Repo2Resume

AI Resume Builder: Crafting your perfect application and matching you with the right job—effortlessly.

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Inspiration

Many students struggle to effectively summarize their projects for resumes, often missing opportunities to showcase their skills.
This challenge motivated us to create a tool that simplifies and automates the process, enabling students to present their projects confidently.

What It Does

  • GitHub Repository to Resume:
    The website takes a GitHub repository as input and generates a resume-friendly summary using the STAR method (Situation, Task, Action, Result). The summary highlights the project's purpose, key features, technologies used, and measurable outcomes.

  • Tailored Cover Letter:
    It creates personalized cover letters by analyzing the job description, required skills, desired role, and company details, ensuring a professional and customized application.

  • Tinder-Like Job Search:
    The platform offers an engaging Tinder-style experience for job discovery. Using a vector database, it retrieves the most relevant job opportunities based on the user's resume, making the job search process interactive and efficient.

How We Built It

  1. GitHub to Resume Conversion:

    • Utilized the GPT-4o Mini model, fine-tuned on a curated dataset of 50 samples.
    • Integrated strict prompting to ensure outputs adhered to the STAR method format.

  2. Tailored Cover Letter Creation:

    • Employed the GPT-4o Mini model with inputs including job description, required skills, role, and company details to generate tailored cover letters.

  3. Tinder-Style Job Search:

    • Implemented a vector database for job matching.
    • Tools Used:
      • Pinecone for vector storage and retrieval.
      • Hugging Face models to embed text into vector format for semantic search.

  4. Frontend Development:

    • Built using React.js for dynamic user interfaces.
    • Styled with Tailwind CSS for a modern, responsive design.

  5. Deployment:

    • Backend: Dockerized and deployed on Render.
    • Frontend: Deployed using Terraform on AWS, enabling automated and scalable infrastructure setup.

Challenges We Ran Into

  • Learning Curve with Next.js:
    We initially struggled with Next.js due to limited experience, leading to delays before transitioning to React.

  • Terraform Complexity:
    Applying Terraform for AWS deployment was challenging due to its abstracted automation, requiring significant effort to understand its setup and usage.

  • Work Distribution:
    Uneven task distribution was a significant challenge, as one team member was new to hackathons and lacked experience in various frameworks, necessitating rapid role adjustments.

Accomplishments We're Proud Of

  • Successfully built a functioning website with core features.
  • Overcame deployment challenges, successfully launching the platform using Terraform on AWS.

What We Learned

  • Gained practical experience in web development with React and deployment automation using Terraform.
  • Recognized the importance of understanding team capabilities before starting a competition to ensure fair and effective task allocation.

What's Next for Repo2Resume

The project is still under development, leaving room for significant improvements.
Future enhancements include:

  • Adding suggestions for skills, frameworks, and technologies when analyzing GitHub repositories.
  • Improving fine-tuning for the AI model to deliver more precise outputs, keeping costs manageable for students.

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