The problem skill-eval solves

We have tried creating an automation for resume screening that happens before any hiring process. In the project we are aiming to create chatbots that can ask questions after the user has submitted his/her resume and the next chatbot will answer with the help of the resume. We are also aiming to create a GitHub bot that will rate the projects after carefully judging the code mentioned and will score them based on various criteria. In all, we are making the work of HR much easier and also trying to replace the ATS score system as it is manipulative to a great extent. We have kept in mind various scenarios and are trying to build an application that will facilitate authenticating, automated, and unique products for resume-based screening.
We have used LM Studio, for the mistral 7B model. For making the frontend we have used ReactJs, used Django for the backend and also used python.

Challenges we ran into

It is a very intricate project with a lot of parameters to decide on and then to find out the scores for these parameters. It was a difficult task to figure out what should be the criteria and the parameters which we should evaluate the candidate’s resume or github projects on, as per the job description. Deciding the strictness of parameters that we have decided to score the candidates was also confusing.
We faced challenges also while running openAI in our local setup.Managing a project which includes such vast features and alot to focus on, becomes difficult. Keeping in mind every single detail and use case as we build what we aim for feels a little bit difficult to manage. We were uncertain at every step and had our share of doubts. We took it step by step and started making basic things and then built the project over it.