processors: implement Pipeline, simplify usage

server/reflector/processors.py

@@ -8,6 +8,7 @@ from reflector.settings import settings
 from reflector.logger import logger
 import httpx
 import asyncio
+import json
 from concurrent.futures import ThreadPoolExecutor
 
 
@@ -19,6 +20,9 @@ class AudioFile:
     sample_width: int
     timestamp: float = 0.0
 
+    def release(self):
+        self.path.unlink()
+
 
 @dataclass
 class Word:
@@ -69,11 +73,16 @@ class Processor:
     INPUT_TYPE: type = None
     OUTPUT_TYPE: type = None
 
-    def __init__(self):
+    def __init__(self, callback=None):
         self._processors = []
         self._callbacks = []
+        if callback:
+            self.on(callback)
 
     def connect(self, processor: "Processor"):
+        """
+        Connect this processor output to another processor
+        """
         if processor.INPUT_TYPE != self.OUTPUT_TYPE:
             raise ValueError(
                 f"Processor {processor} input type {processor.INPUT_TYPE} "
@@ -82,27 +91,41 @@ class Processor:
         self._processors.append(processor)
 
     def disconnect(self, processor: "Processor"):
+        """
+        Disconnect this processor data from another processor
+        """
         self._processors.remove(processor)
 
     def on(self, callback):
+        """
+        Register a callback to be called when data is emitted
+        """
         self._callbacks.append(callback)
 
     def off(self, callback):
+        """
+        Unregister a callback to be called when data is emitted
+        """
         self._callbacks.remove(callback)
 
     async def emit(self, data):
         for callback in self._callbacks:
-            if isinstance(data, AudioFile):
-                import pdb; pdb.set_trace()
             await callback(data)
         for processor in self._processors:
             await processor.push(data)
 
     async def push(self, data):
+        """
+        Push data to this processor. `data` must be of type `INPUT_TYPE`
+        The function returns the output of type `OUTPUT_TYPE`
+        """
         # logger.debug(f"{self.__class__.__name__} push")
         return await self._push(data)
 
     async def flush(self):
+        """
+        Flush data to this processor
+        """
         # logger.debug(f"{self.__class__.__name__} flush")
         return await self._flush()
 
@@ -114,12 +137,24 @@ class Processor:
 
     @classmethod
     def as_threaded(cls, *args, **kwargs):
+        """
+        Return a single threaded processor where output is guaranteed
+        to be in order
+        """
         return ThreadedProcessor(cls(*args, **kwargs), max_workers=1)
 
 
 class ThreadedProcessor(Processor):
+    """
+    A processor that runs in a separate thread
+    """
+
     def __init__(self, processor: Processor, max_workers=1):
         super().__init__()
+        # FIXME: This is a hack to make sure that the processor is single threaded
+        # but if it is more than 1, then we need to make sure that the processor
+        # is emiting data in order
+        assert max_workers == 1
         self.processor = processor
         self.INPUT_TYPE = processor.INPUT_TYPE
         self.OUTPUT_TYPE = processor.OUTPUT_TYPE
@@ -231,9 +266,12 @@ class AudioTranscriptProcessor(Processor):
     OUTPUT_TYPE = Transcript
 
     async def _push(self, data: AudioFile):
-        result = await self._transcript(data)
+        try:
-        if result:
+            result = await self._transcript(data)
-            await self.emit(result)
+            if result:
+                await self.emit(result)
+        finally:
+            data.release()
 
     async def _transcript(self, data: AudioFile):
         raise NotImplementedError
@@ -282,8 +320,8 @@ class TranscriptLineProcessor(Processor):
     INPUT_TYPE = Transcript
     OUTPUT_TYPE = Transcript
 
-    def __init__(self, max_text=1000):
+    def __init__(self, max_text=1000, **kwargs):
-        super().__init__()
+        super().__init__(**kwargs)
         self.transcript = Transcript(words=[])
         self.max_text = max_text
 
