openinference-instrumentation-pydantic-ai 0.1.12
OpenInference PydanticAI Instrumentation
Requires Python: <3.15,>=3.10

# OpenInference PydanticAI

[![pypi](https://badge.fury.io/py/openinference-instrumentation-pydantic-ai.svg)](https://pypi.org/project/openinference-instrumentation-pydantic-ai/)

Python auto-instrumentation library for PydanticAI. These traces are fully OpenTelemetry compatible and can be sent to an OpenTelemetry collector for viewing, such as [Arize Phoenix](https://github.com/Arize-ai/phoenix).

## Installation

```shell
pip install openinference-instrumentation-pydantic-ai
```

## Quickstart

This quickstart shows you how to instrument your PydanticAI agents.

Install required packages.

```shell
pip install pydantic-ai arize-phoenix opentelemetry-sdk opentelemetry-exporter-otlp
```

Start Phoenix in the background as a collector. By default, it listens on `http://localhost:6006`. You can visit the app via a browser at the same address. (Phoenix does not send data over the internet. It only operates locally on your machine.)

```shell
phoenix serve
```

Here's a simple example that demonstrates how to use PydanticAI with OpenInference instrumentation:

```python
import os
from pydantic import BaseModel
from pydantic_ai import Agent
from pydantic_ai.models.instrumented import InstrumentationSettings
from pydantic_ai.models.openai import OpenAIModel
from pydantic_ai.providers.openai import OpenAIProvider
from opentelemetry import trace
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk.trace import TracerProvider
from openinference.instrumentation.pydantic_ai import OpenInferenceSpanProcessor
from opentelemetry.sdk.trace.export import SimpleSpanProcessor

# Set your OpenAI API key
os.environ["OPENAI_API_KEY"] = "YOUR_OPENAI_API_KEY"

# Set up the tracer provider
tracer_provider = TracerProvider()
trace.set_tracer_provider(tracer_provider)

# Add the OpenInference span processor
endpoint = "http://127.0.0.1:6006/v1/traces"
exporter = OTLPSpanExporter(endpoint=endpoint)
tracer_provider.add_span_processor(OpenInferenceSpanProcessor())
tracer_provider.add_span_processor(SimpleSpanProcessor(exporter))


# Define your Pydantic model
class LocationModel(BaseModel):
    city: str
    country: str

instrumentation = InstrumentationSettings(version=2)

# Create and configure the agent
model = OpenAIModel("gpt-4", provider=OpenAIProvider())
agent = Agent(model, output_type=LocationModel, instrument=instrumentation)

# Run the agent
result = agent.run_sync("The windy city in the US of A.")
print(result)
```

This example:

1. Sets up OpenTelemetry tracing with Phoenix
2. Defines a simple Pydantic model for location data
3. Creates a PydanticAI agent with instrumentation enabled
4. Runs a query and gets structured output

The traces will be visible in the Phoenix UI at `http://localhost:6006`.

## More Info

-   [More info on OpenInference and Phoenix](https://docs.arize.com/phoenix)
-   [How to customize spans to track sessions, metadata, etc.](https://github.com/Arize-ai/openinference/tree/main/python/openinference-instrumentation#customizing-spans)
-   [How to account for private information and span payload customization](https://github.com/Arize-ai/openinference/tree/main/python/openinference-instrumentation#tracing-configuration)