What is Opik used for?

Opik is an open-source platform from Comet for tracing, evaluating and monitoring LLM applications, RAG systems and AI agents. It is a good fit for debugging multi-step agent behavior, regression testing LLM pipelines in CI and monitoring RAG quality in production.

Yes. Opik is open source under the Apache-2.0 licence. Its source code is on GitHub at comet-ml/opik and is written mainly in Python.

Yes. Opik is open source, so the software itself is free to use. A managed cloud version is also available.

Can I self-host Opik?

Yes. Opik can be self-hosted on your own server or infrastructure.

What is Opik an alternative to?

Opik is an open-source alternative to Weights & Biases, LangSmith, Arize AI and Braintrust. Other open-source alternatives to Weights & Biases include Arize Phoenix, Langfuse and MLflow.

Is Opik actively maintained?

Yes. The most recent commit to Opik was on 2 October 2026, and the latest release is 2.2.88, published on 2 October 2026. The project has 22k stars on GitHub.

Opik: open-source alternative to Weights & Biases, LangSmith

About Opik

Opik is an open-source LLM observability and evaluation platform built by Comet. It covers the application lifecycle starting with early traces during development and ending with production monitoring, for teams that build LLM apps and AI agents. The code is Python, licensed under Apache-2.0, and the README says the full platform is free to self-host. The project documentation lives on the Comet site.

Capabilities include deep tracing of LLM calls and agent activity including complete trace trees for agents with several steps and tool calls, and evaluation with datasets, experiments and LLM-as-a-judge metrics for tasks like hallucination detection, moderation and RAG assessment. An Agent Optimizer SDK improves prompts and agents, dashboards and online evaluation rules support production monitoring, guardrails help with safe AI practices, and a PyTest integration tests LLM pipelines on each commit. Integrations include frameworks such as LangChain, LlamaIndex and OpenAI clients.

Key features

Tracing for LLM calls and agent steps
Datasets and experiments for evaluation
Evaluation metrics using LLM-as-a-judge
Prompt and agent optimization SDK
Production dashboards and online evaluation
PyTest integration for CI checks

Good fit for

→Debugging multi-step agent behavior
→Regression testing LLM pipelines in CI
→Monitoring RAG quality in production

Built with: Python
Tags: llm-observability; llm-evaluation; tracing; agents; rag; llmops; python; monitoring

Opik: questions and answers

What is Opik used for?: Opik is an open-source platform from Comet for tracing, evaluating and monitoring LLM applications, RAG systems and AI agents. It is a good fit for debugging multi-step agent behavior, regression testing LLM pipelines in CI and monitoring RAG quality in production.
Is Opik open source?: Yes. Opik is open source under the Apache-2.0 licence. Its source code is on GitHub at comet-ml/opik and is written mainly in Python.
Is Opik free?: Yes. Opik is open source, so the software itself is free to use. A managed cloud version is also available.
Can I self-host Opik?: Yes. Opik can be self-hosted on your own server or infrastructure.
What is Opik an alternative to?: Opik is an open-source alternative to Weights & Biases, LangSmith, Arize AI and Braintrust. Other open-source alternatives to Weights & Biases include Arize Phoenix, Langfuse and MLflow.
Is Opik actively maintained?: Yes. The most recent commit to Opik was on 2 October 2026, and the latest release is 2.2.88, published on 2 October 2026. The project has 22k stars on GitHub.