FastAPI backend powering JobSuite AI — resume analysis, cover letter generation, and job description matching using Groq LLM.
Live API: https://jobsuite-backend.onrender.com
Frontend Repo: jobsuite-ai
API Docs: https://jobsuite-backend.onrender.com/docs
Three AI-powered endpoints that help job seekers optimize their applications:
- Resume Analyzer — scores a resume and returns strengths, weaknesses, and improvements
- Cover Letter Generator — generates a tailored cover letter from a resume and job description
- JD Matcher — calculates match score, detects skill gaps, and returns AI tips
| Method | Endpoint | Description |
|---|---|---|
GET |
/ |
Health check |
POST |
/analyze-resume |
Analyze and score a resume |
POST |
/generate-cover-letter |
Generate a tailored cover letter |
POST |
/match-job |
Match resume to job description |
| Layer | Technology |
|---|---|
| Framework | FastAPI |
| Language | Python 3.11 |
| LLM | Groq — Llama 3.3 70B |
| Similarity | TF-IDF + cosine similarity |
| Resume Parsing | pdfplumber + python-docx |
| Deployment | Render |
# 1. Clone the repo
git clone https://github.com/Yusufcommit/jobsuite-backend.git
cd jobsuite-backend
# 2. Create virtual environment
python -m venv venv
source venv/bin/activate # Windows: venv\Scripts\activate
# 3. Install dependencies
pip install -r requirements.txt
# 4. Add your Groq API key
echo "GROQ_API_KEY=your_key_here" > .env
# 5. Start the server
uvicorn main:app --reloadAPI runs at http://localhost:8000
Swagger docs at http://localhost:8000/docs
- Resume analysis with LLM scoring
- Cover letter generation with tone options
- JD matching with skill gap detection
- AI tips per job application
- Production deployment on Render
- PostgreSQL session storage
- JWT authentication
- Docker + CI/CD pipeline
- API versioning
- Frontend: jobsuite-ai
- HireLens AI: hirelens-ai
Yusuf Abdirashid — AI Full Stack Developer
Building polished AI-powered tools for hiring and job applications.
