754 lines
27 KiB
Python
754 lines
27 KiB
Python
from fastapi import APIRouter, Depends, HTTPException, UploadFile, File, status
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from fastapi.security import HTTPBearer
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from sqlalchemy.orm import Session
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from typing import Optional, Dict, Any, List
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import pandas as pd
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from th_agenter.utils.schemas import FileListResponse,ExcelPreviewRequest,NormalResponse
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import os
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import tempfile
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from th_agenter.utils.schemas import BaseResponse
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from th_agenter.services.smart_query import (
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SmartQueryService,
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ExcelAnalysisService,
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DatabaseQueryService
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)
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from th_agenter.services.excel_metadata_service import ExcelMetadataService
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import uuid
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from pathlib import Path
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from th_agenter.utils.file_utils import FileUtils
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from fastapi import APIRouter, Depends, HTTPException, status
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from fastapi.responses import StreamingResponse
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from sqlalchemy.orm import Session
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from typing import Optional, AsyncGenerator
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import json
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from datetime import datetime
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from th_agenter.db.database import get_db
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from th_agenter.services.auth import AuthService
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from th_agenter.services.smart_workflow import SmartWorkflowManager
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from th_agenter.services.conversation_context import ConversationContextService
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import logging
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from pydantic import BaseModel
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logger = logging.getLogger(__name__)
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router = APIRouter(prefix="/smart-query", tags=["smart-query"])
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security = HTTPBearer()
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# Request/Response Models
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class DatabaseConfig(BaseModel):
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type: str
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host: str
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port: str
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database: str
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username: str
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password: str
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class QueryRequest(BaseModel):
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query: str
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page: int = 1
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page_size: int = 20
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table_name: Optional[str] = None
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class TableSchemaRequest(BaseModel):
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table_name: str
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class ExcelUploadResponse(BaseModel):
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file_id: int
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success: bool
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message: str
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data: Optional[Dict[str, Any]] = None # 添加data字段
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class QueryResponse(BaseModel):
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success: bool
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message: str
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data: Optional[Dict[str, Any]] = None
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@router.post("/upload-excel", response_model=ExcelUploadResponse)
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async def upload_excel(
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file: UploadFile = File(...),
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current_user = Depends(AuthService.get_current_user),
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db: Session = Depends(get_db)
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):
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"""
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上传Excel文件并进行预处理
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"""
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try:
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# 验证文件类型
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allowed_extensions = ['.xlsx', '.xls', '.csv']
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file_extension = os.path.splitext(file.filename)[1].lower()
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if file_extension not in allowed_extensions:
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raise HTTPException(
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status_code=status.HTTP_400_BAD_REQUEST,
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detail="不支持的文件格式，请上传 .xlsx, .xls 或 .csv 文件"
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)
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# 验证文件大小 (10MB)
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content = await file.read()
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file_size = len(content)
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if file_size > 10 * 1024 * 1024:
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raise HTTPException(
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status_code=status.HTTP_400_BAD_REQUEST,
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detail="文件大小不能超过 10MB"
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)
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# 创建持久化目录结构
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backend_dir = Path(__file__).parent.parent.parent.parent # 获取backend目录
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data_dir = backend_dir / "data/uploads"
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excel_user_dir = data_dir / f"excel_{current_user.id}"
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# 确保目录存在
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excel_user_dir.mkdir(parents=True, exist_ok=True)
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# 生成文件名：{uuid}_{原始文件名称}
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file_id = str(uuid.uuid4())
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safe_filename = FileUtils.sanitize_filename(file.filename)
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new_filename = f"{file_id}_{safe_filename}"
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file_path = excel_user_dir / new_filename
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# 保存文件
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with open(file_path, 'wb') as f:
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f.write(content)
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# 使用Excel元信息服务提取并保存元信息
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metadata_service = ExcelMetadataService(db)
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excel_file = metadata_service.save_file_metadata(
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file_path=str(file_path),
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original_filename=file.filename,
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user_id=current_user.id,
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file_size=file_size
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)
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# 为了兼容现有前端，仍然创建pickle文件
