Remove LLMThoughtSignatureFrame in favor of using the more generic LLMMessagesAppendFrame

src/pipecat/adapters/services/gemini_adapter.py

@@ -222,10 +222,10 @@ class GeminiLLMAdapter(BaseLLMAdapter[GeminiLLMInvocationParams]):
                 # messages
                 if (
                     isinstance(message.message, dict)
-                    and message.message.get("type") == "fn_call_thought_signature"
+                    and message.message.get("type") == "fn_thought_signature"
                     and (thought_signature := message.message.get("signature"))
                 ):
-                    self._apply_function_call_thought_signature_to_messages(
+                    self._apply_function_thought_signature_to_messages(
                         thought_signature, message.message.get("tool_call_id"), messages
                     )
                     continue
@@ -234,7 +234,7 @@ class GeminiLLMAdapter(BaseLLMAdapter[GeminiLLMInvocationParams]):
                 # signature messages (Gemini 3 Pro)
                 if (
                     isinstance(message.message, dict)
-                    and message.message.get("type") == "thought_signature"
+                    and message.message.get("type") == "non_fn_thought_signature"
                     and (thought_signature := message.message.get("signature"))
                 ):
                     non_fn_thought_signatures.append(thought_signature)
@@ -444,7 +444,7 @@ class GeminiLLMAdapter(BaseLLMAdapter[GeminiLLMInvocationParams]):
             tool_call_id_to_name_mapping=tool_call_id_to_name_mapping,
         )
 
-    def _apply_function_call_thought_signature_to_messages(
+    def _apply_function_thought_signature_to_messages(
         self, thought_signature: bytes, tool_call_id: str, messages: List[Content]
     ) -> None:
         """Apply tool_call_extra metadata to the corresponding function call message.

src/pipecat/frames/frames.py

@@ -654,28 +654,6 @@ class LLMThoughtEndFrame(ControlFrame):
         return f"{self.name}(pts: {pts}, signature: {self.signature})"
 
 
-@dataclass
-class LLMThoughtSignatureFrame(DataFrame):
-    """Frame containing a standalone LLM thought signature (as opposed to a thought signature associated with a thought).
-
-    This is useful for Gemini 3 Pro, which can output a signature at the end of
-    a response.
-
-    Parameters:
-        llm: Identifier of the LLM provider for LLM-specific handling.
-            Needed because the thought signature is appended to context as an
-            `LLMSpecificMessage`.
-        signature: The thought signature data.
-    """
-
-    llm: str
-    signature: Any
-
-    def __str__(self):
-        pts = format_pts(self.pts)
-        return f"{self.name}(pts: {pts}, signature: {self.signature})"
-
-
 @dataclass
 class LLMMessagesFrame(DataFrame):
     """Frame containing LLM messages for chat completion.

src/pipecat/processors/aggregators/llm_response_universal.py

@@ -48,7 +48,6 @@ from pipecat.frames.frames import (
     LLMSetToolChoiceFrame,
     LLMSetToolsFrame,
     LLMThoughtEndFrame,
-    LLMThoughtSignatureFrame,
     LLMThoughtStartFrame,
     LLMThoughtTextFrame,
     SpeechControlParamsFrame,
@@ -644,8 +643,6 @@ class LLMAssistantAggregator(LLMContextAggregator):
             await self._handle_thought_text(frame)
         elif isinstance(frame, LLMThoughtEndFrame):
             await self._handle_thought_end(frame)
-        elif isinstance(frame, LLMThoughtSignatureFrame):
-            await self._handle_standalone_thought_signature(frame)
         elif isinstance(frame, LLMRunFrame):
             await self._handle_llm_run(frame)
         elif isinstance(frame, LLMMessagesAppendFrame):
@@ -896,17 +893,6 @@ class LLMAssistantAggregator(LLMContextAggregator):
             )
         )
 
-    async def _handle_standalone_thought_signature(self, frame: LLMThoughtSignatureFrame):
-        self._context.add_message(
-            LLMSpecificMessage(
-                llm=frame.llm,
-                message={
-                    "type": "thought_signature",
-                    "signature": frame.signature,
-                },
-            )
-        )
-
     def _context_updated_task_finished(self, task: asyncio.Task):
         self._context_updated_tasks.discard(task)
 

src/pipecat/services/google/llm.py

@@ -32,10 +32,10 @@ from pipecat.frames.frames import (
     LLMContextFrame,
     LLMFullResponseEndFrame,
     LLMFullResponseStartFrame,
+    LLMMessagesAppendFrame,
     LLMMessagesFrame,
     LLMTextFrame,
     LLMThoughtEndFrame,
-    LLMThoughtSignatureFrame,
     LLMThoughtStartFrame,
     LLMThoughtTextFrame,
     LLMUpdateSettingsFrame,
@@ -986,13 +986,12 @@ class GoogleLLMService(LLMService):
                                         function_name=function_call.name,
                                         arguments=function_call.args or {},
                                         append_extra_context_messages=[
-                                            LLMSpecificMessage(
-                                                llm=self.get_llm_adapter().id_for_llm_specific_messages,
-                                                message={
-                                                    "type": "fn_call_thought_signature",
+                                            self.get_llm_adapter().create_llm_specific_message(
+                                                {
+                                                    "type": "fn_thought_signature",
                                                     "signature": part.thought_signature,
                                                     "tool_call_id": id,
-                                                },
+                                                }
                                             )
                                         ]
                                         if part.thought_signature
@@ -1011,9 +1010,15 @@ class GoogleLLMService(LLMService):
                             # calls. It will come in the last part of a response.
                             if part.thought_signature and not part.function_call:
                                 await self.push_frame(
-                                    LLMThoughtSignatureFrame(
-                                        llm=self.get_llm_adapter().id_for_llm_specific_messages,
-                                        signature=part.thought_signature,
+                                    LLMMessagesAppendFrame(
+                                        [
+                                            self.get_llm_adapter().create_llm_specific_message(
+                                                {
+                                                    "type": "non_fn_thought_signature",
+                                                    "signature": part.thought_signature,
+                                                }
+                                            )
+                                        ]
                                     )
                                 )