Exercise - Implement semantic search in Azure Managed Redis
In this exercise, you create an Azure Managed Redis resource and complete the code for a vector storage application. The application loads sample vector data, stores new vectors with metadata, retrieves vectors by key, and performs similarity searches to find related products. You implement core vector operations including storing vectors with metadata, retrieving stored vectors, calculating vector similarity using cosine similarity, and searching for similar vectors.
Tasks performed in this exercise:
- Download the project starter files
- Create an Azure Managed Redis resource
- Add code to complete business logic
- Run the apps to load, store, and search vector data
This exercise takes approximately 40 minutes to complete.
Before you start
To complete the exercise, you need:
- An Azure subscription with the permission to create an Azure Managed Redis instance with an enterprise SKU. If you don't already have one, you can sign up for one.
- Visual Studio Code on one of the supported platforms.
- Python 3.12 or greater.
- The latest version of the Azure CLI.
- The Azure CLI redisenterprise extension.
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
