CVDOTAI

CVDOTAI is a web application designed to analyze resumés and job descriptions. It uses artificial intelligence to provide structured recommendations that help optimize the match between the candidate’s profile and the job requirements.

Features

• Resumé Analysis: Upload your resumé in pdf format, with detailed content analysis.
• Job Offer Evaluation: Allows input of a descriptive text of a job offer for analysis.
• AI-based Recommendations: Uses the Gemini AI API to compare the résumé with the job offer, generating suggestions on how to improve the candidate's presentation.
• Modern and User-Friendly Interface: The application is built with Angular 18 and Angular Material, offering a smooth and intuitive user experience.
• Robust Backend: The backend of the application is developed with Django 4, ensuring efficient data management and request processing.

Technologies

• Frontend: Angular 18, Angular Material
• Backend: Django 4
• AI API: Gemini AI

Installation and Configuration

Prerequisites

• Node.js (v16 or higher)
• Angular CLI (v18 or higher)
• Python (v3.8 or higher)
• Django (v4 or higher)
• Gemini AI API Key

Installation

1. Clone the repository:

   git clone https://github.com/your-username/cvdotai.git
   cd cvdotai

2. Install frontend dependencies:

   cd frontend
   npm install

3. Install backend dependencies:

   cd backend
   pip install -r requirements.txt

Configuration

1. Gemini AI API Key:

   In the backend, make sure to configure your Gemini AI API key in a .env file:

   AI_API_KEY=your-api-key

2. Frontend Enviroment Variable:

   In the frontend, make sure to configure your API_URL in a .env file:

   NG_APP_API_URL=your-backend-url

Running

1. Start the Angular development server:

   cd frontend
   ng serve

   The application will be available at http://localhost:4200.

2. Start the Django server:

   cd backend
   python manage.py runserver

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

Usage

1. Upload a resumé in PDF.
2. Enter the text of the job offer.
3. Receive recommendations to improve the match between the candidate’s profile and the job offer.

Contributions

Contributions are welcome. Please open an issue or create a pull request to discuss proposed changes.

License

This project is licensed under the MIT License. See the LICENSE file for more details.