---
title: "openlit"
type: "tool"
slug: "openlit-openlit"
canonical_url: "https://www.graphcanon.com/tools/openlit-openlit"
github_url: "https://github.com/openlit/openlit"
homepage_url: "https://docs.openlit.io"
stars: 2580
forks: 317
primary_language: "TypeScript"
license: "Apache-2.0"
categories: ["evaluation-observability", "llm-frameworks", "developer-tools"]
tags: ["otel-native", "gpu-monitoring", "dist-tracing", "llms", "monitoring-tool", "prompt-management", "ai-observability", "metrics"]
updated_at: "2026-07-07T18:44:14.149039+00:00"
---

# openlit

> Open source platform for AI Engineering

A comprehensive toolkit for managing, monitoring, securing, and evaluating LLMs and AI systems with support for over 50 providers.

## Facts

- Repository: https://github.com/openlit/openlit
- Homepage: https://docs.openlit.io
- Stars: 2,580 · Forks: 317 · Open issues: 46 · Watchers: 17
- Primary language: TypeScript
- License: Apache-2.0
- Last pushed: 2026-07-07T14:34:36+00:00

## Categories

- [Evaluation & Observability](/categories/evaluation-observability.md)
- [LLM Frameworks](/categories/llm-frameworks.md)
- [Developer Tools](/categories/developer-tools.md)

## Tags

otel-native, gpu-monitoring, dist-tracing, llms, monitoring-tool, prompt-management, ai-observability, metrics

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## README (excerpt)

```text
<div align="center">
<img src="https://github.com/openlit/.github/blob/main/profile/assets/wide-logo-no-bg.png?raw=true" alt="OpenLIT Logo" width="30%">

#### Observability, Evaluations, Rule Engine, Guardrails, Prompts, Vault, Playground, FleetHub

# Open Source Platform for AI Engineering

**[Documentation](https://docs.openlit.io/) | [Quickstart](-getting-started-with-llm-observability) | [Python SDK](https://github.com/openlit/openlit/tree/main/sdk/python) | [Typescript SDK](https://github.com/openlit/openlit/tree/main/sdk/typescript) | [Go SDK](https://github.com/openlit/openlit/tree/main/sdk/go) |**

**❤️ [Sponsor this project](https://opencollective.com/openlit) ❤️** 









</div>

---

<https://github.com/user-attachments/assets/6909bf4a-f5b4-4060-bde3-95e91fa36168>

**OpenLIT** allows you to simplify your AI development workflow, especially for Generative AI and LLMs. It streamlines essential tasks like experimenting with LLMs, organizing and versioning prompts, and securely handling API keys. With just one line of code, you can enable **OpenTelemetry-native** observability, offering full-stack monitoring that includes LLMs, vector databases, and GPUs. This enables developers to confidently build AI features and applications, transitioning smoothly from testing to production.

This project proudly follows and maintains the [Semantic Conventions](https://github.com/open-telemetry/semantic-conventions/tree/main/docs/gen-ai) with the OpenTelemetry community, consistently updating to align with the latest standards in Observability.

## ⚡ Features



- 📈 **Analytics Dashboard**: Monitor your AI application's health and performance with detailed dashboards that track metrics, costs, and user interactions, providing a clear view of overall efficiency.

- 🔌 **OpenTelemetry-native Observability SDKs**: Vendor-neutral SDKs (Python, TypeScript, Go) to send traces and metrics to your existing observability tools.

- 🛡️ **11 Built-in Evaluation Types**: Automated LLM-as-a-Judge evaluation with hallucination, bias, toxicity, safety, instruction following, completeness, conciseness, sensitivity, relevance, coherence, and faithfulness detection. Context-aware evaluation that treats provided context as the source of truth.

- ⚙️ **Rule Engine**: Define conditional rules with AND/OR logic to match runtime trace attributes and dynamically retrieve contexts, prompts, and evaluation configs. SDK support across Python, TypeScript, and Go.

- 💲 **Cost Tracking for Custom and Fine-Tuned Models**: Tailor cost estimations for specific models using custom pricing files for precise budgeting.

- 🐛 **Exceptions Monitoring Dashboard**: Quickly spot and resolve issues by tracking common exceptions and errors with a dedicated monitoring dashboard.

- 💭 **Prompt Management**: Manage and version prompts using Prompt Hub for consistent and easy access across applications.

- 🔑 **API Keys and Secrets Management**: Securely handle your API keys and secrets centrally, avoiding insecure practices.

- 🎮 **Experiment with different LLMs**: Use OpenGround to explore, test and compare various LLMs side by side.

- 🚀 **Fleet Hub for OpAMP Management**: Centrally manage and monitor OpenTelemetry Collectors across your infrastructure using the OpAMP (Open Agent Management Protocol) with secure TLS communication.

## 🚀 Getting Started with LLM Observability

```mermaid
flowchart TB;
    subgraph " "
        direction LR;
        subgraph " "
            direction LR;
            OpenLIT_SDK[OpenLIT SDK] -->|Sends Traces & Metrics| OTC[OpenTelemetry Collector];
            OTC -->|Stores Data| ClickHouseDB[ClickHouse];
        end
        subgraph " "
            direction RL;
            OpenLIT_UI[OpenLIT] -->|Pulls Data| ClickHouseDB;
        end
    end
```

### Step 1: Deploy OpenLIT Stack

1. Git Clone OpenLIT Repository

   Open your command line or terminal and run:

   ```shell
   git clone git@github.com:openlit/openlit.git
   ```

2. Self-h
```

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/tools/openlit-openlit`](/api/graphcanon/tools/openlit-openlit)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_