Offria

The Django application aims to assist individuals in their job search in the field of data and AI.

Application Content:

A dashboard presenting statistics on available job offers.
Mapping of job offers throughout France.
An advanced search system that displays job offers matching specific criteria (occupation, date, keywords, etc.).
A system for generating a tailored cover letter based on the job title, keywords from a selected job offer, and the user's profile.
A translation feature for job offers (any language to French | French to English).
A chatbot that provides assistance to the user during the application process.
Application support by redirecting users to relevant links containing various tips (CV writing, job interviews, etc.).

Used Models:

Azure Named Entity Recognition (NER) and corresponding naive model:

The Azure Named Entity Recognition API and the corresponding naive model are used to identify the skills present in the user's PDF CV and match them to a list of job offers containing the extracted skills.

Keyword extraction (KeyBERT):

KeyBERT is a Python project that simplifies the extraction of keywords from text. This model is used to extract keywords from the description of a job offer for which the user would like to apply. These keywords are then used to customize the generation of the cover letter based on the specific job offer description.

Cover letter generation using the OpenAI completion module:

The OpenAI API provides a completion service that generates text based on a prompt provided by the user. It is used to generate a cover letter tailored to the job offer selected by the user and their profile.

Language detection and translation:

The Python libraries used are langdetect and deeptranslator. The former is used to detect the language used in the text, while the latter is used for translation purposes.

OffrIA

Description:

Application Content:

Used Models: