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app/controllers/multi_agent_controller.py
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app/controllers/multi_agent_controller.py
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"""多 Agent 控制器"""
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import uuid
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from fastapi import APIRouter, Depends, Query, Path
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from sqlalchemy.orm import Session
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from app.db import get_db
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from app.dependencies import get_current_user
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from app.core.response_utils import success
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from app.core.logging_config import get_business_logger
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from app.schemas import multi_agent_schema
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from app.schemas.response_schema import PageData, PageMeta
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from app.services.multi_agent_service import MultiAgentService
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from app.models import User
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router = APIRouter(prefix="/apps", tags=["Multi-Agent"])
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logger = get_business_logger()
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# ==================== 多 Agent 配置管理 ====================
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@router.post(
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"/{app_id}/multi-agent",
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summary="创建多 Agent 配置"
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)
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def create_multi_agent_config(
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app_id: uuid.UUID = Path(..., description="应用 ID"),
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data: multi_agent_schema.MultiAgentConfigCreate = ...,
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current_user: User = Depends(get_current_user),
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db: Session = Depends(get_db),
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):
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"""创建多 Agent 配置
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支持四种编排模式：
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- sequential: 顺序执行
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- parallel: 并行执行
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- conditional: 条件路由
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- loop: 循环执行
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"""
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service = MultiAgentService(db)
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config = service.create_config(
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app_id=app_id,
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data=data,
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created_by=current_user.id
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)
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return success(
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data=multi_agent_schema.MultiAgentConfigSchema.model_validate(config),
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msg="多 Agent 配置创建成功"
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)
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@router.get(
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"/{app_id}/multi-agent",
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summary="获取当前应用的最新有效多 Agent 配置"
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)
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def get_multi_agent_configs(
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app_id: uuid.UUID = Path(..., description="应用 ID"),
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current_user: User = Depends(get_current_user),
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db: Session = Depends(get_db),
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):
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"""获取指定应用的最新有效多 Agent 配置，如果不存在则返回默认模板"""
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service = MultiAgentService(db)
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# 通过 app_id 获取最新有效配置（已转换 agent_id 为 app_id）
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config = service.get_multi_agent_configs(app_id)
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if not config:
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# 返回默认模板
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default_template = {
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"app_id": str(app_id),
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"master_agent_id": None,
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"master_agent_name": None,
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"orchestration_mode": "conditional",
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"sub_agents": [],
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"routing_rules": [],
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"execution_config": {
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"max_iterations": 10,
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"timeout": 300,
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"enable_parallel": False,
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"error_handling": "stop"
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},
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"aggregation_strategy": "merge",
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}
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return success(
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data=default_template,
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msg="该应用暂无配置，返回默认模板"
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)
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# config 已经是字典格式，直接返回
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return success(data=config)
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@router.put(
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"/{app_id}/multi-agent",
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summary="更新多 Agent 配置"
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)
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def update_multi_agent_config(
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app_id: uuid.UUID = Path(..., description="应用 ID"),
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data: multi_agent_schema.MultiAgentConfigUpdate = ...,
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current_user: User = Depends(get_current_user),
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db: Session = Depends(get_db),
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):
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"""更新多 Agent 配置"""
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service = MultiAgentService(db)
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config = service.update_config(app_id, data)
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return success(
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data=multi_agent_schema.MultiAgentConfigSchema.model_validate(config),
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msg="多 Agent 配置更新成功"
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)
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@router.delete(
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"/{app_id}/multi-agent",
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summary="删除多 Agent 配置"
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)
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def delete_multi_agent_config(
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app_id: uuid.UUID = Path(..., description="应用 ID"),
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current_user: User = Depends(get_current_user),
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db: Session = Depends(get_db),
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):
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"""删除多 Agent 配置"""
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service = MultiAgentService(db)
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service.delete_config(app_id)
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return success(msg="多 Agent 配置删除成功")
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# ==================== 多 Agent 运行 ====================
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@router.post(
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"/{app_id}/multi-agent/run",
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summary="运行多 Agent 任务"
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)
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async def run_multi_agent(
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app_id: uuid.UUID = Path(..., description="应用 ID"),
