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Groq provides low latency and lightning-fast inference for AI models. Arize supports instrumenting Groq API calls, including role types such as system, user, and assistant messages, as well as tool use. You can create a free GroqCloud account and generate a Groq API Key here to get started.

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Install

pip install openinference-instrumentation-groq groq

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Setup

Connect to your Phoenix instance using the register function. 
from phoenix.otel import register

# configure the Phoenix tracer
tracer_provider = register(
  project_name="my-llm-app", # Default is 'default'
  auto_instrument=True # Auto-instrument your app based on installed OI dependencies
)

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Run Groq

A simple Groq application that is now instrumented 
import os
from groq import Groq

client = Groq(
    # This is the default and can be omitted
    api_key=os.environ.get("GROQ_API_KEY"),
)

chat_completion = client.chat.completions.create(
    messages=[
        {
            "role": "user",
            "content": "Explain the importance of low latency LLMs",
        }
    ],
    model="mixtral-8x7b-32768",
)
print(chat_completion.choices[0].message.content)

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Observe

Now that you have tracing setup, all invocations of pipelines will be streamed to your running Phoenix for observability and evaluation.

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Resources: