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Doorlook

Doorlook is a project designed to analyze companies and how they treat their employees. It consists of a backend built with FastAPI and a frontend built with React. The project utilizes web scraping and various AI tools to gather and analyze opinions about companies.

Table of Contents

Features

  • Analyze companies based on various metrics.
  • Evaluate employee treatment and satisfaction.
  • Web scraping to gather opinions from various sources.
  • AI tools for opinion analysis and sentiment detection.
  • RESTful API for backend services.

Project Structure

The project scaffold could be found in STRUCTURE.

Getting Started

Prerequisites

  • Python 3.12
  • Node.js and npm
  • Docker (optional, for containerization)

Installation

  1. Clone the repository:

    git clone https://github.com/Gogeloo/doorlook.git
    cd doorlook
  2. Backend setup:

    Navigate to the backend directory and install dependencies using Poetry:

    cd backend
    poetry install
  3. Frontend setup:

    Navigate to the frontend directory and install dependencies using npm:

    cd frontend
    npm install

Running the Project

  1. Running the backend:

    cd backend
    poetry run uvicorn app.main:app --reload

    The backend will be available at http://localhost:8000.

  2. Running the frontend:

    cd frontend
    npm start

    The frontend will be available at http://localhost:3000.

  3. Using Docker:

    Alternatively, you can use Docker to run both backend and frontend:

    docker-compose up --build

    This will start both services and make them available at their respective ports.

Pre-commit Hooks

This project uses pre-commit hooks to ensure code quality. To install and update the hooks, run:

pre-commit install

Usage

Navigate to http://localhost:3000 to access the frontend interface. Use the available endpoints to interact with the backend API (e.g., http://localhost:8000/docs for the FastAPI documentation).

Contributing

Contributions are welcome! Please follow these steps to contribute:

  • Fork the repository.
  • Create a new branch (git checkout -b feature/your-feature).
  • Make your changes.
  • Commit your changes (git commit -am 'feat: add new feature').
  • Push to the branch (git push origin feature/your-feature).
  • Create a new Pull Request.

Please read the CONTRIBUTING for more details.

License

This project is licensed under the MIT License - see the LICENSE file for details.

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Analyze employers with the help of AI

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