NotebookLM

A NotebookLM-like application for creating summaries from uploaded documents using RAG (Retrieval-Augmented Generation).

Features

• Project Management: Create and manage document projects
• File Upload: Support for PDF, TXT, and DOCX files
• AI Summarization: Generate intelligent summaries using OpenAI
• Vector Search: Efficient document chunking and embedding with Cohere
• Authentication: Secure user authentication with Keycloak
• Modern UI: Responsive Angular frontend with Angular Material

Tech Stack

Backend (.NET 8)

• Architecture: Clean Architecture pattern
• Database: PostgreSQL with PgVector extension
• Authentication: Keycloak integration
• AI Services: OpenAI for text generation, Cohere for embeddings

Frontend (Angular + TypeScript)

• Framework: Angular 17 with standalone components
• UI Library: Angular Material
• State Management: RxJS
• Routing: Angular Router
• Authentication: Keycloak Angular

DevOps

• Containerization: Docker Compose
• Database: PostgreSQL with PgVector
• Authentication: Keycloak

Quick Start

Prerequisites

• Docker and Docker Compose
• .NET 8 SDK (for local development)
• Node.js 18+ (for local development)

Setup

1. Clone the repository

   git clone <repository-url>
   cd Notebook-LM

2. Environment Configuration

   cp .env.example .env
   # Edit .env with your OpenAI API key and other configuration

3. Start with Docker Compose

   docker-compose up -d

   This will start:

   • PostgreSQL with PgVector (port 5432)
   • Keycloak (port 8080)
   • Backend API (port 5000)
   • Frontend (port 3000)

4. Access the application

   • Frontend: http://localhost:3000
   • Backend API: http://localhost:5000
   • Keycloak Admin: http://localhost:8080 (admin/admin)

Local Development

Backend

cd backend
dotnet restore
dotnet run --project src/NotebookLM.API

Frontend

cd frontend
npm install
npm start

Project Structure

├── backend/                 # .NET Core backend
│   ├── src/
│   │   ├── NotebookLM.API/          # Web API layer
│   │   ├── NotebookLM.Application/  # Application layer
│   │   ├── NotebookLM.Domain/       # Domain layer
│   │   └── NotebookLM.Infrastructure/ # Infrastructure layer
│   └── Dockerfile
├── frontend/                # Angular frontend
│   ├── src/
│   │   ├── app/
│   │   │   ├── components/  # Angular components
│   │   │   ├── pages/      # Page components
│   │   │   ├── services/   # Angular services
│   │   │   ├── guards/     # Route guards
│   │   │   └── models/     # TypeScript interfaces
│   │   ├── assets/         # Static assets
│   │   └── environments/   # Environment configs
│   ├── angular.json        # Angular CLI config
│   └── Dockerfile
├── docker/                 # Docker configuration
│   └── init-scripts/       # Database initialization
├── docker-compose.yml      # Container orchestration
└── .env.example           # Environment variables template

Environment Variables

Create a .env file with the following variables:

# OpenAI API Configuration
OPENAI_API_KEY=your_openai_api_key_here

# Database Configuration
DB_HOST=localhost
DB_PORT=5432
DB_NAME=notebooklm
DB_USER=postgres
DB_PASSWORD=postgres

# Keycloak Configuration
KEYCLOAK_URL=http://localhost:8080
KEYCLOAK_REALM=notebooklm
KEYCLOAK_CLIENT_ID=notebooklm-client

# API Configuration
API_URL=http://localhost:5000
FRONTEND_URL=http://localhost:3000

Development Workflow

1. Database Migrations (when schema changes)

   cd backend
   dotnet ef migrations add MigrationName --project src/NotebookLM.Infrastructure --startup-project src/NotebookLM.API
   dotnet ef database update --project src/NotebookLM.Infrastructure --startup-project src/NotebookLM.API

2. Running Tests

   # Backend tests
   cd backend && dotnet test
   
   # Frontend tests
   cd frontend && npm test

3. Building for Production

   # Build all services
   docker-compose -f docker-compose.yml build
   
   # Or build individually
   cd backend && dotnet build --configuration Release
   cd frontend && npm run build

API Documentation

Once the backend is running, visit:

• Swagger UI: http://localhost:5000/swagger

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

License

This project is licensed under the MIT License - see the LICENSE file for details.