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Implementation of a chatbot for a stock management application

Python 1.33% HTML 4.45% CSS 16.31% JavaScript 77.90% Shell 0.01%
flask rasa rasa-chatbot rasa-core rasa-nlu rest-api

chatbot-sart's Introduction

Chatbot SART

As part of the end-of-year project (PFA) as engineering students at ENSIAS, we chose to work on the implementation of a chatbot for a stock management application for a clothing store . Our project was to develop a chatbot, named "Chatbot SART - Style Assistant and Retail Technology", which was integrated into the application. This chatbot uses artificial intelligence, speech recognition, speech synthesis and natural language processing techniques to intuitively interact with users. The main objective of this chatbot is to assist users with their stock management needs, by providing information on available products, stock levels, orders, etc.

Built with

  • RASA
  • Flask
  • Bootstrap

To run the bot

  • Create a new virtual environment by choosing a Python interpreter and making a .\venv directory to hold it:

    C:\> python3 -m venv ./venv

  • Activate the virtual environment:

    C:\> .\venv\Scripts\activate

  • First make sure your pip version is up to date:

    pip3 install -U pip

  • To install Requirements:

    pip3 install -r requirements.txt

  • Finally run the bot using bash terminal:

    $ ./run_bot.sh

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