+        """Get conversation history for initializing AWS Nova Sonic session.
+
+        Processes stored messages and extracts system instruction and conversation
+        history in the format expected by AWS Nova Sonic.
+
+        Returns:
+            Formatted conversation history with system instruction and messages.
+        """
         history = AWSNovaSonicConversationHistory(system_instruction=self._system_instruction)
 
         # Bail if there are no messages
@@ -103,6 +153,11 @@ class AWSNovaSonicLLMContext(OpenAILLMContext):
         return history
 
     def get_messages_for_persistent_storage(self):
+        """Get messages formatted for persistent storage.
+
+        Returns:
+            List of messages including system instruction if present.
+        """
         messages = super().get_messages_for_persistent_storage()
         # If we have a system instruction and messages doesn't already contain it, add it
         if self._system_instruction and not (messages and messages[0].get("role") == "system"):
@@ -110,6 +165,14 @@ class AWSNovaSonicLLMContext(OpenAILLMContext):
         return messages
 
     def from_standard_message(self, message) -> AWSNovaSonicConversationHistoryMessage:
+        """Convert standard message format to Nova Sonic format.
+
+        Args:
+            message: Standard message dictionary to convert.
+
+        Returns:
+            Nova Sonic conversation history message, or None if not convertible.
+        """
         role = message.get("role")
         if message.get("role") == "user" or message.get("role") == "assistant":
             content = message.get("content")
@@ -131,10 +194,20 @@ class AWSNovaSonicLLMContext(OpenAILLMContext):
         # Sonic conversation history
 
     def buffer_user_text(self, text):
+        """Buffer user text for later flushing to context.
+
+        Args:
+            text: User text to buffer.
+        """
         self._user_text += f" {text}" if self._user_text else text
         # logger.debug(f"User text buffered: {self._user_text}")
 
     def flush_aggregated_user_text(self) -> str:
+        """Flush buffered user text to context as a complete message.
+
+        Returns:
+            The flushed user text, or empty string if no text was buffered.
+        """
         if not self._user_text:
             return ""
         user_text = self._user_text
@@ -148,10 +221,16 @@ class AWSNovaSonicLLMContext(OpenAILLMContext):
         return user_text
 
     def buffer_assistant_text(self, text):
+        """Buffer assistant text for later flushing to context.
+
+        Args:
+            text: Assistant text to buffer.
+        """
         self._assistant_text += text
         # logger.debug(f"Assistant text buffered: {self._assistant_text}")
 
     def flush_aggregated_assistant_text(self):
+        """Flush buffered assistant text to context as a complete message."""
         if not self._assistant_text:
             return
         message = {
@@ -165,13 +244,31 @@ class AWSNovaSonicLLMContext(OpenAILLMContext):
 
 @dataclass
 class AWSNovaSonicMessagesUpdateFrame(DataFrame):
+    """Frame containing updated AWS Nova Sonic context.
+
+    Parameters:
+        context: The updated AWS Nova Sonic LLM context.
+    """
+
     context: AWSNovaSonicLLMContext
 
 
 class AWSNovaSonicUserContextAggregator(OpenAIUserContextAggregator):
+    """Context aggregator for user messages in AWS Nova Sonic conversations.
+
+    Extends the OpenAI user context aggregator to emit Nova Sonic-specific
+    context update frames.
+    """
+
     async def process_frame(
         self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM
     ):
+        """Process frames and emit Nova Sonic-specific context updates.
+
+        Args:
+            frame: The frame to process.
+            direction: The direction the frame is traveling.
+        """
         await super().process_frame(frame, direction)
 
         # Parent does not push LLMMessagesUpdateFrame
@@ -180,7 +277,19 @@ class AWSNovaSonicUserContextAggregator(OpenAIUserContextAggregator):
 
 
 class AWSNovaSonicAssistantContextAggregator(OpenAIAssistantContextAggregator):
+    """Context aggregator for assistant messages in AWS Nova Sonic conversations.
+
+    Provides specialized handling for assistant responses and function calls
+    in AWS Nova Sonic context, with custom frame processing logic.
+    """
+
     async def process_frame(self, frame: Frame, direction: FrameDirection):
+        """Process frames with Nova Sonic-specific logic.
+
+        Args:
+            frame: The frame to process.
+            direction: The direction the frame is traveling.
+        """
         # HACK: For now, disable the context aggregator by making it just pass through all frames
         # that the parent handles (except the function call stuff, which we still need).
         # For an explanation of this hack, see
@@ -205,6 +314,11 @@ class AWSNovaSonicAssistantContextAggregator(OpenAIAssistantContextAggregator):
             await super().process_frame(frame, direction)
 
     async def handle_function_call_result(self, frame: FunctionCallResultFrame):
+        """Handle function call results for AWS Nova Sonic.
+
+        Args:
+            frame: The function call result frame to handle.
+        """
         await super().handle_function_call_result(frame)
 
         # The standard function callback code path pushes the FunctionCallResultFrame from the LLM
@@ -217,11 +331,28 @@ class AWSNovaSonicAssistantContextAggregator(OpenAIAssistantContextAggregator):
 
 @dataclass
 class AWSNovaSonicContextAggregatorPair:
+    """Pair of user and assistant context aggregators for AWS Nova Sonic.
+
+    Parameters:
+        _user: The user context aggregator.
+        _assistant: The assistant context aggregator.
+    """
+
     _user: AWSNovaSonicUserContextAggregator
     _assistant: AWSNovaSonicAssistantContextAggregator
 
     def user(self) -> AWSNovaSonicUserContextAggregator:
+        """Get the user context aggregator.
+
+        Returns:
+            The user context aggregator instance.
+        """
         return self._user
 
     def assistant(self) -> AWSNovaSonicAssistantContextAggregator:
+        """Get the assistant context aggregator.
+
+        Returns:
+            The assistant context aggregator instance.
+        """
         return self._assistant

src/pipecat/services/aws_nova_sonic/frames.py

@@ -4,6 +4,8 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
+"""Custom frames for AWS Nova Sonic LLM service."""
+
 from dataclasses import dataclass
 
 from pipecat.frames.frames import DataFrame, FunctionCallResultFrame
@@ -11,4 +13,13 @@ from pipecat.frames.frames import DataFrame, FunctionCallResultFrame
 
 @dataclass
 class AWSNovaSonicFunctionCallResultFrame(DataFrame):
+    """Frame containing function call result for AWS Nova Sonic processing.
+
+    This frame wraps a standard function call result frame to enable
+    AWS Nova Sonic-specific handling and context updates.
+
+    Parameters:
+        result_frame: The underlying function call result frame.
+    """
+
     result_frame: FunctionCallResultFrame