👥 多 Agent 协作

@dataclass
class AgentRole:
    """Agent 角色定义"""
    name: str
    role: str           # 角色名称
    skills: List[str]   # 核心技能
    system_prompt: str  # 角色提示词
    tools: List[str]    # 可用工具
    
class RoleManager:
    def __init__(self):
        self.roles = {
            "planner": AgentRole(
                name="规划师",
                role="任务分解与规划",
                skills=["task_analysis", "planning"],
                system_prompt="你是一个专业的任务规划师..."
            ),
            "executor": AgentRole(
                name="执行者",
                role="具体任务执行",
                skills=["coding", "writing", "analysis"],
                system_prompt="你是一个专业的执行者..."
            ),
            "reviewer": AgentRole(
                name="评审员",
                role="质量审查与反馈",
                skills=["review", "critique", "evaluation"],
                system_prompt="你是一个严格的质量评审员..."
            ),
        }

class DynamicRoleAssignment:
    def assign_roles(self, task: Task, agents: List[Agent]):
        """基于能力匹配动态分配角色"""
        scores = {}
        for agent in agents:
            scores[agent.id] = self.compute_fit_score(
                agent.capabilities, task.required_skills
            )
        
        # 排序并分配
        sorted_agents = sorted(scores.items(), key=lambda x: -x[1])
        role_assignments = {}
        for role, (agent_id, score) in zip(task.roles, sorted_agents):
            if score > self.threshold:
                role_assignments[role] = agent_id
        
        return role_assignments

class VotingSystem:
    def vote(self, options: List[str], agents: List[Agent]) -> str:
        """多 Agent 投票决策"""
        votes = {}
        for agent in agents:
            choice = agent.vote(options, context=self.context)
            votes[choice] = votes.get(choice, 0) + 1
        
        # 多数决
        winner = max(votes.items(), key=lambda x: x[1])
        
        # 计算置信度
        confidence = winner[1] / len(agents)
        
        return winner[0], confidence

from crewai import Agent, Task, Crew, Process

# 定义 Agent
researcher = Agent(
    role="市场分析师",
    goal="分析市场趋势并识别机会",
    backstory="你是一位经验丰富的市场分析师...",
    tools=[search_tool, analyzer_tool],
    verbose=True
)

writer = Agent(
    role="内容作家",
    goal="基于分析结果撰写专业报告",
    backstory="你是一位专业的技术文档作家...",
    tools=[writer_tool, formatter_tool]
)

# 定义任务
research_task = Task(
    description="分析{行业}市场的最新趋势",
    agent=researcher,
    expected_output="市场分析报告"
)

write_task = Task(
    description="基于研究报告撰写执行摘要",
    agent=writer,
    expected_output="执行摘要文档"
)

# 组建 Crew
crew = Crew(
    agents=[researcher, writer],
    tasks=[research_task, write_task],
    process=Process.sequential  # 串行执行
)

result = crew.kickoff()

import autogen

# 创建 Agent
user_proxy = autogen.UserProxyAgent(
    name="UserProxy",
    human_input_mode="NEVER",
    code_execution_config={"work_dir": "coding"}
)

assistant = autogen.AssistantAgent(
    name="Assistant",
    llm_config={"config_list": [{"model": "gpt-4"}]}
)

# 发起对话
user_proxy.initiate_chat(
    assistant,
    message="请帮我写一个 Python 函数，实现快速排序"
)