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microsoft/microsoft-sql

v1.0.0

Build and operate Azure SQL Database applications, from provisioning and secure connections through schema design, deployment, data movement, performance tuning, vector search, RAG, and local development with the Azure SQL Database container.

langchain-and-llamaindex-on-azure-sql

Wires LangChain or LlamaIndex to Azure SQL Database from Python: the SQL toolkits, their text to SQL prompts, the langchain-sqlserver vector store, and the guardrails neither framework enforces. Use when someone asks to "use LangChain with Azure SQL", "build a SQL agent over the database", "text to SQL", "SQLDatabaseToolkit", "NLSQLTableQueryEngine", "which LlamaIndex vector store works with Azure SQL", or "make the SQL agent read only"; when a SQL agent keeps generating LIMIT, its query checker approves a query the database refuses, or its schema tool puts real rows into the prompt; or when a framework-created embedding table refuses CREATE VECTOR INDEX or a metadata filter throws arithmetic overflow. Vector type and query shape are vector-search-azure-sql, the cloud pipeline is rag-on-azure-sql, and drivers and token authentication are connect-from-python. Offline local embedding is an application-side workflow.

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