ResumeTuner is a FastAPI-based backend service that uses OpenAI's GPT-4o-mini model to generate and optimize resumes tailored to specific job descriptions. It helps align resumes with modern hiring systems, including ATS (Applicant Tracking Systems), recruiter filters, and AI resume screeners.
✨ Resume generation from job posting using AI
🧠 Resume optimization for ATS and AI hiring pipelines
📄 Optional LaTeX formatting with downloadable .tex output
🔁 Plain Text vs LaTeX toggle in the frontend
🖥️ User-friendly web interface built with React and Tailwind CSS
git clone https://github.com/0xCompileError/resume-tuner.git
cd resume-tuner
cd backend
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
pip install -r requirements.txt
Create a .env file in the backend root:
OPENAI_API_KEY=sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
Use the included Makefile for easy startup:
make run
The server will be available at http://127.0.0.1:8000.
Swagger docs: http://127.0.0.1:8000/docs
curl -X POST "http://127.0.0.1:8000/analyze/?latex=true" \
-F "resume=@resume.txt" \
-F "job=@job.txt" \
-F "latex_format=@format_template.txt"
cd ../frontend
npm install
npm run dev
The frontend will be available at http://localhost:5173.
You can upload these via the UI or using the API:
-
resume.txt: Your current resume (factual work experience)
-
job.txt: The job description for the role you’re targeting
-
format_template.txt (optional): A LaTeX template to style the generated output
Feel free to open an issue or submit a pull request with improvements. Feature ideas, bug reports, and feedback are always welcome!
MIT License © 2025 – 0xCompileError