dsProject/dsRag/StartEs.py

import os
import subprocess
import tempfile
import urllib.parse
import uuid
from contextlib import asynccontextmanager
from io import BytesIO
from logging.handlers import RotatingFileHandler
from typing import List

import jieba  # 导入 jieba 分词库
import uvicorn
from fastapi import FastAPI, Request, HTTPException
from fastapi.staticfiles import StaticFiles
from gensim.models import KeyedVectors
from pydantic import BaseModel, Field, ValidationError
from starlette.responses import StreamingResponse

from Config.Config import MS_MODEL_PATH, MS_MODEL_LIMIT, MS_HOST, MS_PORT, MS_MAX_CONNECTIONS, MS_NPROBE, \
    MS_COLLECTION_NAME
from Milvus.Utils.MilvusCollectionManager import MilvusCollectionManager
from Milvus.Utils.MilvusConnectionPool import *
from Milvus.Utils.MilvusConnectionPool import MilvusConnectionPool
from Util.ALiYunUtil import ALiYunUtil

# 初始化日志
logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)
handler = RotatingFileHandler('Logs/start.log', maxBytes=1024 * 1024, backupCount=5)
handler.setFormatter(logging.Formatter('%(asctime)s - %(levelname)s - %(message)s'))
logger.addHandler(handler)


# 将HTML文件转换为Word文件
def html_to_word_pandoc(html_file, output_file):
    subprocess.run(['pandoc', html_file, '-o', output_file])


@asynccontextmanager
async def lifespan(app: FastAPI):
    # 初始化阿里云大模型工具
    app.state.aliyun_util = ALiYunUtil()
    yield
    pass

app = FastAPI(lifespan=lifespan)

# 挂载静态文件目录
app.mount("/static", StaticFiles(directory="Static"), name="static")



class QueryRequest(BaseModel):
    query: str = Field(..., description="用户查询的问题")
    documents: List[str] = Field(..., description="用户上传的文档")


class SaveWordRequest(BaseModel):
    html: str = Field(..., description="要保存为Word的HTML内容")


@app.post("/api/save-word")
async def save_to_word(request: Request):
    temp_html = None
    output_file = None
    try:
        # Parse request data
        try:
            data = await request.json()
            html_content = data.get('html_content', '')
            if not html_content:
                raise ValueError("Empty HTML content")
        except Exception as e:
            logger.error(f"Request parsing failed: {str(e)}")
            raise HTTPException(status_code=400, detail=f"Invalid request: {str(e)}")

        # 创建临时HTML文件
        temp_html = os.path.join(tempfile.gettempdir(), uuid.uuid4().hex + ".html")
        with open(temp_html, "w", encoding="utf-8") as f:
            f.write(html_content)

        # 使用pandoc转换
        output_file = os.path.join(tempfile.gettempdir(), "小学数学问答.docx")
        subprocess.run(['pandoc', temp_html, '-o', output_file], check=True)

        # 读取生成的Word文件
        with open(output_file, "rb") as f:
            stream = BytesIO(f.read())

        # 返回响应
        encoded_filename = urllib.parse.quote("小学数学问答.docx")
        return StreamingResponse(
            stream,
            media_type="application/vnd.openxmlformats-officedocument.wordprocessingml.document",
            headers={"Content-Disposition": f"attachment; filename*=UTF-8''{encoded_filename}"})

    except HTTPException:
        raise
    except Exception as e:
        logger.error(f"Unexpected error: {str(e)}")
        raise HTTPException(status_code=500, detail="Internal server error")
    finally:
        # 清理临时文件
        try:
            if temp_html and os.path.exists(temp_html):
                os.remove(temp_html)
            if output_file and os.path.exists(output_file):
                os.remove(output_file)
        except Exception as e:
            logger.warning(f"Failed to clean up temp files: {str(e)}")


@app.post("/api/rag")
async def rag_stream(request: Request):
    pass
    # todo



if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=8000)