Agent

The Agent class provides a convenient interface for the most important Rasa functionality.

This includes training, handling messages, loading a dialogue model, getting the next action, and handling a channel.

Methods:

• create_processor(preprocessor=None)
• async execute_action(sender_id, action, output_channel, policy, confidence)
• handle_channels(channels, http_port=5005, route='/webhooks/', cors=None)
• async handle_message(message, message_preprocessor=None, **kwargs)
• async handle_text(text_message, message_preprocessor=None, output_channel=None, sender_id='default')
• is_core_ready()
• is_ready()
• classmethod load(model_path, interpreter=None, generator=None, tracker_store=None, lock_store=None, action_endpoint=None, model_server=None, remote_storage=None, path_to_model_archive=None)
• async load_data(training_resource, remove_duplicates=True, unique_last_num_states=None, augmentation_factor=50, tracker_limit=None, use_story_concatenation=True, debug_plots=False, exclusion_percentage=None)
• async log_message(message, message_preprocessor=None, **kwargs)
• async parse_message_using_nlu_interpreter(message_data, tracker=None)
• persist(model_path)
• async predict_next(sender_id, **kwargs)
• toggle_memoization(activate)
• train(training_trackers, **kwargs)
• async trigger_intent(intent_name, entities, output_channel, tracker)