Let Users Talk to Your Databases: Build a RAG-Powered SQL Assistant with Streamlit

Create a database-agnostic chatbot that connects to SQLite, BigQuery, and Redshift.

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Most business users don’t directly access databases because they do not know where to look or how to query them. Rather, they might ask a data practitioner, ‘What were our top 5 products last quarter?’ From experience, I know that these requests can be frustrating and tend to be a productivity killer. Therefore, a core goal of any data practitioner should be to empower individuals to access data and insights independently.

So what if users could just talk to your database?

Retrieval and Augmentation (RAG) systems speak to this idea. By leveraging large language models (LLMs) and integrating them with specific data sources, RAG systems allow individuals to ask questions using natural language.

In this article, I’ll focus on a specific application of RAG: transforming natural language into SQL queries and executing them against a database engine.

Data storage rarely happens centrally. Therefore, this article covers building a database-agnostic RAG pipeline allowing users to access data in…