This is how nlu.md file look like # intent:greet You can see some intents are already there in the nlu.md file. In Rasa, you can create the intent and add the training phrases in the data/nlu.md file. Training phrases are the user input, that for greeting users may say: ‘hello’, ‘hi’, ‘hie’, ‘hi there’ etc. For example, a user input ‘Hello’ or ‘Hi’ may call the intent ‘greet’. Intent can be understood as labels that are attached based on the overall goal of user’s message. Note : The files with ‘*’ marked are the important files. Endpoints.yml ⇒ details for connecting to channels like fb messenger.domain.yml ‘*’ ⇒ your assistant’s domain.data/nlu.md ‘*’ ⇒ your NLU training data.Credentials.yml ⇒ details for connecting to other services.config.yml ‘*’ ⇒ configuration of your NLU and Core models.Actions.py ⇒ code for your custom actions._init_.py ⇒ an empty file that helps python find your actions.To create a rasa project run the following command: rasa init -no-prompt You can install Rasa using the below command : pip install rasa Create RASA Projectīefore creating Rasa Project make sure you are in the directory “rasaDemo”. Once you have created the virtualenv, activate it using the following command : source env_name/bin/activate Install RASA Now create the virtual environment by the given command : virtualenv env_name -python=python3 If you don’t have virtual environment, you can install it using following command : sudo apt install virtualenv Create and activate Virtual Environmentīefore creating virtual environment, create a new directory/folder : mkdir rasaDemo cd rasaDemo Install & Create Virtual Environment in Python Install Virtual Environment In this tutorial we will see, how to install rasa, what are intents, stories and actions in rasa, and how to train and test the rasa model. Rasa has the Machine learning-based approach to learn the conversational data. You can build your contextual assistant using Rasa. The Rasa is an open-source Machine learning framework particularly developed for building chatbots.
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