- Python
- Flask
- MongoDB
- RabbitMQ
- PyMongo
- Unittest
This is a list of needed steps to set up your project locally, to get a local copy up and running follow these instructions.
- Clone the repository
$ git clone https://github.com/IntelliTalent/IntelliTalent-Flask.git - Navigate to project folder and create file named ".env"
$ touch .env & cd IntelliTalent-Flask - Fill ".env" file with required fields
- Install Docker and Docker Compose
- Start all microservices
$ docker compose up -d
This platform was implemented for our Graduation Project by a team of 4 students.
Intelli-Talent streamlines job searching and recruitment with features like automated CV and cover letter generation, job matching, and a Chrome extension for auto-filling application forms. For recruiters, it offers a comprehensive Application Tracking System (ATS) and multi-stage candidate filtration, including quizzes and interviews.
This platform is developed with React js for the frontend, Nest.js for some backend services, and Flask for the other backend services.
You can look at the API documentation after running the nest.js application at API Documentation
- Validation and template selection based on word embedding similarity.
- Template filling and file uploading.
- Extract common patterns from user job creation prompts.
- Generate structured jobs to be inserted into DB.
- Extract multiple sections information from user CV, (education, experience, ...)
- Helps to easily create powerful profiles for users.
- Extract information from unstrctured jobs (scraped from multiple channels, LinkedIn, Wuzzuf, ...).
- Genereate structured jobs to be inserted into DB.
- Map wanted job skills into certain topics.
- Generate MCQ quizzes based on wanted topics.
- Periodically scrapes jobs from multiple channels, currently, LinkedIn & Wuzzuf.
- Periodically checks whether jobs are active/not active in all channels.
 Yousef Alwaer |
 Beshoy Morad |
 Mohamed Nabil |
 Moaz Hassan |