FishFlow 🐟💨

Slogan: "Where your eyes flow effortlessly, like a fish in the sea."

Logo: A minimalistic fish swimming in a stream, representing focus and flow.

Project Overview

This project is a Swift-based application designed to read texts displayed on Apple devices using OpenAI's Text-to-Speech (TTS) API. The app focuses on providing a minimalist yet powerful solution, seamlessly integrated across the Apple ecosystem.

Key Features

1. Text Extraction:

   • Online texts: Extract content from webpages (e.g., articles, blogs).
   • Local texts: Read from files like PDFs, Apple Pages documents, and plain text files.
   • OCR for screen text using the Vision framework.

2. Text-to-Speech:

   • Use OpenAI's API for generating satisfying voice outputs.
   • Native integration with AVSpeechSynthesizer for fallback functionality.

3. User Interface:

   • Unified interface using SwiftUI for macOS, iOS, and iPadOS.
   • Accessibility-first design for users with ADHD and other needs.

Use Cases

• Reading long paragraphs from web browsers, PDF viewers, Apple Pages, or Google Docs.
• Accessible reading tool for both online and offline content.
• Seamless usage across Apple devices.

Feasibility Evaluation

The transition to Swift for a cross-Apple ecosystem app is feasible due to:

Advantages

1. Seamless Ecosystem Integration:

   • Swift enables deep integration with Apple hardware and software.
   • Frameworks like SwiftUI, AVFoundation, and Vision provide robust tools for this project.

2. User Experience:

   • Apps built with Swift are optimized for responsiveness and performance.
   • Accessibility features can be seamlessly integrated.

3. Performance:

   • Swift's optimizations ensure real-time performance.
   • Native support for modern Apple APIs.

4. Skill Growth:

   • Transitioning to Swift offers valuable experience for future Apple ecosystem projects.

Challenges

1. Learning Curve:

   • Familiarity with Swift and Apple frameworks requires initial investment.

2. Cross-Platform Scope:

   • Limited to the Apple ecosystem, with potential expansion challenges if cross-platform support is needed later.

3. API Integration:

   • Requires managing RESTful calls to OpenAI's API in Swift.

4. Testing & Deployment:

   • Testing across multiple Apple devices and joining the Apple Developer Program ($99/year).

Development Goals

1. Build a Minimal Viable Product (MVP) with essential functionality:

   • Extract and process text from various sources.
   • Use OpenAI's TTS API to convert text to speech.
   • SwiftUI-based interface for cross-device compatibility.

2. Plan future improvements:

   • Add advanced OCR for screen-wide text recognition.
   • Optimize performance for real-time text-to-speech conversion.
   • Cloud sync for reading progress across devices.

Technologies Used

• Programming Language: Swift
• Frameworks:
  • SwiftUI: For building the user interface.
  • AVFoundation: For TTS and audio playback.
  • Vision: For OCR and text detection.
• APIs: OpenAI's Text-to-Speech API

Why This Project?

Inspired by the functionality of the Speechify Chrome extension, this project aims to provide:

• Independence from web browsers.
• A seamless experience across the Apple ecosystem.
• A clever solution balancing functionality with simplicity, catering to ADHD challenges.

Developer's Note

I am an intermediate programmer transitioning from Python to Swift for this project. I aim to create a solution that is elegant, intuitive, and deeply integrated with Apple's ecosystem. Suggestions and contributions are welcome!