PathPilot

PathPilot is an AI-powered career roadmap generator. Enter your education background, existing skills, and career goals, and PathPilot produces a structured, stage-wise learning roadmap — complete with a skill gap analysis, recommended certifications, estimated timelines, and alternative career paths.

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Project Structure

PathPilot/
├── backend/    # FastAPI + OpenAI backend
└── frontend/   # Next.js 14 frontend

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Tech Stack

Layer	Technologies
Frontend	Next.js 14 (App Router), TypeScript, Tailwind CSS, Axios
Backend	Python 3.11+, FastAPI, Uvicorn, OpenAI SDK, Pydantic v2
AI	OpenAI GPT-4o-mini (configurable)

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Features

• Profile Form — Select your education level, field of study, career goal, learning pace, weekly availability, and target location.
• AI Roadmap Generation — OpenAI produces a structured JSON roadmap with:
  • Skill gap analysis (strengths & missing skills)
  • Foundation → Intermediate → Advanced learning stages
  • Estimated timeline in months
  • Recommended certifications
  • Alternative adjacent career paths
• Results Page — Clean display of the generated roadmap alongside a profile summary.

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Getting Started

Prerequisites

• Node.js 18+
• Python 3.11+
• An OpenAI API key

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Backend

cd backend

# Create and activate a virtual environment
python -m venv venv
source venv/bin/activate        # macOS / Linux
# venv\Scripts\activate         # Windows

# Install dependencies
pip install -r requirements.txt

# Configure environment variables
cp .env.example .env
# Edit .env — OPENAI_API_KEY is required; see the Environment Variables Reference below for all options

# Start the development server
uvicorn app.main:app --reload --port 8000

API is available at http://localhost:8000.

API Endpoints

Method	Path	Description
GET	/health	Health check
POST	/generate	Generate career roadmap

POST /generate — Request Body

{
  "education": "Bachelor's Degree",
  "field_of_study": "Computer Science & Technology",
  "skills": "Python, SQL",
  "career_goal": "Transition into a new field entirely",
  "learning_pace": "moderate",
  "weekly_hours": 10,
  "location": "India"
}

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Frontend

cd frontend

# Install dependencies
npm install

# Start the development server (connects to http://localhost:8000 by default)
npm run dev

Open http://localhost:3000 in your browser.

Environment Variables

Variable	Default	Description
NEXT_PUBLIC_API_URL	http://localhost:8000	Backend API base URL

Pages

Route	Description
/	Landing page
/generate	Career profile form
/results	AI-generated roadmap

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Deployment

Backend (Render / Railway / Fly.io)

1. Set OPENAI_API_KEY, OPENAI_MODEL, and FRONTEND_ORIGIN as environment variables on your platform.
2. Set the root directory to backend/.
3. Use the start command: uvicorn app.main:app --host 0.0.0.0 --port $PORT (Render and Railway assign a dynamic $PORT; use --port 8000 for platforms with a fixed port).

Frontend (Vercel)

1. Import the frontend/ directory as a Vercel project.
2. Set NEXT_PUBLIC_API_URL to your deployed backend URL.
3. Set the root directory to frontend/.
4. Deploy.

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Environment Variables Reference

Backend (backend/.env)

Variable	Required	Description
OPENAI_API_KEY	✅ Yes	Your OpenAI API key
OPENAI_MODEL	No (default: gpt-4o-mini)	Model to use
FRONTEND_ORIGIN	No (default: http://localhost:3000)	Allowed CORS origin (e.g. https://your-app.vercel.app)

Frontend (frontend/.env.local)

Variable	Description
NEXT_PUBLIC_API_URL	Backend API base URL

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License

This project is open source. See LICENSE for details.