Anthropic
Managed Agents
完整指南

npm install @anthropic-ai/sdk
# 或
bun add @anthropic-ai/sdk

import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic({
  apiKey: process.env.ANTHROPIC_API_KEY,
});

async function runAgent() {
  // 步骤 1: 创建 Agent（一次性，可复用）
  const agent = await client.beta.agents.create({
    name: "Coding Assistant",
    model: "claude-sonnet-4-6",
    system:
      "You are a helpful coding assistant. Write clean, " +
      "well-documented code and explain your decisions.",
    tools: [{ type: "agent_toolset_20260401" }],
  });
  console.log(`Agent created: ${agent.id}`);

  // 步骤 2: 创建 Environment
  const environment = await client.beta.environments.create({
    name: "quickstart-env",
    config: {
      type: "cloud",
      networking: { type: "unrestricted" },
    },
  });

  // 步骤 3: 创建 Session
  const session = await client.beta.sessions.create({
    agent: agent.id,
    environment_id: environment.id,
    title: "Fibonacci Task",
  });

  // 步骤 4: 建立 SSE 流并发送消息
  const stream = await client.beta.sessions.events.stream(session.id);

  // 发送用户消息
  await client.beta.sessions.events.send(session.id, {
    events: [
      {
        type: "user.message",
        content: [
          {
            type: "text",
            text: "创建一个 Fibonacci 数列生成脚本，包含单元测试。",
          },
        ],
      },
    ],
  });

  // 消费事件流
  for await (const event of stream) {
    switch (event.type) {
      case "agent.message":
        console.log("🤖 Agent:", event.content);
        break;
      case "agent.tool_use":
        console.log(`🔧 工具: [${event.name}]`);
        break;
      case "agent.tool_result":
        console.log("✅ 结果:", String(event.content).slice(0, 200));
        break;
      case "session.status_idle":
        console.log("✨ 任务完成");
        stream.return(); // 关闭流
        break;
      case "session.status_error":
        console.error("❌ 错误:", event);
        stream.return();
        break;
    }
  }
}

runAgent().catch(console.error);

interface AgentRunOptions {
  agentId: string;       // 复用已存在的 Agent
  environmentId: string; // 复用已存在的 Environment
  prompt: string;
  onToolUse?: (name: string, input: unknown) => void;
  onMessage?: (content: string) => void;
  timeoutMs?: number;    // 默认 5 分钟
}

async function runAgentTask(opts: AgentRunOptions): Promise {
  const { agentId, environmentId, prompt, timeoutMs = 300_000 } = opts;

  const session = await client.beta.sessions.create({
    agent: agentId,
    environment_id: environmentId,
    title: `Task — ${new Date().toISOString()}`,
  });

  const controller = new AbortController();
  const timeout = setTimeout(() => controller.abort(), timeoutMs);

  try {
    const stream = await client.beta.sessions.events.stream(session.id, {
      signal: controller.signal,
    });

    await client.beta.sessions.events.send(session.id, {
      events: [{ type: "user.message", content: [{ type: "text", text: prompt }] }],
    });

    for await (const event of stream) {
      if (event.type === "agent.message") opts.onMessage?.(event.content as string);
      if (event.type === "agent.tool_use") opts.onToolUse?.(event.name, event.input);
      if (event.type === "session.status_idle") break;
      if (event.type === "session.status_error") throw new Error(`Session error: ${JSON.stringify(event)}`);
    }
  } finally {
    clearTimeout(timeout);
  }
}