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request: multi_agent_schema.MultiAgentRunRequest = ...,
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current_user: User = Depends(get_current_user),
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db: Session = Depends(get_db),
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):
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"""运行多 Agent 任务
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根据配置的编排模式执行多个 Agent：
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- sequential: 按优先级顺序执行
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- parallel: 并行执行所有 Agent
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- conditional: 根据条件选择 Agent
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- loop: 循环执行直到满足条件
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"""
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service = MultiAgentService(db)
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result = await service.run(app_id, request)
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return success(
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data=multi_agent_schema.MultiAgentRunResponse(**result),
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msg="多 Agent 任务执行成功"
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)
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# ==================== 智能路由测试 ====================
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@router.post(
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"/{app_id}/multi-agent/test-routing",
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summary="测试智能路由"
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)
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async def test_routing(
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app_id: uuid.UUID = Path(..., description="应用 ID"),
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request: multi_agent_schema.RoutingTestRequest = ...,
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current_user: User = Depends(get_current_user),
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db: Session = Depends(get_db),
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):
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"""测试智能路由功能
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支持三种路由模式：
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- keyword: 仅使用关键词路由
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- llm: 使用 LLM 路由（需要提供 routing_model_id）
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- hybrid: 混合路由（关键词 + LLM）
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参数：
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- message: 测试消息
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- conversation_id: 会话 ID（可选）
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- routing_model_id: 路由模型 ID（可选，用于 LLM 路由）
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- use_llm: 是否启用 LLM（默认 False）
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- keyword_threshold: 关键词置信度阈值（默认 0.8）
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"""
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from app.services.conversation_state_manager import ConversationStateManager
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from app.services.llm_router import LLMRouter
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from app.models import ModelConfig
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# 1. 获取多 Agent 配置
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service = MultiAgentService(db)
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config = service.get_config(app_id)
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if not config:
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return success(
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data=None,
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msg="应用未配置多 Agent，无法测试路由"
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)
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# 2. 准备子 Agent 信息
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sub_agents = {}
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for sub_agent_info in config.sub_agents:
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agent_id = sub_agent_info["agent_id"]
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sub_agents[agent_id] = {
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"name": sub_agent_info.get("name", agent_id),
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"role": sub_agent_info.get("role", "")
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}
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# 3. 获取路由模型（如果指定）
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routing_model = None
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if request.routing_model_id:
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routing_model = db.get(ModelConfig, request.routing_model_id)
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if not routing_model:
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return success(
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data=None,
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msg=f"路由模型不存在: {request.routing_model_id}"
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)
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# 4. 初始化路由器
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state_manager = ConversationStateManager()
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router = LLMRouter(
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db=db,
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state_manager=state_manager,
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routing_rules=config.routing_rules or [],
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sub_agents=sub_agents,
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routing_model_config=routing_model,
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use_llm=request.use_llm and routing_model is not None
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)
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# 5. 设置阈值
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if request.keyword_threshold:
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router.keyword_high_confidence_threshold = request.keyword_threshold
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# 6. 执行路由
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try:
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routing_result = await router.route(
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message=request.message,
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conversation_id=str(request.conversation_id) if request.conversation_id else None,
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force_new=request.force_new
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)
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# 7. 获取 Agent 信息
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agent_id = routing_result["agent_id"]
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agent_info = sub_agents.get(agent_id, {})
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# 8. 构建响应
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response_data = {
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"message": request.message,
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"routing_result": {
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"agent_id": agent_id,
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"agent_name": agent_info.get("name", agent_id),
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"agent_role": agent_info.get("role", ""),
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"confidence": routing_result["confidence"],
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"strategy": routing_result["strategy"],
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"topic": routing_result["topic"],
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"topic_changed": routing_result["topic_changed"],
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"reason": routing_result["reason"],
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"routing_method": routing_result["routing_method"]
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},
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"cmulti-agent/batch-test-routingonfig_info": {
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"use_llm": request.use_llm and routing_model is not None,
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"routing_model": routing_model.name if routing_model else None,
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"keyword_threshold": router.keyword_high_confidence_threshold,
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"total_sub_agents": len(sub_agents)
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}
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}
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return success(
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data=response_data,
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msg="路由测试成功"
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)
