Fix docstrings for 0.0.93 release, fix classmethod placement in RequestHandler

src/pipecat/services/aws/nova_sonic/context.py

@@ -11,36 +11,34 @@ including conversation history management and role-specific message processing.
 
 .. deprecated:: 0.0.91
     AWS Nova Sonic no longer uses types from this module under the hood.
-    It now uses `LLMContext` and `LLMContextAggregatorPair`.
+    It now uses ``LLMContext`` and ``LLMContextAggregatorPair``.
     Using the new patterns should allow you to not need types from this module.
 
-    BEFORE:
-    ```
-    # Setup
-    context = OpenAILLMContext(messages, tools)
-    context_aggregator = llm.create_context_aggregator(context)
+    BEFORE::
 
-    # Context frame type
-    frame: OpenAILLMContextFrame
+        # Setup
+        context = OpenAILLMContext(messages, tools)
+        context_aggregator = llm.create_context_aggregator(context)
 
-    # Context type
-    context: AWSNovaSonicLLMContext
-    # or
-    context: OpenAILLMContext
-    ```
+        # Context frame type
+        frame: OpenAILLMContextFrame
 
-    AFTER:
-    ```
-    # Setup
-    context = LLMContext(messages, tools)
-    context_aggregator = LLMContextAggregatorPair(context)
+        # Context type
+        context: AWSNovaSonicLLMContext
+        # or
+        context: OpenAILLMContext
 
-    # Context frame type
-    frame: LLMContextFrame
+    AFTER::
 
-    # Context type
-    context: LLMContext
-    ```
+        # Setup
+        context = LLMContext(messages, tools)
+        context_aggregator = LLMContextAggregatorPair(context)
+
+        # Context frame type
+        frame: LLMContextFrame
+
+        # Context type
+        context: LLMContext
 """
 
 import warnings

src/pipecat/services/aws/nova_sonic/llm.py

@@ -1163,7 +1163,8 @@ class AWSNovaSonicLLMService(LLMService):
         """Create context aggregator pair for managing conversation context.
 
         NOTE: this method exists only for backward compatibility. New code
-        should instead do:
+        should instead do::
+
             context = LLMContext(...)
             context_aggregator = LLMContextAggregatorPair(context)
 

src/pipecat/services/google/gemini_live/llm.py

@@ -1742,7 +1742,8 @@ class GeminiLiveLLMService(LLMService):
         Constructor keyword arguments for both the user and assistant aggregators can be provided.
 
         NOTE: this method exists only for backward compatibility. New code
-        should instead do:
+        should instead do::
+
             context = LLMContext(...)
             context_aggregator = LLMContextAggregatorPair(context)
 

src/pipecat/services/openai/realtime/context.py

@@ -8,42 +8,40 @@
 
 .. deprecated:: 0.0.92
     OpenAI Realtime no longer uses types from this module under the hood.
-    It now uses `LLMContext` and `LLMContextAggregatorPair`.
+    It now uses ``LLMContext`` and ``LLMContextAggregatorPair``.
     Using the new patterns should allow you to not need types from this module.
 
-    BEFORE:
-    ```
-    # Setup
-    context = OpenAILLMContext(messages, tools)
-    context_aggregator = llm.create_context_aggregator(context)
+    BEFORE::
 
-    # Context aggregator type
-    context_aggregator: OpenAIContextAggregatorPair
+        # Setup
+        context = OpenAILLMContext(messages, tools)
+        context_aggregator = llm.create_context_aggregator(context)
 
-    # Context frame type
-    frame: OpenAILLMContextFrame
+        # Context aggregator type
+        context_aggregator: OpenAIContextAggregatorPair
 
-    # Context type
-    context: OpenAIRealtimeLLMContext
-    # or
-    context: OpenAILLMContext
-    ```
+        # Context frame type
+        frame: OpenAILLMContextFrame
 
-    AFTER:
-    ```
-    # Setup
-    context = LLMContext(messages, tools)
-    context_aggregator = LLMContextAggregatorPair(context)
+        # Context type
+        context: OpenAIRealtimeLLMContext
+        # or
+        context: OpenAILLMContext
 
-    # Context aggregator type
-    context_aggregator: LLMContextAggregatorPair
+    AFTER::
 
-    # Context frame type
-    frame: LLMContextFrame
+        # Setup
+        context = LLMContext(messages, tools)
+        context_aggregator = LLMContextAggregatorPair(context)
 
-    # Context type
-    context: LLMContext
-    ```
+        # Context aggregator type
+        context_aggregator: LLMContextAggregatorPair
+
+        # Context frame type
+        frame: LLMContextFrame
+
+        # Context type
+        context: LLMContext
 """
 
 import warnings

src/pipecat/services/openai/realtime/frames.py

@@ -12,7 +12,7 @@
     It now works more like most LLM services in Pipecat, relying on updates to
     its context, pushed by context aggregators, to update its internal state.
 
-    Listen for `LLMContextFrame`s for context updates.
+    Listen for ``LLMContextFrame`` s for context updates.
 """
 
 import warnings

src/pipecat/services/openai/realtime/llm.py

@@ -845,7 +845,8 @@ class OpenAIRealtimeLLMService(LLMService):
         """Create an instance of OpenAIContextAggregatorPair from an OpenAILLMContext.
 
         NOTE: this method exists only for backward compatibility. New code
-        should instead do:
+        should instead do::
+
             context = LLMContext(...)
             context_aggregator = LLMContextAggregatorPair(context)
 

src/pipecat/transports/smallwebrtc/request_handler.py

@@ -39,13 +39,12 @@ class SmallWebRTCRequest:
     restart_pc: Optional[bool] = None
     request_data: Optional[Any] = None
 
-
-@classmethod
-def from_dict(cls, data: dict):
-    """Accept both snake_case and camelCase for the request_data field."""
-    if "requestData" in data and "request_data" not in data:
-        data["request_data"] = data.pop("requestData")
-    return cls(**data)
+    @classmethod
+    def from_dict(cls, data: dict):
+        """Accept both snake_case and camelCase for the request_data field."""
+        if "requestData" in data and "request_data" not in data:
+            data["request_data"] = data.pop("requestData")
+        return cls(**data)
 
 
 @dataclass