feat: 实现智能指令的格式转换和文档编辑功能
主要更新： - 新增 transform 意图：支持 Word/Excel/Markdown 格式互转 - 新增 edit 意图：使用 LLM 润色编辑文档内容 - 智能指令接口增加异步执行模式（async_execute 参数） - 修复 Word 模板导出文档损坏问题（改用临时文件方式） - 优化 intent_parser 增加 transform/edit 关键词识别 新增文件： - app/api/endpoints/instruction.py: 智能指令 API 端点 - app/services/multi_doc_reasoning_service.py: 多文档推理服务 其他优化： - RAG 服务混合搜索（BM25 + 向量）融合 - 模板填充服务表头匹配增强 - Word AI 解析服务返回结构完善 - 前端 InstructionChat 组件对接真实 API
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backend/app/api/endpoints/instruction.py
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439
backend/app/api/endpoints/instruction.py
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"""
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智能指令 API 接口
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支持自然语言指令解析和执行
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"""
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import logging
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import uuid
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from typing import Any, Dict, List, Optional
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from fastapi import APIRouter, HTTPException, Query, BackgroundTasks
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from pydantic import BaseModel
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from app.instruction.intent_parser import intent_parser
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from app.instruction.executor import instruction_executor
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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="/instruction", tags=["智能指令"])
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# ==================== 请求/响应模型 ====================
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class InstructionRequest(BaseModel):
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instruction: str
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doc_ids: Optional[List[str]] = None # 关联的文档 ID 列表
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context: Optional[Dict[str, Any]] = None # 额外上下文
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class IntentRecognitionResponse(BaseModel):
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success: bool
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intent: str
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params: Dict[str, Any]
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message: str
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class InstructionExecutionResponse(BaseModel):
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success: bool
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intent: str
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result: Dict[str, Any]
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message: str
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# ==================== 接口 ====================
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@router.post("/recognize", response_model=IntentRecognitionResponse)
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async def recognize_intent(request: InstructionRequest):
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"""
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意图识别接口
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将自然语言指令解析为结构化的意图和参数
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示例指令:
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- "提取文档中的医院数量和床位数"
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- "根据这些数据填表"
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- "总结一下这份文档"
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- "对比这两个文档的差异"
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"""
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try:
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intent, params = await intent_parser.parse(request.instruction)
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# 添加文档关联信息
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if request.doc_ids:
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params["document_refs"] = [f"doc_{doc_id}" for doc_id in request.doc_ids]
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intent_names = {
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"extract": "信息提取",
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"fill_table": "表格填写",
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"summarize": "摘要总结",
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"question": "智能问答",
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"search": "文档搜索",
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"compare": "对比分析",
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"transform": "格式转换",
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"edit": "文档编辑",
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"unknown": "未知"
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}
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return IntentRecognitionResponse(
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success=True,
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intent=intent,
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params=params,
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message=f"识别到意图: {intent_names.get(intent, intent)}"
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)
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except Exception as e:
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logger.error(f"意图识别失败: {e}")
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return IntentRecognitionResponse(
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success=False,
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intent="error",
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params={},
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message=f"意图识别失败: {str(e)}"
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)
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@router.post("/execute")
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async def execute_instruction(
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background_tasks: BackgroundTasks,
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request: InstructionRequest,
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async_execute: bool = Query(False, description="是否异步执行（仅返回任务ID）")
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):
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"""
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指令执行接口
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解析并执行自然语言指令
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示例:
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- 指令: "提取文档1中的医院数量"
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返回: {"extracted_data": {"医院数量": ["38710个"]}}
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- 指令: "填表"
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返回: {"filled_data": {...}}
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设置 async_execute=true 可异步执行，返回任务ID用于查询进度
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"""
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task_id = str(uuid.uuid4())
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if async_execute:
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# 异步模式：立即返回任务ID，后台执行
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background_tasks.add_task(
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_execute_instruction_task,
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task_id=task_id,
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instruction=request.instruction,
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doc_ids=request.doc_ids,
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context=request.context
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)
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return {
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"success": True,
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"task_id": task_id,
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"message": "指令已提交执行",
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"status_url": f"/api/v1/tasks/{task_id}"
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}
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# 同步模式：等待执行完成
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return await _execute_instruction_task(task_id, request.instruction, request.doc_ids, request.context)
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async def _execute_instruction_task(
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task_id: str,
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instruction: str,
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doc_ids: Optional[List[str]],
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context: Optional[Dict[str, Any]]
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) -> InstructionExecutionResponse:
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"""执行指令的后台任务"""
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from app.core.database import redis_db, mongodb as mongo_client
