Getting started with Rasa on windows

In my journey as Data Scientist aspirant, I came across building up of conversational Chatbot with help of rasa nlu. Making a chatbot or virtual assistance is used to transform the user experience. Nowadays, chatbots are gaining attraction. Here is my small effort to build beginners.

RASA

Rasa is a machine learning conversational ai which is used to build a chatbot. It is one of the best open-source machine learning toolkits which is used to developer complex chatbot with minimal training data.

It is based on two frameworks-

1.Rasa nlu– a library for natural language understanding (NLU) which does the classification of intent and extracts the entity from the user input.

2.Rasa Core– A chatbot framework that predicts the next best response or action based on conversational history.

• When Rasa receives a message from the user, it predicts or extracts the intent and entities present in the. This part is handled by Rasa NLU.
• Rasa then tries to predict the next action. This is done by Rasa Core.

Requirements

There are some pre requirements for rasa to get working on window:

Microsoft VC++ Compiler

Python (version 3.5, 3.6 )

Anaconda Framework

spacy library to be installed separately after creating virtual environment.

After installing python and anaconda. Make sure you create separate virtual environment for rasa project. Python virtual environments help resolve dependency issues by allowing you to use different versions of a package for different projects. Use following command:

conda create -n rasa python=3.6
#rasa is name of environment I have used
conda activate rasa

#installing rasa package
pip install rasa
#installing spacy
pip install spacy

Create a directory where you want to store your project. Navigate to that directory. Use following command:

rasa init

After above command following files will get created in your project directory as initial project structure of RASA.

Now you can create your model and train it. I will be highly grateful if I could get appreciation in form of claps.

Thanks for reading:)