Gemini Resume Analyzer

Our tool provides enhanced feedback and personalized guidance to tailor your resume to any job description, increasing your visibility to employers and helping you stand out in a competitive market.

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Inspiration

In today's competitive job market, students and professionals struggle to optimize their resumes for Applicant Tracking Systems (ATS) and hiring managers. Inspired by my own personal experience of applying to 300 jobs accross the globe, I set out to build an AI-powered resume analyzer with that provided actionable insights to improve job application success rates.

In spirit with vibe coding I've decided to only submit code written by Perplexity such that I have to prompt engineer my request so that the AI will fix it's own bugs. 100% of my code is written by AI, I am just a human debugger. Let me tell you this was not a vibe, I spent more time deep in Stack Overflow and issue documentation than I was in Perplexity!

What it does

  1. Resume Parsing - Handles file uploads and extracts text from resumes efficiently using React.js.
  2. Job Matching Analysis -Uses Google Gemini API with prompt engineering to provide keyword suggestions and improvement tips.
  3. Hosting & Deployment - Application is hosted on Firebase, with backend services on Google Cloud (Heroku deployment in progress).

How we built it

Frontend: Developed using React.js Backend: Built with Flask and integrated with Google Gemini API for AI-driven resume analysis. File Handling: Used Python libraries such as pdfplumber and docx2txt to extract text from various resume formats. Cloud Services: Leveraged Firebase for frontend hosting andHeroku for backend processing. AI & NLP: Used spaCy and Gemini API for keyword extraction and job-resume matching.

Challenges we ran into

Deployment Issues: Debugging dependency conflicts and ensuring smooth hosting on Firebase and Google Cloud.

Accomplishments that we're proud of

1 Integrated Google Gemini API effectively to provide real-time job matching and ATS score insights.

  1. Developed an intuitive UI that allows users to quickly upload resumes and receive actionable feedback.
  2. Successfully built an end-to-end AI-powered resume analysis tool within a limited timeframe.

What we learned

  1. Improved skills in React.js and Flask integration for seamless frontend-backend communication.
  2. Understood the importance of prompt engineering for effective AI-powered analysis.
  3. Gained hands-on experience with Firebase, Google Cloud and Heroku for full-stack deployment.

What's next for Gemini Resume Analyzer

  1. GitHub Integration: Auto-analyze projects from a user’s GitHub profile to enhance portfolio evaluation.
  2. Deploy it on Heroku and Firebase
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