Skip to content

TextFlow: A Streamlit app providing text correction and autocomplete functionalities using n-grams and LSTM models. It corrects text and predicts the next words with customizable settings.

License

Notifications You must be signed in to change notification settings

achrafib1/Text-Flow

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

66 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Text-Flow

Introduction

TextFlow is a Streamlit app providing text correction and autocomplete functionalities using n-grams language model or an LSTM model. Users can correct their text and predict the next words with configurable options. TextFlow offers powerful text correction and autocompletion features to enhance your writing experience. Whether you prefer n-grams or LSTM models, TextFlow has you covered with customizable options to suit your needs.

TextFlow App Interface

Features

  • Text correction
  • Autocomplete next words
  • Choose between n-grams and LSTM models
  • Customize the number of words to be predicted
  • Various configurable settings for a personalized experience

Installation

Follow these steps to get the TextFlow App up and running:

Method 1: Using Docker

  1. Clone the repository:

    git clone https://github.com/achrafib1/Text-Flow.git
    cd textflow
  2. Build and run the Docker container:

    docker build -t textflow .
    docker run -p 8501:8501 textflow

Method 2: Regular Setup

  1. Clone the repository:

    git clone https://github.com/achrafib1/Text-Flow.git
    cd textflow
  2. Set up a virtual environment (Optional but Recommended):

    python -m venv venv
  3. Activate the Virtual Environment:

    • For Windows:
      .\venv\Scripts\activate
    • For macOS/Linux:
      source venv/bin/activate
  4. Install the necessary files:

    python config.py
  5. Install the dependencies:

    pip install -r requirements.txt
  6. Run the Streamlit app:

    streamlit run src/app.py

Usage

Access the App

Method 1: Using Docker

After running the Docker container, open your browser and navigate to http://localhost:8501.

Method 2: Regular Setup

After running the Streamlit app with:

streamlit run src/app.py

Open your browser and navigate to http://localhost:8501.

License

Distributed under the MIT License. See LICENSE for more information.

About

TextFlow: A Streamlit app providing text correction and autocomplete functionalities using n-grams and LSTM models. It corrects text and predicts the next words with customizable settings.

Topics

Resources

License

Stars

Watchers

Forks

Packages

No packages published