Text-to-SQL with Streamlit & LangChain

This project is a Text-to-SQL web application built with Streamlit and LangChain, powered by Google Generative AI (Gemini).
It allows users to ask natural language questions about their data, automatically generates SQL queries, and also executes those queries on the connected database to return results.

Live Demo: https://textto-sql.streamlit.app/

---

Features

• Convert natural language questions into SQL queries.
• Execute the generated SQL queries directly on the database.
• View both the generated SQL and the query results.
• Simple Streamlit-based UI for easy interaction.
• Powered by LangChain and Google Generative AI (Gemini).

---

Tech Stack

• Frontend/UI: Streamlit
• LLM & Orchestration: LangChain
• LLM Provider: Google Generative AI (Gemini)
• Database: SQLite (example, can be replaced with your own DB)
• Deployment: Streamlit Cloud (Free hosting)

---

Project Structure

. ├── sql.py # Main Streamlit app ├── requirements.txt # Python dependencies ├── .streamlit/ │ └── secrets.toml # Environment variables (API key, DB config) └── README.md # Project documentation

Setup & Installation

1. Clone the repository

   git clone https://github.com/Sreenath67/text-to-sql.git
   cd text-to-sql
   

Example Question: "What are the different tables in the database?"

Generated SQL:

SELECT name FROM sqlite_master WHERE type='table';

Executed Result: [('users',), ('orders',), ('products',)]