LangSmith 可观测性

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

from langchain.agents import create_agent


def send_email(to: str, subject: str, body: str):
    """向收件人发送电子邮件。"""
    # ... 电子邮件发送逻辑
    return f"Email sent to {to}"

def search_web(query: str):
    """在网络上搜索信息。"""
    # ... 网络搜索逻辑
    return f"Search results for: {query}"

agent = create_agent(
    model="gpt-5.4",
    tools=[send_email, search_web],
    system_prompt="You are a helpful assistant that can send emails and search the web."
)

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

import langsmith as ls

# 这将被追踪
with ls.tracing_context(enabled=True):
    agent.invoke({"messages": [{"role": "user", "content": "Send a test email to alice@example.com"}]})

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

response = agent.invoke(
    {"messages": [{"role": "user", "content": "Send a welcome email"}]},
    config={
        "tags": ["production", "email-assistant", "v1.0"],
        "metadata": {
            "user_id": "user_123",
            "session_id": "session_456",
            "environment": "production"
        }
    }
)

with ls.tracing_context(
    project_name="email-agent-test",
    enabled=True,
    tags=["production", "email-assistant", "v1.0"],
    metadata={"user_id": "user_123", "session_id": "session_456", "environment": "production"}):
    response = agent.invoke(
        {"messages": [{"role": "user", "content": "Send a welcome email"}]}
    )