#55th of 13 in Observability
Opik
Trace, evaluate and monitor LLM apps and agents, Apache-2.0 end to end
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- Stars
- 22.5k
- License
- Apache-2.0
- Last commit
- Oct 2026
- Last release
- Oct 2026
Overview
Logs trace trees for LLM calls, tool executions and agent steps via Python and TypeScript SDKs, OpenTelemetry or framework integrations, then runs datasets, experiments and LLM-as-a-judge metrics for hallucination, moderation and RAG quality, with online evaluation rules in production. Self-hosts with ./opik.sh (Docker Compose, UI on port 5173) or a Helm chart. For ML engineers moving agents to production.
Who it is for: ML engineers moving LLM agents to production
Strengths
- Full platform (backend, web app, evals, prompt management) under Apache-2.0
- Designed for 40M+ traces per day; online evaluation rules on production traffic
- PyTest integration gates LLM pipelines in CI
- MCP server lets Claude Code, Cursor, Codex or opencode query traces and run evals
Weaknesses
- No Dockerfile or compose file at the repo root; install goes through opik.sh
- Multi-service stack (databases, caches, backend, frontend); not a single binary
- Guardrails and the optimizer are separate profiles and SDKs to enable
- README is heavy with Comet Cloud links and UTM tracking
What it needs
- no GPU
- Compose
- Models: any LLM via SDK, OpenTelemetry or framework integrations (Google ADK, AG2, Autogen, Flowise)
- port 5173
Also in Observability
See all 13| Rank | Project | Score |
|---|---|---|
| 1 | LangfuseTracing, prompt management and evals for LLM apps on ClickHouse | 74 out of 100 |
| 2 | PhoenixLLM tracing, evals, datasets and prompt playground built on OpenTelemetry | 74 out of 100 |
| 3 | promptfooCLI for evaluating and red-teaming prompts, agents and RAG | 71 out of 100 |
| #4 | MLflowTracing, evals, prompt registry and AI gateway plus classic ML tracking | 70 out of 100 |
| #6 | LatitudeAgent observability that groups failures and dispatches coding agents to fix them | 62 out of 100 |