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try:
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# 记录任务
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try:
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await mongo_client.insert_task(
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task_id=task_id,
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task_type="instruction_execute",
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status="processing",
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message="正在执行指令"
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)
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except Exception:
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pass
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# 构建执行上下文
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ctx: Dict[str, Any] = context or {}
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# 如果提供了文档 ID，获取文档内容
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if doc_ids:
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docs = []
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for doc_id in doc_ids:
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doc = await mongo_client.get_document(doc_id)
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if doc:
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docs.append(doc)
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if docs:
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ctx["source_docs"] = docs
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logger.info(f"指令执行上下文: 关联了 {len(docs)} 个文档")
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# 执行指令
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result = await instruction_executor.execute(instruction, ctx)
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# 更新任务状态
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try:
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await mongo_client.update_task(
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task_id=task_id,
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status="success",
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message="执行完成",
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result=result
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)
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except Exception:
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pass
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return InstructionExecutionResponse(
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success=result.get("success", False),
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intent=result.get("intent", "unknown"),
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result=result,
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message=result.get("message", "执行完成")
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)
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except Exception as e:
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logger.error(f"指令执行失败: {e}")
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try:
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await mongo_client.update_task(
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task_id=task_id,
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status="failure",
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message="执行失败",
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error=str(e)
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)
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except Exception:
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pass
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return InstructionExecutionResponse(
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success=False,
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intent="error",
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result={"error": str(e)},
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message=f"指令执行失败: {str(e)}"
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)
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@router.post("/chat")
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async def instruction_chat(
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background_tasks: BackgroundTasks,
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request: InstructionRequest,
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async_execute: bool = Query(False, description="是否异步执行（仅返回任务ID）")
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):
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"""
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指令对话接口
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支持多轮对话的指令执行
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示例对话流程:
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1. 用户: "上传一些文档"
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2. 系统: "请上传文档"
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3. 用户: "提取其中的医院数量"
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4. 系统: 返回提取结果
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设置 async_execute=true 可异步执行，返回任务ID用于查询进度
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"""
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task_id = str(uuid.uuid4())
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if async_execute:
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# 异步模式：立即返回任务ID，后台执行
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background_tasks.add_task(
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_execute_chat_task,
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task_id=task_id,
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instruction=request.instruction,
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doc_ids=request.doc_ids,
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context=request.context
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)
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return {
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"success": True,
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"task_id": task_id,
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"message": "指令已提交执行",
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"status_url": f"/api/v1/tasks/{task_id}"
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}
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# 同步模式：等待执行完成
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return await _execute_chat_task(task_id, request.instruction, request.doc_ids, request.context)
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async def _execute_chat_task(
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task_id: str,
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instruction: str,
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doc_ids: Optional[List[str]],
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context: Optional[Dict[str, Any]]
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):
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"""执行指令对话的后台任务"""
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from app.core.database import mongodb as mongo_client
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try:
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# 记录任务
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try:
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await mongo_client.insert_task(
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task_id=task_id,
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task_type="instruction_chat",
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status="processing",
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message="正在处理对话"
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)
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except Exception:
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pass
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# 构建上下文
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ctx: Dict[str, Any] = context or {}
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# 获取关联文档
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if doc_ids:
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docs = []
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for doc_id in doc_ids:
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doc = await mongo_client.get_document(doc_id)
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if doc:
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docs.append(doc)
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if docs:
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ctx["source_docs"] = docs
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# 执行指令
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result = await instruction_executor.execute(instruction, ctx)
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# 根据意图类型添加友好的响应消息
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response_messages = {
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"extract": f"已提取 {len(result.get('extracted_data', {}))} 个字段的数据",
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"fill_table": f"填表完成，填写了 {len(result.get('result', {}).get('filled_data', {}))} 个字段",
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"summarize": "已生成文档摘要",
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"question": "已找到相关答案",
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"search": f"找到 {len(result.get('results', []))} 条相关内容",
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"compare": f"对比了 {len(result.get('comparison', []))} 个文档",
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"edit": "编辑操作已完成",
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"transform": "格式转换已完成",
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"unknown": "无法理解该指令，请尝试更明确的描述"
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}
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response = {
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"success": result.get("success", False),
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"intent": result.get("intent", "unknown"),
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"result": result,
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"message": response_messages.get(result.get("intent", ""), result.get("message", "")),
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"hint": _get_intent_hint(result.get("intent", ""))
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}
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# 更新任务状态
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try:
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await mongo_client.update_task(
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task_id=task_id,
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status="success",
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message="处理完成",
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result=response
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)
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except Exception:
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pass
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return response
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except Exception as e:
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logger.error(f"指令对话失败: {e}")
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try:
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await mongo_client.update_task(
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task_id=task_id,
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status="failure",
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message="处理失败",
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error=str(e)
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)
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except Exception:
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pass
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return {
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"success": False,
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"error": str(e),
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"message": f"处理失败: {str(e)}"
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}
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def _get_intent_hint(intent: str) -> Optional[str]:
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"""根据意图返回下一步提示"""
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hints = {
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"extract": "您可以继续说 '提取更多字段' 或 '将数据填入表格'",
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"fill_table": "您可以提供表格模板或说 '帮我创建一个表格'",
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"question": "您可以继续提问或说 '总结一下这些内容'",
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"search": "您可以查看搜索结果或说 '对比这些内容'",
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"unknown": "您可以尝试: '提取数据'、'填表'、'总结'、'问答' 等指令"
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}
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return hints.get(intent)
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@router.get("/intents")
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async def list_supported_intents():
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"""
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获取支持的意图类型列表
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返回所有可用的自然语言指令类型
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"""
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return {
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"intents": [
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{
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"intent": "extract",
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"name": "信息提取",
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"examples": [
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"提取文档中的医院数量",
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"抽取所有机构的名称",
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"找出表格中的数据"
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],
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"params": ["field_refs", "document_refs"]
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},
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{
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"intent": "fill_table",
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"name": "表格填写",
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"examples": [
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"填表",
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"根据这些数据填写表格",
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"帮我填到Excel里"
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],
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"params": ["template", "document_refs"]
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},
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{
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"intent": "summarize",
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"name": "摘要总结",
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"examples": [
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"总结一下这份文档",
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"生成摘要",
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"概括主要内容"
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],
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"params": ["document_refs"]
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},
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{
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"intent": "question",
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"name": "智能问答",
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"examples": [
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"这段话说的是什么？",
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"有多少家医院？",
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"解释一下这个概念"
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],
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"params": ["question", "focus"]
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},
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{
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"intent": "search",
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"name": "文档搜索",
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"examples": [
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"搜索相关内容",
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"找找看有哪些机构",
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"查询医院相关的数据"
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],
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"params": ["field_refs", "question"]
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},
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{
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"intent": "compare",
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"name": "对比分析",
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"examples": [
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"对比这两个文档",
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"比较一下差异",
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"找出不同点"
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],
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"params": ["document_refs"]
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},
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{
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"intent": "edit",
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"name": "文档编辑",
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"examples": [
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"润色这段文字",
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"修改格式",
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"添加注释"
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],
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"params": []
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}
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]
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}
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