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This project creates an AI chat bot for an ed-tech website, using NLP to understand user queries and integrating a FAQ database for responses. It includes features like fallback to a doubt assistant, user feedback, data sharing with sales team, and performance monitoring.

TusharKesarwani/AI-Chatbot

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AI Chat Bot

Overview

This project implements an AI chat bot for an ed-tech website to assist users with queries related to courses. The chat bot utilizes natural language processing (NLP) techniques to understand user queries and provides relevant responses. It also integrates a FAQ database to retrieve answers to frequently asked questions. The project includes features such as fallback to a doubt assistant, user satisfaction feedback, data sharing with the sales team, and performance monitoring.

Key Features

  • Chat Bot: A user-friendly chat bot interface where users can input their queries regarding courses.
  • FAQ Integration: Integration of a database of frequently asked questions (FAQs) related to courses. The chat bot retrieves relevant answers from the FAQ database to respond to user queries.
  • Natural Language Processing (NLP): Utilizes NLP techniques to understand user queries and extract key information required to provide relevant responses.
  • Fallback to Doubt Assistant: Implements a mechanism where if a user is not satisfied with the response, the chat bot will fallback to a doubt assistant for further assistance.
  • User Satisfaction Feedback: After resolving a user query, prompts the user for feedback on their satisfaction level.
  • Data Sharing with Sales Team: Shares user data and chat transcripts with the sales executive team for follow-up and analysis purposes.
  • Performance Monitoring: Implements monitors to track the efficiency and effectiveness of the chat bot.

FAQ Questions

  1. Suitable for beginner or advanced users ?
  2. Can I learn at my own pace?
  3. What type of assignment do you give ?
  4. What are the pre-requirement for this course ?
  5. How long does this course take to complete ?
  6. How much does the course cost ?
  7. How is the doubt support ?
  8. Does this course offer placement opportunities also ?
  9. How is the course different from other platform courses ?
  10. Is there any money back guarantee if I did not like the course ?
  11. Is this course relevant in todays market ?
  12. Is good DSA a prerequisite for this course ?
  13. How much I can make after completing this course ?
  14. Can I pay in EMI for this course ?
  15. Does this course offer financial aid for under-previleged people ?
  16. Does this course offer any certificate ?
  17. Where can I get testimonials for this course ?
  18. Who is the mentor for this course ?
  19. Is it an online or offline course ?

Installation

  1. Clone the repository: git clone https://github.com/TusharKesarwani/AI-Chatbot.git
  2. Navigate to the project directory: cd AI-Chatbot

Backend Setup

  1. Navigate to the backend directory: cd chatbot-backend
  2. Install dependencies: npm install
  3. Start the backend server: npm start
  4. The backend server will run at http://localhost:3000

Frontend Setup

  1. Navigate to the frontend directory: cd ai-chatbot-frontend
  2. Install dependencies: npm install
  3. Start the frontend server: npm start
  4. The frontend application will run at http://localhost:3001

Usage

  1. Access the frontend application at http://localhost:3001 in your web browser.
  2. Start interacting with the chat bot by entering your queries.
  3. The chat bot will respond with relevant answers based on the FAQs and NLP processing.
  4. Provide feedback on your satisfaction level after each query resolution.

Technologies Used

  • Backend: Node.js, Express.js, MongoDB
  • Frontend: React.js, Axios
  • Database: MongoDB

Credits

This project was created by Tushar Kesarwani as a part of AI Chatbot Project.

About

This project creates an AI chat bot for an ed-tech website, using NLP to understand user queries and integrating a FAQ database for responses. It includes features like fallback to a doubt assistant, user feedback, data sharing with sales team, and performance monitoring.

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