🏛️ Aadhar Insight: Sophisticated Data Intelligence

An AI-powered analytics agent designed to query, visualize, and analyze 2.2 Million rows of UIDAI Aadhar enrollment data using Natural Language.

🚀 Project Overview

The Aadhar Insight platform bridges the gap between massive, complex SQL databases and end-users. Instead of writing manual SQL queries, users can interact with the data using natural language. The system interprets the intent, executes optimized SQL against a PostgreSQL backend, and returns structured analysis alongside interactive visualizations.

✨ Key Features

• Generative AI Querying: Integrated Gemini 1.5 Flash with LlamaIndex to translate English questions into high-performance SQL.
• Big Data Optimization: Engineered to handle and process a dataset of 2.2 Million records stored in PostgreSQL.
• Dynamic Dashboard: A custom Streamlit interface with a "Soft UI" aesthetic.
• Interactive Visuals: Automated bar charts generated via Plotly Express based on real-time data results.
• Modular Data Views: Uses expandable sections to organize Analysis, Visualizations, Raw Data, and the generated SQL Query for transparency.
• Enterprise Security: Implemented python-dotenv for secure management of API keys and database credentials.

🛠️ Tech Stack

• AI Model: Google Gemini 1.5 Flash
• Orchestration: LlamaIndex (NLSQLTableQueryEngine)
• Database: PostgreSQL & SQLAlchemy
• Frontend: Streamlit
• Visualization: Plotly & Pandas

📂 Project Structure

• app.py: Main application UI and session state management.
• body.py: AI engine configuration and LlamaIndex logic.
• database_connection.py: Secure database engine setup.
• .env.example: Template for required environment variables.
• .gitignore: Ensures sensitive files like .env and __pycache__ are not tracked.

📦 Installation & Setup

To run this project locally, follow these steps:

1. Clone the Repo:

   git clone [https://github.com/susendran-k/Natural-Language-to-SQL.git](https://github.com/susendran-k/Natural-Language-to-SQL.git)
   cd Natural-Language-to-SQL```
   

2. Install Dependencies:

   pip install streamlit llama-index-llms-gemini sqlalchemy psycopg2 python-dotenv plotly pandas ```
   

3. Configure Environment: Create a .env file in the root directory and add:

   GEMINI_API_KEY=your_key DB_USER=postgres DB_PASSWORD=your_password DB_HOST=localhost DB_NAME=your_db_name

4. Run the App:

   streamlit run app.py
   

Developed as a sophisticated data intelligence solution for high-volume Aadhar record analysis.