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automation

opik: Simplify LLM Monitoring

Get comprehensive tracing and automated evaluations for LLM applications with opik, a tool for startup founders, with 20k+ GitHub stars.
intermediate⏱ 1-2 hours💵 Free (self-hosted)
19,997 stars1,567 forksPythonQuality 8/10Updated 6/29/2026100% free · open source
What it is

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

What you can make with it

Automations like: when your LLM model misclassifies a customer, send a notification to your Slack channel.

How it helps

Opik helps you catch bugs and issues early in your AI project, saving time and effort down the line. It also gives you valuable insights to refine your models.

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."

If you're new

Pick up opik if you want to learn about AI debugging and evaluation without any prior experience.

If you're senior

Senior engineers will reach for opik when needing a robust and customizable solution for monitoring and evaluating their LLM applications.

Common confusion cleared up

Some users might confuse opik with generic logging tools, but opik is specifically designed for AI application debugging.

Best inside these AI tools
CursorCodex CLIContinue
Pairs with
Claude APIStripe webhookNotion database
Why we list it on WorkflowStacks: Opik is included because it's a comprehensive and open-source option for monitoring and evaluating LLM applications.

About this skill

Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.

Topics

evaluation
hacktoberfest
hacktoberfest2025
langchain
llama-index
llm
llm-evaluation
llm-observability
llmops
open-source
openai
playground
prompt-engineering
What's inside — free to inspect
No purchase needed

Read the entire source before you build — unlike paid marketplaces that hide it behind a buy button.

31
top-level files
11
folders
657.9M
repo size
Apache-2.0
license
Key files
.editorconfig
.pre-commit-config.yaml
AGENTS.md
readme_AR.md
readme_CN.md
readme_DE.md
File tree
.agents/
.claude/
.github/
.hooks/
apps/
deployment/
extensions/
scripts/
sdks/
tests_end_to_end/
tests_load/
.codex
.cursor
.cursorignore
.editorconfig
.env.template
.git-blame-ignore-revs
.gitattributes
.gitignore
.java-version
.pre-commit-config.yaml
AGENTS.md
CHANGELOG.md
CLA.md
Quick Actions
Details
Creator
comet-ml
Language
Python
Category
automation
Published
5/10/2023

Are you the creator of this tool? Claim your listing → and earn 85% of every sale.

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