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except Exception as e:
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logger.error(f"路由测试失败: {str(e)}")
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return success(
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data=None,
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msg=f"路由测试失败: {str(e)}"
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)
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@router.post(
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"/{app_id}/",
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summary="批量测试智能路由"
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)
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async def batch_test_routing(
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app_id: uuid.UUID = Path(..., description="应用 ID"),
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request: multi_agent_schema.BatchRoutingTestRequest = ...,
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current_user: User = Depends(get_current_user),
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db: Session = Depends(get_db),
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):
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"""批量测试智能路由功能
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用于测试多条消息的路由效果，并统计准确率
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参数：
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- test_cases: 测试用例列表
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- routing_model_id: 路由模型 ID（可选）
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- use_llm: 是否启用 LLM
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- keyword_threshold: 关键词置信度阈值
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"""
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from app.services.conversation_state_manager import ConversationStateManager
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from app.services.llm_router import LLMRouter
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from app.models import ModelConfig
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# 1. 获取多 Agent 配置
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service = MultiAgentService(db)
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config = service.get_config(app_id)
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if not config:
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return success(
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data=None,
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msg="应用未配置多 Agent，无法测试路由"
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)
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# 2. 准备子 Agent 信息
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sub_agents = {}
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for sub_agent_info in config.sub_agents:
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agent_id = sub_agent_info["agent_id"]
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sub_agents[agent_id] = {
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"name": sub_agent_info.get("name", agent_id),
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"role": sub_agent_info.get("role", "")
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}
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# 3. 获取路由模型
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routing_model = None
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if request.routing_model_id:
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routing_model = db.get(ModelConfig, request.routing_model_id)
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# 4. 初始化路由器
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state_manager = ConversationStateManager()
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router = LLMRouter(
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db=db,
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state_manager=state_manager,
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routing_rules=config.routing_rules or [],
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sub_agents=sub_agents,
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routing_model_config=routing_model,
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use_llm=request.use_llm and routing_model is not None
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)
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if request.keyword_threshold:
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router.keyword_high_confidence_threshold = request.keyword_threshold
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# 5. 批量测试
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results = []
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correct_count = 0
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total_count = len(request.test_cases)
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for test_case in request.test_cases:
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try:
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routing_result = await router.route(
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message=test_case.message,
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conversation_id=str(uuid.uuid4()) # 每个测试用例使用独立会话
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)
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agent_id = routing_result["agent_id"]
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agent_info = sub_agents.get(agent_id, {})
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# 判断是否正确
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is_correct = None
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if test_case.expected_agent_id:
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is_correct = (agent_id == str(test_case.expected_agent_id))
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if is_correct:
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correct_count += 1
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results.append({
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"message": test_case.message,
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"description": test_case.description,
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"routed_agent_id": agent_id,
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"routed_agent_name": agent_info.get("name"),
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"expected_agent_id": str(test_case.expected_agent_id) if test_case.expected_agent_id else None,
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"is_correct": is_correct,
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"confidence": routing_result["confidence"],
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"routing_method": routing_result["routing_method"],
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"strategy": routing_result["strategy"]
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})
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except Exception as e:
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logger.error(f"测试用例失败: {test_case.message}, 错误: {str(e)}")
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results.append({
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"message": test_case.message,
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"description": test_case.description,
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"error": str(e)
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})
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# 6. 统计
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accuracy = None
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if correct_count > 0:
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total_with_expected = sum(1 for r in results if r.get("expected_agent_id"))
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if total_with_expected > 0:
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accuracy = correct_count / total_with_expected * 100
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response_data = {
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"total_count": total_count,
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"correct_count": correct_count,
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"accuracy": accuracy,
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"results": results,
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"config_info": {
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"use_llm": request.use_llm and routing_model is not None,
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"routing_model": routing_model.name if routing_model else None,
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"keyword_threshold": router.keyword_high_confidence_threshold
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}
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}
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return success(
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data=response_data,
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msg=f"批量测试完成，准确率: {accuracy:.1f}%" if accuracy else "批量测试完成"
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)
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