完整实现 Swarm 多智能体协作系统
- 新增 CLIPluginAdapter 统一接口 (backend/app/core/agent_adapter.py) - 新增 LLM 服务层，支持 Anthropic/OpenAI/DeepSeek/Ollama (backend/app/services/llm_service.py) - 新增 Agent 执行引擎，支持文件锁自动管理 (backend/app/services/agent_executor.py) - 新增 NativeLLMAgent 原生 LLM 适配器 (backend/app/adapters/native_llm_agent.py) - 新增进程管理器 (backend/app/services/process_manager.py) - 新增 Agent 控制 API (backend/app/routers/agents_control.py) - 新增 WebSocket 实时通信 (backend/app/routers/websocket.py) - 更新前端 AgentsPage，支持启动/停止 Agent - 测试通过：Agent 启动、批量操作、栅栏同步 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Claude Code
497
backend/app/adapters/native_llm_agent.py
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497
backend/app/adapters/native_llm_agent.py
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@@ -0,0 +1,497 @@
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"""
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原生 LLM Agent 适配器
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直接调用 LLM API 实现 Agent，不需要外部进程。
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这是主要使用的适配器类型。
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"""
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import asyncio
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import logging
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from typing import Dict, Optional, Any
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from datetime import datetime
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from ..core.agent_adapter import (
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CLIPluginAdapter,
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Task,
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Result,
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AgentCapabilities
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)
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from ..services.llm_service import ModelRouter, get_llm_service
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from ..services.agent_executor import AgentExecutor, get_agent_executor
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from ..services.meeting_scheduler import get_meeting_scheduler
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from ..services.agent_registry import get_agent_registry
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from ..services.heartbeat import get_heartbeat_service
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logger = logging.getLogger(__name__)
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class NativeLLMAgent(CLIPluginAdapter):
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"""
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原生 LLM Agent
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直接通过 LLM API 实现的 Agent，特点：
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1. 无需外部进程，完全异步
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2. 支持所有主流 LLM 提供商
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3. 自动管理资源（文件锁、心跳）
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4. 支持会议协作
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"""
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def __init__(
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self,
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agent_id: str,
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name: str,
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role: str,
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model: str,
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config: Dict[str, Any] = None,
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llm_service: ModelRouter = None,
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executor: AgentExecutor = None
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):
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self._id = agent_id
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self._name = name
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self._role = role
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self._model = model
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self.config = config or {}
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self._version = "1.0.0"
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# 获取服务
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self.llm_service = llm_service or get_llm_service()
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self.executor = executor or get_agent_executor(self.llm_service)
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self.scheduler = get_meeting_scheduler()
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self.registry = get_agent_registry()
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self.heartbeat_service = get_heartbeat_service()
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# 状态
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self._is_running = False
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self._current_task: Optional[Task] = None
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logger.info(f"NativeLLMAgent 初始化: {self._id} ({self._name})")
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# ========== 属性 ==========
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@property
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def id(self) -> str:
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return self._id
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@property
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def name(self) -> str:
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return self._name
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@property
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def version(self) -> str:
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return self._version
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@property
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def role(self) -> str:
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return self._role
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@property
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def model(self) -> str:
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return self._model
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@property
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def capabilities(self) -> AgentCapabilities:
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"""返回 Agent 能力声明"""
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return AgentCapabilities(
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can_execute_code=True,
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can_read_files=True,
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can_write_files=True,
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can_analyze_code=True,
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can_generate_tests=self._role in ["developer", "qa"],
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can_review_code=self._role == "reviewer",
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supported_languages=["Python", "JavaScript", "TypeScript", "Java", "Go"],
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max_context_length=200000
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)
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@property
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def is_running(self) -> bool:
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return self._is_running
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# ========== 核心能力 ==========
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async def execute(self, task: Task) -> Result:
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"""
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执行任务
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通过 AgentExecutor 协调 LLM 调用和资源管理
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"""
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self._current_task = task
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try:
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# 获取或注册 Agent 信息
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agent_info = await self._ensure_registered()
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# 使用执行引擎执行任务
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result = await self.executor.execute_task(
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agent_info,
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task,
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context=self.config.get("context", {})
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)
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logger.info(f"任务执行完成: {task.task_id} -> {result.success}")
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return result
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except Exception as e:
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logger.error(f"任务执行失败: {task.task_id}: {e}", exc_info=True)
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return Result(
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success=False,
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output="",
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error=str(e)
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)
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finally:
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self._current_task = None
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async def join_meeting(self, meeting_id: str, timeout: int = 300) -> str:
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"""
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加入会议等待队列（栅栏同步）
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当最后一个参与者到达时，会议自动开始
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"""
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logger.info(f"Agent {self._id} 等待会议: {meeting_id}")
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# 更新心跳为等待状态
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await self.update_heartbeat("waiting", f"等待会议: {meeting_id}", 0)
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# 调用会议调度器
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result = await self.scheduler.wait_for_meeting(
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self._id,
