LangSmith 可观测性

export LANGSMITH_TRACING=true
export LANGSMITH_API_KEY=<your-api-key>

import { createAgent } from "@langchain/agents";

function sendEmail(to: string, subject: string, body: string): string {
    // ... 发送电子邮件的逻辑
    return `Email sent to ${to}`;
}

function searchWeb(query: string): string {
    // ... 网络搜索的逻辑
    return `Search results for: ${query}`;
}

const agent = createAgent({
    model: "gpt-5.5",
    tools: [sendEmail, searchWeb],
    systemPrompt: "You are a helpful assistant that can send emails and search the web."
});

// 运行智能体 - 所有步骤将被自动追踪
const response = await agent.invoke({
    messages: [{ role: "user", content: "Search for the latest AI news and email a summary to john@example.com" }]
});

import { LangChainTracer } from "@langchain/core/tracers/tracer_langchain";

// 这将被追踪
const tracer = new LangChainTracer();
await agent.invoke(
  {
    messages: [{role: "user", content: "Send a test email to alice@example.com"}]
  },
  { callbacks: [tracer] }
);

// 这将不会被追踪（如果未设置 LANGSMITH_TRACING）
await agent.invoke(
  {
    messages: [{role: "user", content: "Send another email"}]
  }
);

import { LangChainTracer } from "@langchain/core/tracers/tracer_langchain";

const tracer = new LangChainTracer({ projectName: "email-agent-test" });
await agent.invoke(
  {
    messages: [{role: "user", content: "Send a test email to alice@example.com"}]
  },
  {
    tags: ["production", "email-assistant", "v1.0"],
    metadata: {
      userId: "user123",
      sessionId: "session456",
      environment: "production"
    }
  },

);