parent
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import os
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import subprocess
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import tempfile
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import urllib.parse
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import uuid
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from contextlib import asynccontextmanager
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from io import BytesIO
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from logging.handlers import RotatingFileHandler
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from typing import List
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import jieba # 导入 jieba 分词库
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import uvicorn
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from fastapi import FastAPI, Request, HTTPException
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from fastapi.staticfiles import StaticFiles
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from gensim.models import KeyedVectors
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from pydantic import BaseModel, Field, ValidationError
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from starlette.responses import StreamingResponse
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from Config.Config import MS_MODEL_PATH, MS_MODEL_LIMIT, MS_HOST, MS_PORT, MS_MAX_CONNECTIONS, MS_NPROBE, \
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MS_COLLECTION_NAME
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from Milvus.Utils.MilvusCollectionManager import MilvusCollectionManager
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from Milvus.Utils.MilvusConnectionPool import *
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from Milvus.Utils.MilvusConnectionPool import MilvusConnectionPool
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from Util.ALiYunUtil import ALiYunUtil
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# 初始化日志
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logger = logging.getLogger(__name__)
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logger.setLevel(logging.INFO)
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handler = RotatingFileHandler('Logs/start.log', maxBytes=1024 * 1024, backupCount=5)
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handler.setFormatter(logging.Formatter('%(asctime)s - %(levelname)s - %(message)s'))
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logger.addHandler(handler)
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# 将HTML文件转换为Word文件
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def html_to_word_pandoc(html_file, output_file):
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subprocess.run(['pandoc', html_file, '-o', output_file])
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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# 初始化阿里云大模型工具
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app.state.aliyun_util = ALiYunUtil()
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yield
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pass
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app = FastAPI(lifespan=lifespan)
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# 挂载静态文件目录
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app.mount("/static", StaticFiles(directory="Static"), name="static")
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class QueryRequest(BaseModel):
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query: str = Field(..., description="用户查询的问题")
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documents: List[str] = Field(..., description="用户上传的文档")
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class SaveWordRequest(BaseModel):
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html: str = Field(..., description="要保存为Word的HTML内容")
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@app.post("/api/save-word")
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async def save_to_word(request: Request):
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temp_html = None
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output_file = None
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try:
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# Parse request data
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try:
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data = await request.json()
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html_content = data.get('html_content', '')
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if not html_content:
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raise ValueError("Empty HTML content")
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except Exception as e:
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logger.error(f"Request parsing failed: {str(e)}")
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raise HTTPException(status_code=400, detail=f"Invalid request: {str(e)}")
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# 创建临时HTML文件
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temp_html = os.path.join(tempfile.gettempdir(), uuid.uuid4().hex + ".html")
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with open(temp_html, "w", encoding="utf-8") as f:
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f.write(html_content)
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# 使用pandoc转换
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output_file = os.path.join(tempfile.gettempdir(), "小学数学问答.docx")
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subprocess.run(['pandoc', temp_html, '-o', output_file], check=True)
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# 读取生成的Word文件
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with open(output_file, "rb") as f:
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stream = BytesIO(f.read())
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# 返回响应
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encoded_filename = urllib.parse.quote("小学数学问答.docx")
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return StreamingResponse(
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stream,
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media_type="application/vnd.openxmlformats-officedocument.wordprocessingml.document",
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headers={"Content-Disposition": f"attachment; filename*=UTF-8''{encoded_filename}"})
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except HTTPException:
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raise
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except Exception as e:
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logger.error(f"Unexpected error: {str(e)}")
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raise HTTPException(status_code=500, detail="Internal server error")
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finally:
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# 清理临时文件
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try:
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if temp_html and os.path.exists(temp_html):
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os.remove(temp_html)
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if output_file and os.path.exists(output_file):
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os.remove(output_file)
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except Exception as e:
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logger.warning(f"Failed to clean up temp files: {str(e)}")
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@app.post("/api/rag")
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async def rag_stream(request: Request):
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pass
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# todo
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if __name__ == "__main__":
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uvicorn.run(app, host="0.0.0.0", port=8000)
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