- Azure account and subscription with Owner permissions
- Python 3.11 or higher
- Visual Studio Code
- Python extension for VS Code
- Jupyter Notebook extension for VS Code
- Docker Desktop with WSL 2 backend (if on Windows)
- Azure CLI
- Bicep CLI
- Powershell
The future of software involves combining AI and data services, also known as intelligent applications. This guide is for MongoDB developers looking to implement intelligent applications quickly while leveraging existing skills. The content will focus on the developer journey implementing an Azure-based AI-enabled GPT-based chat application that is augmented using data stored in vCore for Azure Cosmos DB for MongoDB while leveraging Azure OpenAI services.
This guide will walks through the creating intelligent solutions that combines vCore-based Azure Cosmos DB for MongoDB vector search and document retrieval with Azure OpenAI services to build a chat bot experience. The guide includes labs that build and deploy a sample chat app using these technologies, with a focus on vCore-based Azure Cosmos DB for MongoDB, Vector Search, and Azure OpenAI using the Python programming language. For those new to using Azure OpenAI and Vector Search technologies, the guide includes explanations of the core concepts and techniques used when implementing these technologies.
Note: This developer guide is targeted towards Python developers. If you are a Node.js developer, then you may be interested in the Node.js version here: https://github.com/AzureCosmosDB/Azure-OpenAI-Node.js-Developer-Guide