44 lines
1.0 KiB
Python
44 lines
1.0 KiB
Python
import asyncio
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import json
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import pickle
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from fastapi import FastAPI
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import deepseek_module
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import nlp_processor
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import nlp_teacher
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app = FastAPI(title="NLP API", version="1.0")
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# Загрузить сохраненную модель
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@app.get('/predict')
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async def predict(req, cloud:int=0, async_op: int=0):
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print('here')
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# Получить входные данные из запроса
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if cloud==1:
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if async_op==1:
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response_msg = await deepseek_module.nlp_yandex(req)
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else:
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response_msg = deepseek_module.fast_nlp_yandex(req)
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print(response_msg)
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return json.loads(response_msg.encode('latin1').decode('utf-8'))
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else:
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# Сделать предсказание модели
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prediction = nlp_processor.predict_category(req)
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# Вернуть предсказание в виде JSON
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return prediction
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@app.get('/reteach')
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async def reteach():
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print(nlp_teacher.reteach())
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if __name__ == '__main__':
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import uvicorn
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uvicorn.run(app, port=8000) |