dj
e5d4724e82
- 新增对话历史管理：MongoDB新增conversations集合，存储用户与AI的对话上下文，支持多轮对话意图延续
- 新增对话历史API（conversation.py）：GET/DELETE conversation历史、列出所有会话
- 意图解析增强：支持基于对话历史的意图识别，上下文理解更准确
- 字段提取优化：支持"提取文档中的医院数量"等自然语言模式，智能去除"文档中的"前缀
- 文档对比优化：从指令中提取文件名并精确匹配source_docs，支持"对比A和B两个文档"
- 文档摘要优化：使用LLM生成真实AI摘要而非返回原始文档预览
【Word模板填表核心功能】
- Word模板字段生成：空白Word上传后，自动从源文档（Excel/Word/TXT/MD）内容AI生成字段名
- Word模板填表（_fill_docx）：将提取数据写入Word模板表格，支持精确匹配、模糊匹配、追加新行
- 数据润色（_polish_word_filled_data）：LLM对多行Excel数据进行统计归纳（合计/平均/极值），转化为专业自然语言描述
- 段落格式输出：使用📌字段名+值段落+分隔线（灰色横线）格式，提升可读性
- 导出链打通：fill_template返回filled_file_path，export直接返回已填好的Word文件
【其他修复】
- 修复Word导出Windows文件锁问题：NamedTemporaryFile改为mkstemp+close
- 修复Word方框非法字符：扩展clean_text移除\uFFFD、□等Unicode替代符和零宽字符
- 修复文档对比"需要至少2个文档"：从指令提取具体文件名优先匹配而非取前2个
- 修复导出format硬编码：自动识别docx/xlsx格式
- Docx解析器增加备用解析方法和更完整的段落/表格/标题提取
- RAG服务新增MySQL数据源支持
98 lines
2.4 KiB
Python
98 lines
2.4 KiB
Python
"""
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对话历史 API 接口
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提供对话历史的存储和查询功能
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"""
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import logging
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from typing import Optional
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from fastapi import APIRouter, HTTPException
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from pydantic import BaseModel
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from app.core.database import mongodb
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logger = logging.getLogger(__name__)
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router = APIRouter(prefix="/conversation", tags=["对话历史"])
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# ==================== 请求/响应模型 ====================
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class ConversationMessage(BaseModel):
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role: str
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content: str
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intent: Optional[str] = None
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class ConversationHistoryResponse(BaseModel):
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success: bool
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messages: list
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class ConversationListResponse(BaseModel):
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success: bool
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conversations: list
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# ==================== 接口 ====================
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@router.get("/{conversation_id}/history", response_model=ConversationHistoryResponse)
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async def get_conversation_history(conversation_id: str, limit: int = 20):
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"""
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获取对话历史
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Args:
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conversation_id: 对话会话ID
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limit: 返回消息数量（默认20条）
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"""
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try:
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messages = await mongodb.get_conversation_history(conversation_id, limit=limit)
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return ConversationHistoryResponse(
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success=True,
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messages=messages
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)
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except Exception as e:
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logger.error(f"获取对话历史失败: {e}")
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return ConversationHistoryResponse(
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success=False,
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messages=[]
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)
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@router.delete("/{conversation_id}")
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async def delete_conversation(conversation_id: str):
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"""
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删除对话会话
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Args:
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conversation_id: 对话会话ID
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"""
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try:
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success = await mongodb.delete_conversation(conversation_id)
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return {"success": success}
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except Exception as e:
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logger.error(f"删除对话失败: {e}")
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return {"success": False, "error": str(e)}
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@router.get("/all", response_model=ConversationListResponse)
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async def list_conversations(limit: int = 50, skip: int = 0):
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"""
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获取会话列表
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Args:
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limit: 返回数量
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skip: 跳过数量
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"""
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try:
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conversations = await mongodb.list_conversations(limit=limit, skip=skip)
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return ConversationListResponse(
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success=True,
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conversations=conversations
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)
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except Exception as e:
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logger.error(f"获取会话列表失败: {e}")
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return ConversationListResponse(
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success=False,
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conversations=[]
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) |