🚀 SkillSetu — AI-Powered Personalized Learning Plan Generator

(Frontend + Backend + RAG + Ollama)

SkillSetu is a full-stack AI product that generates a personalized learning roadmap based on your goal, skills, and time availability.
It uses React (Vite + Tailwind) for UI, FastAPI for backend logic, PostgreSQL for plan storage, and Ollama (local LLM) for AI plan generation.

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⭐ Features

Area	Features
✅ Authentication	JWT login/register, token stored securely, route protection
✅ Plans Dashboard	View, delete, open AI plans
✅ AI Auto Plan	Generate multi-week learning plan using Ollama
✅ System Status	Shows if token + Ollama is working
✅ RAG (optional)	Chunking, embeddings, retrieval utilities
✅ API-first	Fully documented via FastAPI swagger (/docs)

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📸 Screenshots

🔐 Login Page

📊 Plans List

🤖 Auto Plan Generation Screen

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🏗 Architecture

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📁 Monorepo Structure

SkillSetu/ ├── frontend/ # React + Vite + Tailwind + TS UI ├── backend/ # FastAPI backend + DB + Ollama integration ├── rag/ # RAG utilities (data ingestion, embeddings, retrieval) ├── docs/ # (optional) screenshots, diagrams └── README.md # <--- this file

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🧠 Tech Stack

Layer	Tech
Frontend	React + Vite + TypeScript + Tailwind CSS + Axios + React Router
Backend	FastAPI + PostgreSQL + SQLAlchemy + JWT Auth
AI Model (Local)	Ollama (llama3, mistral, or others)
Optional RAG	Python + embeddings + chunking

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🚀 Setup Instructions (Local)

✅ 1. Clone Repo

git clone https://github.com/<YOUR_USERNAME>/SkillSetu.git cd SkillSetu

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✅ 2. Backend Setup (FastAPI)

Install dependencies

cd backend python -m venv venv

Activate env:

Windows:

venv\Scripts\activate

Mac/Linux:

source venv/bin/activate

pip install -r requirements.txt

Configure environment

cp .env.example .env

Modify .env:

POSTGRES_HOST=localhost POSTGRES_PORT=5432 POSTGRES_DB=skillsetu POSTGRES_USER=postgres POSTGRES_PASSWORD=postgres OLLAMA_URL=http://localhost:11434

Start backend

uvicorn app.main:app --reload --port 8000

➡️ API Docs: http://localhost:8000/docs

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✅ 3. Start Ollama (LLM Server)

ollama serve

Pull model:

ollama pull llama3

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✅ 4. Frontend Setup (Vite + React)

cd frontend npm install cp .env.example .env

Set backend URL in .env:

VITE_API_BASE=http://localhost:8000

Run app:

npm run dev

➡️ Frontend: http://localhost:5173

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✅ 5. RAG Setup (Optional)

cd rag python -m venv venv source venv/bin/activate pip install -r requirements.txt cp .env.example .env

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🔐 Authentication Flow

Token stored in: localStorage → skillsetu_token

Axios automatically attaches: Authorization: Bearer

401 → redirects to /login

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🧪 APIs

Method	Endpoint	Description
POST	/auth/auth/register	Register user
POST	/auth/auth/login	Login & return JWT
GET	/users/me	Verify token
GET	/plans/	List plans
POST	/plans/auto	Generate AI plan using Ollama
GET	/plans/{id}	Plan detail
DELETE	/plans/{id}	Delete plan

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📄 License

MIT License

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⭐ Author

Made with ❤️ by Deepak Kusumkar