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Intelligent Text Assistant for Prediction and Completion

In this project, we’ll build an intelligent text assistant Flask application for predictive typing and text correction using Hugging Face models and Python libraries.

Intelligent Text Assistant for Prediction and Completion

You will learn to:

Create a Flask application.

Create a dynamic application with AJAX.

Use Hugging Face models in Flask applications.

Perform language processing with the help of Python libraries.


Web Development

Artificial Intelligence

Natural Language Processing


Hands-on experience with Python

Basic knowledge of Flask




Hugging Face

Project Description

In this project, we’ll develop an intelligent text assistant—a Flask-based text editor application. This application utilizes the Python library (pyspellchecker) for text checking and Hugging Face models based on GPT-2 to implement the advanced prediction functionality.

In this project, we‘ll aim to create an intelligent text assistant that can assist users in predicting and completing text. We will use Python libraries and Hugging Face models for quick, powerful, and flexible implementation, providing users with a reliable and efficient text assistant experience.

Project Tasks


Getting Started

Task 0: Get Started

Task 1: Import the Libraries

Task 2: Create a Form


Next Word Suggestion

Task 3: Implement the Next-Word Suggestion Feature

Task 4: Handle and Route the Request Object


Sentence Completion

Task 5: Implement the Sentence Completion Functionality

Task 6: Handle and Route the Request Object


Fix by Selection

Task 7: Implement the Spell-Fix Functionality

Task 8: Handle and Route the Request Object


Fix All Misspellings

Task 9: Implement the Fix-All Functionality

Task 10: Handle and Route the Request Object