Learn about the new capabilities of Azure Cosmos DB for MongoDB vCore and Semantic Kernel that enable you to use vector search and integrate your AI-based movie recommendation applications. Vector search enables you to efficiently store, index, and query high-dimensional vector data along with operational data that is stored directly in Cosmos DB for MongoDB vCore. Semantic Kernel enables integration with Azure OpenAI to perform retrieval augmented generation (RAG) and bring everything together.
In this session, you’ll learn about vector search, RAG, and the steps you need to perform to enable it using the semantic kernel, discover how to set up an Azure Cosmos DB for MongoDB vCore, deploy the Azure OpenAI chat and embedding model, learn about how the semantic kernel works, and integrate it in a quart app.
Join us in building a Flask application capable of generating responses using vector search and RAG, catering to tech enthusiasts of all expertise levels.
#azurecosmosdb #ai #azureopenai
Useful links:
• (GitHub) RAG using Semantic Kernel with Azure OpenAI and Azure Cosmos DB for MongoDB vCore – https://github.com/john0isaac/rag-semantic-kernel-mongodb-vcore
• Azure OpenAI Service documentation
– https://learn.microsoft.com/azure/ai-services/openai
• Azure Cosmos DB for MongoDB vCore documentation
– https://learn.microsoft.com/azure/cosmos-db/mongodb/vcore
• Semantic Kernel documentation
– https://learn.microsoft.com/semantic-kernel
• Use vector search on embeddings in Azure Cosmos DB for MongoDB vCore
– https://learn.microsoft.com/azure/cosmos-db/mongodb/vcore/vector-search
• Semantic Kernel GitHub with Samples and Notebooks – https://github.com/microsoft/semantic-kernel
• Subscribe to this channel – https://aka.ms/AzureCosmosDBYouTube
• Check out past meetups on YouTube to catch anything you might have missed – https://www.youtube.com/playlist?list=PLmamF3YkHLoJSJ1qdHDXXSlmkj2HKz-nb
• Want to present at a future meetup? Fill out our intake form – https://aka.ms/AzureCosmosDB/UserGroupSubmission
• Try Azure Cosmos DB Free – https://aka.ms/trycosmosdb
• Microsoft Reactor – https://aka.ms/Reactor
Speakers:
Khelan Modi – Microsoft, Product Manager
Bio: Khelan Modi, a dynamic Product Manager at the forefront of the Azure Cosmos DB team, seamlessly integrates his deep expertise in databases with a passion for AI innovation. Focused on the transformative potential of vector search, Khelan consistently pioneers modern AI methodologies to enhance product functionalities across industries like advertisements and retail.
John Aziz – GEMINDZ, Software Developer
Bio: John is deeply passionate about continuously expanding his knowledge in software engineering and developer roles, driven by the desire to both learn new technologies and share my insights with others. His expertise extends to the realm of Cloud Computing, where he has honed his skills and demonstrated my capabilities. Additionally, He possesses the Microsoft AI MVP award. He had the privilege of developing official content for both the Microsoft Tech Community and Microsoft Learn, contributing to the broader knowledge-sharing ecosystem.
