FocusSuite

An intelligent desktop productivity tool to eliminate distractions and streamline video editing.

FocusSuite is a Python-based desktop application designed to help users maintain focus. It has two main features:

1. Focus Monitor: It actively watches your screen, using AI to identify and obscure distracting text in real-time.
2. Focus Video: It processes video files, automatically blurring elements based on a simple descriptive prompt you provide.

You can replace this text with a GIF or video of FocusSuite once you've created it!

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Key Features ✨

Focus Monitor (Distraction Blocker)

• Real-time Screen Analysis: Employs Tesseract OCR to extract on-screen text for analysis.
• Intelligent Obscuring: Uses OpenAI's gpt-4o (or a local LLM alternative) to intelligently find and blur distracting content.
• Efficient Performance: A smart monitoring loop uses SSIM image comparison to detect screen changes, preventing redundant analysis and saving system resources.

Focus Video (Automated Blurring)

• Prompt-Based Editing: Simply describe what you want blurred, and FocusSuite handles the rest.
• Flicker-Free Results: It generates a definitive "blur timeline" after analyzing keyframes, ensuring the blur is smooth and consistent without the flickering common in frame-by-frame AI analysis.
• Audio Preservation: The original audio track is perfectly preserved and re-attached to the final edited video using MoviePy.

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Tech Stack 🛠️

Category	Technology
UI Framework	Tkinter (with modern themed widgets)
AI & LLM	OpenAI (gpt-4o), Tesseract OCR, Local LLM via Worker Endpoint
Video Processing	OpenCV, MoviePy
Image Analysis	Pillow, scikit-image
System Tools	pystray (for system tray icon), keyboard (for global hotkeys), pywin32 (for Windows functions)

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🚀 Getting Started

Follow these instructions to get FocusSuite running on your local machine.

Prerequisites

• Python 3.9+
• Tesseract OCR
• FFmpeg

Installation & Configuration

1. Clone the repository:

   git clone https://github.com/your-username/FocusSuite.git
   cd FocusSuite

2. Install Python dependencies:

   pip install -r requirements.txt

   This will install all necessary packages like openai, opencv-python, moviepy, and others.

3. Configure your environment variables:

   • Create a copy of the example environment file and name it .env:

     cp .env.example .env

   • Open the new .env file and add your secret API keys and URLs.

Running the Application

Once the installation and configuration are complete, you can start the application with:

python FocusSuite/main.py

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Architecture Highlights 🏗️

This project is built on a foundation of clean, maintainable code principles.

• Separation of Concerns (SoC): The application is strictly modularized. The UI (ui/), core logic (core/), and external API communication (api/) are completely decoupled, making the system easy to scale and test.
• Callback-Driven UI: The core application logic is headless and has no direct knowledge of the UI. It communicates with the Tkinter front-end via a dictionary of callback functions, meaning the user interface can be completely replaced without affecting the backend.
• Encapsulated Feature Managers: Each major feature is orchestrated by a dedicated manager (e.g., FocusMonitorManager, VideoFeatureManager). The main app.py orchestrator simply delegates tasks, keeping the central logic clean and readable.

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Contributing 🤝

Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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License 📜

Distributed under the MIT License. See LICENSE for more information.