PathToOffer AI

Local web app that uses AI to align your resume and interview prep with a specific job posting—so you see gaps, scores, and exports before you apply.

---

What it’s for

Job seekers paste a real job description, upload a resume, and get structured feedback (match score, missing keywords, tailored copy, practice questions). Everything runs on your machine with your own OpenAI key.

---

What you can do

Area	Capability
Job	Paste a JD; extract skills, keywords, and requirements
Resume	Upload PDF/text; parse, score vs job, see gaps
Optimization	Generate a resume version tuned to the posting
Cover letter	Draft tailored to that role
Prep	Interview questions with feedback; coding problems with review
Learning	Study roadmap when you’re missing skills
Export	Download resume, cover letter, interview pack, or a ZIP bundle

Try without your data: use Start demo on the home page.

---

Tools used

Layer	Tech
UI	Next.js, React, TypeScript, Tailwind CSS
API	Python, FastAPI, Uvicorn
AI	OpenAI API (configurable model; see ai/openai_provider.py)
Data	SQLite, SQLAlchemy
Files	PDF parsing (e.g. pypdf), PDF generation (ReportLab)

---

How to use

Prerequisites: Python 3.11+, Node.js 18+, an OpenAI API key.

1. Clone the repo and open a terminal at the project root.

2. Environment — create .env in the project root (same folder as this README):

   OPENAI_API_KEY=sk-...

   See .env.example for optional variables.

3. Install dependencies

   pip install -r requirements.txt -r backend/requirements.txt
   cd frontend && npm install && cd ..

4. Run — two terminals:

   # Terminal 1 — API
   cd backend
   python -m uvicorn main:app --reload

   # Terminal 2 — UI
   cd frontend
   npm run dev

5. Open http://localhost:3000 in the browser.

Data on disk: path_to_offer.db (database), uploads/ (resumes), exports/ (generated PDFs)—all under the project root.