comet-ml/opik
Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards. observed · 2026-08-28
Health v2 · maintenance only
92/100
- Activity 99
- Release rhythm 87
- Longevity 86
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 0.0
- age_days: 1211
- days_rel: 7
- days_push: 7
- n_releases_24m: 527
Adoption not part of the score
21624 stars · 1732 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
Opik is an open-source LLM observability and evaluation platform by Comet for tracing, evaluating, and monitoring LLM applications, RAG pipelines, and agentic workflows. It offers Python/TypeScript SDKs, broad framework integrations, prompt management, guardrails, an MCP server, and can be self-hosted via Docker or Kubernetes or used as a managed cloud.
Use cases
- trace and debug LLM agent workflows in production
- evaluate LLM outputs with automated metrics and datasets
- manage and version prompts for a RAG pipeline
- monitor LLM app costs and latency with dashboards
- self-host an LLM observability platform on Kubernetes
- add guardrails against prompt injection
- integrate LangChain or OpenAI tracing into an evaluation workflow
When to choose
- you need end-to-end tracing and evaluation for LLM apps, RAG systems, or agents
- you want an open-source, self-hostable alternative to LangSmith or Langfuse
- you use LangChain, LlamaIndex, OpenAI, or similar frameworks and want drop-in instrumentation
- you need prompt management, guardrails, and production monitoring in one platform
When to avoid
- you only need simple application metrics without LLM-specific tracing
- you need full user management features in a self-hosted deployment (limited there)
- your stack has no LLM components to observe or evaluate
Facets
service · maturity active
monitoring tracing llm-inference rag agent-framework prompt-engineering analytics mcp self-hosted sdk large-language-models monitoring developer-tools machine-learning chatbots python self-hosted cross-platform llm-observability llm-evaluation llmops agent-tracing prompt-management guardrails opentelemetry langchain-integration ai-agents retrieval-augmented-generation docker kubernetes web-server
9 sources
- readme: https://github.com/comet-ml/opik · fetched 2026-08-28 · 426b4a14ce16
- homepage: https://www.comet.com/docs/opik/ · fetched 2026-08-29 · b72977ac9bca
- site_page: https://www.comet.com/docs/opik/integrations/overview · fetched 2026-08-29 · a292ade434e4
- site_page: https://www.comet.com/docs/opik/cost-intelligence/overview · fetched 2026-08-29 · 2b9f0530dbb5
- site_page: https://www.comet.com/docs/opik/self-host/overview · fetched 2026-08-29 · 9a2c8455a3fe
- site_page: https://www.comet.com/docs/opik/reference/overview · fetched 2026-08-29 · eb1437a39a8a
- site_page: https://www.comet.com/docs/opik/quickstart · fetched 2026-08-29 · c3da8b07fcce
- site_page: https://www.comet.com/docs/opik/mcp-server · fetched 2026-08-29 · 863058c31d76
- site_page: https://www.comet.com/docs/opik/ollie · fetched 2026-08-29 · 1b074e170fad
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| comet-ml/opik | main | 92 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem