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RAG using Semantic Kernel with Azure OpenAI and Azure Cosmos DB | Python Data Science Day

Visual Studio Code
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604 views 1 year ago
"Learn about the new capabilities of Azure Cosmos DB for MongoDB vCore and Semantic Kernel that enables you to use vector search and integrate your AI-based applications with your data that's stored in Azure Cosmos DB. Vector search enables you to efficiently store, index, and query high-dimensional vector data that are stored directly in Azure Cosmos DB for MongoDB vCore. Semantic Kernel enables the integration with Azure OpenAI to perform retrieval augmented generation (RAG) and bring everything together. John Aziz, a Microsoft AI MVP and a Gold Microsoft Learn Student Ambassador from Egypt. 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 flask app. Follow along as we provide clear inst …...more
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RAG using Semantic Kernel with Azure OpenAI and Azure Cosmos DB | Python Data Science Day
12Likes
604Views
2024Mar 28
"Learn about the new capabilities of Azure Cosmos DB for MongoDB vCore and Semantic Kernel that enables you to use vector search and integrate your AI-based applications with your data that's stored in Azure Cosmos DB. Vector search enables you to efficiently store, index, and query high-dimensional vector data that are stored directly in Azure Cosmos DB for MongoDB vCore. Semantic Kernel enables the integration with Azure OpenAI to perform retrieval augmented generation (RAG) and bring everything together. John Aziz, a Microsoft AI MVP and a Gold Microsoft Learn Student Ambassador from Egypt. 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 flask app. Follow along as we provide clear instructions, make the process accessible to both beginners and experienced tech enthusiasts. By the end, you'll have a fully functional Flask application capable of generating responses using vector search and rag. Check it out here: https://github.com/john0isaac/rag-sem..." Chapters: 00:00 RAG using Semantic Kernel with Azure OpenAI and Azure Cosmos DB 00:33 Agenda 01:06 Prerequisites 01:43 Microsoft Technologies used 12:05 Concepts used 14:34 Demo - RAG in Jupyter Notebooks 29:32 Resources Resources: Blog: https://aka.ms/Python/DataScienceDay/... Access to Azure OpenAI: https://aka.ms/oai/access Code: https://github.com/john0isaac/rag-sem... Docs: https://learn.microsoft.com/azure/ai-... https://learn.microsoft.com/azure/cos... https://learn.microsoft.com/semantic-... Repo: https://github.com/microsoft/semantic... Vector Search on embeddings with Azure Cosmos DB for MongoDB vCore https://learn.microsoft.com/azure/cos... Survey https://aka.ms/Python/DataScienceDay/... Python at Microsoft https://aka.ms/python Cloud Skills Challenge - through April 15, 2024 https://aka.ms/Python/DataScienceDay/CSC GitHub codespaces https://github.com/codespaces VS Code Release notes https://code.visualstudio.com/updates Featuring: John Azia, Microsoft, MVP (@john00isaac)

Follow along using the transcript.

Visual Studio Code

754K subscribers