Build contextual chatbots and AI assistants with Rasa

These docs are for version 1.x of Rasa Open Source.
Docs for the new version 2.0 can be found here.

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
• Rasa SDK
• Events
• Tracker
• Tracker Stores
• Event Brokers
• Lock Stores
• Training Data Importers
• Featurization of Conversations
• Migration Guide
• Rasa OSS Change Log

Migrate from (beta)

• Dialogflow
• Wit.ai
• LUIS
• IBM Watson

Reference

• Glossary

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

This is the documentation for version 1.6.2 of Rasa. Please make sure you are reading the documentation that matches the version you have installed.

Rasa is an open source machine learning framework for automated text and voice-based conversations. Understand messages, hold conversations, and connect to messaging channels and APIs.

👋 I can help you get started with Rasa and answer your technical questions.