# 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/1.8.3/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.  
  If a message preprocessor is passed, the message will be passed to that function first and the return value is then used as the input for the dialogue engine.

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

### Example
```python
>>> from rasa.core.agent import Agent
>>> from rasa.core.interpreter import RasaNLUInterpreter
>>> agent = Agent.load("examples/restaurantbot/models/current")
>>> await agent.handle_text("hello")
[u'how can I help you?']
```

- `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`

- `_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)`  
  Load a persisted model from the passed path.
  **Return type**: [`Agent`](https://legacy-docs-v1.rasa.com/1.8.3/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`](https://legacy-docs-v1.rasa.com/1.8.3/api/tracker/#rasa.core.trackers.DialogueStateTracker)

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

## Other
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