frames: add LLMTextFrame and TTSTextFrame

This is to distinguish what type of service has generated the TextFrames.

src/pipecat/frames/frames.py

@@ -177,6 +177,20 @@ class TextFrame(DataFrame):
         return f"{self.name}(pts: {pts}, text: [{self.text}])"
 
 
+@dataclass
+class LLMTextFrame(TextFrame):
+    """A text frame generated by LLM services."""
+
+    pass
+
+
+@dataclass
+class TTSTextFrame(TextFrame):
+    """A text frame generated by TTS services."""
+
+    pass
+
+
 @dataclass
 class TranscriptionFrame(TextFrame):
     """A text frame with transcription-specific data. Will be placed in the

src/pipecat/processors/frameworks/rtvi.py

@@ -34,14 +34,15 @@ from pipecat.frames.frames import (
     InterimTranscriptionFrame,
     LLMFullResponseEndFrame,
     LLMFullResponseStartFrame,
+    LLMTextFrame,
     MetricsFrame,
     StartFrame,
     SystemFrame,
-    TextFrame,
     TranscriptionFrame,
     TransportMessageUrgentFrame,
     TTSStartedFrame,
     TTSStoppedFrame,
+    TTSTextFrame,
     UserStartedSpeakingFrame,
     UserStoppedSpeakingFrame,
 )
@@ -479,7 +480,7 @@ class RTVIBotTranscriptionProcessor(RTVIFrameProcessor):
 
         if isinstance(frame, UserStartedSpeakingFrame):
             await self._push_aggregation()
-        elif isinstance(frame, TextFrame):
+        elif isinstance(frame, LLMTextFrame):
             self._aggregation += frame.text
             if match_endofsentence(self._aggregation):
                 await self._push_aggregation()
@@ -504,7 +505,7 @@ class RTVIBotLLMProcessor(RTVIFrameProcessor):
             await self._push_transport_message_urgent(RTVIBotLLMStartedMessage())
         elif isinstance(frame, LLMFullResponseEndFrame):
             await self._push_transport_message_urgent(RTVIBotLLMStoppedMessage())
-        elif type(frame) is TextFrame:
+        elif isinstance(frame, LLMTextFrame):
             message = RTVIBotLLMTextMessage(data=RTVITextMessageData(text=frame.text))
             await self._push_transport_message_urgent(message)
 
@@ -522,7 +523,7 @@ class RTVIBotTTSProcessor(RTVIFrameProcessor):
             await self._push_transport_message_urgent(RTVIBotTTSStartedMessage())
         elif isinstance(frame, TTSStoppedFrame):
             await self._push_transport_message_urgent(RTVIBotTTSStoppedMessage())
-        elif type(frame) is TextFrame:
+        elif isinstance(frame, TTSTextFrame):
             message = RTVIBotTTSTextMessage(data=RTVITextMessageData(text=frame.text))
             await self._push_transport_message_urgent(message)
 

src/pipecat/services/ai_services.py

@@ -30,6 +30,7 @@ from pipecat.frames.frames import (
     TTSSpeakFrame,
     TTSStartedFrame,
     TTSStoppedFrame,
+    TTSTextFrame,
     TTSUpdateSettingsFrame,
     UserImageRequestFrame,
     VisionImageRawFrame,
@@ -358,7 +359,7 @@ class TTSService(AIService):
         if self._push_text_frames:
             # We send the original text after the audio. This way, if we are
             # interrupted, the text is not added to the assistant context.
-            await self.push_frame(TextFrame(text))
+            await self.push_frame(TTSTextFrame(text))
 
     async def _stop_frame_handler(self):
         try:
@@ -437,7 +438,7 @@ class WordTTSService(TTSService):
                     frame = TTSStoppedFrame()
                     frame.pts = last_pts
                 else:
-                    frame = TextFrame(word)
+                    frame = TTSTextFrame(word)
                     frame.pts = self._initial_word_timestamp + timestamp
                 if frame:
                     last_pts = frame.pts

src/pipecat/services/anthropic.py

@@ -26,10 +26,10 @@ from pipecat.frames.frames import (
     LLMFullResponseEndFrame,
     LLMFullResponseStartFrame,
     LLMMessagesFrame,
+    LLMTextFrame,
     LLMUpdateSettingsFrame,
     OpenAILLMContextAssistantTimestampFrame,
     StartInterruptionFrame,
-    TextFrame,
     UserImageRawFrame,
     UserImageRequestFrame,
     VisionImageRawFrame,
@@ -191,7 +191,7 @@ class AnthropicLLMService(LLMService):
 