@@ -340,9 +378,58 @@ class TitleSummaryProcessor(Processor):
             summary = TitleSummary(title=result.title, summary=result.description)
             await self.emit(summary)
 
+        except httpx.ConnectError as e:
+            logger.error(f"Failed to call llm: {e}")
+
         except Exception:
             logger.exception("Failed to call llm")
-            return
+
+
+class Pipeline(Processor):
+    """
+    A pipeline of processors
+    """
+
+    INPUT_TYPE = None
+    OUTPUT_TYPE = None
+
+    def __init__(self, *processors):
+        super().__init__()
+        self.processors = processors
+
+        for i in range(len(processors) - 1):
+            processors[i].connect(processors[i + 1])
+
+        self.INPUT_TYPE = processors[0].INPUT_TYPE
+        self.OUTPUT_TYPE = processors[-1].OUTPUT_TYPE
+
+    async def _push(self, data):
+        await self.processors[0].push(data)
+
+    async def _flush(self):
+        for processor in self.processors:
+            await processor.flush()
+
+
+class FinalSummaryProcessor(Processor):
+    """
+    Assemble all summary into a line-based json
+    """
+
+    INPUT_TYPE = TitleSummary
+    OUTPUT_TYPE = Path
+
+    def __init__(self, filename: Path, **kwargs):
+        super().__init__(**kwargs)
+        self.filename = filename
+
+    async def _push(self, data: TitleSummary):
+        with open(self.filename, "a", encoding="utf8") as fd:
+            fd.write(json.dumps(data))
+
+    async def _flush(self):
+        logger.info(f"Writing to {self.filename}")
+        await self.emit(self.filename)
 
 
 if __name__ == "__main__":
@@ -353,44 +440,40 @@ if __name__ == "__main__":
     args = parser.parse_args()
 
     async def main():
-        chunker = AudioChunkerProcessor()
-
-        # merge audio
-        merger = AudioMergeProcessor.as_threaded()
-        chunker.connect(merger)
-
-        # transcript audio
-        transcripter = AudioWhisperTranscriptProcessor()
-        merger.connect(transcripter)
-
-        # merge transcript and output lines
-        line_processor = TranscriptLineProcessor()
-        transcripter.connect(line_processor)
-
         async def on_transcript(transcript):
             print(f"Transcript: [{transcript.human_timestamp}]: {transcript.text}")
 
-        line_processor.on(on_transcript)
+        async def on_summary(summary):
+            print(f"Summary: {summary.title} - {summary.summary}")
 
-        # # title and summary
+        async def on_final_summary(path):
-        # title_summary = TitleSummaryProcessor.as_threaded()
+            print(f"Final Summary: {path}")
-        # line_processor.connect(title_summary)
+
-        #
+        # transcription output
-        # async def on_summary(summary):
+        result_fn = Path(args.source).with_suffix(".jsonl")
-        #     print(f"Summary: title={summary.title} summary={summary.summary}")
+
-        #
+        pipeline = Pipeline(
-        # title_summary.on(on_summary)
+            AudioChunkerProcessor(),
+            AudioMergeProcessor(),
+            AudioWhisperTranscriptProcessor().as_threaded(),
+            TranscriptLineProcessor(callback=on_transcript),
+            TitleSummaryProcessor.as_threaded(callback=on_summary),
+            FinalSummaryProcessor.as_threaded(
+                filename=result_fn, callback=on_final_summary
+            ),
+        )
 
         # start processing audio
+        logger.info(f"Opening{args.source}")
         container = av.open(args.source)
-        for frame in container.decode(audio=0):
+        try:
-            await chunker.push(frame)
+            logger.info("Start pushing audio into the pipeline")
+            for frame in container.decode(audio=0):
+                await pipeline.push(frame)
+        finally:
+            logger.info("Flushing the pipeline")
+            await pipeline.flush()
 
-        # audio done, flush everything
+        logger.info("All done !")
-        await chunker.flush()
-        await merger.flush()
-        await transcripter.flush()
-        await line_processor.flush()
-        # await title_summary.flush()
 
     asyncio.run(main())