Groq OpenTelemetry Integration

Overview

This integration provides support for using OpenTelemetry with the Groq framework. It enables tracing and monitoring of applications built with Groq.

Installation

1. Install traceAI Groq

pip install traceAI-groq

Set Environment Variables

Set up your environment variables to authenticate with FutureAGI.

import os

os.environ["FI_API_KEY"] = FI_API_KEY
os.environ["FI_SECRET_KEY"] = FI_SECRET_KEY
os.environ["GROQ_API_KEY"] = GROQ_API_KEY

Quickstart

Register Tracer Provider

Set up the trace provider to establish the observability pipeline. The trace provider:

from fi_instrumentation import register
from fi_instrumentation.fi_types import ProjectType

trace_provider = register(
    project_type=ProjectType.OBSERVE,
    project_name="groq_app"
)

Configure Groq Instrumentation

Instrument the Groq client to enable telemetry collection. This step ensures that all interactions with the Groq SDK are tracked and monitored.

from groq import Groq

def test():
    client = Groq(
        api_key=os.environ.get("GROQ_API_KEY"),
    )

    weather_function = {
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "finds the weather for a given city",
            "parameters": {
                "type": "object",
                "properties": {
                    "city": {
                        "type": "string",
                        "description": "The city to find the weather for, e.g. 'London'",
                    }
                },
                "required": ["city"],
            },
        },
    }

    sys_prompt = "Respond to the user's query using the correct tool."
    user_msg = "What's the weather like in San Francisco?"

    messages = [
        {"role": "system", "content": sys_prompt},
        {"role": "user", "content": user_msg},
    ]
    response = client.chat.completions.create(
        model="mixtral-8x7b-32768",
        messages=messages,
        temperature=0.0,
        tools=[weather_function],
        tool_choice="required",
    )

    message = response.choices[0].message
    assert (tool_calls := message.tool_calls)
    tool_call_id = tool_calls[0].id
    messages.append(message)
    messages.append(
        ChatCompletionToolMessageParam(
            content="sunny", role="tool", tool_call_id=tool_call_id
        ),
    )
    final_response = client.chat.completions.create(
        model="mixtral-8x7b-32768",
        messages=messages,
    )
    return final_response

if __name__ == "__main__":
    response = test()
    print("Response\n")
    print(response)