TextClassifierProject

Overview

An end-to-end AI project that classifies text inputs into categories using a trained ML model. The project includes a Flask API as backend and a Streamlit frontend for real-time interaction.

Project Structure

File	Purpose
data.py	Load training dataset and category labels
ML.py	Train the Naive Bayes model and save necessary files
app.py	Flask backend API for predictions
frontend.py	Streamlit frontend interface
model.pkl	Trained ML model
vectorizer.pkl	Text vectorizer
categories.pkl	Category labels
requirements.txt	Python dependencies

Installation

Clone the repository:

git clone https://github.com/shahdkabi/TextClassifierProject/
cd TextClassifierProject

Install dependencies:

pip install -r requirements.txt

Usage

Flask API

python app.py

Server runs at: http://127.0.0.1:5000/

Streamlit Frontend

streamlit run frontend.py

Opens a web interface to enter text and see predictions

Examples

Input	Output
"I want to buy a new car"	Category: Cars
"New research shows medicine can cure disease"	Category: Medical

Workflow Diagram

graph TD
    A[User Input Text] --> B[Streamlit Frontend]
    B --> C[Flask API]
    C --> D[Load model.pkl]
    C --> E[Load vectorizer.pkl]
    C --> F[Text Preprocessing]
    F --> G[Vectorize Text]
    G --> D
    D --> H[Predict Category]
    H --> I[Return Result]
    I --> B
    B --> J[Display Prediction]

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Future Enhancements

• ✅ Show prediction confidence scores
• ✅ Support more categories
• ✅ Store predictions in a database
• ✅ Deploy online for public use