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

User Guide

• Installation
• Rasa Tutorial
• Command Line Interface
• Architecture
• Messaging and Voice Channels
• Evaluating Models
• Validate Data
• Running the Server
• Running Rasa with Docker
• Cloud Storage

NLU

• About
• Using NLU Only
• Training Data Format
• Choosing a Pipeline
• Language Support
• Entity Extraction
• Components

Core

• About
• Stories
• Domains
• Responses
• Actions
• 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
• Events
• Tracker
• Tracker Stores
• Event Brokers
• Lock Stores
• Training Data Importers
• Featurization
• Migration Guide
• Rasa Change Log

Migrate from (beta)

• Dialogflow
• Wit.ai
• LUIS
• IBM Watson

Reference

• Glossary

Versions

viewing: 1.4.6

Warning

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

Training Data Format

The training data for Rasa NLU is structured into different parts:

• common examples
• synonyms
• regex features and
• lookup tables