Code review feedback

src/pipecat/services/ai_services.py

@@ -248,25 +248,7 @@ class TTSService(AIService):
             # interrupted, the text is not added to the assistant context.
             await self.push_frame(TextFrame(text))
 
-    async def process_frame(self, frame: Frame, direction: FrameDirection):
+    async def _update_tts_settings(self, frame: TTSUpdateSettingsFrame):
-        await super().process_frame(frame, direction)
-
-        if isinstance(frame, TextFrame):
-            await self._process_text_frame(frame)
-        elif isinstance(frame, StartInterruptionFrame):
-            await self._handle_interruption(frame, direction)
-        elif isinstance(frame, LLMFullResponseEndFrame) or isinstance(frame, EndFrame):
-            sentence = self._current_sentence
-            self._current_sentence = ""
-            await self._push_tts_frames(sentence)
-            if isinstance(frame, LLMFullResponseEndFrame):
-                if self._push_text_frames:
-                    await self.push_frame(frame, direction)
-            else:
-                await self.push_frame(frame, direction)
-        elif isinstance(frame, TTSSpeakFrame):
-            await self._push_tts_frames(frame.text)
-        elif isinstance(frame, TTSUpdateSettingsFrame):
         if frame.model is not None:
             await self.set_model(frame.model)
         if frame.voice is not None:
@@ -293,6 +275,27 @@ class TTSService(AIService):
             await self.set_style_degree(frame.style_degree)
         if frame.role is not None:
             await self.set_role(frame.role)
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        if isinstance(frame, TextFrame):
+            await self._process_text_frame(frame)
+        elif isinstance(frame, StartInterruptionFrame):
+            await self._handle_interruption(frame, direction)
+        elif isinstance(frame, LLMFullResponseEndFrame) or isinstance(frame, EndFrame):
+            sentence = self._current_sentence
+            self._current_sentence = ""
+            await self._push_tts_frames(sentence)
+            if isinstance(frame, LLMFullResponseEndFrame):
+                if self._push_text_frames:
+                    await self.push_frame(frame, direction)
+            else:
+                await self.push_frame(frame, direction)
+        elif isinstance(frame, TTSSpeakFrame):
+            await self._push_tts_frames(frame.text)
+        elif isinstance(frame, TTSUpdateSettingsFrame):
+            await self._update_tts_settings(frame)
         else:
             await self.push_frame(frame, direction)
 
@@ -454,6 +457,12 @@ class STTService(AIService):
         """Returns transcript as a string"""
         pass
 
+    async def _update_stt_settings(self, frame: STTUpdateSettingsFrame):
+        if frame.model is not None:
+            await self.set_model(frame.model)
+        if frame.language is not None:
+            await self.set_language(frame.language)
+
     async def process_audio_frame(self, frame: AudioRawFrame):
         await self.process_generator(self.run_stt(frame.audio))
 
@@ -466,10 +475,7 @@ class STTService(AIService):
             # push a TextFrame. We don't really want to push audio frames down.
             await self.process_audio_frame(frame)
         elif isinstance(frame, STTUpdateSettingsFrame):
-            if frame.model is not None:
+            await self._update_stt_settings(frame)
-                await self.set_model(frame.model)
-            if frame.language is not None:
-                await self.set_language(frame.language)
         else:
             await self.push_frame(frame, direction)
 

src/pipecat/services/anthropic.py

@@ -279,6 +279,21 @@ class AnthropicLLMService(LLMService):
                 cache_read_input_tokens=cache_read_input_tokens,
             )
 
+    async def _update_settings(self, frame: LLMUpdateSettingsFrame):
+        if frame.model is not None:
+            logger.debug(f"Switching LLM model to: [{frame.model}]")
+            self.set_model_name(frame.model)
+        if frame.max_tokens is not None:
+            await self.set_max_tokens(frame.max_tokens)
+        if frame.temperature is not None:
+            await self.set_temperature(frame.temperature)
+        if frame.top_k is not None:
+            await self.set_top_k(frame.top_k)
+        if frame.top_p is not None:
+            await self.set_top_p(frame.top_p)
+        if frame.extra:
+            await self.set_extra(frame.extra)
+
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
@@ -294,19 +309,7 @@ class AnthropicLLMService(LLMService):
             # to the context.
             context = AnthropicLLMContext.from_image_frame(frame)
         elif isinstance(frame, LLMUpdateSettingsFrame):
-            if frame.model is not None:
+            await self._update_settings(frame)
-                logger.debug(f"Switching LLM model to: [{frame.model}]")
-                self.set_model_name(frame.model)
-            if frame.max_tokens is not None:
-                await self.set_max_tokens(frame.max_tokens)
-            if frame.temperature is not None:
-                await self.set_temperature(frame.temperature)
-            if frame.top_k is not None:
-                await self.set_top_k(frame.top_k)
-            if frame.top_p is not None:
-                await self.set_top_p(frame.top_p)
-            if frame.extra:
-                await self.set_extra(frame.extra)
         elif isinstance(frame, LLMEnablePromptCachingFrame):
             logger.debug(f"Setting enable prompt caching to: [{frame.enable}]")
             self._enable_prompt_caching_beta = frame.enable

