OpenInference OpenAI Instrumentation

Python auto-instrumentation library for OpenAI's python SDK.

The traces emitted by this instrumentation are fully OpenTelemetry compatible and can be sent to an OpenTelemetry collector for viewing, such as Arize Phoenix or Arize AX.

Installation

pip install openinference-instrumentation-openai

Quickstart

In this example we will instrument a small program that uses OpenAI and observe the traces via arize-phoenix.

Install packages.

pip install openinference-instrumentation-openai "openai>=1.26" arize-phoenix opentelemetry-sdk opentelemetry-exporter-otlp

Start the phoenix server so that it is ready to collect traces. The Phoenix server runs entirely on your machine and does not send data over the internet.

python -m phoenix.server.main serve

In a python file, setup the OpenAIInstrumentor and configure the tracer to send traces to Phoenix.

import openai
from openinference.instrumentation.openai import OpenAIInstrumentor
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk import trace as trace_sdk
from opentelemetry.sdk.trace.export import ConsoleSpanExporter, SimpleSpanProcessor

endpoint = "http://127.0.0.1:6006/v1/traces"
tracer_provider = trace_sdk.TracerProvider()
tracer_provider.add_span_processor(SimpleSpanProcessor(OTLPSpanExporter(endpoint)))
# Optionally, you can also print the spans to the console.
tracer_provider.add_span_processor(SimpleSpanProcessor(ConsoleSpanExporter()))

OpenAIInstrumentor().instrument(tracer_provider=tracer_provider)


if __name__ == "__main__":
    client = openai.OpenAI()
    response = client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=[{"role": "user", "content": "Write a haiku."}],
        max_tokens=20,
        stream=True,
        stream_options={"include_usage": True},
    )
    for chunk in response:
        if chunk.choices and (content := chunk.choices[0].delta.content):
            print(content, end="")

Since we are using OpenAI, we must set the OPENAI_API_KEY environment variable to authenticate with the OpenAI API.

export OPENAI_API_KEY=your-api-key

Now simply run the python file and observe the traces in Phoenix.

python your_file.py

FAQ

Q: How to get token counts when streaming?

A: To get token counts when streaming, install openai>=1.26 and set stream_options={"include_usage": True} when calling create. See the example shown above. For more info, see here.

More Info

Release files for openinference-instrumentation-openai 0.1.59

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Source distribution for openinference-instrumentation-openai 0.1.59
File	Size	Uploaded
openinference_instrumentation_openai-0.1.59.tar.gz	23.8 kB	Sep 9, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for openinference-instrumentation-openai 0.1.59
File	Interpreter	ABI	Platform	Reset
openinference_instrumentation_openai-0.1.59-py3-none-any.whl 31.4 kB Sep 9, 2026	Python 3	none	any	Details

Total release size: 55.1 kB

Release files / openinference_instrumentation_openai-0.1.59.tar.gz

Download URL	openinference_instrumentation_openai-0.1.59.tar.gz
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Publishing commit: github.com/Arize-ai/openinference/tree/8abaf899cb9a039284663b2f65cb63738d26b1ed

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Download URL	openinference_instrumentation_openai-0.1.59-py3-none-any.whl
Size	31.4 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`f7a17e0fa9ca4944533fdc8af012ecb2531552b22473860ec169093a09fb6671`
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Upload date	Sep 9, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

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Publishing platform: GitHub Actions
Publishing repository: github.com/Arize-ai/openinference
Publishing commit: github.com/Arize-ai/openinference/tree/8abaf899cb9a039284663b2f65cb63738d26b1ed

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Publishing configuration: github.com/Arize-ai/openinference/blob/8abaf899cb9a039284663b2f65cb63738d26b1ed/.github/workflows/publish.yaml
Publishing logs: github.com/Arize-ai/openinference/actions/runs/34322596540/attempts/1

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