This Chrome extension tells you what a website is about before you visit it. It's like having a quick preview or a summary of the site's content.
It uses AI to read the website's content and gives you a brief description. Here's how it's set up:
- Backend with FastAPI: This part talks to the AI service to get the website descriptions.
- Chrome Extension Frontend: This is what you interact with in your browser.
- Get quick summaries of websites with a click.
- Powered by AI for accurate descriptions.
- Simple and easy to use.
- Clone this repo to your computer
git clone https://github.com/Ahmet-Dedeler/ai-site_description-chrome-extension.git
- Create a virtual environment
python -m venv openai-env
# Activate virtual environment (Linux/Mac)
source openai-env/bin/activate
# Activate virtual environment (Windows)
openai-env\Scripts\activate
- Set up the backend by installing required packages
pip install -r requirements.txt
- Create a .env file
- Run the FastAPI server
uvicorn main:app --reload
- Load the extension in Chrome by going to
chrome://extensions/
, turning on Developer mode, and loading thefrontend
folder.
If you prefer to use Docker, you can easily set up the backend without manually configuring the environment.
- Build the Docker image
docker build -t uvicorn-backend .
- Run the Docker container
docker run -d -p 8000:8000 \
-e OPENAI_API_KEY=your_value_here \
-e ENVIRONMENT=production \
ai-site_description-chrome-extension-backend
Replace your_value_here with your actual OpenAI API key.
For development mode, use:
docker run -d -p 8000:8000 \
-e OPENAI_API_KEY=your_value_here \
-e ENVIRONMENT=development \
ai-site_description-chrome-extension-backend
This command starts the backend service, making it accessible on port 8000.
-
The Docker setup includes both development and production configurations.
-
In development mode, the app uses uvicorn with hot-reloading enabled.
-
In production mode, the app uses gunicorn for better performance and stability.
-
Set the ENVIRONMENT variable to either development or production when running the container.
If you have ideas for improvements or find a bug, feel free to contribute. Your input helps make this tool better for everyone.
This project is open-source under the MIT License. You're free to use, change, and share it.