Groq

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Prerequisites

• Python 3.10+
• An Arize AX account (sign up)
• A GROQ_API_KEY from the Groq Console

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Launch Arize AX

1. Sign in to your Arize AX account.
2. From Space Settings, copy your Space ID and API Key. You will set them as ARIZE_SPACE_ID and ARIZE_API_KEY below.

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Install

pip install arize-otel openinference-instrumentation-groq groq

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Configure credentials

export ARIZE_SPACE_ID="<your-space-id>"
export ARIZE_API_KEY="<your-api-key>"
export ARIZE_PROJECT_NAME="groq-tracing-example"
export GROQ_API_KEY="<your-groq-api-key>"

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Setup tracing

# instrumentation.py
import os

from arize.otel import register
from openinference.instrumentation.groq import GroqInstrumentor

tracer_provider = register(
    space_id=os.environ["ARIZE_SPACE_ID"],
    api_key=os.environ["ARIZE_API_KEY"],
    project_name=os.environ["ARIZE_PROJECT_NAME"],
)

GroqInstrumentor().instrument(tracer_provider=tracer_provider)
print("Arize AX tracing initialized for Groq.")

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Run Groq

# example.py

# Importing instrumentation first ensures tracing is set up
# before `groq` is imported.
from instrumentation import tracer_provider

from groq import Groq

# The client reads GROQ_API_KEY from the environment.
client = Groq()

response = client.chat.completions.create(
    model="llama-3.3-70b-versatile",
    messages=[
        {
            "role": "user",
            "content": "Why is the ocean salty? Answer in two sentences.",
        },
    ],
)

print(response.choices[0].message.content)

​

Expected output

Arize AX tracing initialized for Groq.
The ocean is salty because rivers continuously dissolve mineral salts from rocks and soil and carry them to the sea, where they accumulate over millions of years. Water leaves the ocean through evaporation but the salts remain, steadily concentrating until reaching today's roughly 3.5% salinity.

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Verify in Arize AX

1. Open your Arize AX space and select project groq-tracing-example.
2. You should see a new trace within ~30 seconds containing a Completions LLM span with the prompt, response, and token usage attached.
3. If no traces appear, see Troubleshooting.

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Check from the skill, CLI, or SDK

npx skills add Arize-ai/arize-skills

ax spans export "$ARIZE_PROJECT_NAME" --space "$ARIZE_SPACE_ID" \
  --limit 5 --stdout | jq 'length'

import os
from arize import ArizeClient

client = ArizeClient(api_key=os.environ["ARIZE_API_KEY"])
resp = client.spans.list(
    project=os.environ["ARIZE_PROJECT_NAME"],
    space=os.environ["ARIZE_SPACE_ID"],
    limit=5,
)
count = len(resp.spans)
print(
    f"{count} span(s) found" if count else "No spans yet — recheck setup"
)

// Reads ARIZE_API_KEY from the environment.
import { listSpans } from "@arizeai/ax-client";

const { data: spans } = await listSpans({
  project: process.env.ARIZE_PROJECT_NAME!,
  space: process.env.ARIZE_SPACE_ID!,
  limit: 5,
});
const count = spans.length;
console.log(
  count ? `${count} span(s) found` : "No spans yet — recheck setup",
);

client, err := arize.NewClient(
    arize.Config{APIKey: os.Getenv("ARIZE_API_KEY")},
)
if err != nil {
    log.Fatal(err)
}
resp, err := client.Spans.List(ctx, spans.ListRequest{
    Project: os.Getenv("ARIZE_PROJECT_NAME"),
    Space:   os.Getenv("ARIZE_SPACE_ID"),
    Limit:   5,
})
if err != nil {
    log.Fatal(err)
}
fmt.Printf("%d span(s) found\n", len(resp.Spans))

​

Troubleshooting

• No traces in Arize AX. Confirm ARIZE_SPACE_ID and ARIZE_API_KEY are set in the same shell that runs example.py. Enable OpenTelemetry debug logs with export OTEL_LOG_LEVEL=debug and re-run.
• Groq spans missing but other spans present. GroqInstrumentor().instrument(...) must run before any from groq import Groq import. Make sure instrumentation.py is the first import in your entry point.
• 401 from Groq. Verify GROQ_API_KEY is set and active in the Groq Console.
• 404 NOT_FOUND for the model. Groq retires older model aliases periodically. If llama-3.3-70b-versatile returns 404, see the Groq supported models list and pick a current one.

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