WeatherGPT

WeatherGPT is weather forecast application build with Angular and Django. It uses the Open Meteo API to get the weather forecast data and the GPT-3 API to generate the weather forecast summary.

Key Features • Key Technologies • Requirements • Docker Setup • Local Setup • Support • License

Key Features

• Weather forecast based on location
• Weather forecast summary generated by GPT-3
• ChartJS weather forecast visualization
• Responsive design

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Key Technologies

• Angular
• Django
• GPT-3
• Open Meteo API
• ChartJS
• TailwindCSS
• TypeScript
• Docker

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Requirements

• Dockeror (if running with Docker)
• Python
• Node.js

Docker Setup

1. Clone the repository:

git clone https://github.com/MartsTech/WeatherGPT.git

2. Navigate to the project directory:

cd WeatherGPT

3. Set up environment variables for the frontend. Navigate to the environments and then open the environment files and fill in the required variables.

4. Set up environment variables for the backend. Navigate to the .env.example file and copy it to a new file called .env and fill in the required variables.

5. Start the project using Docker Compose:

docker-compose up --build

6. Navigate to http://localhost:4200 to see the frontend running and http://localhost:8000 to see the backend.

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Local Setup

1. Clone the repository:

git clone https://github.com/MartsTech/WeatherGPT.git

2. Navigate to the project directory:

cd WeatherGPT

3. Set up environment variables for the frontend. Navigate to the environments and then open the environment files and fill in the required variables.

4. Set up environment variables for the backend. Navigate to the .env.example file and copy it to a new file called .env and fill in the required variables.

5. Install the frontend dependencies and start the development server (if you don't have pnpm installed, you can install it with npm install -g pnpm or use npm or yarn instead of pnpm):

cd frontend
pnpm install
pnpm start

6. Install the backend dependencies and start the development server:

cd backend
pip install -r requirements.txt
python manage.py runserver

7. Navigate to http://localhost:4200 to see the frontend running and http://localhost:8000 to see the backend.

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Support

Whether you use this project, have learned something from it, or just like it, please consider supporting it by buying me a coffee, so I can dedicate more time on open-source projects like this :)

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License

You can check out the full license here

This project is licensed under the terms of the MIT license