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try:
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if file_extension == '.csv':
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df = pd.read_csv(file_path, encoding='utf-8')
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else:
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df = pd.read_excel(file_path)
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except UnicodeDecodeError:
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if file_extension == '.csv':
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df = pd.read_csv(file_path, encoding='gbk')
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else:
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raise HTTPException(
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status_code=status.HTTP_400_BAD_REQUEST,
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detail="文件编码错误，请确保文件为UTF-8或GBK编码"
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)
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except Exception as e:
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raise HTTPException(
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status_code=status.HTTP_400_BAD_REQUEST,
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detail=f"文件读取失败: {str(e)}"
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)
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# 保存pickle文件到同一目录
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pickle_filename = f"{file_id}_{safe_filename}.pkl"
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pickle_path = excel_user_dir / pickle_filename
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df.to_pickle(pickle_path)
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# 数据预处理和分析（保持兼容性）
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excel_service = ExcelAnalysisService()
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analysis_result = excel_service.analyze_dataframe(df, file.filename)
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# 添加数据库文件信息
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analysis_result.update({
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'file_id': str(excel_file.id),
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'database_id': excel_file.id,
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'temp_file_path': str(pickle_path), # 更新为新的pickle路径
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'original_filename': file.filename,
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'file_size_mb': excel_file.file_size_mb,
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'sheet_names': excel_file.sheet_names,
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})
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return ExcelUploadResponse(
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file_id=excel_file.id,
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success=True,
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message="Excel文件上传成功",
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data=analysis_result
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)
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except HTTPException:
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raise
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except Exception as e:
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raise HTTPException(
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status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
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detail=f"文件处理失败: {str(e)}"
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)
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@router.post("/preview-excel", response_model=QueryResponse)
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async def preview_excel(
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request: ExcelPreviewRequest,
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current_user = Depends(AuthService.get_current_user),
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db: Session = Depends(get_db)
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):
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"""
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预览Excel文件数据
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"""
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try:
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logger.info(f"Preview request for file_id: {request.file_id}, user: {current_user.id}")
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# 验证file_id格式
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try:
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file_id = int(request.file_id)
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except ValueError:
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raise HTTPException(
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status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
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detail=f"无效的文件ID格式: {request.file_id}"
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)
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# 从数据库获取文件信息
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metadata_service = ExcelMetadataService(db)
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excel_file = metadata_service.get_file_by_id(file_id, current_user.id)
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if not excel_file:
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raise HTTPException(
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status_code=status.HTTP_404_NOT_FOUND,
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detail="文件不存在或已被删除"
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)
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# 检查文件是否存在
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if not os.path.exists(excel_file.file_path):
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raise HTTPException(
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status_code=status.HTTP_404_NOT_FOUND,
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detail="文件已被移动或删除"
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)
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# 更新最后访问时间
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metadata_service.update_last_accessed(file_id, current_user.id)
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# 读取Excel文件
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if excel_file.file_type.lower() == 'csv':
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df = pd.read_csv(excel_file.file_path, encoding='utf-8')
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else:
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# 对于Excel文件，使用默认sheet或第一个sheet
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sheet_name = excel_file.default_sheet if excel_file.default_sheet else 0
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df = pd.read_excel(excel_file.file_path, sheet_name=sheet_name)
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# 计算分页
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total_rows = len(df)
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start_idx = (request.page - 1) * request.page_size
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end_idx = start_idx + request.page_size
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# 获取分页数据
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paginated_df = df.iloc[start_idx:end_idx]
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# 转换为字典格式
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data = paginated_df.fillna('').to_dict('records')
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columns = df.columns.tolist()
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return QueryResponse(
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success=True,
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message="Excel文件预览加载成功",
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data={
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'data': data,
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'columns': columns,
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'total_rows': total_rows,
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'page': request.page,
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'page_size': request.page_size,
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'total_pages': (total_rows + request.page_size - 1) // request.page_size
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}
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)
