from typing import Dict, Optional
from pydantic import BaseModel

class AgentInfo(BaseModel):
    """
    表示一个 Agent 实例的信息。
    """
    id: str
    agent_type: str
    mcp_endpoint: str  # MCP 服务的访问地址 (e.g., "http://localhost:8001")
    status: str = "running"  # Agent 的状态 (e.g., "running", "stopped", "error")
    created_at: str
    last_heartbeat: str
    metadata: Dict = {} # 存储其他元数据，如资源使用情况、版本等

class CreateAgentRequest(BaseModel):
    """
    创建 Agent 实例的请求模型。
    """
    agent_type: str
    image_name: str  # Docker 镜像名称 (e.g., "my-echo-agent:latest")
    env_vars: Dict[str, str] = {}  # 环境变量字典
    resource_limits: Dict = {}  # 资源限制 (e.g., {"cpu": "0.5", "memory": "512m"})
    config: Dict = {} # Agent 自身的配置信息

class AgentUpdateRequest(BaseModel):
    """
    更新 Agent 实例信息的请求模型。
    """
    status: Optional[str] = None
    mcp_endpoint: Optional[str] = None
    last_heartbeat: Optional[str] = None
    metadata: Optional[Dict] = None