tabmind 0.3.0

TabMind - Smart Tab Manager with AI assistance and productivity features

TabMind - Smart Tab Manager with AI Assistance

A powerful Python CLI tool to manage your browser tabs, track why you opened them, set deadlines, and get AI-powered productivity reminders using GitHub Copilot.

Features

• Save Tabs: Quickly save URLs with context about why you opened them
• Auto-Fetch Titles: Automatically retrieve page titles from URLs
• Due Dates: Set deadlines for your tabs to stay on track
• Mark as Done: Track which tabs you've completed
• Statistics: View analytics about your saved tabs
• Review Tabs: View all saved tabs with their reasons, titles, due dates, and status
• AI Prompts: Generate smart motivation prompts for your pending tasks using GitHub Copilot
• Simple CLI: Easy-to-use command-line interface
• Persistent Storage: Tabs are saved locally in JSON format
• Python Library: Use TabMind as a library in your own Python projects

Table of Contents

• Installation
• Quick Start
• Usage
  • CLI Commands
  • Using as a Python Library
• Requirements
• Project Structure
• Contributing
• License

Installation

From Source (Development)

git clone https://github.com/IshikaBanga26/TabMind.git
cd TabMind
pip install -e .

From PyPI (Once Published)

pip install tabmind

Quick Start

Add a Tab

tabmind add https://example.com
# When prompted, enter why you opened this link
# The page title will be fetched automatically

Add a Tab with Due Date

tabmind add https://example.com --due-date 2024-12-31
# or
tabmind add https://example.com -d 2024-12-31

Review Your Tabs

tabmind review

Mark a Tab as Done

tabmind mark-done 1
# Marks tab #1 as completed

Set a Due Date

tabmind due-date 2 2024-12-25
# Sets a due date for tab #2 (format: YYYY-MM-DD)

View Statistics

tabmind stats

Shows total tabs, completed count, pending count, and tabs with due dates.

Generate AI Prompts

tabmind ai-prompt

This will output GitHub Copilot prompts for pending tabs that you can run manually:

gh copilot -p "Your generated prompt here"

Usage

CLI Commands

tabmind add <URL> [OPTIONS]

Save a new tab with a reason for opening it. Optionally set a due date.

$ tabmind add https://github.com
Why did you open this link? Learn Git workflows
✓ Tab saved successfully!

$ tabmind add https://python.org --due-date 2024-12-31
Why did you open this link? Check Python documentation
✓ Tab saved successfully!

tabmind review

Display all saved tabs with their details including titles, due dates, and status.

$ tabmind review

[1] ⏳ Pending | Due: 2024-12-31
    Title: GitHub: Where the world builds software
    URL: https://github.com
    Reason: Learn Git workflows
    Added: 2026-02-14 19:18:23

[2] ✓ Done
    Title: Welcome to Python.org
    URL: https://python.org
    Reason: Check Python documentation
    Added: 2026-02-14 19:20:15

tabmind mark-done <TAB_NUMBER>

Mark a specific tab as completed.

$ tabmind mark-done 1
✓ Tab 1 marked as done!

tabmind due-date <TAB_NUMBER> <DATE>

Set or update a due date for a tab (format: YYYY-MM-DD).

$ tabmind due-date 3 2024-12-25
✓ Due date for Tab 3 set to 2024-12-25

tabmind stats

Display statistics about your saved tabs.

$ tabmind stats

TabMind Statistics
========================================
Total Tabs:      10
Completed:       4 
Pending:         6 
With Due Date:   5 
========================================

tabmind ai-prompt

Generate AI-powered productivity reminders for pending tabs.

$ tabmind ai-prompt

-----------------------------------
Run this command in your terminal:

gh copilot -p "You are a productivity assistant.

The user saved this link:
URL: https://github.com
Reason: Learn Git workflows
Date Added: 2026-02-14 19:18:23

Write a short motivational reminder asking if they want to continue this task.
Keep it under 3 lines."

