opentelemetry-instrumentation-genai-openai 1.0b0

OpenTelemetry Official OpenAI instrumentation

This library allows tracing LLM requests and logging of messages made by the OpenAI Python API library. It also captures the duration of the operations and the number of tokens used as metrics.

Note

This package continues the project previously published as opentelemetry-instrumentation-openai-v2

Many LLM platforms support the OpenAI SDK. This means systems such as the following are observable with this instrumentation when accessed using it:

OpenAI Compatible Platforms

Name	gen_ai.system
Azure OpenAI	azure.ai.openai
Gemini	gemini
Perplexity	perplexity
xAI (Compatible with Anthropic)	xai
DeepSeek	deepseek
Groq	groq
MistralAI	mistral_ai

Installation

If your application is already instrumented with OpenTelemetry, add this package to your requirements.

pip install opentelemetry-instrumentation-genai-openai

If you don’t have an OpenAI application, yet, try our examples which only need a valid OpenAI API key.

Check out zero-code example for a quick start.

Usage

This section describes how to set up OpenAI instrumentation if you’re setting OpenTelemetry up manually. Check out the manual example for more details.

Instrumenting all clients

When using the instrumentor, all clients will automatically trace OpenAI operations including chat completions and embeddings. You can also optionally capture prompts and completions as log events.

Make sure to configure OpenTelemetry tracing, logging, and events to capture all telemetry emitted by the instrumentation.

from opentelemetry.instrumentation.genai.openai import OpenAIInstrumentor

OpenAIInstrumentor().instrument()

client = OpenAI()
# Chat completion example
response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[
        {"role": "user", "content": "Write a short poem on open telemetry."},
    ],
)

# Embeddings example
embedding_response = client.embeddings.create(
    model="text-embedding-3-small",
    input="Generate vector embeddings for this text"
)

Enabling message content

Message content such as the contents of the prompt, completion, function arguments and return values are not captured by default. To capture message content, set the environment variable OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT to one of the following values:

• span_only - capture content on span attributes.

• event_only - capture content on event attributes.

• span_and_event - capture content on both span and event attributes.

• no_content - do not capture content (the default).

Uploading prompts and completions

To enable the built-in upload hook, set:

• OTEL_INSTRUMENTATION_GENAI_COMPLETION_HOOK=upload

• OTEL_INSTRUMENTATION_GENAI_UPLOAD_BASE_PATH to an fsspec-compatible URI/path (e.g. /path/to/prompts or gs://my_bucket).

Install the upload extra to pull in fsspec:

pip install opentelemetry-util-genai[upload]

See the opentelemetry-util-genai for additional options.

Enabling the latest experimental features

The latest experimental GenAI semantic conventions are used unconditionally; there is no environment variable to opt in or out.

Note

Generative AI semantic conventions are still evolving. The latest experimental features may introduce breaking changes in future releases.

Uninstrument

To uninstrument clients, call the uninstrument method:

from opentelemetry.instrumentation.genai.openai import OpenAIInstrumentor

OpenAIInstrumentor().instrument()
# ...

# Uninstrument all clients
OpenAIInstrumentor().uninstrument()

References

• OpenTelemetry Project

• OpenTelemetry GenAI semantic conventions

• OpenAI SDK (Python)

• OpenAI Documentation