Glossary

Action

A single step that a bot takes in a conversation (e.g. calling an API or sending a response back to the user).

Annotation

Adding labels to messages and conversations so that they can be used to train a model.

CMS

A Content Management System (CMS) can be used to store bot responses externally instead of directly including it as part of the domain. This provides more flexibility in changing them as they are not tightly-coupled with the training data.

Custom Action

An action written by a Rasa developer that can run arbitrary code mainly to interact with the outside world.

Default Action

A built-in action that comes with predefined functionality.

Domain

Defines the inputs and outputs of an assistant. It includes a list of all the intents, entities, slots, actions, and forms that the assistant knows about.

Entity

Structured information that can be extracted from a user message.

Event

All conversations in Rasa are represented as a sequence of events. For instance, a UserUttered represents a user entering a message, and an ActionExecuted represents the assistant executing an action.

Form

A type of custom action that asks the user for multiple pieces of information.

Happy / Unhappy Paths

If your assistant asks a user for some information and the user provides it, we call that a happy path. Unhappy paths are all the possible edge cases of a bot.

Intent

Something that a user is trying to convey or accomplish (e.g., greeting, specifying a location).

Interactive Learning

A mode of training the bot where the user provides feedback to the bot while talking to it.

Minimum viable assistant

A basic assistant that can handle the most important happy path stories.

NLG

Natural Language Generation (NLG) is the process of generating natural language messages to send to a user.

Rasa NLU

Natural Language Understanding (NLU) deals with parsing and understanding human language into a structured format.

Pipeline

A Rasa bot’s NLU system is defined by a pipeline, which is a list of NLU components.

Policy

Policies make decisions on how conversation flow should proceed.

Rasa Core

The dialogue engine that decides on what to do next in a conversation based on the context.

Rasa NLU Component

An element in the Rasa NLU pipeline.

Slot

A key-value store that Rasa uses to track information over the course of a conversation.

Story

A conversation between a user and a bot annotated with the intent/entities of the users’ messages as well as the sequence of actions to be performed by the bot.

Template / Response / Utterance

A message template that is used to respond to a user.

User Goal

A goal that a user wants to achieve.

Word embedding / Word vector

A vector of floating point numbers which represent the meaning of a word.