splunk-otel-instrumentation-openai 0.1.2

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.

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	az.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 splunk-otel-instrumentation-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.openai_v2 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 as log events, set the environment variable OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT to true.

See the upstream OpenTelemetry documentation for more details.

Suppressing nested instrumentation

When using multiple instrumentations together (e.g., LangChain + OpenAI), the higher-level instrumentation automatically sets SUPPRESS_LANGUAGE_MODEL_INSTRUMENTATION_KEY in the OpenTelemetry context to prevent duplicate spans for the same underlying LLM call.

This is handled transparently — no user configuration is needed. For example, when LangChain instrumentation is active alongside OpenAI instrumentation, you will see LangChain spans without redundant nested OpenAI spans.

Note

This is not an environment variable and cannot be configured for zero-code instrumentation. It is a context key managed programmatically by instrumentation libraries.

Uninstrument

To uninstrument clients, call the uninstrument method:

from opentelemetry.instrumentation.openai_v2 import OpenAIInstrumentor

OpenAIInstrumentor().instrument()
# ...

# Uninstrument all clients
OpenAIInstrumentor().uninstrument()

References

• Splunk OpenTelemetry OpenAI Instrumentation

• OpenTelemetry Project

• OpenTelemetry Python Examples