Rasa SDK
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
- 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
Versions
viewing: 1.10.6
Rasa SDK
Rasa SDK provides the tools you need to write custom actions in python.
Installation
Use pip to install rasa-sdk on your action server.
pip install rasa-sdk
Note
You do not need to install rasa for your action server. E.g. if you are running Rasa in a docker container, it is recommended to create a separate container for your action server. In this separate container, you only need to install rasa-sdk.
Running the Action Server
If you have rasa installed, run this command to start your action server:
rasa run actions
Otherwise, if you do not have rasa installed, run this command:
python -m rasa_sdk --actions actions
You can verify that the action server is up and running with the command:
curl http://localhost:5055/health
You can get the list of registered custom actions with the command:
curl http://localhost:5055/actions
The file that contains your custom actions should be called actions.py. Alternatively, you can use a package directory called actions or else manually specify an actions module or package with the --actions flag.
Actions
The Action class is the base class for any custom action. It has two methods that both need to be overwritten, name() and run().
In a restaurant bot, if the user says “show me a Mexican restaurant”, your bot could execute the action ActionCheckRestaurants, which might look like this:
from rasa_sdk import Action
from rasa_sdk.events import SlotSet
class ActionCheckRestaurants(Action):
def name(self) -> Text:
return "action_check_restaurants"
def run(self,
dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: Dict[Text, Any]) -> List[Dict[Text, Any]]:
cuisine = tracker.get_slot('cuisine')
q = "select * from restaurants where cuisine='{0}' limit 1".format(cuisine)
result = db.query(q)
return [SlotSet("matches", result if result is not None else [])]
You should add the action name action_check_restaurants to the actions in your domain file. The action’s run() method receives three arguments. You can access the values of slots and the latest message sent by the user using the tracker object, and you can send messages back to the user with the dispatcher object, by calling dispatcher.utter_message.
Tracker
The rasa_sdk.Tracker lets you access the bot’s memory in your custom actions. You can get information about past events and the current state of the conversation through Tracker attributes and methods.
The following are available as attributes of a Tracker object:
sender_id- The unique ID of person talking to the bot.slots- The list of slots that can be filled as defined in the domains.latest_message- A dictionary containing the attributes of the latest message:intent,entitiesandtext.events- A list of all previous events.active_form- The name of the currently active form.latest_action_name- The name of the last action the bot executed.