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meeting_id,
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timeout=timeout
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)
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logger.info(f"会议 {meeting_id} 结果: {result}")
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return result
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async def write_state(self, state: Dict) -> None:
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"""
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写入状态到注册表
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状态包含：当前任务、进度、临时数据等
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"""
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task = state.get("task", "")
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progress = state.get("progress", 0)
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await self.registry.update_state(self._id, task, progress)
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logger.debug(f"状态已更新: {self._id} -> {progress}%")
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async def read_others(self, agent_id: str) -> Dict:
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"""
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读取其他 Agent 的状态
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用于 Agent 之间互相了解工作状态
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"""
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agent = await self.registry.get_agent(agent_id)
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if not agent:
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return {"error": f"Agent {agent_id} 不存在"}
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state = await self.registry.get_state(agent_id)
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heartbeat = await self.heartbeat_service.get_heartbeat(agent_id)
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return {
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"agent": {
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"agent_id": agent.agent_id,
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"name": agent.name,
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"role": agent.role,
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"model": agent.model,
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"status": agent.status
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},
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"state": {
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"current_task": state.current_task if state else None,
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"progress": state.progress if state else 0
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} if state else None,
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"heartbeat": {
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"status": heartbeat.status if heartbeat else None,
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"last_seen": heartbeat.last_seen.isoformat() if heartbeat else None,
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"is_alive": heartbeat.is_alive() if heartbeat else False
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} if heartbeat else None
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}
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async def update_heartbeat(self, status: str, task: str = "", progress: int = 0) -> None:
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"""
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更新心跳
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参数:
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status: working, waiting, idle, error
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task: 当前任务描述
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progress: 进度 0-100
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"""
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await self.heartbeat_service.update_heartbeat(
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self._id,
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status,
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task,
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progress
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)
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# ========== 生命周期 ==========
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async def initialize(self) -> None:
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"""Agent 初始化"""
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logger.info(f"Agent 初始化: {self._id}")
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# 确保已注册
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await self._ensure_registered()
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# 发送初始心跳
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await self.update_heartbeat("idle", "", 0)
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self._is_running = True
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async def shutdown(self) -> None:
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"""Agent 关闭"""
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logger.info(f"Agent 关闭: {self._id}")
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# 更新状态为离线
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await self.update_heartbeat("offline", "", 0)
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self._is_running = False
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async def health_check(self) -> bool:
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"""健康检查"""
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try:
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heartbeat = await self.heartbeat_service.get_heartbeat(self._id)
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return heartbeat is not None and heartbeat.is_alive()
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except Exception:
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return False
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# ========== 会议相关 ==========
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async def propose(self, meeting_id: str, content: str, step: str = "") -> None:
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"""在会议中提出提案"""
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from ..services.meeting_recorder import get_meeting_recorder
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recorder = get_meeting_recorder()
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await recorder.add_discussion(
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meeting_id,
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self._id,
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self._role.upper(),
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content,
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step
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)
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logger.debug(f"提案已添加: {self._id} -> {meeting_id}")
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async def discuss(self, meeting_id: str, content: str, step: str = "") -> None:
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"""在会议中参与讨论"""
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await self.propose(meeting_id, content, step)
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async def vote(self, meeting_id: str, proposal_id: str, agree: bool) -> None:
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"""对提案进行投票"""
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# TODO: 实现投票机制
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logger.debug(f"投票: {self._id} -> {proposal_id}: {agree}")
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# ========== 私有方法 ==========
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async def _ensure_registered(self):
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"""确保 Agent 已注册"""
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agent = await self.registry.get_agent(self._id)
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if agent is None:
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# 注册 Agent
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agent = await self.registry.register_agent(
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self._id,
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self._name,
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self._role,
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self._model,
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self.config.get("description", f"{self._name} - {self._role}")
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)
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logger.info(f"Agent 已注册: {self._id}")
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return agent
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# ========== 高级功能 ==========
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async def collaborate_with(
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self,
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other_agent_ids: list,
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task: str,
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meeting_id: str = None
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) -> Dict:
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"""
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与其他 Agent 协作完成任务
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流程：
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1. 创建或加入会议
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2. 等待所有 Agent 到达
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3. 讨论和分工
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4. 执行分配的任务
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5. 汇总结果
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"""
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if not meeting_id:
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# 生成会议 ID
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import uuid
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meeting_id = f"meeting_{uuid.uuid4().hex[:12]}"
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# 创建会议
