--- description: Learn how to use Opik Agent Optimizer with the HotPotQA dataset through an interactive notebook, covering setup, configuration, and optimization techniques. headline: Optimizer introduction | Opik Documentation og:description: Learn to optimize prompts using Opik Agent on the HotPotQA dataset with a hands-on Colab notebook for seamless experimentation. og:site_name: Opik Documentation og:title: End-to-End Prompt Optimization with Opik subtitle: Quick example notebook using HotPotQA dataset title: Optimizer Introduction Cookbook --- 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. | Platform | Launch Link | | ---------------------------- | ----------- | | **Google Colab (Preferred)** | [Open in Colab](https://colab.research.google.com/github/comet-ml/opik/blob/main/sdks/opik_optimizer/notebooks/OpikOptimizerIntro.ipynb) | | **GitHub** | [View the notebook on GitHub](https://github.com/comet-ml/opik/blob/main/sdks/opik_optimizer/notebooks/OpikOptimizerIntro.ipynb) | ## 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](/development/optimization-runs/overview).