Architecture
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
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)
Reference
Architecture
Message Handling
This diagram shows the basic steps of how an assistant built with Rasa responds to a message:
The steps are:
- The message is received and passed to an
Interpreter, which converts it into a dictionary including the original text, the intent, and any entities that were found. This part is handled by NLU. - The
Trackeris the object which keeps track of conversation state. It receives the info that a new message has come in. - The policy receives the current state of the tracker.
- The policy chooses which action to take next.
- The chosen action is logged by the tracker.
- A response is sent to the user.
Note: Messages can be text typed by a human, or structured input like a button press.
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