> ## Documentation Index
> Fetch the complete documentation index at: https://docs.openlayer.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Pydantic AI
> Learn how to trace Pydantic AI agents with Openlayer
[Pydantic AI](https://ai.pydantic.dev/) is a Python framework for building
production-ready applications powered by generative AI. Created by the
team behind Pydantic, it offers type-safe agents with structured outputs,
built-in dependency injection, and native support for leading LLM providers
like OpenAI, Anthropic, and Gemini.
This guide shows how to trace Pydantic AI agents with Openlayer.
## Configuration
The integration works by sending trace data to Openlayer's [OpenTelemetry endpoint](/integrations/opentelemetry).
The full code used in this guide is available
[here](https://colab.research.google.com/github/openlayer-ai/openlayer-python/blob/main/examples/tracing/pydantic-ai/pydantic_ai_tracing.ipynb).
To set it up, you need to:
Set the following environment variables:
```bash theme={null}
OTEL_EXPORTER_OTLP_ENDPOINT="https://api.openlayer.com/v1/otel"
OTEL_EXPORTER_OTLP_HEADERS="Authorization=Bearer YOUR_OPENLAYER_API_KEY_HERE, x-bt-parent=pipeline_id:YOUR_PIPELINE_ID_HERE"
```
Configure Logfire in your application:
```python theme={null}
import logfire
logfire.configure(send_to_logfire=False)
logfire.instrument_pydantic_ai()
```
Once instrumentation is set up, you can run your Agents as usual.
Trace data will be automatically captured and exported to Openlayer, where
you can begin testing and analyzing it.
For example:
```python theme={null}
from pydantic_ai import Agent
agent = Agent('openai:gpt-4o')
result = await agent.run('What is the capital of France?')
```