Skip to main content

OpenInference PydanticAI Instrumentation

Project description

OpenInference PydanticAI

pypi

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.

Installation

pip install openinference-instrumentation-pydantic-ai

Quickstart

This quickstart shows you how to instrument your PydanticAI agents.

Install required packages.

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.)

phoenix serve

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

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

File details

Details for the file openinference_instrumentation_pydantic_ai-0.1.10.tar.gz.

File metadata

File hashes

Hashes for openinference_instrumentation_pydantic_ai-0.1.10.tar.gz
Algorithm Hash digest
SHA256 b8759382a235351fae46351fcae94fc791790b82a2d72d220d1e9e92957ac7e9
MD5 1109e2dbe64966cac16514250d6b1d68
BLAKE2b-256 caa2fe0741809b368d1f794de7ca4e94ce323d36656e4a2a3403aee5be628e07

See more details on using hashes here.

File details

Details for the file openinference_instrumentation_pydantic_ai-0.1.10-py3-none-any.whl.

File metadata

File hashes

Hashes for openinference_instrumentation_pydantic_ai-0.1.10-py3-none-any.whl
Algorithm Hash digest
SHA256 27fd60d7b7bda667a8e4e54438f382a528b400707983e0bf65e4135ed0f4719e
MD5 54029a220d32450c2ced8016e94b15ce
BLAKE2b-256 6784f295f400412a38f42acc84c3d3a8114075271edd8f1ce7471e7c04a81dff

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page