JobGPT

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  Logo

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  Skill selection

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  Upon load

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  Job recommendation result

Inspiration

Economic recession in 2023 has cast a discouraging shadow over individuals’ job search endeavors, further exacerbated by the pervasive oversaturation witnessed across all industries within the market. We seek to harness the power of JobGPT, a cutting-edge application, to facilitate the discovery of employment opportunities that align precisely with individuals’ unique skill sets. We aspire to reignite the motivation of job seekers in persisting with their pursuits of gainful employment during these challenging times.

What it does

Users can upload their resume to the app, and then it will automatically be parsed and the skills, work experience, and other important details are extracted. From that data, our backend server-side code selects a suggest set of skills and job titles that the user can choose from, and based on these choices, we scrape the API for BCJobs, a popular job site to come up with recommendations that suit the user. Then, users can see information about the recommended jobs, such as title, location, company, and a link to apply for the job.

How we built it

Frontend: HTML, CSS, MUI, React.js Backend: FastAPI, Python, BCJobs API, resume-parser library

Challenges we ran into

• SFU wifi sucks
• Difficulties setting up development environment at the start
• A very short timeline. The hackathon was only 9 hours long.

Accomplishments that we're proud of

• We are succesfully able to implement a recommendation system for jobs
• Integrating server-side code to parse resumes and provide recommendations with client-side code
• Learning FastAPI

What we learned

• To not dabble too much with the setup process so we can focus more on the hacking
• Integrating a React frontend with a Python FastAPI backend
• How to handle file uploads properly

Built With

• bcjobs-api
• css
• fastapi
• html
• mui
• python
• react.js
• react.js-backend:-fastapi