comet-ml / opik

English | 简体中文 | Español | Français | Deutsch | 日本語 
 Opik: Open-Source LLM Observability, Evaluation & AI Agent Tracing
 Opik is the open-source LLM observability and evaluation platform for AI agent tracing, LLM evaluation, prompt management, and production monitoring. Built by Comet . Apache-2.0 licensed, free to self-host the full platform, with 20,000+ GitHub stars.
 Website •
 Slack Community •
 Twitter •
 Changelog •
 Documentation 
 Last updated: 2026-07-17 
 🚀 What is Opik? • ⚡ Quick Start • 📊 How Does Opik Compare? • ❓ FAQ • 🛠️ Opik Server Installation • 💻 Opik Client SDK • 📝 Logging Traces 
 🧑‍⚖️ LLM as a Judge • 🔍 Evaluating your Application • ⭐ Star Us • 🤝 Contributing 
## 🚀 What is Opik?
Opik covers the full LLM application lifecycle, from the first trace in development to production monitoring, for teams building LLM apps and AI agents. Key offerings include:
- **AI Agent Tracing & Observability**: Deep tracing of LLM calls, conversation logging, and agent activity, with full trace trees for multi-step agents and tool calls.
- **LLM Evaluation**: Datasets, experiments, and LLM-as-a-judge metrics for hallucination detection, moderation, and RAG assessment.
- **Prompt & Agent Optimization**: The Opik Agent Optimizer SDK to improve prompts and agents.
- **Production-Ready Monitoring**: Scalable dashboards and online evaluation rules.
- **Opik Guardrails**: Features to help you implement safe and responsible AI practices.
- **CI/CD Evaluation**: A PyTest integration to test LLM pipelines on every commit.
Key capabilities include:
- **Development & Tracing:**
 - Track all LLM calls and traces with detailed context during development and in production (Quickstart).
 - Extensive 3rd-party integrations for easy observability: Seamlessly integrate with a growing list of frameworks, supporting many of the largest and most popular ones natively (including recent additions like **Google ADK**, **Autogen**, and **Flowise AI**). (Integrations)
 - Annotate traces and spans with feedback scores via the Python SDK or the UI.
 - Experiment with prompts and models in the Prompt Playground.
- **Evaluation & Testing**:
 - Automate your LLM application evaluation with Datasets and Experiments.
 - Leverage powerful LLM-as-a-judge metrics for complex tasks like hallucination detection, moderation, and RAG assessment (Answer Relevance, Context Precision).
 - Integrate evaluations into your CI/CD pipeline with our PyTest integration.
- **Production Monitoring & Optimization**:
 - Log high volumes of production traces: Opik is designed for scale (40M+ traces/day).
 - Monitor feedback scores, trace counts, and token usage over time in the Opik Dashboard.
 - Utilize Online Evaluation Rules with LLM-as-a-Judge metrics to identify production issues.
 - Leverage **Opik Agent Optimizer** and **Opik Guardrails** to continuously improve and secure your LLM applications in production.
**Who it's for:** ML engineers building LLM-powered agents, AI teams moving from pr