ApplyMate is an AI-powered personal job assistant that automates your entire application journey — from customizing resumes & cover letters to auto-applying for jobs and preparing you for interviews with interactive mock questions.

ApplyMate streamlines the job hunting process by combining NLP, OCR, and generative AI.

• On signup, users provide personal details and upload their CV.
• When given a job description (text, file, or screenshot), ApplyMate parses the requirements and tailors a resume + cover letter.
• The system then applies automatically to the job portal on your behalf.
• Finally, ApplyMate supports you with interview prep, generating likely questions and simulating Q&A sessions with interactive cards.

• 📝 Smart Resume Customization — Tailors CV for each job role
• 📄 Cover Letter Generator — Drafts professional letters aligned with JD
• 📤 Auto Job Application — Submits applications on your behalf
• 🖼 Multi-Input JD Parsing — Accepts JD as text, PDF, or image (OCR)
• 🎤 Interactive Interview Prep — Mock questions & practice cards
• 🧠 AI-Powered — Uses NLP & LLMs for semantic understanding
• 📊 Application Tracking — Keeps record of applied jobs
• 🌐 Web App — Accessible from browser, no installs needed
• ⚡ Deployed on Vercel for scalability and smooth user access

ApplyMate/
├── backend/ # API logic (resume, JD parsing, auto apply)
│ ├── main.py # FastAPI entry point
│ ├── resume_builder.py # Resume customization logic
│ ├── cover_letter.py # Cover letter generator
│ ├── jd_parser.py # Job description parsing (OCR + NLP)
│ ├── auto_apply.py # Job application automation
│ ├── interview_prep.py # Mock interview module
│ ├── database.py # Supabase/Postgres integration
│ └── requirements.txt # Python dependencies
│
├── frontend/ # Next.js + React web app
│ ├── pages/ # Routes
│ ├── components/ # Reusable UI components
│ ├── styles/ # TailwindCSS + Shadcn UI styling
│ └── package.json # Node dependencies
│
├── .env.example # Environment variable template
├── README.md # Documentation
└── vercel.json # Vercel deployment config

git clone https://github.com/your-username/ApplyMate.git
cd ApplyMate

cd backend
pip install -r requirements.txt

Configure .env:

OPENAI_API_KEY=your_openai_key 
SUPABASE_URL=your_supabase_url 
SUPABASE_KEY=your_supabase_key 
GOOGLE_CREDENTIALS=path_to_google.json 

Run backend:

uvicorn main:app --reload

cd frontend
npm install
npm run dev

1. Push repo to GitHub.
2. Go to Vercel.
3. Import repo → Select frontend as root → Add env vars.
4. Deploy 🎉

1. Signup → Provide details + upload CV
2. Input JD → Upload as text, file, or screenshot
3. Customization → AI rewrites CV & cover letter
4. Auto-Apply → Fills forms & submits application
5. Interview Prep → Interactive Q&A session with mock questions

👤 Usama Shahid

📧 dev.usamashahid@gmail.com

🔗 LinkedIn

🐙 GitHub

This project is for academic and career-assistance purposes. Feel free to fork & improve, but credit is appreciated 🙏