> ## Documentation Index
> Fetch the complete documentation index at: https://phidatainc-agui.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# LangSmith

> Integrate Agno with LangSmith to send traces and gain insights into your agent's performance.

## Integrating Agno with LangSmith

LangSmith offers a comprehensive platform for tracing and monitoring AI model calls. By integrating Agno with LangSmith, you can utilize OpenInference to send traces and gain insights into your agent's performance.

## Prerequisites

1. **Create a LangSmith Account**

   * Sign up for an account at [LangSmith](https://smith.langchain.com).
   * Obtain your API key from the LangSmith dashboard.

2. **Set Environment Variables**

   Configure your environment with the LangSmith API key and other necessary settings:

   ```bash theme={null}
   export LANGSMITH_API_KEY=<your-key>
   export LANGSMITH_TRACING=true
   export LANGSMITH_ENDPOINT=https://eu.api.smith.langchain.com  # or https://api.smith.langchain.com for US
   export LANGSMITH_PROJECT=<your-project-name>
   ```

3. **Install Dependencies**

   Ensure you have the necessary packages installed:

   ```bash theme={null}
   uv pip install openai openinference-instrumentation-agno opentelemetry-sdk opentelemetry-exporter-otlp
   ```

## Sending Traces to LangSmith

This example demonstrates how to instrument your Agno agent with OpenInference and send traces to LangSmith.

```python theme={null}
import os

from agno.agent import Agent
from agno.models.openai import OpenAIResponses
from agno.tools.hackernews import HackerNewsTools
from openinference.instrumentation.agno import AgnoInstrumentor
from opentelemetry import trace as trace_api
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import SimpleSpanProcessor

# Set the endpoint and headers for LangSmith
endpoint = "https://eu.api.smith.langchain.com/otel/v1/traces"
headers = {
    "x-api-key": os.getenv("LANGSMITH_API_KEY"),
    "Langsmith-Project": os.getenv("LANGSMITH_PROJECT"),
}

# Configure the tracer provider
tracer_provider = TracerProvider()
tracer_provider.add_span_processor(
    SimpleSpanProcessor(OTLPSpanExporter(endpoint=endpoint, headers=headers))
)
trace_api.set_tracer_provider(tracer_provider=tracer_provider)

# Start instrumenting agno
AgnoInstrumentor().instrument()

# Create and configure the agent
agent = Agent(
    name="Stock Market Agent",
    model=OpenAIResponses(id="gpt-5.2"),
    tools=[HackerNewsTools()],
    markdown=True,
    debug_mode=True,
)

# Use the agent
agent.print_response("What is news on the stock market?")
```

## Notes

* **Environment Variables**: Ensure your environment variables are correctly set for the API key, endpoint, and project name.
* **Data Regions**: Choose the appropriate `LANGSMITH_ENDPOINT` based on your data region.

By following these steps, you can effectively integrate Agno with LangSmith, enabling comprehensive observability and monitoring of your AI agents.