JobCopilot — AI-Powered Job Application Tailoring

Stop sending generic applications. Start getting hired.

Live Demo: https://job-copilot-cyan.vercel.app

JobCopilot is a full-stack AI web app that takes your resume PDF and a job description, then rewrites your resume bullets to match the job's ATS keywords and generates a tailored cover letter — all in under 60 seconds.

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Features

• Upload resume PDF + paste job description
• AI extracts ATS keywords from the job description
• Rewrites your resume bullets to match naturally — using your real projects by name
• Generates a 3-paragraph tailored cover letter
• Downloads a formatted DOCX file instantly
• User auth with Supabase (login / signup)
• Dashboard with application history and stats
• Tone selector: Professional / Technical / Casual

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Tech Stack

Layer	Tech
Frontend	Next.js 14, TypeScript, Inline Styles
Backend	FastAPI, Python 3.11
AI	Groq API — llama-3.3-70b-versatile
Auth + DB	Supabase
PDF Parsing	PyMuPDF (fitz)
DOCX Export	python-docx
Frontend Deploy	Vercel
Backend Deploy	HuggingFace Spaces (Docker)

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Project Structure

job-copilot/
├── backend/
│   ├── main.py          # FastAPI app — POST /tailor endpoint
│   ├── parser.py        # PyMuPDF PDF text extraction
│   ├── ai.py            # Groq llama-3.3-70b prompt chains
│   ├── exporter.py      # python-docx DOCX generation
│   ├── requirements.txt
│   └── Dockerfile       # HuggingFace Spaces deployment
│
└── frontend/
    ├── app/
    │   ├── page.tsx         # Landing page
    │   ├── auth/page.tsx    # Login + Signup
    │   ├── dashboard/page.tsx # Application history
    │   └── tool/page.tsx    # Main tailoring tool
    └── lib/
        └── supabase.ts      # Supabase client

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How It Works

1. User uploads resume PDF + pastes job description
2. FastAPI parses the PDF using PyMuPDF
3. Groq llama-3.3-70b extracts ATS keywords from the JD
4. Second Groq call rewrites resume bullets using candidate's real projects
5. Third Groq call generates a tailored cover letter
6. Output packaged as DOCX and returned for download
7. Application saved to Supabase for dashboard tracking

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Local Setup

Backend

cd backend
python -m venv venv
venv\Scripts\activate
pip install -r requirements.txt

Create .env:

GROQ_API_KEY=your_groq_key
SUPABASE_URL=your_supabase_url
SUPABASE_SERVICE_KEY=your_service_role_key

Run:

uvicorn main:app --reload

Frontend

cd frontend
npm install

Create .env.local:

NEXT_PUBLIC_SUPABASE_URL=your_supabase_url
NEXT_PUBLIC_SUPABASE_ANON_KEY=your_anon_key
NEXT_PUBLIC_API_URL=http://127.0.0.1:8000

Run:

npm run dev

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API

POST /tailor

Accepts multipart form data:

Field	Type	Description
resume_file	File	PDF resume
jd_text	string	Job description
candidate_name	string	User's name
tone	string	professional / technical / casual
user_id	string	Supabase user ID (optional)

Returns: DOCX file download

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Deployment

• Frontend: Vercel — auto-deploys from GitHub main branch
• Backend: HuggingFace Spaces (Docker) — https://huggingface.co/spaces/musadiq7860/job-copilot-api

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Built By

Mussadiq — Pakistan

• GitHub: @musadiq7860
• LinkedIn: muhammad-musadiq