/NLP-chat-bot

Input: emails , Output: customer support, appointment scheduling, or information retrieval.

NLP Chatbot Project

Introduction

Welcome to the NLP Chatbot project! This project aims to leverage natural language processing (NLP) techniques and a BERT transformer model for text classification to improve the efficiency of handling emails for small companies. The primary objectives of this project are:

  1. Classify incoming emails into one of the following categories:

    • General Query
    • Meeting
    • Spam

  2. Automatically add meeting requests to the receiver's calendar once they are notified.

  3. Develop a chatbot to detect and retrieve specific information from a database, allowing for data sorting and retrieval.

  4. Create an API using Django for communication and integration.

  5. Store email data in an AWS bucket for efficient management and scalability.

  6. Implement the BERT model to classify emails either after a certain threshold of emails is reached or on a regular schedule (e.g., every Monday morning).

Project Timeline

The project officially starts on 4th February 2024 and will be an ongoing effort with continuous improvements. Here is a rough timeline of the project's key milestones:

  • Phase 1: Data Collection (February 2024)

    • Gather and collect email data for training the BERT model.
    • Set up an AWS bucket to store email data securely.

  • Phase 2: Model Development (March 2024)

    • Develop and fine-tune the BERT transformer model for text classification.
    • Implement the classification system to categorize emails as General Query, Meeting, or Spam.

  • Phase 3: Chatbot Integration (April 2024)

    • Build and integrate a chatbot for interacting with the email system.
    • Implement natural language processing capabilities for database queries.

  • Phase 4: Calendar Integration (May 2024)

    • Develop a mechanism to add meeting requests to the recipient's calendar.
    • Implement notifications for meeting invitations.

  • Phase 5: API Development (June 2024)

    • Create a RESTful API using Django for seamless communication with the system.
    • Ensure secure access to email and database information through the API.

  • Phase 6: Deployment and Scaling (July 2024)

    • Deploy the complete system to a production environment.
    • Set up automated processes for periodic model retraining and maintenance.

Project Goals

The main objectives of this project are to:

  • Streamline email handling and categorization for small companies.
  • Improve efficiency by automatically scheduling meetings and handling database queries.
  • Enhance communication through a user-friendly chatbot.
  • Store and manage email data securely in an AWS bucket.
  • Provide a robust API for external integrations and interactions.