Retrievia 📚🧠

Retrievia is an AI-powered Corrective Retrieval-Augmented Generation (CRAG) platform that helps students learn from their textbooks, notes, research papers, and previous-year question papers.

Upload your study material, then ask questions, generate summaries, and discover important topics, with answers grounded in your own documents.

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✨ Features

• 📄 Document Intelligence: upload PDF, TXT, and Markdown files; they are parsed and indexed automatically
• 🔍 Question Answering: ask naturally, e.g. "Explain deadlock prevention." or "Where is Dijkstra's Algorithm discussed in my notes?"
• 🧠 Summaries: chapter-wise summaries, revision notes, and exam guides
• 📊 Past Paper Analysis: frequently asked concepts, important chapters, topic trends, and estimated weightage
• 🎯 Topic Discovery: finds relevant chapters, sections, and related concepts
• 🌐 Hybrid Retrieval: combines your documents with trusted educational resources
• 🔄 Corrective RAG: evaluates retrieval quality and corrects weak results to reduce hallucinations

Query → Retrieval → Quality Check → (Corrective Retrieval if needed) → Generation → Grounded Answer

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🏗️ Tech Stack

Layer	Tools
Frontend	Next.js 15, React, TypeScript, ShadCN UI, Tailwind CSS
Backend	Python, FastAPI, LangChain, LangGraph
Retrieval	RAG, CRAG, vector embeddings, semantic search
Infra	REST APIs, Docker, vector database

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📁 Project Structure

Retrievia/
├── backend/        # FastAPI app (entry point: app/main.py)
│   ├── app/
│   └── requirements.txt
├── client/         # Next.js frontend
└── README.md

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🚀 Getting Started

Prerequisites

• Python 3.x
• Node.js and npm
• Git

1. Clone

git clone <repository-url>
cd Retrievia

2. Run the backend

cd backend
python -m venv venv

Activate the virtual environment:

# Windows PowerShell
venv\Scripts\Activate.ps1

:: Windows CMD
venv\Scripts\activate

# macOS / Linux
source venv/bin/activate

Install dependencies and start the server:

pip install -r requirements.txt
python -m uvicorn app.main:app --reload

• API: http://127.0.0.1:8000
• Docs: http://127.0.0.1:8000/docs

Keep this terminal running.

3. Run the frontend

In a new terminal:

cd client
npm install
npm run dev

Open http://localhost:3000.

4. Use the app

1. Choose Notes, Textbook, or Past Paper and upload a PDF, TXT, or MD file.
2. Ask: enter a question about the material.
3. Summaries: pick Revision notes, Chapter-wise, or Exam guide.
4. Past papers: analyze repeated questions and important topics.

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⚠️ Troubleshooting

Problem	Fix
Could not import module "main"	Run from the backend folder with python -m uvicorn app.main:app --reload (not uvicorn main:app).
Python dependency errors	Activate the virtual environment, then run pip install -r requirements.txt.
Frontend dependency errors	In client, run npm install again, then npm run dev.
Port 3000 / 8000 in use	Stop the process using it, or run on another port.

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🔐 Configuration

Keep API keys and secrets in environment variables (e.g. a .env file) and add .env to .gitignore. Never commit credentials.

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🎓 Use Cases

Exam preparation • Revision planning • Topic discovery • Previous-year question analysis • Research assistance • Personalized learning

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🎯 Vision

Retrievia aims to become an AI-native learning companion that turns static educational resources into an interactive, searchable, and personalized knowledge system for students worldwide.

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📄 License

Intended for academic and educational purposes. Add an open-source license if distributing publicly.