notice

This is documentation for Rasa Open Source Documentation v2.0.x, which is no longer actively maintained.
For up-to-date documentation, see the latest version (2.6.x).

Version: 2.0.x

rasa.core.processor

MessageProcessor Objects

class MessageProcessor()

handle_message

| async handle_message(message: UserMessage) -> Optional[List[Dict[Text, Any]]]

Handle a single message with this processor.

get_tracker_with_session_start

| async get_tracker_with_session_start(sender_id: Text, output_channel: Optional[OutputChannel] = None, metadata: Optional[Dict] = None) -> Optional[DialogueStateTracker]

Get tracker for sender_id or create a new tracker for sender_id.

If a new tracker is created, action_session_start is run.

Arguments:

  • metadata - Data sent from client associated with the incoming user message.
  • output_channel - Output channel associated with the incoming user message.
  • sender_id - Conversation ID for which to fetch the tracker.

Returns:

Tracker for sender_id if available, None otherwise.

get_tracker

| get_tracker(conversation_id: Text) -> Optional[DialogueStateTracker]

Get the tracker for a conversation.

In contrast to get_tracker_with_session_start this does not add any action_session_start or session_start events at the beginning of a conversation.

Arguments:

  • conversation_id - The ID of the conversation for which the history should be retrieved.

Returns:

Tracker for the conversation. Creates an empty tracker in case it's a new conversation.

log_message

| async log_message(message: UserMessage, should_save_tracker: bool = True) -> Optional[DialogueStateTracker]

Log message on tracker belonging to the message's conversation_id.

Optionally save the tracker if should_save_tracker is True. Tracker saving can be skipped if the tracker returned by this method is used for further processing and saved at a later stage.

predict_next_action

| predict_next_action(tracker: DialogueStateTracker) -> Tuple[rasa.core.actions.action.Action, Optional[Text], float]

Predicts the next action the bot should take after seeing x.

This should be overwritten by more advanced policies to use ML to predict the action. Returns the index of the next action.

handle_reminder

| async handle_reminder(reminder_event: ReminderScheduled, sender_id: Text, output_channel: OutputChannel) -> None

Handle a reminder that is triggered asynchronously.

trigger_external_user_uttered

| async trigger_external_user_uttered(intent_name: Text, entities: Optional[Union[List[Dict[Text, Any]], Dict[Text, Text]]], tracker: DialogueStateTracker, output_channel: OutputChannel) -> None

Triggers an external message.

Triggers an external message (like a user message, but invisible; used, e.g., by a reminder or the trigger_intent endpoint).

Arguments:

  • intent_name - Name of the intent to be triggered.
  • entities - Entities to be passed on.
  • tracker - The tracker to which the event should be added.
  • output_channel - The output channel.

parse_message

| async parse_message(message: UserMessage, tracker: Optional[DialogueStateTracker] = None) -> Dict[Text, Any]

Interprete the passed message using the NLU interpreter.

Arguments:

  • message - Message to handle
  • tracker - Dialogue context of the message

Returns:

Parsed data extracted from the message.

is_action_limit_reached

| is_action_limit_reached(num_predicted_actions: int, should_predict_another_action: bool) -> bool

Check whether the maximum number of predictions has been met.

Arguments:

  • num_predicted_actions - Number of predicted actions.
  • should_predict_another_action - Whether the last executed action allows for more actions to be predicted or not.

Returns:

True if the limit of actions to predict has been reached.

should_predict_another_action

| @staticmethod
| should_predict_another_action(action_name: Text) -> bool

Determine whether the processor should predict another action.

Arguments:

  • action_name - Name of the latest executed action.

Returns:

False if action_name is ACTION_LISTEN_NAME or ACTION_SESSION_START_NAME, otherwise True.

execute_side_effects

| async execute_side_effects(events: List[Event], tracker: DialogueStateTracker, output_channel: OutputChannel) -> None

Send bot messages, schedule and cancel reminders that are logged in the events array.