import io import argparse import asyncio import numpy as np import ffmpeg from time import time from fastapi import FastAPI, WebSocket, WebSocketDisconnect from fastapi.responses import HTMLResponse from fastapi.middleware.cors import CORSMiddleware from whisper_online import asr_factory, add_shared_args app = FastAPI() app.add_middleware( CORSMiddleware, allow_origins=["*"], allow_credentials=True, allow_methods=["*"], allow_headers=["*"], ) 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() asr, online = asr_factory(args) # Load demo HTML for the root endpoint with open("src/live_transcription.html", "r") as f: html = f.read() @app.get("/") async def get(): return HTMLResponse(html) SAMPLE_RATE = 16000 CHANNELS = 1 SAMPLES_PER_SEC = SAMPLE_RATE * int(args.min_chunk_size) BYTES_PER_SAMPLE = 2 # s16le = 2 bytes per sample BYTES_PER_SEC = SAMPLES_PER_SEC * BYTES_PER_SAMPLE async def start_ffmpeg_decoder(): """ Start an FFmpeg process in async streaming mode that reads WebM from stdin and outputs raw s16le PCM on stdout. Returns the process object. """ process = ( ffmpeg .input('pipe:0', format='webm') .output('pipe:1', format='s16le', acodec='pcm_s16le', ac=CHANNELS, ar=str(SAMPLE_RATE)) .run_async(pipe_stdin=True, pipe_stdout=True, pipe_stderr=True) ) return process @app.websocket("/asr") async def websocket_endpoint(websocket: WebSocket): await websocket.accept() print("WebSocket connection opened.") 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 = "" beg = time() while True: try: elapsed_time = int(time() - beg) beg = time() chunk = await loop.run_in_executor(None, ffmpeg_process.stdout.read, 32000*elapsed_time) if not chunk: # The first chunk will be almost empty, FFmpeg is still starting up chunk = await loop.run_in_executor(None, ffmpeg_process.stdout.read, 4096) if not chunk: # FFmpeg might have closed print("FFmpeg stdout closed.") break pcm_buffer.extend(chunk) if len(pcm_buffer) >= BYTES_PER_SEC: # Convert int16 -> float32 pcm_array = np.frombuffer(pcm_buffer, dtype=np.int16).astype(np.float32) / 32768.0 pcm_buffer = bytearray() online.insert_audio_chunk(pcm_array) transcription = online.process_iter()[2] full_transcription += transcription 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, "buffer": buffer }) except Exception as e: print(f"Exception in ffmpeg_stdout_reader: {e}") break print("Exiting ffmpeg_stdout_reader...") stdout_reader_task = asyncio.create_task(ffmpeg_stdout_reader()) try: while True: # Receive incoming WebM audio chunks from the client message = await websocket.receive_bytes() # Pass them to ffmpeg via stdin ffmpeg_process.stdin.write(message) ffmpeg_process.stdin.flush() except WebSocketDisconnect: print("WebSocket connection closed.") except Exception as e: print(f"Error in websocket loop: {e}") finally: # Clean up ffmpeg and the reader task try: ffmpeg_process.stdin.close() except: pass stdout_reader_task.cancel() try: ffmpeg_process.stdout.close() except: pass ffmpeg_process.wait() if __name__ == "__main__": import uvicorn uvicorn.run("whisper_fastapi_online_server:app", host=args.host, port=args.port, reload=True)