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BosomBuddy

BosomBuddy is a Django-based web application that integrates Google Dialogflow (on Google Cloud Platform) to simulate conversational AI workflows. The system was designed as a rapid prototype exploring AI-driven interaction systems combined with automated messaging and scheduled notifications.


System Overview

BosomBuddy demonstrates an end-to-end workflow integrating multiple system components:

  • Conversational AI using Google Dialogflow (GCP)
  • Django-based backend web application
  • Automated email messaging system
  • Scheduled notification engine using APScheduler

The project focuses on system integration, workflow automation, and building a functional AI-enabled web application.


Key Features

1. Conversational Chatbot (Dialogflow + GCP)

  • Integrated with Google Dialogflow for intent recognition and conversational flow management
  • Web interface uses jQuery to communicate with backend APIs and render real-time chatbot responses
  • Demonstrates structured conversation handling using NLP-based intent mapping

2. Automated Email Messaging System

  • Uses Python APScheduler for time-based scheduling of tasks
  • Sends automated email notifications to users at configured intervals
  • Demonstrates background processing and scheduled workflow execution

Technical Stack

  • Backend: Django (Python)
  • AI / NLP: Google Dialogflow (Google Cloud Platform)
  • Scheduling: APScheduler
  • Frontend: HTML, CSS, jQuery
  • Messaging: SMTP-based email system

Architecture & Design Notes

  • Modular separation of chatbot, scheduling, and messaging components
  • Event-driven scheduling for automated notifications
  • External API integration with Dialogflow for NLP processing
  • Backend-driven workflow orchestration using Django services

Project Context

BosomBuddy was developed as part of a Microsoft-organized overnight hackathon (~8 hours of development time). The objective was to rapidly prototype an end-to-end system integrating conversational AI, backend workflows, and automated messaging.

The focus was on fast system integration, working prototype design, and multi-service connectivity rather than production-scale engineering.


Purpose

This project was built to explore:

  • AI-powered conversational interfaces
  • Cloud-based NLP integration using Dialogflow
  • Automated scheduling and messaging workflows
  • End-to-end system integration using Django

About

Django web application made to cure the severe problem of depression among the people, it provide talk therapy by the means of chatbot which is train on Dialogflow i.e google cloud . It also has a message sending feature via mail . A motivational message will be sent to user at a prticular time to cheerup the users mood and brightup his day.

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