Exercise - Build a RAG document store on Azure Cosmos DB for NoSQL
In this exercise, you create an Azure Cosmos DB for NoSQL database that serves as a document store for retrieval-augmented generation (RAG) applications. The database stores chunked documents with metadata that an AI application can retrieve to provide context to language models. You design a schema optimized for document retrieval, build Python functions that store and query document chunks, and test the complete workflow using a Flask web application. This pattern provides a foundation for building AI applications that ground language model responses in your organization's documents.
Tasks performed in this exercise:
- Download project starter files and configure the deployment script
- Deploy an Azure Cosmos DB for NoSQL account with a database and container
- Build Python functions for storing and retrieving document chunks
- Test the RAG functions using a Flask web application
- Query document context using the Cosmos DB SQL API
This exercise takes approximately 30 minutes to complete.
Before you start
To complete the exercise, you need:
- An Azure subscription with the permissions to deploy the necessary Azure services. If you don't already have one, you can sign up for one.
- Visual Studio Code on one of the supported platforms.
- The latest version of the Azure CLI.
- Python 3.12 or greater.
Get started
Select the Launch Exercise button to open the exercise instructions in a new browser window. When you're finished with the exercise, return here to:
- Complete the module
- Earn a badge for completing this module
