https://github.com/teakulo/eventime-app

Eventime App is an event management platform using Angular, Spring Boot, Flask, and PostgreSQL. It offers AI-powered event recommendations, social features, and secure authentication. Users can manage events, chat with a chatbot, and view their calendar.
https://github.com/teakulo/eventime-app

ai angular authentication calendar chatbot event flask lemmatization nlp nltk postgresql spacy springboot

Last synced: 2 months ago
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Eventime App is an event management platform using Angular, Spring Boot, Flask, and PostgreSQL. It offers AI-powered event recommendations, social features, and secure authentication. Users can manage events, chat with a chatbot, and view their calendar.

• Host: GitHub
• URL: https://github.com/teakulo/eventime-app
• Owner: teakulo
• Created: 2024-06-09T17:07:00.000Z (7 months ago)
• Default Branch: main
• Last Pushed: 2024-06-15T13:45:46.000Z (6 months ago)
• Last Synced: 2024-10-14T04:02:55.425Z (2 months ago)
• Topics: ai, angular, authentication, calendar, chatbot, event, flask, lemmatization, nlp, nltk, postgresql, spacy, springboot
• Language: Java
• Homepage:
• Size: 3.41 MB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Eventime App

## Overview

This project is an AI-enhanced web application designed for organising and recommending events. The system leverages Natural Language Processing (NLP) techniques for text processing and provides functionalities for creating, editing, and viewing events from a database. The application features a calendar for event management and includes a robust backend for authentication and data handling.

## Features

- **Event Management**: Users can create, edit, and view events.

- **Calendar Integration**: A calendar view to manage events efficiently.

- **NLP Processing**: Utilises various NLP techniques such as NLTK WordNet for dictionary-based approaches, lemmatisation, and synonyms.

- **Authentication**: Secure login and signup functionalities.

- **AI-Powered Recommendations**: Events are recommended based on text processing using NLP techniques.

- **Testing**: Postman used for testing API endpoints.

- **Chatbot**: Chat with a chatbot to get event recommendations.

## Technologies Used

### Frontend

- **Angular**: Framework for building the user interface.

- **Angular Material**: UI components for Angular.

- **Bootstrap/NGX-Bootstrap**: For responsive design and additional UI components.

- **Angular OAuth2 OIDC**: For handling authentication.

- **Date-Fns**: Library for date manipulation.

- **JWT-Decode**: Library for decoding JSON Web Tokens.

### Backend

- **Spring Boot**: Framework for building the backend application.

- **Spring Security**: For authentication and authorisation.

- **PostgreSQL**: Database for storing user and event data.

- **HikariCP**: Connection pooling for PostgreSQL.

- **Lombok**: For reducing boilerplate code.

- **JJWT**: For JWT creation and parsing.

- **Commons Validator**: For data validation.

### NLP and AI

- **SpaCy**: Library for advanced NLP in Python.

- **NLTK WordNet**: For dictionary-based approaches and synonyms.

- **Lemmatisation**: Reducing words to their base or root form.

### Chatbot

- **Flask**: Python framework for the chatbot.

- **SpaCy**: For NLP in chatbot.

- **NLTK**: For additional NLP tasks.

## Application Structure

### Backend

- **Spring Boot Application**: Manages the business logic, data access, and authentication.

- **Repositories**: Interfaces for data access using Spring Data JPA.

- **Services**: Business logic for handling event and user operations.

- **Controllers**: RESTful endpoints for frontend communication.

- **Security**: Configured using Spring Security for login and signup processes.

### Frontend

- **Angular Application**: Manages the user interface and communicates with the backend via RESTful APIs.

- **Components**: Modular UI components for managing events and user interactions.

- **Services**: Angular services for handling API calls and business logic on the client side.

- **Routing**: Configured for navigating between different views within the application.

### Chatbot

- **Flask Application**: Manages the chatbot interactions.

- **Endpoints**: RESTful endpoints for chatbot communication.

- **NLP Processing**: Uses SpaCy and NLTK for processing user input.

## Getting Started

### Prerequisites

- **Node.js**: Required for running Angular.

- **Java**: Required for running Spring Boot.

- **Python 3.9**: Required for running NLP tasks with SpaCy and Flask.

- **PostgreSQL**: Database setup.

- **Flask**: Required for running the chatbot.

### Installation

1. **Clone the Repository**:

   ```sh

   git clone https://github.com/teakulo/ETfrontend.git

   ```

2. **Backend Setup**:

   - Navigate to the backend directory.

   - Configure the database settings in `application.yml`.

   - Run the Spring Boot application:

     ```sh

     ./mvnw spring-boot:run

     ```

3. **Frontend Setup**:

   - Navigate to the frontend directory.

   - Install dependencies:

     ```sh

     npm install

     ```

   - Run the Angular application:

     ```sh

     ng serve

     ```

4. **Chatbot Setup**:

   - Navigate to the chatbot directory.

   - Install Python dependencies:

     ```sh

     pip install -r requirements.txt

     ```

   - Run the Flask application:

     ```sh

     flask run

     ```

### Usage

- **Access the application** at `http://localhost:4200`.

- **Sign up or log in** to start managing your events.

- **Chat with the chatbot** to get event recommendations.

- **See who is attending** events and add friends.

- **Edit your profile** information.

- **View events you are attending** on your calendar.

- **Scroll through the homepage** to see various events.