Project Overview

Introduction

This project is a web application designed to provide AI-driven chatbot solutions for businesses. It leverages modern technologies to enhance user interaction and streamline communication processes. The application is built using React, TypeScript, Tailwind, Radix, React-Query, React-Router and Vite for the frontend, while the backend is powered by Python with FastAPI, Transformers, Huggingface, TinyLlama, SQLAlchemy, Neon for the PostgreSQL DB.

Project Structure

Frontend

The frontend is structured to provide a responsive and interactive user experience. Here’s a breakdown of the key directories and files:

• src/: Contains the main source code for the application.

  • components/: Reusable UI components such as ChatWindow, EmailValidationDialog, and ChatItem.
  • hooks/: Custom hooks like useChat for managing chat interactions with the backend.
  • pages/: Contains the main pages of the application, including Home and AdminDashboard.
  • types/: TypeScript interfaces and types for better type safety across the application.
  • lib/: Utility functions like sentiment analysis.

• public/: Static assets like images and icons.

• package.json: This file lists dependencies and scripts for building, running, and testing the application.

• README.md: Documentation for setting up and running the project.

Backend

The backend is designed to handle API requests and manage data interactions. Key components include:

• app/: Main application directory.

  • api/: Contains API routes for handling chatbot interactions.
  • services/: Business logic and services, including ChatService for chat data and behavior.
  • data/: JSON files for logging conversations and storing company information.
  • db/: Database models and connection logic.

• main.py: Entry point for the FastAPI application.

• requirements.txt: Lists Python dependencies required for the backend.

Technologies Used

• Frontend:

  • React: A JavaScript library for building user interfaces.
  • TypeScript: A superset of JavaScript that adds static types.
  • Vite: A build tool that provides a fast development environment.
  • Tailwind CSS: A utility-first CSS framework for styling.
  • React Query: For managing server state and caching.

• Backend:

  • FastAPI: A modern web framework for building APIs with Python.
  • SQLAlchemy: For database interactions and ORM.
  • Pydantic: For data validation and settings management.

• Development Tools:

  • ESLint: For linting and maintaining code quality.
  • Prettier: For code formatting.
  • Docker: For containerization and deployment.

Features

• Chatbot Interaction: Users can interact with a chatbot that responds based on user queries.
• User Validation: Users must validate their email before starting a chat.
• Admin Dashboard: Admins can view chat activity and user interactions.
• Sentiment Analysis: The application analyzes user messages to determine sentiment.

Getting Started

To get started with the project, follow these steps:

1. Clone the repository:

   git clone <repository-url>

2. Navigate to the directory:

   cd repo folder

3. Build and run the container:

   docker-compose up --build                                           

4. For the backend, navigate to the backend directory, install dependencies, and run the server.

Conclusion

This project aims to provide a robust solution for businesses looking to enhance their customer interaction through an RAG GenAI-driven chatbot