📊 AI-Powered SQL Data Analyst

This Streamlit app enables users to upload CSV or Excel files and perform automated SQL-based data analysis using Groq's LLM API. The app uses DuckDB to execute SQL queries generated from natural language inputs, making data exploration and analytics seamless for non-technical users.

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🎥 Demo

watch the demo

🔧 Features

• 🗂 Upload and manage multiple datasets (CSV, Excel)
• 🧠 Ask questions in plain English — the app generates and executes SQL queries using Groq’s LLM
• 🐥 Lightweight SQL execution engine (DuckDB)
• 🚀 Instant results and table previews

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🧪 Example Use Case

Upload a dataset like sales.csv and ask:

"What is the total revenue grouped by region?"

The app will:

1. Convert your question into an SQL query using Groq
2. Execute the query using DuckDB
3. Show the results in a clean table format

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🛠️ Technologies Used

• Python
• Streamlit – for web UI
• DuckDB – in-memory SQL execution engine
• Groq API – LLM-based SQL generation
• dotenv – environment variable management
• pandas – for data manipulation

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🚀 Getting Started

1. Install dependencies

pip install -r requirements.txt

2. Add your Groq API Key

Create a .env file in the root directory and include:

GROQ_API_KEY=your_actual_api_key_here

3. Run the App

streamlit run your_script_name.py

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📂 File Structure

.
├── app.py
├── requirements.txt
├── .env
└── README.md

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📌 Notes

• Only .csv and .xlsx files are supported
• Make sure to name tables meaningfully when uploading
• The SQL queries are generated based on column names and data types