better buffer gestion

README.md

@@ -68,7 +68,9 @@ This project extends the [Whisper Streaming](https://github.com/ufal/whisper_str
     python whisper_fastapi_online_server.py --host 0.0.0.0 --port 8000
     ```
 
-    - `--host` and `--port` let you specify the server’s IP/port.  
+    - `--host` and `--port` let you specify the server’s IP/port. 
+    - `-min-chunk-size` sets the minimum chunk size for audio processing. Make sure this value aligns with the chunk size selected in the frontend. If not aligned, the system will work but may unnecessarily over-process audio data.
+    - For a full list of configurable options, run `python whisper_fastapi_online_server.py -h`
 
 4. **Open the Provided HTML**:
 
@@ -88,7 +90,7 @@ This project extends the [Whisper Streaming](https://github.com/ufal/whisper_str
 
 If you want to **deploy** this setup:
 
-1. **Host the FastAPI app** behind a production-grade HTTP(S) server (like **Uvicorn + Nginx** or Docker).  
+1. **Host the FastAPI app** behind a production-grade HTTP(S) server (like **Uvicorn + Nginx** or Docker). If you use HTTPS, use "wss" instead of "ws" in WebSocket URL.
 2. The **HTML/JS page** can be served by the same FastAPI app or a separate static host.  
 3. Users open the page in **Chrome/Firefox** (any modern browser that supports MediaRecorder + WebSocket).  
 

whisper_fastapi_online_server.py

@@ -20,27 +20,24 @@ app.add_middleware(
 )
 
 
-# Argument parsing
-parser = argparse.ArgumentParser()
-parser.add_argument("--host", type=str, default='localhost')
-parser.add_argument("--port", type=int, default=8000)
+parser = argparse.ArgumentParser(description="Whisper FastAPI Online Server")
+parser.add_argument("--host", type=str, default='localhost', help="The host address to bind the server to.")
+parser.add_argument("--port", type=int, default=8000, help="The port number to bind the server to.")
 parser.add_argument("--warmup-file", type=str, dest="warmup_file", 
         help="The path to a speech audio wav file to warm up Whisper so that the very first chunk processing is fast. It can be e.g. https://github.com/ggerganov/whisper.cpp/raw/master/samples/jfk.wav .")
 add_shared_args(parser)
 args = parser.parse_args()
 
-# Initialize Whisper
 asr, online = asr_factory(args)
 
 # Load demo HTML for the root endpoint
-with open("live_transcription.html", "r") as f:
+with open("src/live_transcription.html", "r") as f:
     html = f.read()
 
 @app.get("/")
 async def get():
     return HTMLResponse(html)
 
-# Streaming constants
 SAMPLE_RATE = 16000
 CHANNELS = 1
 SAMPLES_PER_SEC = SAMPLE_RATE * int(args.min_chunk_size)
@@ -67,11 +64,11 @@ async def websocket_endpoint(websocket: WebSocket):
 
     ffmpeg_process = await start_ffmpeg_decoder()
     pcm_buffer = bytearray()
-
     # Continuously read decoded PCM from ffmpeg stdout in a background task
     async def ffmpeg_stdout_reader():
         nonlocal pcm_buffer
         loop = asyncio.get_event_loop()
+        full_transcription = ""
         while True:
             try:
                 chunk = await loop.run_in_executor(None, ffmpeg_process.stdout.read, 4096)
@@ -81,7 +78,6 @@ async def websocket_endpoint(websocket: WebSocket):
 
                 pcm_buffer.extend(chunk)
 
-                # Process in 3-second batches
                 while len(pcm_buffer) >= BYTES_PER_SEC:
                     three_sec_chunk = pcm_buffer[:BYTES_PER_SEC]
                     del pcm_buffer[:BYTES_PER_SEC]
@@ -89,15 +85,17 @@ async def websocket_endpoint(websocket: WebSocket):
                     # Convert int16 -> float32
                     pcm_array = np.frombuffer(three_sec_chunk, dtype=np.int16).astype(np.float32) / 32768.0
 
-                    # Send PCM data to Whisper
                     online.insert_audio_chunk(pcm_array)
-                    transcription = online.process_iter()
-                    buffer = online.to_flush(online.transcript_buffer.buffer)
-
-                    # Return partial transcription results to the client
+                    transcription = online.process_iter()[2]
+                    if args.vac:
+                        buffer = online.online.to_flush(online.online.transcript_buffer.buffer)[2] # We need to access the underlying online object to get the buffer
+                    else:
+                        buffer = online.to_flush(online.transcript_buffer.buffer)[2]
+                    if buffer in full_transcription: # With VAC, the buffer is not updated until the next chunk is processed
+                        buffer = ""
                     await websocket.send_json({
-                        "transcription": transcription[2],
-                        "buffer": buffer[2]
+                        "transcription": transcription,
+                        "buffer": buffer
                     })
             except Exception as e:
                 print(f"Exception in ffmpeg_stdout_reader: {e}")