Assistify - Your AI Powered Helper!

Introduction

This assessment explores the development of a natural language processing (NLP)-based dialog chatbot named Assistify. Designed as a personal assistant replacement, Assistify offers various practical features, including:

• Wikipedia Integration: Learn about topics with ease.
• Weather Reports: Stay informed to ensure the weather doesn’t disrupt your day.
• Meeting Scheduler: Keep track of your meetings effortlessly.

These features make Assistify a valuable tool for busy individuals to organize their day and handle unexpected events. Unlike casual conversational chatbots, Assistify focuses on practicality and work-oriented tasks. By leveraging NLP and other techniques, it ensures a smooth user experience. Furthermore, Assistify is free and accessible anytime, anywhere unlike a traditional personal assistant.

NLP Techniques

Assistify utilizes several NLP techniques. A critical decision during development was choosing between a deep learning approach and a rule-based system:

• Deep Learning: Ideal for handling unexpected or conversational inputs. With proper training, it can mimic human-like interactions. However, it requires significant data, time, and tuning.
• Rule-Based System: Selected for this project due to its simplicity and suitability for predefined use cases. It provides consistent and precise responses within its scope.

Input Cleaning

To ensure accurate responses, user inputs are cleaned by:

• Removing punctuation.
• Converting text to lowercase.

This preprocessing improves message consistency and response accuracy.
Extracting Locations for Weather Updates

Determining the user's location for weather updates posed a unique challenge. Listing all possible place names was inefficient. Instead, a smarter approach was implemented:

• Use a library to categorize words as nouns, verbs, locations, etc.
  Identify location names by cycling through these categorized words.
  Supplement this with a custom list of New Zealand’s most populous cities (as the library might lack local names).

While not 100% accurate, this method covers most scenarios effectively.
Storage

Storage

A key aspect of Assistify is its ability to store login credentials and meeting information. To ensure data separation for different users, a login system was introduced. User-specific information, such as names, is stored in a MySQL database, enabling:

• Personalization of the chatbot experience.
• Easy data syncing across devices due to its online nature.

Although a local database could have sufficed, a MySQL database was chosen for its versatility and ability to support multi-user functionality. This ensures seamless data storage and retrieval.

Front-End

Creating an intuitive and user-friendly interface was a priority. A graphical user interface (GUI) was developed using Tkinter, chosen for its simplicity and ease of integration.
Key Features:

• Chatbox: Facilitates sending and receiving messages seamlessly.
• Buttons: Guide users intuitively through available actions.

Unlike console-based chatbots, the Tkinter GUI provides a modern and accessible interface that aligns with user expectations for contemporary applications.