Lessume

Inspiration

We were inspired by the need for a simpler way to apply for jobs. The process of going to multiple websites, logging in, uploading a resume, and then having to refill information that is already on the resume is time consuming and frustrating. We wanted to eliminate those steps and make it easy for job hunters and recruiters alike to find a match.

What it does

Lessume takes a PDF file of the users resume. It then uses a LLM to organize and analyze the text, focusing on the applicants skills and experience, and uploaded to a database. Recruiters can use the application to search for keywords to find exactly the right applicants for their needs.

How we built it

Lessume was written in Python, using Streamlit for the UI, ChatGPT for language processing, and mongoDB for the database.

Challenges we ran into

One challenge was settling on a feasible project for the team to work on, after spending some time on a concept that didn't work. We also had some hurdles setting up the application and getting the different parts to communicate with each other.

Accomplishments that we're proud of

We are proud that we pushed through the difficulties and continued our project late into the night and throughout the next day.

What we learned

We learned how to set up streamlit and mongoDB, and how to avoid problems with simultaneous changes being made to the source code.

What's next for Lessume

Using Llama for LLM, expanding tokenization features, and scalability.

Built With

• chatgpt
• cloudflare
• mongodb
• python
• streamlit