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except HTTPException:
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raise
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except Exception as e:
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raise HTTPException(
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status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
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detail=f"预览文件失败: {str(e)}"
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)
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@router.post("/test-db-connection", response_model=NormalResponse)
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async def test_database_connection(
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config: DatabaseConfig,
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current_user = Depends(AuthService.get_current_user)
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):
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"""
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测试数据库连接
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"""
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try:
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db_service = DatabaseQueryService()
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is_connected = await db_service.test_connection(config.dict())
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if is_connected:
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return NormalResponse(
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success=True,
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message="数据库连接测试成功"
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)
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else:
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return NormalResponse(
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success=False,
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message="数据库连接测试失败"
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)
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except Exception as e:
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return NormalResponse(
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success=False,
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message=f"连接测试失败: {str(e)}"
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)
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# 删除第285-314行的connect_database方法
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# @router.post("/connect-database", response_model=QueryResponse)
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# async def connect_database(
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# config_id: int,
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# current_user = Depends(AuthService.get_current_user),
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# db: Session = Depends(get_db)
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# ):
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# """连接数据库并获取表列表"""
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# ... (整个方法都删除)
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@router.post("/table-schema", response_model=QueryResponse)
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async def get_table_schema(
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request: TableSchemaRequest,
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current_user = Depends(AuthService.get_current_user)
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):
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"""
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获取数据表结构
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"""
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try:
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db_service = DatabaseQueryService()
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schema_result = await db_service.get_table_schema(request.table_name, current_user.id)
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if schema_result['success']:
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return QueryResponse(
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success=True,
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message="获取表结构成功",
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data=schema_result['data']
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)
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else:
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return QueryResponse(
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success=False,
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message=schema_result['message']
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)
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except Exception as e:
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return QueryResponse(
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success=False,
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message=f"获取表结构失败: {str(e)}"
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)
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class StreamQueryRequest(BaseModel):
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query: str
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conversation_id: Optional[int] = None
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is_new_conversation: bool = False
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class DatabaseStreamQueryRequest(BaseModel):
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query: str
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database_config_id: int
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conversation_id: Optional[int] = None
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is_new_conversation: bool = False
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@router.post("/execute-excel-query")
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async def stream_smart_query(
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request: StreamQueryRequest,
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current_user=Depends(AuthService.get_current_user),
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db: Session = Depends(get_db)
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):
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"""
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流式智能问答查询接口
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支持实时推送工作流步骤和最终结果
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"""
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async def generate_stream() -> AsyncGenerator[str, None]:
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workflow_manager = None
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try:
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# 验证请求参数
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if not request.query or not request.query.strip():
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yield f"data: {json.dumps({'type': 'error', 'message': '查询内容不能为空'}, ensure_ascii=False)}\n\n"
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return
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if len(request.query) > 1000:
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yield f"data: {json.dumps({'type': 'error', 'message': '查询内容过长，请控制在1000字符以内'}, ensure_ascii=False)}\n\n"
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return
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# 发送开始信号
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yield f"data: {json.dumps({'type': 'start', 'message': '开始处理查询', 'timestamp': datetime.now().isoformat()}, ensure_ascii=False)}\n\n"
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# 初始化服务
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workflow_manager = SmartWorkflowManager(db)
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conversation_context_service = ConversationContextService()
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# 处理对话上下文
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conversation_id = request.conversation_id
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# 如果是新对话或没有指定对话ID，创建新对话
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if request.is_new_conversation or not conversation_id:
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try:
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conversation_id = await conversation_context_service.create_conversation(
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user_id=current_user.id,
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title=f"智能问数: {request.query[:20]}..."
