For AI agents: a documentation index is available at the root level at /llms.txt and /llms-full.txt. Append /llms.txt to any URL for a page-level index, or .md for the markdown version of any page.
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DocumentationIntegrationsAgent OptimizationSelf-hosting OpikSDK & API referenceOpik University
DocumentationIntegrationsAgent OptimizationSelf-hosting OpikSDK & API referenceOpik University
    • Overview
  • Intro
    • Opik Overview
    • Next steps / Set expectations
  • Observability
    • Log Traces
    • Annotate Traces
  • Evaluation
    • Evaluation Concepts and Overview
    • Create Evaluation Datasets
    • Define Evaluation Metrics
    • Evaluate your LLM Application
    • No-code LLM Evaluation Workflow
  • Prompt Engineering
    • Prompt Management
    • Prompt Playground
  • Testing
    • PyTest Integration
  • Production Monitoring
    • Online Evaluation Rules
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  • What to Expect from Opik University
  • Key Highlights
Intro

Next steps / Set expectations

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What to Expect from Opik University

This video sets the stage for your learning journey through Opik University. You’ll understand the structure of the upcoming video series, learn what topics will be covered, and discover what you need to get started with hands-on practice using Opik’s comprehensive LLM platform.

Key Highlights

  • Comprehensive Coverage: Series covers observability, evaluation, prompt engineering, testing, and production monitoring in detail
  • Hands-On Learning: Each video includes example notebooks accessible via links, with all content available in Opik documentation and cookbooks
  • Bite-Sized Format: Videos are focused on specific tasks, making them easy to reference when needed
  • Flexible Learning Path: Watch in order for building concepts, or jump to specific topics as needed
  • Easy Setup: Requires a Comet account (free at https://comet.com) and basic Python/LLM familiarity
  • Framework Flexibility: Choose from extensive integrations page, or use LiteLLM/OpenRouter for unsupported models
  • Beginner-Friendly: High-level concepts make it accessible even for beginners with willingness to learn
  • Complete Preparation: By series end, you’ll have all knowledge needed for robust LLM observability, evaluation, and monitoring