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An intelligent chatbot built with Flask and MySQL that translates natural language queries into SQL to explore global development indicators like GDP, life expectancy, and internet usage across countries and years. It combines NLU, database design, and query generation to deliver insights from structured data.

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ShubhamP1028/Development-Metrics-Chatbot

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🌍 Global Development Insights Chatbot

A conversational AI chatbot that translates natural language questions into SQL queries and retrieves data from a MySQL database of global development indicators. It is developed using Flask, MySQL, and proprietary NLP logic.

Chatbot Preview License Language


📂 Project Structure

project/

├── app.py

├── devmatric.py

├── datatransformation.py

├── cleaneddata.py

├── templates/

└── index.html

✨ Features

  • 🔍 Ask questions like:
    "What was the GDP of India in 2021?"
    "Show top 5 countries by life expectancy in 2010."
    "Which countries had birth rate above 50 in 2015?"

  • 🧠 Intelligent Natural Language Parsing

  • 🔗 Live SQL Query Generation

  • 📊 Real-time Results from MySQL

  • 🌐 Clean Web UI with Flask + HTML

  • ✅ Supports range filters, comparisons, top/bottom queries, and aggregations

✅ Sample Queries

Try the following:

  • "What was GDP of India in 2021?"
  • "Average life expectancy in Brazil from 2000 to 2020"
  • "Top 10 countries by HDI in 2018"
  • "Infant mortality above 50 in 2005"

📊 Dataset Info

This project uses a global development dataset that includes:

HDI, PHI, GDP, GNI, Education & Health Metrics

Cleaned, normalized, and loaded via MySQL

📁 datacleaning.py and datatransformation.py scripts prepare your data.

🔒 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙌 Author Shubham P. 3rd Year B.Tech (Data Science) 📧 shubham30p@gmail.com

⭐️ Star this repo if you find it useful!


Visit http://localhost:5000 in your browser.

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An intelligent chatbot built with Flask and MySQL that translates natural language queries into SQL to explore global development indicators like GDP, life expectancy, and internet usage across countries and years. It combines NLU, database design, and query generation to deliver insights from structured data.

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