src/pipecat/services/openai.py

@@ -273,17 +273,7 @@ class BaseOpenAILLMService(LLMService):
             arguments=arguments,
         )
 
-    async def process_frame(self, frame: Frame, direction: FrameDirection):
+    async def _update_settings(self, frame: LLMUpdateSettingsFrame):
-        await super().process_frame(frame, direction)
-
-        context = None
-        if isinstance(frame, OpenAILLMContextFrame):
-            context: OpenAILLMContext = frame.context
-        elif isinstance(frame, LLMMessagesFrame):
-            context = OpenAILLMContext.from_messages(frame.messages)
-        elif isinstance(frame, VisionImageRawFrame):
-            context = OpenAILLMContext.from_image_frame(frame)
-        elif isinstance(frame, LLMUpdateSettingsFrame):
         if frame.model is not None:
             logger.debug(f"Switching LLM model to: [{frame.model}]")
             self.set_model_name(frame.model)
@@ -299,6 +289,19 @@ class BaseOpenAILLMService(LLMService):
             await self.set_top_p(frame.top_p)
         if frame.extra:
             await self.set_extra(frame.extra)
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        context = None
+        if isinstance(frame, OpenAILLMContextFrame):
+            context: OpenAILLMContext = frame.context
+        elif isinstance(frame, LLMMessagesFrame):
+            context = OpenAILLMContext.from_messages(frame.messages)
+        elif isinstance(frame, VisionImageRawFrame):
+            context = OpenAILLMContext.from_image_frame(frame)
+        elif isinstance(frame, LLMUpdateSettingsFrame):
+            await self._update_settings(frame)
         else:
             await self.push_frame(frame, direction)
 

src/pipecat/services/together.py

@@ -128,6 +128,25 @@ class TogetherLLMService(LLMService):
         logger.debug(f"Switching LLM extra to: [{extra}]")
         self._extra = extra
 
+    async def _update_settings(self, frame: LLMUpdateSettingsFrame):
+        if frame.model is not None:
+            logger.debug(f"Switching LLM model to: [{frame.model}]")
+            self.set_model_name(frame.model)
+        if frame.frequency_penalty is not None:
+            await self.set_frequency_penalty(frame.frequency_penalty)
+        if frame.max_tokens is not None:
+            await self.set_max_tokens(frame.max_tokens)
+        if frame.presence_penalty is not None:
+            await self.set_presence_penalty(frame.presence_penalty)
+        if frame.temperature is not None:
+            await self.set_temperature(frame.temperature)
+        if frame.top_k is not None:
+            await self.set_top_k(frame.top_k)
+        if frame.top_p is not None:
+            await self.set_top_p(frame.top_p)
+        if frame.extra:
+            await self.set_extra(frame.extra)
+
     async def _process_context(self, context: OpenAILLMContext):
         try:
             await self.push_frame(LLMFullResponseStartFrame())
@@ -206,23 +225,7 @@ class TogetherLLMService(LLMService):
         elif isinstance(frame, LLMMessagesFrame):
             context = TogetherLLMContext.from_messages(frame.messages)
         elif isinstance(frame, LLMUpdateSettingsFrame):
-            if frame.model is not None:
+            await self._update_settings(frame)
-                logger.debug(f"Switching LLM model to: [{frame.model}]")
-                self.set_model_name(frame.model)
-            if frame.frequency_penalty is not None:
-                await self.set_frequency_penalty(frame.frequency_penalty)
-            if frame.max_tokens is not None:
-                await self.set_max_tokens(frame.max_tokens)
-            if frame.presence_penalty is not None:
-                await self.set_presence_penalty(frame.presence_penalty)
-            if frame.temperature is not None:
-                await self.set_temperature(frame.temperature)
-            if frame.top_k is not None:
-                await self.set_top_k(frame.top_k)
-            if frame.top_p is not None:
-                await self.set_top_p(frame.top_p)
-            if frame.extra:
-                await self.set_extra(frame.extra)
         else:
             await self.push_frame(frame, direction)