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)
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yield f"data: {json.dumps({'type': 'conversation_created', 'conversation_id': conversation_id}, ensure_ascii=False)}\n\n"
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except Exception as e:
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logger.warning(f"创建对话失败: {e}")
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# 不阻断流程，继续执行查询
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# 保存用户消息
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if conversation_id:
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try:
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await conversation_context_service.save_message(
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conversation_id=conversation_id,
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role="user",
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content=request.query
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)
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except Exception as e:
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logger.warning(f"保存用户消息失败: {e}")
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# 执行智能查询工作流（带流式推送）
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async for step_data in workflow_manager.process_excel_query_stream(
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user_query=request.query,
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user_id=current_user.id,
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conversation_id=conversation_id,
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is_new_conversation=request.is_new_conversation
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):
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# 推送工作流步骤
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yield f"data: {json.dumps(step_data, ensure_ascii=False)}\n\n"
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# 如果是最终结果，保存到对话历史
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if step_data.get('type') == 'final_result' and conversation_id:
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try:
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result_data = step_data.get('data', {})
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await conversation_context_service.save_message(
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conversation_id=conversation_id,
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role="assistant",
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content=result_data.get('summary', '查询完成'),
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metadata={
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'query_result': result_data,
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'workflow_steps': step_data.get('workflow_steps', []),
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'selected_files': result_data.get('used_files', [])
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}
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)
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# 更新对话上下文
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await conversation_context_service.update_conversation_context(
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conversation_id=conversation_id,
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query=request.query,
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selected_files=result_data.get('used_files', [])
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)
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logger.info(f"查询成功完成，对话ID: {conversation_id}")
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except Exception as e:
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logger.warning(f"保存消息到对话历史失败: {e}")
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# 发送完成信号
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yield f"data: {json.dumps({'type': 'complete', 'message': '查询处理完成', 'timestamp': datetime.now().isoformat()}, ensure_ascii=False)}\n\n"
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except Exception as e:
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logger.error(f"流式智能查询异常: {e}", exc_info=True)
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yield f"data: {json.dumps({'type': 'error', 'message': f'查询执行失败: {str(e)}'}, ensure_ascii=False)}\n\n"
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finally:
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# 清理资源
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if workflow_manager:
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try:
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workflow_manager.excel_workflow.executor.shutdown(wait=False)
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except:
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pass
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return StreamingResponse(
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generate_stream(),
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media_type="text/plain",
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headers={
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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"Content-Type": "text/event-stream",
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"Access-Control-Allow-Origin": "*",
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"Access-Control-Allow-Headers": "*",
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"Access-Control-Allow-Methods": "*"
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}
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)
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@router.post("/execute-db-query")
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async def execute_database_query(
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request: DatabaseStreamQueryRequest,
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current_user = Depends(AuthService.get_current_user),
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db: Session = Depends(get_db)
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):
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"""
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流式数据库查询接口
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支持实时推送工作流步骤和最终结果
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"""
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async def generate_stream() -> AsyncGenerator[str, None]:
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workflow_manager = None
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try:
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# 验证请求参数
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if not request.query or not request.query.strip():
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yield f"data: {json.dumps({'type': 'error', 'message': '查询内容不能为空'}, ensure_ascii=False)}\n\n"
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return
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if len(request.query) > 1000:
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yield f"data: {json.dumps({'type': 'error', 'message': '查询内容过长，请控制在1000字符以内'}, ensure_ascii=False)}\n\n"
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return
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# 发送开始信号
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yield f"data: {json.dumps({'type': 'start', 'message': '开始处理数据库查询', 'timestamp': datetime.now().isoformat()}, ensure_ascii=False)}\n\n"
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# 初始化服务
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workflow_manager = SmartWorkflowManager(db)
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conversation_context_service = ConversationContextService()
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||
|
||
# 处理对话上下文
|
||
conversation_id = request.conversation_id
|
||
|
||
# 如果是新对话或没有指定对话ID，创建新对话
|
||
if request.is_new_conversation or not conversation_id:
|
||
try:
|
||
conversation_id = await conversation_context_service.create_conversation(
|
||
user_id=current_user.id,
|
||
title=f"数据库查询: {request.query[:20]}..."
