Alpha Notice: These docs cover the v1-alpha release. Content is incomplete and subject to change.For the latest stable version, see the current LangGraph Python or LangGraph JavaScript docs.
Traces are a series of steps that your application takes to go from input to output. Each of these individual steps is represented by a run. You can use LangSmith to visualize these execution steps. To use it, enable tracing for your application. This enables you to do the following:

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Prerequisites

Before you begin, ensure you have the following:

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Enable tracing

To enable tracing for your application, set the following environment variables: 
export LANGSMITH_TRACING=true
export LANGSMITH_API_KEY=<your-api-key>
By default, the trace will be logged to the project with the name default. To configure a custom project name, see Log to a project. For more information, see Trace with LangGraph.

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Trace selectively

You may opt to trace specific invocations or parts of your application using LangSmith’s tracing_context context manager: 
import langsmith as ls

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

# This will NOT be traced (if LANGSMITH_TRACING is not set)
agent.invoke({"messages": [{"role": "user", "content": "Send another email"}]})

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Log to a project

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Add metadata to traces

You can annotate your traces with custom metadata and tags: 
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"
        }
    }
)
tracing_context also accepts tags and metadata for fine-grained control: 
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"}]}
    )
This custom metadata and tags will be attached to the trace in LangSmith.
To learn more about how to use traces to debug, evaluate, and monitor your agents, see the LangSmith documentation.