How easy is it to integrate OpenLIT?

Integration is very simple - you just need to add one line of code 'openlit.init()' to start collecting data from your LLM application. It offers seamless integration with native OpenTelemetry support.

What are the main features of OpenLIT?

OpenLIT's main features include: application and request tracing, exceptions monitoring, cost tracking, prompt management with versioning, secure secrets management through Vault Hub, LLM comparison tools through Openground, and OpenTelemetry-native observability for LLMs, vector databases, and GPUs.

Is OpenLIT privacy-focused?

Yes, OpenLIT is privacy-focused. Users can see exactly what the code does, and they have the option to self-host the platform for additional privacy control.

What kind of monitoring capabilities does OpenLIT provide?

OpenLIT provides comprehensive monitoring including end-to-end request tracing, detailed span tracking, automatic exception monitoring with stacktraces, cost tracking, and real-time data streaming. It also supports integration with popular observability platforms like Datadog and Grafana Cloud.

How does OpenLIT handle prompt management?

OpenLIT offers a centralized prompt repository that allows for organized storage, versioning (with major, minor, and patch updates), and usage of prompts with dynamic variables. It supports creating drafts and customizing prompts using specific variables with the {{variableName}} convention.

OpenLIT

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OpenLIT is an open-source, OpenTelemetry-native observability tool designed specifically for GenAI and LLM applications, offering comprehensive monitoring, prompt management, and evaluation capabilities with just one line of code integration.

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更新日:2025年01月17日

OpenLIT の月間トラフィック傾向

OpenLITは先月5.9kのアクセスを記録し、-4.6%のわずかな減少を示しました。分析によると、このトレンドはAIツール分野の一般的な市場動向と一致しています。

過去のトラフィックを表示

OpenLITとは

OpenLIT is an innovative open-source platform built to simplify AI development workflows, particularly for Generative AI and Large Language Models (LLMs). It serves as a complete observability solution that helps developers monitor, evaluate, and optimize their AI applications. The platform combines essential features like LLM performance tracking, cost monitoring, prompt versioning, and secure API key management into a unified interface, making it easier for teams to manage their AI infrastructure effectively.

OpenLITの主な機能

OpenLIT is an open-source OpenTelemetry-native observability platform specifically designed for GenAI and LLM applications. It provides comprehensive monitoring capabilities including LLM performance tracking, GPU monitoring, cost analysis, prompt management, and secrets management - all achievable with just one line of code integration. The platform offers seamless integration with various LLM providers, vector databases, and existing observability tools while maintaining a strong focus on privacy and ease of use.

OpenTelemetry-Native Observability: Provides end-to-end tracing and monitoring of LLM applications with automatic instrumentation, collecting metrics on performance, costs, tokens, and user interactions

Prompt Management System: Centralized repository for storing, versioning, and managing prompts with support for dynamic variables and version control including draft states

Secure Vault Management: Built-in secure storage system for managing sensitive information and API keys with easy environment integration

Comprehensive Analytics Dashboard: Visual interface for monitoring application performance, tracking exceptions, analyzing costs, and comparing different LLM performances in real-time

OpenLITのユースケース

AI Application Development: Helps developers monitor and optimize their GenAI applications during both development and production phases with comprehensive performance insights

Cost Optimization: Enables organizations to track and analyze LLM usage costs across different providers, helping make informed decisions about resource allocation

LLM Performance Comparison: Allows teams to compare different LLM providers side-by-side to choose the most suitable option for their specific use case

Security Compliance: Helps organizations maintain security standards through secure secrets management and comprehensive monitoring of AI application behavior

メリット

Simple integration with just one line of code

Open-source with self-hosting capability

Comprehensive monitoring and management features

Native OpenTelemetry support for existing observability stacks

デメリット

Requires technical knowledge for self-hosting

Limited community support as a newer tool

OpenLITの使い方

Install OpenLIT: Install OpenLIT using either npm ('npm i openlit') for TypeScript/JavaScript projects or pip ('pip install openlit') for Python projects

Initialize OpenLIT: Add 'openlit.init()' to your code to start collecting observability data from your LLM application. You can configure options like OTLP endpoint and application name during initialization

Deploy OpenLIT Backend: Deploy the OpenLIT backend using either Docker Compose ('docker-compose up -d') for quick setup or Helm charts for Kubernetes deployment. This sets up the UI and required backend services

Configure Secret Management: Use OpenLIT Vault to securely store and manage API keys and other sensitive credentials. Access the Vault through the UI or SDK to store/retrieve secrets

Set Up Prompt Management: Use the Prompt Hub in the UI to create, version and manage your prompts. You can use variables in prompts with {{variableName}} syntax for dynamic content

Monitor Application: Access the OpenLIT dashboard to view traces, metrics, costs and exceptions. You can analyze LLM performance, track errors, and monitor GPU usage

Test LLMs with OpenGround: Use the OpenGround playground to experiment with and compare different LLM providers side-by-side based on performance, cost and other metrics

Set Up Evaluations: Configure evaluations for hallucination, bias and toxicity detection using the evals module to assess LLM outputs quality

Export Data: Optionally configure connections to send OpenLIT's observability data to external tools like Prometheus, Grafana or other OpenTelemetry-compatible platforms

OpenLITのよくある質問

OpenLIT is an open-source platform for AI engineering that simplifies AI development workflow, especially for Generative AI and LLMs. It provides observability, prompt management, and secrets handling capabilities with OpenTelemetry-native support.