OpenInference Groq Instrumentation

Python autoinstrumentation library for the Groq package

This package implements OpenInference tracing for both Groq and AsyncGroq clients.

These traces 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-groq

Quickstart

Through your terminal, install required packages.

pip install openinference-instrumentation-groq groq arize-phoenix opentelemetry-sdk opentelemetry-exporter-otlp

You can start Phoenix with the following terminal command:

python -m phoenix.server.main serve

By default, Phoenix 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.)

Try the following code in a Python file.

Set up GroqInstrumentor to trace your application and sends the traces to Phoenix.
Then, set your Groq API key as an environment variable.
Lastly, create a Groq client, make a request, then go see your results in Phoenix at http://localhost:6006!

import os
from groq import Groq
from openinference.instrumentation.groq import GroqInstrumentor
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk import trace as trace_sdk
from opentelemetry.sdk.trace.export import SimpleSpanProcessor

# Configure GroqInstrumentor with Phoenix endpoint
endpoint = "http://127.0.0.1:6006/v1/traces"
tracer_provider = trace_sdk.TracerProvider()
tracer_provider.add_span_processor(SimpleSpanProcessor(OTLPSpanExporter(endpoint)))

GroqInstrumentor().instrument(tracer_provider=tracer_provider)

os.environ["GROQ_API_KEY"] = "YOUR_KEY_HERE"

client = Groq()

chat_completion = client.chat.completions.create(
    messages=[
        {
            "role": "user",
            "content": "Explain the importance of low latency LLMs",
        }
    ],
    model="llama3-8b-8192",
)

if __name__ == "__main__":
    print(chat_completion.choices[0].message.content)

Now, on the Phoenix UI on your browser, you should see the traces from your Groq application. Click on a trace, then the "Attributes" tab will provide you with in-depth information regarding execution!

More Info

Metadata

Release files for openinference-instrumentation-groq 0.1.33

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Source distribution (sdist)

Source distribution for openinference-instrumentation-groq 0.1.33
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Built distribution (wheel)

Table of built distributions (wheels) for openinference-instrumentation-groq 0.1.33
File	Interpreter	ABI	Platform	Reset
openinference_instrumentation_groq-0.1.33-py3-none-any.whl 17.6 kB Oct 9, 2026	Python 3	none	any	Details

Total release size: 31.1 kB

Release files / openinference_instrumentation_groq-0.1.33.tar.gz

Download URL	openinference_instrumentation_groq-0.1.33.tar.gz
Size	13.5 kB
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SHA-256 checksum How to use checksums	`cec2b81228ac19134b210e3611e61ac1b7042fed3164052f3658957d3a9c2d82`
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Download URL	openinference_instrumentation_groq-0.1.33-py3-none-any.whl
Size	17.6 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`7e91278d60f7cb82b451744ed1e5f75bfe3b054bde2471099f3bc48f8daa8ce2`
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Upload date	Oct 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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Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/Arize-ai/openinference
Publishing commit: github.com/Arize-ai/openinference/tree/453da0e0b49acec7b78182ac3aacffbbde030f62

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Publishing logs: github.com/Arize-ai/openinference/actions/runs/37973512043/attempts/1

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SHA-256 checksum: 7e91278d60f7cb82b451744ed1e5f75bfe3b054bde2471099f3bc48f8daa8ce2 Verifying attestations