DevPath AI

A Next-Generation Software Career Navigator & Salary Predictor

📖 Project Overview

DevPath AI is a full-stack, data-driven web application designed to guide software developers in their career journeys. Leveraging the Stack Overflow Developer Survey 2025 data (analyzing over 49,000+ responses), this platform offers two main features:

1. Salary Prediction: An AI model trained using XGBoost to predict your potential software engineering salary based on your experience, location, education, and tech stack.
2. Career Quiz: A comprehensive 15-question assessment that matches your personality and skills with 9 major software fields (Frontend, Backend, AI/Data, Cloud, etc.) and generates a personalized learning roadmap.

🛠️ Tech Stack

This project leverages modern frameworks and machine learning libraries:

Frontend

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Backend & Machine Learning

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📂 File Structure

ML Internship Project/
├── client/                     # Frontend React application
│   ├── src/
│   │   ├── api/                # API client configuration
│   │   ├── components/         # Reusable UI components
│   │   ├── pages/              # Main view routes (Home, Predict, Quiz, Results)
│   │   ├── App.jsx             # Main routing and layout wrapper
│   │   └── index.css           # Global Tailwind & Theme CSS
│   ├── package.json            # Node dependencies
│   └── tailwind.config.js      # Tailwind UI configurations
├── server/                     # Backend Python application
│   ├── main.py                 # FastAPI endpoints & static file serving
│   ├── quiz.py                 # Quiz logic and scoring engine
│   └── schemas.py              # Pydantic data models
├── models/                     # Saved ML models (Joblib)
│   ├── maas_tahmin_modeli.joblib
│   └── model_bilgisi.json
├── readme banner/              # Banner assets for GitHub README
├── stitch_devcareer_navigator/ # UI Mockups and wireframes
├── train_model.py              # ML model training pipeline
└── devpath.ipynb               # Data exploration & Jupyter Notebook

🚀 Installation & Setup

Prerequisites

Make sure you have installed on your local machine:

• Python 3.10+
• Node.js 20+

1. Clone the repository

git clone https://github.com/sukrutan1/Devpath-AI-.git
cd "Devpath-AI-"

2. Install Python Dependencies

pip install -r requirements.txt

3. Train the Machine Learning Model

This script processes the dataset and exports the XGBoost model into the models/ directory.

python train_model.py

4. Setup the Frontend

Install the Node.js packages and build the frontend bundle.

cd client
npm install
npm run build
cd ..

5. Run the Application (Production Mode)

This will serve both the backend API and the compiled frontend static files simultaneously on port 8000.

python -m uvicorn server.main:app --reload --port 8000

Open http://localhost:8000 in your browser.

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👨‍💻 Development Mode

If you wish to make changes to the frontend and see them update in real-time, run the services separately:

Terminal 1 (Backend):

python -m uvicorn server.main:app --reload --port 8000

Terminal 2 (Frontend):

cd client
npm run dev

The Vite development server will start at http://localhost:5173 and automatically proxy API requests to your FastAPI backend.

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Developed as part of the Software Persona ML Internship Project.