-----------------------------------

Using as a Python Library

Import TabMind functions in your own Python projects:

from storage import add_tab, get_tabs, mark_tab_done, set_due_date, get_stats, fetch_page_title

# Add a tab with auto-fetched title
add_tab("https://example.com", "Research machine learning")

# Add a tab with due date
add_tab("https://github.com", "Learn Git workflows", due_date="2024-12-31")

# Get all saved tabs
tabs = get_tabs()
for tab in tabs:
    print(f"Title: {tab['title']}")
    print(f"URL: {tab['url']}")
    print(f"Reason: {tab['reason']}")
    print(f"Status: {'Done' if tab['completed'] else 'Pending'}")
    print(f"Due: {tab.get('due_date', 'N/A')}")

# Mark a tab as done
mark_tab_done(0)

# Set a due date
set_due_date(1, "2024-12-25")

# Get statistics
stats = get_stats()
print(f"Total: {stats['total']}, Completed: {stats['completed']}")

# Fetch page title
title = fetch_page_title("https://example.com")
print(f"Page title: {title}")

Requirements

• Python 3.8+
• click >= 8.0.0 (for CLI functionality)
• requests >= 2.28.0 (for fetching page titles)
• beautifulsoup4 >= 4.11.0 (for parsing HTML)
• (Optional) GitHub CLI with Copilot access (for AI features)

Install Requirements

pip install -r requirements.txt

Project Structure

TabMind/
├── main.py                 # CLI entry point and commands
├── storage.py              # Tab storage, retrieval, and title fetching
├── ai_helper.py            # GitHub Copilot integration
├── tabs.json               # Local storage for tabs (auto-generated)
├── setup.py                # Package setup configuration
├── pyproject.toml          # Modern Python packaging config
├── requirements.txt        # Project dependencies
├── MANIFEST.in             # Additional files to include in distribution
├── LICENSE                 # MIT License
└── README.md               # This file

Data Storage

Tabs are stored locally in a tabs.json file in your current directory. Each tab entry contains:

{
  "url": "https://example.com",
  "title": "Example Domain",
  "reason": "Why you opened this link",
  "date_added": "2026-02-14 19:18:23",
  "due_date": "2024-12-31",
  "completed": false
}

Note: The storage location can be customized by modifying the FILE_NAME variable in storage.py.

Development

Setup Development Environment

# Clone the repository
git clone https://github.com/IshikaBanga26/TabMind.git
cd TabMind

# Create a virtual environment
python -m venv venv

# Activate virtual environment
# On Windows:
venv\Scripts\activate
# On macOS/Linux:
source venv/bin/activate

# Install in development mode
pip install -e .

# Install development dependencies
pip install -r requirements.txt

Testing Commands

# Test adding a tab
tabmind add https://test.com

# Test reviewing tabs
tabmind review

# Test AI prompt generation (requires GitHub Copilot)
tabmind ai-prompt

Contributing

Contributions are welcome! Here's how you can help:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/AmazingFeature)
3. Make your changes
4. Commit your changes (git commit -m 'Add some AmazingFeature')
5. Push to the branch (git push origin feature/AmazingFeature)
6. Open a Pull Request

Areas for Contribution

• Add unit tests
• Improve error handling
• Add support for additional data formats (CSV, SQLite)
• Implement cloud synchronization
• Add more AI integration options
• Improve documentation

Reporting Issues

Found a bug? Please open an issue on the GitHub Issues page with:

• Description of the bug
• Steps to reproduce
• Expected behavior
• Your environment (OS, Python version)

Future Features

• Web-based dashboard for viewing tabs
• Browser extension for quick tab saving
• Cloud synchronization
• Tab categorization and tagging
• Advanced analytics and insights
• Integration with more AI services
• Export to various formats (PDF, CSV, HTML)

License

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

Author

Your Name - Ishika Banga

Acknowledgments

• Built with Click - Python CLI framework
• GitHub Copilot integration for AI assistance
• Inspired by productivity and tab management tools

Contact & Support

For questions or support:

• Open an issue on GitHub
• Email: [e-mail]
• Check the Discussions page

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Happy tab management!