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90 lines
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---
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title: Home
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headline: Opik Documentation - Open-Source LLM Observability & Optimization
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og:site_name: Opik Documentation
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og:title: "Opik - Open-Source LLM Observability & Agent Optimization"
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og:description: "Build, test, and optimize GenAI apps from prototype to production. Comprehensive tracing, evaluation, and prompt optimization for RAG, agents, and more."
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canonical-url: https://www.comet.com/docs/opik/
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---
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Opik is an [open-source](https://github.com/comet-ml/opik) logging, debugging, and optimization
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platform for AI agents and LLM applications. If you're building AI features, you know it's easy to
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spin up a working prototype but harder to log, test, iterate, and monitor to meet production
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requirements.
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Opik gives you all the tools you need to go from LLM observability to action across your AI
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application footprint and dev cycle. Ship measurable improvements with gorgeous logs, annotation and
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scoring functions, pre-configured LLM-as-a-judge [eval metrics](/v1/evaluation/metrics/overview), and
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even [automated agent optimization algorithms](/v1/agent_optimization/overview) to maximize performance.
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## End-to-End AI Engineering
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<Frame>
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<img src="/img/home/EndToEnd-Engineering-Diagram.jpg" />
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</Frame>
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<Tip>
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Opik is Open Source! You can find the full source code on [GitHub](https://github.com/comet-ml/opik) and the complete
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self-hosting guide can be found [here](/v1/self-host/local_deployment).
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</Tip>
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## Core Functions
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<CardGroup cols={2}>
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<Card title="Quickstart Guide" href="/v1/quickstart" icon="fa-solid fa-rocket" iconPosition="left">
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Opik integrates with your existing AI stack through your model provider or LLM framework.
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</Card>
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<Card title="LLM Observability - Log LLM Traces" href="/v1/tracing/log_traces" icon="fa-solid fa-eye" iconPosition="left">
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Traces give you instant visibility into what's working, what's not, and why and includes
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advanced analysis and debugging features built in.
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</Card>
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<Card title="Evaluation - Score Performance" href="/v1/evaluation/overview" icon="fa-solid fa-chart-line" iconPosition="left">
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Use LLM-as-a-judge and heuristic eval metrics to score your app or agent on hallucination,
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context recall, and more.
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</Card>
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<Card title="Agent Optimization" href="/v1/agent_optimization/overview" icon="fa-solid fa-brain" iconPosition="left">
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Choose from six advanced optimization algorithms to auto-generate and score the best prompts for
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the steps in your agentic system.
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</Card>
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<Card title="Prompt Engineering" href="/v1/prompt_engineering/prompt_management" icon="fa-solid fa-wand-magic-sparkles" iconPosition="left">
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Store and version system prompts, compare results live in the [Prompt Playground](/v1/prompt_engineering/playground),
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and experiment with different models with our LLM proxy.
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</Card>
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<Card title="Self-hosting Opik" href="/v1/self-host/overview" icon="fa-solid fa-server" iconPosition="left">
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Deploy Opik on your own infrastructure with local or Kubernetes deployment options.
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</Card>
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</CardGroup>
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## Video Tutorials
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Prefer a visual guide ? Follow along as we cover everything from basic setup and trace logging to
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LLM evaluation metrics, production monitoring, and more.
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<Frame>
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<iframe
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width="100%"
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height="500px"
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src="https://www.youtube-nocookie.com/embed/TO9ar6-OJj4?rel=0"
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frameborder="0"
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allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share; fullscreen"
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referrerpolicy="strict-origin-when-cross-origin"
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allowfullscreen
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></iframe>
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</Frame>
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<Tip>
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You can find a full set of video tutorials in the [Opik University](/v1/opik-university/overview).
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</Tip>
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## Open-Source access meets enterprise performance
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All Opik versions ([cloud](https://www.comet.com/signup?from=llm),
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[open source](https://github.com/comet-ml/opik), and
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[enterprise](https://www.comet.com/site/pricing/)) include the full AI engineering featureset
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and run on the Comet platform, with proven performance at scale supporting many of the world's
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largest organizations.
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Compare Opik to other LLM observability tools and you'll find that traces populate faster,
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evaluations run smoother, and reliability comes standard — even for complex agentic systems serving
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millions of users in production.
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