Quick start: Prompt a foundation model with the retrieval-augmented generation pattern
Quick start: Prompt a foundation model with the retrieval-augmented generation pattern Take this tutorial to learn how to use foundation models in IBM watsonx.ai to generate factually accurate output grounded in information in a knowledge base by applying the retrieval-augmented generation pattern. Foundation models can generate output that is factually inaccurate for a variety of reasons. One way to improve the accuracy of generated output is to provide the needed facts as context in your prompt text. This tutorial uses a sample notebook using the retrieval-augmented generation pattern method to improve the accuracy of the generated output. Required services : Watson Studio : Watson Machine Learning Your basic workflow includes these tasks: 1. Open a project. Projects are where you can collaborate with others to work with data. 2. Add a notebook to your project. You can create your own notebook, or add a [sample notebook](https://dataplatform.cloud.ibm.com/gallery?context=wx&format=notebook) to your project. 3. Add and edit code, then run the notebook. 4. Review the notebook output. Read about retrieval-augmented generation pattern You can scale out the technique of including context in your prompts by leveraging information in a knowledge base. The retrieval-augmented generation pattern involves three basic steps: * Search for relevant content in your knowledge base * Pull the most relevant content into your prompt as context * Send the combined prompt text to the model to generate output [Read more about the retrieval-augmented generation pattern](https://dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/fm-rag.html?context=wx) Watch a video about using the retrieval-augmented generation pattern ![Watch Video](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/images/lc-video.png) Watch this video to preview the steps in this tutorial. There might be slight differences in the user interface shown in the video. The video is intended to be a companion to the written tutorial. This video provides a visual method to learn the concepts and tasks in this documentation. Try a tutorial to prompt a foundation model with the retrieval-augmented generation pattern In this tutorial, you will complete these tasks: * [Task 1: Open a project](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/get-started-fm-notebook.html?context=cdpaas&locale=enstep01) * [Task 2: Add a sample notebook to your project](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/get-started-fm-notebook.html?context=cdpaas&locale=enstep02) * [Task 3: Edit the notebook](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/get-started-fm-notebook.html?context=cdpaas&locale=enstep03) * [Task 4: Run the notebook and review the output](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/get-started-fm-notebook.html?context=cdpaas&locale=enstep04) Expand all sections * Tips for completing this tutorial ### Use the video picture-in-picture Tip: Start the video, then as you scroll through the tutorial, the video moves to picture-in-picture mode. Close the video table of contents for the best experience with picture-in-picture. You can use picture-in-picture mode so you can follow the video as you complete the tasks in this tutorial. Click the timestamps for each task to follow along.The following animated image shows how to use the video picture-in-picture and table of contents features: ![How to use picture-in-picture and chapters](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/images/pip-and-chapters.gif){: width="560px" height="315px" data-tearsheet="this"} ### Get help in the community If you need help with this tutorial, you can ask a question or find an answer in the [watsonx.ai Community discussion forum](https://community.ibm.com/community/user/watsonx/communities/community-home/digestviewer?communitykey=81927b7e-9a92-4236-a0e0-018a27c4ad6e){: new_window}. ### Set up your browser windows For the optimal experience completing this tutorial, open Cloud Pak for Data in one browser window, and keep this tutorial page open in another browser window to switch easily between the two applications. Consider arranging the two browser windows side-by-side to make it easier to follow along. ![Side-by-side tutorial and UI](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/images/tutorial-side-by-side-wx.png){: width="560px" height="315px" data-tearsheet="this"} Tip: If you encounter a guided tour while completing this tutorial in the user interface, click Maybe later. [Back to the top](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/get-started-fm-notebook.html?context=cdpaas&locale=envideo-preview) * Task 1: Open a project You need a project to store the sample notebook. Watch a video to see how to create a sandbox project and associate a service. Then follow the steps to verify that you have an existing project or create a sandbox project. This video provides a visual method to learn the concepts and tasks in this documentation. Follow the steps to verify that you have an existing project or create a project. 1. From the watsonx home screen, scroll to the Projects section. If you see any projects listed, then skip to [Associate the Watson Machine Learning service](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/get-started-fm-notebook.html?context=cdpaas&locale=enassociate). If you don't see any projects, then follow these steps to create a project. 1. Click Create a sandbox project. When the project is created, you will see the sandbox in the Projects section. 1. Open an existing project or the new sandbox project. \ Associate the Watson Machine Learning service with the project You will use Watson Machine Learning to prompt the foundation model, so follow these steps to associate your Watson Machine Learning service instance with your project. 1. In the project, click the Manage tab. 1. Click the Services & Integrations page. 1. Check if this project has an associated Watson Machine Learning service. If there is no associated service, then follow these steps: 1. Click Associate service. 1. Check the box next to your Watson Machine Learning service instance. 1. Click Associate. 1. If necessary, click Cancel to return