🩺 Diabetes Prediction Web Application with AI Chatbot

A machine learning–based web application that predicts diabetes risk based on user health data & also provides an AI chatbot assistant for interactive guidance.

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✨ Features

• Predicts diabetes risk using Support Vector Machine (SVM) model (Final2.pkl)
• Other trained models: Logistic Regression, Random Forest
• Integrated into a Flask web app
• Interactive front-end built with HTML/CSS
• AI Chatbot built with Voiceflow, connected via Replit backend to OpenRouter API
• Health Tools page: Product buttons redirect users to Amazon search results for that product
• Model serialized with Pickle for deployment

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📊 Dataset

• PIMA Indian Diabetes Dataset (diabetes.csv)
• Includes features such as: Glucose, BMI, Blood Pressure, Insulin, Age, Pregnancies, Diabetes Pedigree Function
• Data preprocessing performed with scaling for better model accuracy

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🧠 Model Training

• Trained Models:

  • Logistic Regression
  • Random Forest
  • Support Vector Machine (SVM) ✅

• Best Model:

  • Support Vector Machine (SVM) achieved the best performance
  • Saved as Final2.pkl and used in the deployed app

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💬 AI Chatbot

• Frontend: Integrated in the homepage using Voiceflow
• Backend: Replit server connects the chatbot to the OpenRouter API
• Functionality: Provides answers to user queries related to diabetes, health tips, and lifestyle

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🛠️ Technologies Used

• Backend: Python, Flask
• Frontend: HTML, CSS
• ML Libraries: scikit-learn, pickle
• AI Chatbot: Voiceflow, Replit backend, OpenRouter API
• Development: Jupyter Notebook

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📸 Screenshots

1. Homepage

2. 🤖 AI Chatbot

3. Health Tools

4. Diabetes Checkup Form

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📂 Project Structure

Diabetes_prediction_project/
│
├── main.py                # Flask app entry point
├── proj2.ipynb            # Jupyter Notebook for training models
├── diabetes.csv           # Dataset (PIMA Indian Diabetes Dataset)
├── Final2.pkl             # SVM model used for prediction
├── scaler.pkl             # Scaler for preprocessing
├── templates/             # HTML frontend
    ├── Home.html          # Homepage with AI chatbot
    ├── Test.html          
    ├── AboutUs.html
    ├── Diet&Exer.html
    ├── ExpertAdv.html
    ├── HealthTools.html
    └── prac.html
├── static/                # CSS, images, and other static assets
    ├── Css/
        ├── index.css
        ├── aboutus.css
        ├── test.css
        └── ...
    └── image/
        ├── logo.png
        ├── bg.avif
        ├── Homepage.png
        └── ...
└── README.md              # Project documentation

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🚀 How to Run

1. Clone this repository

   git clone https://github.com/SyedAbbas-02/Diabetes_prediction_project.git
   cd Diabetes_prediction_project
   
   

2. Install dependencies

   pip install flask
   pip install scikit-learn
   
   

3. Run the project

   python main.py
   

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