CrossPlatform-TechSupport-Chatbot

A multi-platform chatbot that provides intelligent customer and tech support using OpenAI, Dialogflow, and a Retrieval-Augmented Generation (RAG) system.

Table of Contents

• Features
• Demo
• How It Works
• Installation
• Tech Stack
• License

Features

• Multi-platform support (Messenger, Telegram, LINE, or custom web page)
• Document storing and chunking
• OpenAI integration for conversational AI and text embedding/semantic search
• Retrieval-Augmented Generation (RAG) for document-based responses
• Context-aware responses and smart routing

Demo

• Live Demo: https://petersun1937.github.io/Custom_Frontend_Chatbot

How It Works

• Users interact with the chatbot through various platforms (support FB Messenger, Telegram, LINE, or custom platform).
• Dialogflow detects intents for common questions and support requests.
• OpenAI generates conversational responses for unrecognized inputs.
• Document upload, which is then chunked and stored in the database along with text embeddings.
• The Retrieval-Augmented Generation (RAG) system fetches relevant documents for FAQs and troubleshooting.

Tech Stack

• Frontend: React (web interaction)
• Backend: Go (Gin framework)
• Database: PostgreSQL
• APIs: OpenAI API, Dialogflow, META APIs, Telegram API, LINE API
• Cloud: Heroku (backend deployment), Github Page (frontend deployment)

Installation

• Clone the Repository:

  git clone https://github.com/petersun1937/CrossPlatform-TechSupport-Chatbot.git
  cd CrossPlatform-TechSupport-Chatbot

• Backend Setup:

  • Ensure Go and Python are installed:

    • Make sure that Go (version 1.16 or higher) and Python (version 3.6 or higher) are installed on your system.
    • You can verify the installation by running the following commands:

      go version
      python --version

  • Install Python packages:

    • The backend requires several Python packages for processing PDFs. To install them, run:

      pip install pdfplumber pytesseract pdf2image PyPDF2

    • These packages handle PDF text extraction and Optical Character Recognition (OCR) for images within PDFs.

• Set up environment variables:
  • Create a .env file in the configs/ directory to store environment variables such as API keys and database configurations (refer to sample.env).

License

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