                 if event.type == "content_block_delta":
                     if hasattr(event.delta, "text"):
-                        await self.push_frame(TextFrame(event.delta.text))
+                        await self.push_frame(LLMTextFrame(event.delta.text))
                         completion_tokens_estimate += self._estimate_tokens(event.delta.text)
                     elif hasattr(event.delta, "partial_json") and tool_use_block:
                         json_accumulator += event.delta.partial_json

src/pipecat/services/gemini_multimodal_live/gemini.py

@@ -28,10 +28,10 @@ from pipecat.frames.frames import (
     LLMFullResponseStartFrame,
     LLMMessagesAppendFrame,
     LLMSetToolsFrame,
+    LLMTextFrame,
     LLMUpdateSettingsFrame,
     StartFrame,
     StartInterruptionFrame,
-    TextFrame,
     TranscriptionFrame,
     TTSAudioRawFrame,
     TTSStartedFrame,
@@ -295,7 +295,7 @@ class GeminiMultimodalLiveLLMService(LLMService):
         # definitely feels like a hack. Need to revisit when the API evolves.
         # context.add_message({"role": "assistant", "content": [{"type": "text", "text": text}]})
         await self.push_frame(LLMFullResponseStartFrame())
-        await self.push_frame(TextFrame(text=text))
+        await self.push_frame(LLMTextFrame(text=text))
         await self.push_frame(LLMFullResponseEndFrame())
 
     async def _transcribe_audio(self, audio, context):
@@ -628,7 +628,7 @@ class GeminiMultimodalLiveLLMService(LLMService):
                 await self.push_frame(LLMFullResponseStartFrame())
 
             self._bot_text_buffer += text
-            await self.push_frame(TextFrame(text=text))
+            await self.push_frame(LLMTextFrame(text=text))
 
         inline_data = part.inlineData
         if not inline_data:

src/pipecat/services/google.py

@@ -23,9 +23,9 @@ from pipecat.frames.frames import (
     LLMFullResponseEndFrame,
     LLMFullResponseStartFrame,
     LLMMessagesFrame,
+    LLMTextFrame,
     LLMUpdateSettingsFrame,
     OpenAILLMContextAssistantTimestampFrame,
-    TextFrame,
     TTSAudioRawFrame,
     TTSStartedFrame,
     TTSStoppedFrame,
@@ -698,7 +698,7 @@ class GoogleLLMService(LLMService):
                 try:
                     for c in chunk.parts:
                         if c.text:
-                            await self.push_frame(TextFrame(c.text))
+                            await self.push_frame(LLMTextFrame(c.text))
                         elif c.function_call:
                             logger.debug(f"!!! Function call: {c.function_call}")
                             args = type(c.function_call).to_dict(c.function_call).get("args", {})

src/pipecat/services/openai.py

@@ -25,10 +25,10 @@ from pipecat.frames.frames import (
     LLMFullResponseEndFrame,
     LLMFullResponseStartFrame,
     LLMMessagesFrame,
+    LLMTextFrame,
     LLMUpdateSettingsFrame,
     OpenAILLMContextAssistantTimestampFrame,
     StartInterruptionFrame,
-    TextFrame,
     TTSAudioRawFrame,
     TTSStartedFrame,
     TTSStoppedFrame,
@@ -258,7 +258,7 @@ class BaseOpenAILLMService(LLMService):
                     # Keep iterating through the response to collect all the argument fragments
                     arguments += tool_call.function.arguments
             elif chunk.choices[0].delta.content:
-                await self.push_frame(TextFrame(chunk.choices[0].delta.content))
+                await self.push_frame(LLMTextFrame(chunk.choices[0].delta.content))
 
         # if we got a function name and arguments, check to see if it's a function with
         # a registered handler. If so, run the registered callback, save the result to

src/pipecat/services/openai_realtime_beta/openai.py

@@ -24,11 +24,11 @@ from pipecat.frames.frames import (
     LLMFullResponseStartFrame,
     LLMMessagesAppendFrame,
     LLMSetToolsFrame,
+    LLMTextFrame,
     LLMUpdateSettingsFrame,
     StartFrame,
     StartInterruptionFrame,
     StopInterruptionFrame,
-    TextFrame,
     TranscriptionFrame,
     TTSAudioRawFrame,
     TTSStartedFrame,
@@ -458,7 +458,7 @@ class OpenAIRealtimeBetaLLMService(LLMService):
 
     async def _handle_evt_audio_transcript_delta(self, evt):
         if evt.delta:
-            await self.push_frame(TextFrame(evt.delta))
+            await self.push_frame(LLMTextFrame(evt.delta))
 
     async def _handle_evt_speech_started(self, evt):
         await self._truncate_current_audio_response()