mirror of https://github.com/gpt-omni/mini-omni
58 lines
1.7 KiB
Python
58 lines
1.7 KiB
Python
import flask
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import base64
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import tempfile
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import traceback
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from flask import Flask, Response, stream_with_context
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from inference import OmniInference
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class OmniChatServer(object):
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def __init__(self, ip='0.0.0.0', port=60808, run_app=True,
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ckpt_dir='./checkpoint', device='cuda:0') -> None:
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server = Flask(__name__)
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# CORS(server, resources=r"/*")
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# server.config["JSON_AS_ASCII"] = False
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self.client = OmniInference(ckpt_dir, device)
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self.client.warm_up()
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server.route("/chat", methods=["POST"])(self.chat)
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if run_app:
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server.run(host=ip, port=port, threaded=False)
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else:
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self.server = server
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def chat(self) -> Response:
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req_data = flask.request.get_json()
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try:
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data_buf = req_data["audio"].encode("utf-8")
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data_buf = base64.b64decode(data_buf)
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stream_stride = req_data.get("stream_stride", 4)
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max_tokens = req_data.get("max_tokens", 2048)
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with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as f:
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f.write(data_buf)
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audio_generator = self.client.run_AT_batch_stream(f.name, stream_stride, max_tokens)
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return Response(stream_with_context(audio_generator), mimetype="audio/wav")
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except Exception as e:
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print(traceback.format_exc())
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# CUDA_VISIBLE_DEVICES=1 gunicorn -w 2 -b 0.0.0.0:60808 'server:create_app()'
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def create_app():
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server = OmniChatServer(run_app=False)
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return server.server
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def serve(ip='0.0.0.0', port=60808, device='cuda:0'):
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OmniChatServer(ip, port=port,run_app=True, device=device)
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if __name__ == "__main__":
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import fire
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fire.Fire(serve)
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