LangChain Integration for Vector Support for Azure SQL and SQL database in Microsoft Fabric
Microsoft SQL now supports native vector search capabilities in Azure SQL and SQL database in Microsoft Fabric. We also released the langchain-sqlserver package, enabling the management of SQL Server as a Vectorstore in LangChain. In this step-by-step tutorial, we will show you how to add generative AI features to your own applications with just a few lines of code using Azure SQL DB, LangChain, and LLMs.
Our Example Dataset
The Harry Potter series, written by J.K. Rowling, is a globally beloved collection of seven books that follow the journey of a young wizard, Harry Potter, and his friends as they battle the dark forces led by the evil Voldemort. Its captivating plot, rich characters, and imaginative world have made it one of the most famous and cherished series in literary history
By using a well-known dataset, we can create engaging and relatable examples that resonate with a wide audience
This Sample dataset from Kaggle contains 7 .txt files of 7 books of Harry Potter. For this demo we will only be using the first book – Harry Potter and the Sorcerer’s Stone.
Use cases:
Whether you’re a tech enthusiast or a Potterhead, we have two exciting use cases to explore:
A Q&A system that leverages the power of SQL Vector Store & LangChain to provide accurate and context-rich answers from the Harry Potter Book. Next, we will push the creative limits of the application by teaching it to generate new AI-driven Harry Potter fan fiction based on our existing dataset of Harry Potter books. This feature is sure to delight Potterheads, allowing them to explore new adventures and create their own magical stories.
Building the sample application
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