frame and pipeline docstrings

src/dailyai/services/ai_services.py

@@ -59,9 +59,6 @@ class AIService(FrameProcessor):
                         break
             else:
                 raise Exception("Frames must be an iterable or async iterable")
-
-            async for output_frame in self.finalize():
-                yield output_frame
         except Exception as e:
             self.logger.error("Exception occurred while running AI service", e)
             raise e
@@ -103,6 +100,7 @@ class TTSService(AIService):
         # yield empty bytes here, so linting can infer what this method does
         yield bytes()
 
+<<<<<<< HEAD
     async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
         if isinstance(frame, EndFrame):
             if self.current_sentence:
@@ -111,6 +109,14 @@ class TTSService(AIService):
             yield frame
 
         if not isinstance(frame, TextFrame):
+=======
+    async def process_frame(self, frame: QueueFrame) -> AsyncGenerator[QueueFrame, None]:
+        if not isinstance(frame, TextQueueFrame):
+            if self.current_sentence:
+                async for audio_chunk in self.run_tts(self.current_sentence):
+                    yield AudioQueueFrame(audio_chunk)
+
+>>>>>>> fa5f38c (frame and pipeline docstrings)
             yield frame
             return
 
@@ -127,9 +133,12 @@ class TTSService(AIService):
             async for audio_chunk in self.run_tts(text):
                 yield AudioFrame(audio_chunk)
 
+<<<<<<< HEAD
             # note we pass along the text frame *after* the audio, so the text frame is completed after the audio is processed.
             yield TextFrame(text)
 
+=======
+>>>>>>> fa5f38c (frame and pipeline docstrings)
     # Convenience function to send the audio for a sentence to the given queue
     async def say(self, sentence, queue: asyncio.Queue):
         await self.run_to_queue(queue, [TextFrame(sentence)])