automation

opik: Debug and Scale LLM Apps with 22k+ GitHub Stars

Turn debugging, evaluation, and monitoring of LLM, RAG, and agentic workflows into a single, production‑ready dashboard. Ideal for founders building AI‑first products.
intermediate⏱ 1-2 hours💵 Free (self-hosted)
22,474 stars+140★ this week1,847 forksPythonGuide quality 9/10 · reviewed Oct 5Install verified Sep 21Updated 10/9/2026100% free · open source
What it is

Use opik to debug and test your AI-powered applications.

Real use case example

"A founder named Alex uses opik to debug a LLM-powered chatbot. They set up opik to automatically track errors and discrepancies in responses. After a few hours, opik sends them an alert when it detects a pattern of misclassifications. Alex investigates and refines the model, greatly improving its accuracy."

Best insideCursorCodex CLIContinue
When to use it
  • •When you need to identify and fix issues in your LLM application's workflow
  • •When you want to evaluate and compare the performance of different LLM models
  • •When you need to monitor and analyze the performance of your RAG systems and agentic workflows
Ready-to-paste prompt
opik.trace(my_llm_model, input_data='example_input', output_data='example_output')
Heads up: Make sure to set the `OPIK_API_KEY` environment variable with a valid Comet ML API key to use opik's production-ready dashboards and automated evaluations
Saves to your device
Use with Claude
New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

🔑 Needs an API key✓ Install verified 9/21/2026

Works after you add credentials — the setup agent will ask you for them.

Try it instantly — no install
Claude Code
mkdir -p ~/.claude/skills/opik && curl -fsSL https://workflowstacks.com/api/skills/opik/claude-skill -o ~/.claude/skills/opik/SKILL.md
Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)
claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

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How opik: Debug and Scale LLM Apps with 22k+ GitHub Stars works
Codeflow
Free to inspect

Opik: Debug and Scale LLM Apps with 22k+ GitHub Stars is a very large Python project (~754k lines across 7930 code files, plus 1676 test files). Setup is light: installs like a normal app — add your API keys. Reading the code is optional. Last commit this month, Apache-2.0 license, has a test suite.

Size
Very large codebase
~754k lines · 7930 code files · days to read — use, don't read
Setup
One-command install
Installs like a normal app — add your API keys. Reading the code is optional.
Runs on
Python
Needs API keys (.env)
Python 59%TypeScript 39%Shell 1%
Where to start reading
  1. 1
    README.md
    Start here — what it does and how to install it
  2. 2
    AGENTS.md
    The instructions the AI actually follows
  3. 3
    .env.template
    The API keys and settings you must provide
What's in each folder
apps/Sub-packages / plugins5279 files
extensions/Sub-packages / plugins30 files
sdks/SDKs / client libraries5369 files
tests_end_to_end/Folder214 files
deployment/Deployment / infrastructure49 files
scripts/Helper scripts28 files
tests_load/Folder23 files
.github/CI / automation (GitHub Actions)113 files
READMEHas testsDocumentedCI checksApache-2.0 licenseUpdated this month
Quick Actions
Details
Creator
comet-ml
Language
Python
Category
automation
Published
5/10/2023

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Featured on WorkflowStacks
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