Task Extraction using Flask and NLP

This project extracts tasks, recognizes names, identifies deadlines, and categorizes tasks from user-input text using Flask, Regex, and Natural Language Processing (NLP). The extracted tasks are displayed dynamically in a web interface with relevant information.

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Features

• ✅ Recognizes and extracts tasks with names and deadlines.
• ✅ Categorizes tasks into relevant categories such as:
  • Shopping
  • Review
  • Submission
  • Meeting
  • General
• ✅ Handles multiple names and deadlines correctly within paragraphs.
• ✅ Provides a clean and interactive UI using Bootstrap.

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Technologies Used

• Python (Flask)
• Regex for pattern matching
• Bootstrap for responsive design
• HTML, CSS, JavaScript for frontend

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How It Works

1. Input Text: User enters text describing multiple tasks with deadlines and names.
2. Task Extraction: The task_extractor.py extracts:
   • Task description
   • Person’s name
   • Task deadline
   • Task category
3. Display Results: Tasks are displayed with relevant information on the results page.

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🖥️ Setup and Installation

1. Clone the Repository

git clone https://github.com/Av-b16/Task-Extraction.git cd Task-Extraction

2. Create a Virtual Environment python3 -m venv venv source venv/bin/activate # For Linux/Mac

or

venv\Scripts\activate # For Windows

3. Install Dependencies pip install -r requirements.txt

4. Run the Flask Application python app.py Visit http://127.0.0.1:5000 in your browser.

Usage-: Open the web app. Enter the text describing tasks with names and deadlines. Click "Submit" to extract and categorize tasks. View extracted tasks with details on the result page.