|
||
)
|
||
yield f"data: {json.dumps({'type': 'conversation_created', 'conversation_id': conversation_id}, ensure_ascii=False)}\n\n"
|
||
except Exception as e:
|
||
logger.warning(f"创建对话失败: {e}")
|
||
# 不阻断流程，继续执行查询
|
||
|
||
# 保存用户消息
|
||
if conversation_id:
|
||
try:
|
||
await conversation_context_service.save_message(
|
||
conversation_id=conversation_id,
|
||
role="user",
|
||
content=request.query
|
||
)
|
||
except Exception as e:
|
||
logger.warning(f"保存用户消息失败: {e}")
|
||
|
||
# 执行数据库查询工作流（带流式推送）
|
||
async for step_data in workflow_manager.process_database_query_stream(
|
||
user_query=request.query,
|
||
user_id=current_user.id,
|
||
database_config_id=request.database_config_id
|
||
):
|
||
# 推送工作流步骤
|
||
yield f"data: {json.dumps(step_data, ensure_ascii=False)}\n\n"
|
||
|
||
# 如果是最终结果，保存到对话历史
|
||
if step_data.get('type') == 'final_result' and conversation_id:
|
||
try:
|
||
result_data = step_data.get('data', {})
|
||
await conversation_context_service.save_message(
|
||
conversation_id=conversation_id,
|
||
role="assistant",
|
||
content=result_data.get('summary', '查询完成'),
|
||
metadata={
|
||
'query_result': result_data,
|
||
'workflow_steps': step_data.get('workflow_steps', []),
|
||
'generated_sql': result_data.get('generated_sql', '')
|
||
}
|
||
)
|
||
|
||
# 更新对话上下文
|
||
await conversation_context_service.update_conversation_context(
|
||
conversation_id=conversation_id,
|
||
query=request.query,
|
||
selected_files=[]
|
||
)
|
||
|
||
logger.info(f"数据库查询成功完成，对话ID: {conversation_id}")
|
||
|
||
except Exception as e:
|
||
logger.warning(f"保存消息到对话历史失败: {e}")
|
||
|
||
# 发送完成信号
|
||
yield f"data: {json.dumps({'type': 'complete', 'message': '数据库查询处理完成', 'timestamp': datetime.now().isoformat()}, ensure_ascii=False)}\n\n"
|
||
|
||
except Exception as e:
|
||
logger.error(f"流式数据库查询异常: {e}", exc_info=True)
|
||
yield f"data: {json.dumps({'type': 'error', 'message': f'查询执行失败: {str(e)}'}, ensure_ascii=False)}\n\n"
|
||
|
||
finally:
|
||
# 清理资源
|
||
if workflow_manager:
|
||
try:
|
||
workflow_manager.database_workflow.executor.shutdown(wait=False)
|
||
except:
|
||
pass
|
||
|
||
return StreamingResponse(
|
||
generate_stream(),
|
||
media_type="text/plain",
|
||
headers={
|
||
"Cache-Control": "no-cache",
|
||
"Connection": "keep-alive",
|
||
"Content-Type": "text/event-stream",
|
||
"Access-Control-Allow-Origin": "*",
|
||
"Access-Control-Allow-Headers": "*",
|
||
"Access-Control-Allow-Methods": "*"
|
||
}
|
||
)
|
||
|
||
@router.delete("/cleanup-temp-files")
|
||
async def cleanup_temp_files(
|
||
current_user = Depends(AuthService.get_current_user)
|
||
):
|
||
"""
|
||
清理临时文件
|
||
"""
|
||
try:
|
||
temp_dir = tempfile.gettempdir()
|
||
user_prefix = f"excel_{current_user.id}_"
|
||
|
||
cleaned_count = 0
|
||
for filename in os.listdir(temp_dir):
|
||
if filename.startswith(user_prefix) and filename.endswith('.pkl'):
|
||
file_path = os.path.join(temp_dir, filename)
|
||
try:
|
||
os.remove(file_path)
|
||
cleaned_count += 1
|
||
except OSError:
|
||
pass
|
||
|
||
return BaseResponse(
|
||
success=True,
|
||
message=f"已清理 {cleaned_count} 个临时文件"
|
||
)
|
||
|
||
except Exception as e:
|
||
return BaseResponse(
|
||
success=False,
|
||
message=f"清理临时文件失败: {str(e)}"
|
||
)
|
||
|
||
@router.get("/files", response_model=FileListResponse)
|
||
async def get_file_list(
|
||
page: int = 1,
|
||
page_size: int = 20,
|
||
current_user = Depends(AuthService.get_current_user),
|
||
db: Session = Depends(get_db)
|
