Intent based search using AI

A custom chatbot built with NestJS, MongoDB, PostgreSQL with pgvector extension for vector similarity search. This project implements a sophisticated chatbot system with authentication, monitoring, and vector-based search capabilities.

Architechture

Features

• Vector similarity search using pgvector
• Authentication and authorization
• MongoDB for document storage
• PostgreSQL for vector storage
• Monitoring with Prometheus and Grafana
• • Swagger API documentation
• Internationalization support
• CSV data processing
• Redis caching
• Security features (XSS protection, JWT)

Prerequisites

• Node.js (>= v16)
• MongoDB
• PostgreSQL (with pgvector extension)
• Ollama (for text embeddings)
• Redis
• Docker and Docker Compose (optional)

Environment Setup

1. Clone the repository
2. Copy .env.example to .env and update the following variables:

# Application
PORT=
NODE_ENV=

# PostgreSQL
POSTGRES_HOST=
POSTGRES_PORT=
POSTGRES_USER=
POSTGRES_PASSWORD=
POSTGRES_DATABASE=
DB_SCHEMA=

# MongoDB
MONGODB_URI=your_mongodb_connection_string

# Redis
REDIS_HOST=
REDIS_PORT=
REDIS_PASSWORD=

# JWT
JWT_SECRET=
JWT_EXPIRATION=

Quick Start

1. Install dependencies:

yarn install

2. Start the development server:

yarn start:dev

3. Access the API documentation at http://localhost:3000/api

Available Scripts

• yarn start - Start the application
• yarn start:dev - Start the application in development mode with hot-reload
• yarn start:debug - Start the application in debug mode
• yarn start:prod - Start the application in production mode
• yarn build - Build the application
• yarn test - Run tests
• yarn test:watch - Run tests in watch mode
• yarn test:coverage - Run tests with coverage report
• yarn lint - Run ESLint
• yarn format - Format code with Prettier
• yarn seed:up - Run database seeds
• yarn create:admin - Create a super admin user

Project Structure

src/
├── common/          # Shared modules and utilities
├── config/          # Configuration files
├── helper/          # Helper functions and utilities
├── modules/         # Feature modules
│   ├── auth/        # Authentication module
│   ├── chatbot/     # Chatbot core functionality
│   └── ...          # Other feature modules
├── main.ts          # Application entry point
└── app.module.ts    # Root module

Monitoring

The application includes Prometheus metrics and Grafana dashboards:

• Prometheus configuration: prometheus.yml
• Grafana dashboard: grafana-dashboard.json

Documentation

Additional documentation can be found in:

• LANGGRAPH_FLOW.md - LangGraph implementation details
• PROBLEM_STATEMENT.md - Project requirements
• PROJECT_PLAN.md - Project planning and architecture
• SETUP.md - Detailed setup instructions

Contributing

1. Fork the repository
2. Create your feature branch
3. Commit your changes
4. Push to the branch
5. Create a new Pull Request

License

This project is licensed under the MIT License.