explaingit

comet-ml/opik

📈 Trending★ 19,337PythonAudience · developerComplexity · 3/5ActiveLicenseSetup · moderate

TLDR

Open-source platform for debugging, evaluating, and monitoring AI applications. Records every AI call, runs quality checks, and shows results in a dashboard.

Mindmap

mindmap
  root((Opik))
    What it does
      Traces AI calls
      Evaluates quality
      Monitors production
      Improves prompts
    Key features
      Full call visibility
      Hallucination detection
      Production dashboard
      Automated testing
    Tech stack
      Python
      LangChain
      LlamaIndex
    Use cases
      Debug chatbots
      Monitor agents
      Catch bad responses
      Improve performance

Things people build with this

USE CASE 1

Debug why your chatbot gives wrong or irrelevant answers by seeing every AI call it makes.

USE CASE 2

Catch hallucinations and quality issues in production before users notice them.

USE CASE 3

Automatically test and improve your AI prompts and agent configurations over time.

USE CASE 4

Monitor thousands of AI conversations at scale and spot patterns in failures.

Tech stack

PythonLangChainLlamaIndexDashboardTracing

Getting it running

Difficulty · moderate Time to first run · 30min

Requires running a backend service and dashboard; likely needs API key or local LLM setup to see meaningful traces.

Use freely for any purpose including commercial. Keep the notice and disclose changes to the patent grant.

In plain English

Opik, built by Comet, is an open-source platform for debugging, evaluating, and monitoring AI applications that use large language models (LLMs). When you build something like a chatbot, a code assistant, or an automated agent powered by an AI model, it can be hard to know whether it is actually working well, or why it sometimes gives bad answers. Opik solves that by giving you full visibility into what the AI is doing under the hood. It records every AI call and conversation in detail (called tracing), lets you run automated quality checks to catch problems like hallucinations (when an AI confidently states something false) or irrelevant responses, and displays everything in a production-ready dashboard. It also includes tools to automatically improve the prompts and tool configurations you use with your AI agent. Opik integrates with popular AI frameworks like LangChain and LlamaIndex, and is designed to handle over 40 million traces per day at scale. You would use Opik if you are building any AI-powered product and want to move beyond guesswork, testing it systematically, catching quality issues in production, and continuously improving its performance without manually reading through thousands of responses.

Copy-paste prompts

Prompt 1
How do I set up Opik tracing for my LangChain chatbot to see what it's doing?
Prompt 2
Show me how to write an evaluation in Opik to detect when my AI model hallucinates.
Prompt 3
How do I integrate Opik with my LlamaIndex RAG application to monitor quality?
Prompt 4
What's the best way to use Opik's dashboard to find and fix common failure patterns in my AI agent?
Prompt 5
How can I use Opik to automatically test and improve my LLM prompts?
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Generated 2026-05-18 · Model: sonnet-4-6 · Verify against the repo before relying on details.