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37 行
788 B
Python
37 行
788 B
Python
# Copyright (c) Microsoft. All rights reserved.
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import os
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import time
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import torch
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import uvicorn
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from fastapi import FastAPI, Request
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from pydantic import BaseModel
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os.environ["CUDA_VISIBLE_DEVICES"] = "0"
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torch.cuda.set_per_process_memory_fraction(0.1, 0)
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num_works = 1
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app = FastAPI()
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from sentence_transformers import SentenceTransformer
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model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
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@app.post("/key_cal/")
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async def compress(request: Request):
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try:
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data = await request.json()
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text = data.get("text", "")
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except:
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text = (await request.body()).decode("utf-8")
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key = model.encode(text)
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return {"key": key.tolist()}
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if __name__ == "__main__":
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uvicorn.run(app, host="0.0.0.0", port=8000, workers=num_works)
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