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.
Copy to LLMGithubGo to App
DocumentationIntegrationsAgent OptimizationSelf-hosting OpikSDK & API referenceOpik University
DocumentationIntegrationsAgent OptimizationSelf-hosting OpikSDK & API referenceOpik University
  • Getting Started
    • Opik Agent Optimizer
    • Optimization Studio
    • Quickstart
    • Quickstart notebook
    • FAQ
    • Changelog
    • Known Issues
  • Optimization
    • Concepts
    • Configure LLM Providers
    • Define datasets
    • Define metrics
    • Optimize prompts
    • Optimize tools (MCP)
    • Optimize agents
    • Optimize multimodal
    • Dashboard results
  • Optimization Algorithms
    • Overview
    • Benchmarks
    • MetaPrompt
    • HRPO
    • Few-Shot Bayesian
    • Evolutionary
    • GEPA
    • Parameter
    • Tool Optimization
  • Cookbooks & Tutorials
    • Optimizer introduction
    • Synthetic data optimizer
    • ARC-AGI tutorial
    • Multimodal agent tutorial
  • Advanced Topics
    • Extending optimizers
    • Custom metrics
    • Custom optimizer prompts
    • Sampling controls
    • Multiple completions (n)
    • Chaining optimizers
    • API Reference
LogoLogo
Copy to LLMGithubGo to App
On this page
  • Load Example Notebook
  • What you’ll learn
  • Quick Start
Cookbooks & Tutorials

Optimizer Introduction Cookbook

Quick example notebook using HotPotQA dataset
Was this page helpful?
Previous

Synthetic Data Optimizer Cookbook

Advanced example notebook using synthetic datasets
Next
Built with

This example demonstrates end-to-end prompt optimization on the HotPotQA dataset using Opik Agent Optimizer. All steps, code, and explanations are provided in the interactive Colab notebook below.

This notebook powers the Quickstart notebook entry in the Agent Optimization navigation.

Load Example Notebook

To follow this example, simply open the Colab notebook below. You can run, modify, and experiment with the workflow directly in your browser—no local setup required.

PlatformLaunch Link
Google Colab (Preferred)Open in Colab
GitHubView the notebook on GitHub

What you’ll learn

  • How to set up Opik Agent Optimizer SDK
  • How to setup Opik Cloud (Comet Account) for prompt optimization
  • How to use the HotPotQA dataset for multi-hop question answering
  • How to define metrics and task configs
  • How to run the FewShotBayesianOptimizer and interpret results
  • How to visualize optimization runs in the Opik UI

Quick Start

  1. Click the Colab badge above to launch the notebook.
  2. Follow the step-by-step instructions in the notebook.
  3. For more details, see the Opik Agent Optimizer documentation.