These docs are for version 1.x of Rasa Open Source.

User Guide

Installation

Tutorial: Rasa Basics

Tutorial: Building Assistants

Command Line Interface

Architecture

Messaging and Voice Channels

Testing Your Assistant

Setting up CI/CD

Validate Data

Configuring the HTTP API

Deploying Your Rasa Assistant

Cloud Storage

NLU

About

Using NLU Only

Training Data Format

Language Support

Choosing a Pipeline

Components

Entity Extraction

Core

About

Stories

Domains

Responses

Actions

Reminders and External Events

Policies

Slots

Forms

Retrieval Actions

Interactive Learning

Fallback Actions

Knowledge Base Actions

Conversation Design

Dialogue Elements

Small Talk

Completing Tasks

Guiding Users

API Reference

Action Server

HTTP API

Jupyter Notebooks

Agent

Custom NLU Components

Rasa SDK

Events

Tracker

Tracker Stores

Event Brokers

Lock Stores

Training Data Importers

Featurization of Conversations

TensorFlow Configuration

Migration Guide

Rasa Open Source Change Log

Migrate from (beta)

Dialogflow

Wit.ai

LUIS

IBM Watson

Reference

Glossary

Versions

viewing: 1.10.7

Warning

This document is for an old version of Rasa. The latest version is 1.10.26.

Training Data Format

Data Formats

You can provide training data as Markdown or as JSON, as a single file or as a directory containing multiple files. Note that Markdown is usually easier to work with.

Markdown Format

Markdown is the easiest Rasa NLU format for humans to read and write. Examples are listed using the unordered list syntax, e.g. minus -, asterisk *, or plus +. Examples are grouped by intent, and entities are annotated as Markdown links, e.g. [<entity text>](<entity name>), or by using the following syntax [<entity-text>]{"entity": "<entity name>"}. Using the latter syntax, you can also assign synonyms, roles, or groups to an entity, e.g. `[]{