Resume Resurrector

Inspiration

The delay in receiving timely and thorough resume feedback poses a significant challenge for students. Waiting for extended periods for reviews only to discover fundamental errors in their resumes can be frustrating and counterproductive. This delay hampers the iterative improvement process critical for an effective resume. Thus we want to provide students a chance to improve these basic mistakes, so that they can get more detailed critique by a professional after waiting in line for hours.

What it does

Review Resumes

How we built it

Our web app, built with Python and Streamlit for the frontend, leverages OpenAI's Language Model (LLM) integrated through Langchain for precise resume evaluation. Users input resumes and the LLM, with its natural language processing offers accurate assessments. This fusion of Python, Streamlit, Langchain and OpenAI's LLM streamlines the review process transforming it from manual to efficient.

Challenges we ran into

Initial Challenges were figuring out how to get Conda installed on everyone's PC's. Following that we struggled with managing the API keys that we utilized for OpenAI and integrating the API in our final project. In the end I believed we accomplished what we set out to do.

Accomplishments that we're proud of

We accomplished our main goal which is integrating OpenAI into our resume reviewer and creating a presentable working product which can be used both personally and professionally multiple times.

What we learned

Over the course of our 2 years of college, we realized the importance of having a good resume. Over time we have collectively had our resumes reviewed by hundreds of individuals, and we realized we wanted to create something that would provide us with instant feedback and a grading score about our resume after we added new material. We learned about the importance of constant feedback on our resumes to positively affect our professional and personal goals.