AI Observability, Evaluation and Guardrails Framework

Introduction

In the rapidly evolving landscape of artificial intelligence, ensuring observability and performance of AI models is crucial. OpenLIT provides a robust framework for monitoring AI applications, particularly focusing on large language models (LLMs) and their interactions with various data sources. This blog post will delve into the features, installation, and usage of OpenLIT, empowering developers to enhance their AI observability.

Key Features of OpenLIT

• Auto Instrumentation: Integrate with over 50 LLM providers, vector databases, and GPUs with a single line of code.
• OpenTelemetry-Native SDKs: Vendor-neutral SDKs that seamlessly send traces and metrics to existing observability tools.
• Cost Tracking: Manage budgets for custom and fine-tuned models with precise cost tracking.
• Support for OpenLIT Features: Includes prompt management and secrets management capabilities.

Technical Architecture

OpenLIT is built on top of OpenTelemetry, a standard for observability that allows developers to collect and export telemetry data. The architecture supports various integrations, enabling users to monitor their AI stack effectively. The SDK is designed to be lightweight and easy to integrate into existing applications.

Installation Process

To get started with OpenLIT, follow these simple steps:

Step 1: Install OpenLIT SDK

pip install openlit

Step 2: Initialize OpenLIT in Your Application

Add the following lines to your code:

import openlit
openlit.init()

Configure the telemetry data destination as needed.

Usage Examples

Once OpenLIT is installed and initialized, you can start monitoring your AI applications. Here’s a simple example:

import openlit

openlit.init(otlp_endpoint="http://127.0.0.1:4318")

This code initializes OpenLIT and sets the OTLP endpoint for telemetry data.

Community and Contribution

OpenLIT thrives on community contributions. Whether you’re reporting bugs, suggesting features, or contributing code, your input is invaluable. Join our Slack community or check out our GitHub Issues to get involved.

License and Legal Considerations

OpenLIT is licensed under the Apache License 2.0, allowing for both personal and commercial use. Ensure to review the license terms before using or contributing to the project.

Conclusion

OpenLIT is a powerful tool for enhancing observability in AI applications. With its easy integration, robust features, and active community, it stands out as a leading solution for developers looking to monitor and evaluate their AI systems effectively.

For more information, visit the OpenLIT Documentation or check out the GitHub Repository.

FAQ