Plagiarism Detection System

A powerful plagiarism and AI-generated content detection system that helps identify potential plagiarism and detect AI-generated text in a variety of file formats, including text documents and images. Built using Flask, SQLite, and advanced AI models, this tool provides a simple and efficient way to ensure the integrity of written content.

Features

• Text Plagiarism Detection: Upload and analyze text files (.txt, .docx, .pdf) to detect similarities with previously uploaded documents.
• Image Plagiarism Detection: Upload image files (.jpeg, .png, .jpg) to compare with stored image embeddings for similarity.
• AI-Generated Text Detection: Detect AI-generated content in text using advanced AI models.
• Web Interface: Simple and user-friendly web interface for easy interaction with the system.
• SQLite Database: Stores document and image embeddings for comparison and similarity detection.

Table of Contents

• Features
• Technologies Used
• Installation
• Usage
• API Endpoints

Technologies Used

• Flask: Web framework for building the backend API and front-end views.
• SQLite: Lightweight relational database for storing document and image embeddings.
• NumPy: Used for handling image and document embeddings.
• AI Models: Pre-trained models for detecting AI-generated content.
• Jinja2: Templating engine for rendering HTML pages.

Installation

To set up the plagiarism detection system locally, follow the steps below.

Prerequisites

• Python 3.12+
• Virtual Environment (recommended)
• SQLite3 (already included with Python)

Step-by-Step Setup

1. Clone the repository:

   git clone https://github.com/Kyle6012/plagiarism-detection.git
   cd plagiarism-detection
   

2. Set up a virtual environment:

   python3 -m venv venv
   source venv/bin/activate
   venv\Scripts\activate # On Windows 
   

3. Install dependencies:

   pip install -r requirements.txt
   

4. **Create the SQLite database(if not already created): The database will automatically be created when the appliaction runs for the first time , but you can manually set any other database:

sqlite3 plagiarism_detection.db < schema.sql

5. Run application:

   flask run 
   # or 
   python3 app.py
   

6. Access the system: Open your browser and go to http://localhost:5000.

Usage

Once the application is running you can interact with the following features:

1. Home Page: Welcome message and a button to get started.
2. File Upload: Upload text or image files to be processed for plagiarism detection. - . Text Files: Supported formats: .txt, .docx, .pdf - . Image Files: Supported formats: .jpeg, png, jpg
3. Compare Files: Upload a file and compare it against a dataset to calculate similarity scores.
4. AI Detection: The uploaded files runs through ai detection to detect if content is ai generated.

API Endpoints

1. POST /upload

Purpose: Upload a filefor processing. Request: file: The file to be uploaded (txt,jpg, etc). Response - . Success: {"message": "Text file processed and saved."} or {"message": "Image file processed and saved."}. - . Error: {"error": "Unsupported Format."}.

2. POST /compare

Purpose: Upload a file to compare against stored documents/images. Request: . file to be compared. Response: . Similarity results for text or image comparison: { "simalarities": [0.92,0.87,0.70], "labels": ["Document 1", "Document 2","Document 3", "Document 3"] }

3. POST /detect-ai

Purpose: Submit text to detect AI-generated content. Request: . text: The text to analyze. Response: . AI-generated probability score { "ai_generated_probability": 0.78 }