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await self.scheduler.create_meeting(
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meeting_id,
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f"协作任务: {task[:50]}",
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[self._id] + other_agent_ids
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)
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# 更新心跳
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await self.update_heartbeat("waiting", f"等待协作会议: {meeting_id}", 0)
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# 提出初始提案
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await self.propose(meeting_id, f"任务: {task}")
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return {
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"meeting_id": meeting_id,
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"status": "waiting",
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"participants": [self._id] + other_agent_ids
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}
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async def start_collaboration_loop(
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self,
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meeting_id: str,
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max_iterations: int = 5
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) -> Dict:
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"""
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启动协作循环
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持续参与会议讨论，直到达成共识或达到最大迭代次数
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"""
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from ..services.meeting_recorder import get_meeting_recorder
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recorder = get_meeting_recorder()
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for iteration in range(max_iterations):
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# 等待会议开始
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result = await self.join_meeting(meeting_id)
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if result == "started":
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# 获取会议信息
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meeting = await recorder.get_meeting(meeting_id)
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if meeting and meeting.status == "completed":
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return {
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"status": "consensus_reached",
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"consensus": meeting.consensus,
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"iterations": iteration + 1
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}
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# 分析当前讨论，提出自己的观点
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await self._analyze_and_respond(meeting_id)
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elif result == "timeout":
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return {
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"status": "timeout",
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"iterations": iteration + 1
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}
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return {
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"status": "max_iterations_reached",
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"iterations": max_iterations
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}
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async def _analyze_and_respond(self, meeting_id: str) -> None:
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"""分析会议讨论并响应"""
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from ..services.meeting_recorder import get_meeting_recorder
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recorder = get_meeting_recorder()
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meeting = await recorder.get_meeting(meeting_id)
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if not meeting:
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return
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# 获取最近的讨论
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recent_discussions = meeting.discussions[-5:] if meeting.discussions else []
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# 构建分析提示
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discussion_summary = "\n".join([
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f"{d.agent} ({d.timestamp}): {d.content}"
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for d in recent_discussions
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])
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response_prompt = f"""
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你是 {self._name} ({self._role})。
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以下是会议讨论的摘要:
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{discussion_summary}
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请基于你的角色 ({self._role})，给出你的回应:
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- 如果你不同意之前的提案，说明理由
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- 如果你有更好的建议，提出新方案
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- 如果你同意，可以表示支持或补充细节
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保持简洁，直接回应。
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"""
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# 调用 LLM 生成响应
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if self.llm_service:
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try:
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llm_response = await self.llm_service.route_task(
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task=response_prompt,
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messages=[
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{"role": "system", "content": f"你是 {self._name}，一个 {self._role}。"},
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{"role": "user", "content": response_prompt}
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]
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)
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# 发送响应到会议
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await self.discuss(meeting_id, llm_response.content)
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except Exception as e:
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logger.error(f"生成会议响应失败: {e}")
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class NativeLLMAgentFactory:
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"""原生 LLM Agent 工厂类"""
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@staticmethod
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async def create(
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agent_id: str,
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name: str = None,
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role: str = "developer",
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model: str = "claude-sonnet-4.6",
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config: Dict = None
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) -> NativeLLMAgent:
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"""
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创建并初始化一个 Agent
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参数:
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agent_id: Agent 唯一标识
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name: 显示名称（默认从 agent_id 生成）
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role: 角色 (architect, pm, developer, qa, reviewer)
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model: 使用的模型
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config: 额外配置
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"""
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if name is None:
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name = agent_id.replace("-", " ").title()
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agent = NativeLLMAgent(
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agent_id=agent_id,
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name=name,
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role=role,
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model=model,
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config=config
|
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)
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|
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# 初始化 Agent
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await agent.initialize()
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return agent
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|
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@staticmethod
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async def create_team(team_config: Dict) -> Dict[str, NativeLLMAgent]:
|
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"""
|
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创建一个 Agent 团队
|
||||
|
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配置格式:
|
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{
|
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"team_id": "dev-team-1",
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"agents": [
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{"id": "arch-001", "role": "architect", "model": "claude-opus-4.6"},
|
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{"id": "dev-001", "role": "developer", "model": "claude-sonnet-4.6"},
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{"id": "qa-001", "role": "qa", "model": "claude-haiku-4.6"}
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]
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||||
}
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"""
|
||||
agents = {}
|
||||
|
||||
for agent_config in team_config.get("agents", []):
|
||||
agent = await NativeLLMAgentFactory.create(
|
||||
agent_id=agent_config["id"],
|
||||
role=agent_config.get("role", "developer"),
|
||||
model=agent_config.get("model", "claude-sonnet-4.6"),
|
||||
config=agent_config.get("config", {})
|
||||
)
|
||||
agents[agent.id] = agent
|
||||
|
||||
return agents
|
||||
Reference in New Issue
Block a user