Groq Integration

Updated on Aug 14, 2026

Use this integration when your app is implemented in Python.

Setup

1. Install SDK

bash

pip install progress-observability

2. Instrument your app

python

Observability.instrument(
    app_name=os.getenv("OBSERVABILITY_APP_NAME"),
    api_key=os.getenv("OBSERVABILITY_API_KEY")
)

3. Complete example

python

import os

from dotenv import load_dotenv
from openai import OpenAI

from progress.observability import Observability

load_dotenv()

# LLM INSTRUMENTATION
Observability.instrument(
    app_name=os.getenv("OBSERVABILITY_APP_NAME"),
    api_key=os.getenv("OBSERVABILITY_API_KEY"),
)


def main() -> None:
    # Groq speaks the OpenAI API, so the OpenAI client pointed at Groq's
    # endpoint is traced like any OpenAI-compatible provider.
    client = OpenAI(
        api_key=os.getenv("GROQ_API_KEY"),
        base_url=os.getenv("GROQ_BASE_URL", "https://api.groq.com/openai/v1"),
    )
    model = os.getenv("GROQ_MODEL", "llama-3.3-70b-versatile")

    response = client.chat.completions.create(
        model=model,
        max_tokens=256,
        messages=[
            {"role": "system", "content": "You are a helpful AI assistant."},
            {"role": "user", "content": "What is the capital of France?"},
        ],
    )



try:
    main()
finally:
    Observability.shutdown()

To get a richer trace tree when building agents on top of this provider, use the @agent, @tool, @workflow, or @task decorators. See the Python SDK for details.