||
):
|
||
"""
|
||
获取用户上传的Excel文件列表
|
||
"""
|
||
try:
|
||
metadata_service = ExcelMetadataService(db)
|
||
skip = (page - 1) * page_size
|
||
files, total = metadata_service.get_user_files(current_user.id, skip, page_size)
|
||
|
||
file_list = []
|
||
for file in files:
|
||
file_info = {
|
||
'id': file.id,
|
||
'filename': file.original_filename,
|
||
'file_size': file.file_size,
|
||
'file_size_mb': file.file_size_mb,
|
||
'file_type': file.file_type,
|
||
'sheet_names': file.sheet_names,
|
||
'sheet_count': file.sheet_count,
|
||
'last_accessed': file.last_accessed.isoformat() if file.last_accessed else None,
|
||
'is_processed': file.is_processed,
|
||
'processing_error': file.processing_error
|
||
}
|
||
file_list.append(file_info)
|
||
|
||
return FileListResponse(
|
||
success=True,
|
||
message="获取文件列表成功",
|
||
data={
|
||
'files': file_list,
|
||
'total': total,
|
||
'page': page,
|
||
'page_size': page_size,
|
||
'total_pages': (total + page_size - 1) // page_size
|
||
}
|
||
)
|
||
|
||
except Exception as e:
|
||
return FileListResponse(
|
||
success=False,
|
||
message=f"获取文件列表失败: {str(e)}"
|
||
)
|
||
|
||
@router.delete("/files/{file_id}", response_model=NormalResponse)
|
||
async def delete_file(
|
||
file_id: int,
|
||
current_user = Depends(AuthService.get_current_user),
|
||
db: Session = Depends(get_db)
|
||
):
|
||
"""
|
||
删除指定的Excel文件
|
||
"""
|
||
try:
|
||
metadata_service = ExcelMetadataService(db)
|
||
success = metadata_service.delete_file(file_id, current_user.id)
|
||
|
||
if success:
|
||
return NormalResponse(
|
||
success=True,
|
||
message="文件删除成功"
|
||
)
|
||
else:
|
||
return NormalResponse(
|
||
success=False,
|
||
message="文件不存在或删除失败"
|
||
)
|
||
|
||
except Exception as e:
|
||
return NormalResponse(
|
||
success=True,
|
||
message=str(e)
|
||
)
|
||
|
||
@router.get("/files/{file_id}/info", response_model=QueryResponse)
|
||
async def get_file_info(
|
||
file_id: int,
|
||
current_user = Depends(AuthService.get_current_user),
|
||
db: Session = Depends(get_db)
|
||
):
|
||
"""
|
||
获取指定文件的详细信息
|
||
"""
|
||
try:
|
||
metadata_service = ExcelMetadataService(db)
|
||
excel_file = metadata_service.get_file_by_id(file_id, current_user.id)
|
||
|
||
if not excel_file:
|
||
raise HTTPException(
|
||
status_code=status.HTTP_404_NOT_FOUND,
|
||
detail="文件不存在"
|
||
)
|
||
|
||
# 更新最后访问时间
|
||
metadata_service.update_last_accessed(file_id, current_user.id)
|
||
|
||
file_info = {
|
||
'id': excel_file.id,
|
||
'filename': excel_file.original_filename,
|
||
'file_size': excel_file.file_size,
|
||
'file_size_mb': excel_file.file_size_mb,
|
||
'file_type': excel_file.file_type,
|
||
'sheet_names': excel_file.sheet_names,
|
||
'default_sheet': excel_file.default_sheet,
|
||
'columns_info': excel_file.columns_info,
|
||
'preview_data': excel_file.preview_data,
|
||
'data_types': excel_file.data_types,
|
||
'total_rows': excel_file.total_rows,
|
||
'total_columns': excel_file.total_columns,
|
||
'upload_time': excel_file.upload_time.isoformat() if excel_file.upload_time else None,
|
||
'last_accessed': excel_file.last_accessed.isoformat() if excel_file.last_accessed else None,
|
||
'sheets_summary': excel_file.get_all_sheets_summary()
|
||
}
|
||
|
||
return QueryResponse(
|
||
success=True,
|
||
message="获取文件信息成功",
|
||
data=file_info
|
||
)
|
||
|
||
except HTTPException:
|
||
raise
|
||
except Exception as e:
|
||
return QueryResponse(
|
||
success=False,
|
||
message=f"获取文件信息失败: {str(e)}"
|
||
) |