# 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)`
Instantiates a processor based on the set state of the agent.

**Return type**  
`MessageProcessor`

### `_async execute_action(sender_id, action, output_channel, policy, confidence)`
Handle a single message.

**Return type**  
[`DialogueStateTracker`](https://legacy-docs-v1.rasa.com/1.10.21/api/tracker/#rasa.core.trackers.DialogueStateTracker)

### `handle_channels(channels, http_port=5005, route='/webhooks/', cors=None)`
Start a webserver attaching the input channels and handling msgs.

**Return type**  
`Sanic`

### `_async handle_message(message, message_preprocessor=None, **kwargs)`
Handle a single message.

**Return type**  
`Optional[List[Dict[str, Any]]}`

### `_async handle_text(text_message, message_preprocessor=None, output_channel=None, sender_id='default')`
Handle a single message.

**Return type**  
`Optional[List[Dict[str, Any]]}`

### `is_core_ready()`
Check if all necessary components and policies are ready to use the agent.

**Return type**  
`bool`

### `is_ready()`
Check if all necessary components are instantiated to use agent.

**Return type**  
`bool`

### `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)`
Load a persisted model from the passed path.

**Return type**  
[`Agent`](https://legacy-docs-v1.rasa.com/1.10.21/api/agent/#rasa.core.agent.Agent)

### `_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)`
Load training data from a resource.

**Return type**  
`List[DialogueStateTracker]`

### `_async log_message(message, message_preprocessor=None, **kwargs)`
Append a message to a dialogue - does not predict actions.

**Return type**  
[`DialogueStateTracker`](https://legacy-docs-v1.rasa.com/1.10.21/api/tracker/#rasa.core.trackers.DialogueStateTracker)

### `_async parse_message_using_nlu_interpreter(message_data, tracker=None)`
Handles message text and intent payload input messages.

**Return type**  
`Dict[str, Any]`

### `persist(model_path)`
Persists this agent into a directory for later loading and usage.

**Return type**  
`None`

### `_async predict_next(sender_id, **kwargs)`
Handle a single message.

**Return type**  
`Optional[Dict[str, Any]]`

### `toggle_memoization(activate)`
Toggles the memoization on and off.

**Return type**  
`None`

### `train(training_trackers, **kwargs)`
Train the policies / policy ensemble using dialogue data from file.

**Return type**  
`None`

### `_async trigger_intent(intent_name, entities, output_channel, tracker)`
Trigger a user intent, e.g. triggered by an external event.

**Return type**  
`None`

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