This project is a web application that analyzes YouTube thumbnail images using AI to provide scores and improvement suggestions. It consists of a FastAPI backend and a React frontend.

• Upload YouTube thumbnail images
• Analyze thumbnails using AI (powered by Groq API)
• Provide scores and improvement suggestions for thumbnails
• Store analysis results in a database

The project is divided into two main parts:

1. Backend (FastAPI)
2. Frontend (React + TypeScript + Vite)

The backend is a FastAPI application that handles image uploads, analysis, and database operations.

Key components:

• FastAPI application
• SQLAlchemy for database operations
• Groq API integration for image analysis
• Error handling and environment configuration

The frontend is a React application built with TypeScript and Vite, providing a user interface for thumbnail uploads and result display.

Key components:

• React with TypeScript
• Vite for build and development
• Tailwind CSS for styling
• Various UI components and utilities

• Docker and Docker Compose
• Node.js (for local frontend development)
• Python 3.11+ (for local backend development)

1. Clone the repository:

   git clone https://github.com/UgolinOlle/ytb-thumbnail-analyser.git
   cd ytb-thumbnail-analyser
   

2. Move the .env.local file in the root directory to .env and complete it with your own credentials

   mv .env.local .env
   

3. Move the .env.local file in the backend directory to .env and complete it with your own credentials

   cd backend
   mv .env.local .env
   

4. Build and run the Docker containers:

   docker-compose up --build
   

5. The application should now be running:

   • Backend: http://localhost:8000
   • Frontend: http://localhost:3000

To run the backend locally for development:

1. Navigate to the backend directory

   cd backend
   

2. Create a virtual environment and activate it

   python -m venv venv
   source venv/bin/activate
   

3. Install dependencies: pip install -r requirements.txt
4. Run the FastAPI server: uvicorn app.main:app --reload

To run the frontend locally for development:

1. Navigate to the frontend directory

   cd frontend
   

2. Install dependencies: yarn
3. Start the development server: yarn dev

Once the backend is running, you can access the API documentation at:

• Swagger UI: http://localhost:8000/docs
• ReDoc: http://localhost:8000/redoc

This project is licensed under the MIT License.