Opik：追踪与评估 AI 应用

Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations,…

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 prototype to production, and engineering teams that need open-source, self-hostable observability they can run in their own environment. Why open source matters here: Opik is Apache-2.0 licensed and free to self-host: the full platform, backend included, not just a client SDK. The repository includes the server backend, web application, tracing, datasets, experiments, evaluations, prompt management, online evaluation, and agent optimization components, all under Apache-2.0. You can run LLM observability inside your own infrastructure with no data leaving your environment and no Enterprise sales conversation required. Tip If you are looking for features that Opik doesn't have today, please raise a new Feature request 🚀 ⚡ Quick Start Install the Python SDK and configure it: pip install opik opik configure Wrap any function with the @track decorator to start logging traces: from opik import track @track def my_function(input: str) -> str: return input Every call to my_function is now logged to Opik, including nested calls, so this works for full agent and pipeline traces, not just single LLM calls. See the Quickstart guide for the TypeScript SDK and other setup options. Connect your coding agent Let Claude Code, Cursor, VS Code Copilot, Codex or opencode read your traces, score outputs and run evaluations from chat. One command sets it up. It needs uv and no SDK: uvx opik mcp configure The badges and the add-mcp fallback below target Opik Cloud; the command above also handles self-hosted deployments. Other MCP clients on Opik Cloud: npx add-mcp https://www.comet.com/opik/api/v1/mcp --name opik-mcp. Details, troubleshooting and FAQ are in the MCP server guide. 📊 How Does Opik Compare? Opik competes in the LLM observability / AI agent evaluation category alongside LangSmith, Arize (Phoenix and Arize AX), Weights & Biases (Weave), Langfuse, and Braintrust. Capability Opik LangSmith Phoenix Arize AX Weights & Biases (Weave) Langfuse Braintrust Open source Yes, Apache-2.0 (full platform) No Source-available (Elastic License 2.0, not OSI-approved) No Open-source SDK/toolkit; self-managed platform requires a commercial license MIT-licensed core platform; commercial enterprise modules No Self-hosted deployment Yes Enterprise only Yes Enterprise only Enterprise only for Weave itself Yes, core Enterprise only Free tier available (cloud or self-hosted) Yes, both Yes, cloud Yes, self-hosted Yes, cloud Yes, cloud Yes, both Yes, cloud Agent / multi-step tracing Yes Yes Yes Yes Yes Yes Yes LLM-as-a-judge evaluation Yes Yes Yes Yes Yes Yes Yes Prompt management Yes Yes Partly Partly Partly Yes Yes Framework-agnostic Yes Partly, built around LangChain Yes Yes Yes Yes Yes When teams choose Opik: Opik's full observability, evaluation, and optimization platform is Apache-2.0 licensed and free to self-host. Unlike closed platforms whose self-hosted deployment requires an Enterprise plan, Opik can be deployed without a commercial license, and it's framework-agnostic so it won't lock you into a single agent ecosystem. See the table above for where self-hosting and licensing differ across alternatives.