Inspiration

Job hunting is stressful enough—writing tailored cover letters for every role shouldn’t add to it. We wanted to automate this repetitive task and help applicants make strong first impressions instantly.

What it does

GotYouCovered auto-generates personalized, professional cover letters based on a user’s resume and the job title or description. It supports PDF and DOCX uploads and outputs a clean, editable letter in the user’s chosen tone—Professional, Friendly, or Enthusiastic.

How we built it

We built the frontend using Streamlit for a fast and interactive UI. Text extraction is handled using fitz (PyMuPDF) for PDFs and python-docx for DOCX files. We integrated DeepSeek R1 via OpenRouter to generate cover letters using advanced language modeling. Prompt engineering ensures letters are concise, relevant, and job-specific.

Challenges we ran into

  • Handling different document formats and extracting clean text.
  • Running into token limits when passing large resumes into the LLM.
  • Initial issues with OpenAI API quotas and model limitations, later resolved by switching to DeepSeek.

Accomplishments that we're proud of

  • A smooth and intuitive UI with reliable document parsing.
  • Successfully swapped out a paid API (OpenAI) with a free, capable alternative (DeepSeek).
  • Built a fully functional MVP in record time.

What we learned

  • Prompt engineering is key to quality outputs.
  • Efficiently managing token lengths is crucial for LLM stability.
  • Streamlit is awesome for quick prototypes with a clean UX.

What's next for GotYouCovered

  • Add support for multiple job titles with batch cover letter generation.
  • Let users import LinkedIn profiles directly for content extraction.
  • Deploy the app with user authentication and usage tracking.
  • Explore voice-based job descriptions for accessibility.

Built With

  • deepseek-r1
  • hugging-face-transformers
  • openrouter
  • promptengineering
  • pymupdf
  • python
  • python-docx
  • streamlit
Share this project:

Updates