135 lines
4.1 KiB
Python
135 lines
4.1 KiB
Python
# /// script
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# requires-python = ">=3.12"
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# dependencies = [
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# "msgpack",
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# "numpy",
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# "sphn",
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# "websockets",
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# ]
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# ///
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import argparse
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import asyncio
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import time
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import msgpack
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import numpy as np
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import sphn
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import websockets
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SAMPLE_RATE = 24000
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TARGET_CHANNELS = 1 # Mono
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FRAME_SIZE = 1920 # Send data in chunks
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HEADERS = {"kyutai-api-key": "open_token"}
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def load_and_process_audio(file_path):
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"""Load an MP3 file, resample to 24kHz, convert to mono, and extract PCM float32 data."""
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pcm_data, _ = sphn.read(file_path, sample_rate=SAMPLE_RATE)
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return pcm_data[0]
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async def receive_messages(websocket):
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transcript = []
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async for message in websocket:
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data = msgpack.unpackb(message, raw=False)
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if data["type"] == "Step":
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# This message contains the signal from the semantic VAD, and tells us how
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# much audio the server has already processed. We don't use either here.
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continue
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if data["type"] == "Word":
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print(data["text"], end=" ", flush=True)
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transcript.append(
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{
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"text": data["text"],
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"timestamp": [data["start_time"], data["start_time"]],
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}
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)
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if data["type"] == "EndWord":
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if len(transcript) > 0:
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transcript[-1]["timestamp"][1] = data["stop_time"]
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if data["type"] == "Marker":
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# Received marker, stopping stream
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break
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return transcript
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async def send_messages(websocket, rtf: float):
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audio_data = load_and_process_audio(args.in_file)
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async def send_audio(audio: np.ndarray):
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await websocket.send(
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msgpack.packb(
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{"type": "Audio", "pcm": [float(x) for x in audio]},
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use_single_float=True,
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)
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)
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# Start with a second of silence.
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# This is needed for the 2.6B model for technical reasons.
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await send_audio([0.0] * SAMPLE_RATE)
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start_time = time.time()
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for i in range(0, len(audio_data), FRAME_SIZE):
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await send_audio(audio_data[i : i + FRAME_SIZE])
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expected_send_time = start_time + (i + 1) / SAMPLE_RATE / rtf
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current_time = time.time()
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if current_time < expected_send_time:
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await asyncio.sleep(expected_send_time - current_time)
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else:
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await asyncio.sleep(0.001)
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for _ in range(5):
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await send_audio([0.0] * SAMPLE_RATE)
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# Send a marker to indicate the end of the stream.
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await websocket.send(
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msgpack.packb({"type": "Marker", "id": 0}, use_single_float=True)
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)
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# We'll get back the marker once the corresponding audio has been transcribed,
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# accounting for the delay of the model. That's why we need to send some silence
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# after the marker, because the model will not return the marker immediately.
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for _ in range(35):
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await send_audio([0.0] * SAMPLE_RATE)
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async def stream_audio(url: str, api_key: str, rtf: float):
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"""Stream audio data to a WebSocket server."""
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headers = {"kyutai-api-key": api_key}
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# Instead of using the header, you can authenticate by adding `?auth_id={api_key}` to the URL
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async with websockets.connect(url, additional_headers=headers) as websocket:
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send_task = asyncio.create_task(send_messages(websocket, rtf))
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receive_task = asyncio.create_task(receive_messages(websocket))
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_, transcript = await asyncio.gather(send_task, receive_task)
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return transcript
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument("in_file")
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parser.add_argument(
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"--url",
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help="The url of the server to which to send the audio",
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default="ws://127.0.0.1:8080",
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)
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parser.add_argument("--api-key", default="public_token")
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parser.add_argument(
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"--rtf",
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type=float,
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default=1.01,
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help="The real-time factor of how fast to feed in the audio.",
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)
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args = parser.parse_args()
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url = f"{args.url}/api/asr-streaming"
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transcript = asyncio.run(stream_audio(url, args.api_key, args.rtf))
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print()
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print()
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print(transcript)
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