Getting Started

This guide will walk you through the process of setting up the Coralogix AI Observability SDK to monitor your LLM applications. By following these steps, you'll be able to start sending AI observability data to Coralogix AI Center in just a few minutes.

Requirements

Python 3.8 or higher.
A Coralogix account with API key.
OpenAI API key (for this example).

Install the SDK

Install the LLM Tracekit library using pip.

pip install llm-tracekit

Set up environment variables

Configure the necessary environment variables.

# Coralogix credentials
export CX_TOKEN="your-coralogix-api-key"
export CX_ENDPOINT="your-coralogix-region-endpoint"  # Replace with your region endpoint (e.g. https://ingress.staging.coralogix.net:443)

# OpenAI API key (for the example)
export OPENAI_API_KEY="your-openai-api-key"

Create a simple application

Create a new Python file (e.g., ai_center_demo.py) using the following code:

import os
from openai import OpenAI
from llm_tracekit import OpenAIInstrumentor, setup_export_to_coralogix

# Configure export to Coralogix
setup_export_to_coralogix(
    service_name="ai-demo-service",
    application_name="ai-demo-app",
    subsystem_name="getting-started"
)

# Instrument OpenAI client
OpenAIInstrumentor().instrument()

# Initialize OpenAI client
client = OpenAI()

# Send a request to OpenAI
def generate_content():
    print("Sending request to OpenAI...")
    response = client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[
            {"role": "system", "content": "You are a helpful assistant."},
            {"role": "user", "content": "Explain what AI observability is in one sentence."},
        ],
    )

    # Display a nicer formatted response
    print("\n" + "="*50)
    print("📝 AI RESPONSE:")
    print(f"{response.choices[0].message.content}")
    print("="*50)

    # Confirmation about traces
    print("\n✅ Traces have been successfully sent to Coralogix AI Center!")
    print("View your data in the Coralogix AI Center dashboard.\n")

if __name__ == "__main__":
    generate_content()

Run the application

Execute your Python script.

python ai_center_demo.py

The output should resemble the following:

Sending request to OpenAI...

==================================================
📝 AI RESPONSE:
AI observability refers to the tools and practices used to monitor, analyze, and understand the behavior and performance of AI models and systems in real-time, ensuring they operate effectively and align with intended outcomes.
==================================================

✅ Traces have been successfully sent to Coralogix AI Center!
View your data in the Coralogix AI Center dashboard.

View your data in Coralogix AI Center

Log into your Coralogix account.
Go to AI Center > Application Catalog to see your new service.
Click on your application to view its detailed information.
Navigate to the LLM Calls section to see the trace for your request.

Capture tool calls

If your application uses OpenAI's function calling capabilities, these will be automatically captured as part of the trace data.

Welcome to AI Center

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