CV Analyzer SaaS (MVP)

Tech stack:

• Next.js (frontend)
• Django REST Framework (backend)
• PostgreSQL
• Redis
• Celery
• Gemini API wrapper

What This Project Does

CV Analyzer is a SaaS-style platform that helps users improve their resumes with AI-powered feedback. Users can upload a CV, get ATS-style analysis, rewrite suggestions, and keyword gap detection, then save and share improved versions.

Core Product Flows

• Analyze-only flow: Upload CV -> async analysis job -> polling result (not permanently stored by default).
• Save flow: User explicitly saves the analyzed CV to PostgreSQL with version history.
• Share flow: User generates a view-only share token and sends a public link.

Key Capabilities

• Analyze source choice: CV file or GitHub profile/repository URL.
• AI output includes ATS score, strengths, weaknesses, missing keywords, rewritten summary, improved bullets, and next actions.
• Premium dashboard UI with dark/light mode.
• Resume builder with structured fields and one-click PDF export.

Product Roadmap

Phase 1 (Now)

• CV/GitHub source analysis with async processing.
• Resume save/share and one-click PDF export.
• Premium dashboard with dark/light mode.

Phase 2 (Next)

• Multiple PDF templates and style presets.
• Better CV parser for PDF/DOCX structured extraction.
• Usage analytics panel for users.

Phase 3 (Scale)

• Stripe billing + plan upgrades.
• Team workspace and shared resume libraries.
• Queue prioritization and AI usage cost controls.

How To Present This In Your CV

• Built an AI-powered CV optimization SaaS using Next.js, Django REST Framework, PostgreSQL, Redis, and Celery.
• Designed asynchronous processing for resume analysis to avoid API timeouts and improve responsiveness.
• Implemented secure auth, resume CRUD/versioning, share links, and environment-based secret management.
• Containerized full stack with Docker and documented reproducible local setup for team onboarding.

Security note

• Keep all secrets in local .env only.
• .env is ignored by git and must not be pushed to GitHub.

Contributing

• See CONTRIBUTING.md for branch, commit, and PR standards.

Live URLs

• Backend admin: https://backend-web-production-f301.up.railway.app/admin/auth/user/
• Frontend: https://shamshods-cv-analyzer.up.railway.app/

Docker Run Guide (Windows CMD)

1. Open Docker Desktop first (wait until engine is running).

2. Open cmd and move to project folder:

cd /d D:\SaaS\CV_analyzer

3. Verify Docker engine:

docker version
docker context use desktop-linux

4. Create .env from template (first time only):

copy .env.example .env

5. Fill required values in .env:

• DJANGO_SECRET_KEY
• POSTGRES_DB, POSTGRES_USER, POSTGRES_PASSWORD
• DATABASE_URL
• GEMINI_API_KEY

6. Build and start all services:

docker compose up -d --build

7. Run migrations:

docker compose exec web python manage.py migrate

8. Check status:

docker compose ps

9. Open:

• Frontend: http://localhost:3000
• API health: http://localhost:8000/api/health
• Backend admin: http://localhost:8000/admin

10. Stop when needed:

docker compose down

API

• GET /api/health
• POST /api/auth/register
• POST /api/auth/login
• POST /api/auth/refresh
• POST /api/analyze
• GET /api/analyze/{job_id}
• POST /api/resumes
• GET /api/resumes
• GET /api/resumes/{id}
• PATCH /api/resumes/{id}
• DELETE /api/resumes/{id}
• POST /api/resumes/{id}/share
• GET /api/resumes/{id}/export
• GET /api/admin/metrics