AUTO docusaurus 20210414

changelog/8428.removal.md

@@ -0,0 +1,3 @@
+`rasa.data.get_test_directory`, `rasa.data.get_core_nlu_directories`, and
+`rasa.shared.nlu.training_data.training_data.TrainingData::get_core_nlu_directories`
+are deprecated and will be removed in Rasa Open Source 3.0.0.

docs/docs/reference/rasa/cli/utils.md

@@ -102,3 +102,11 @@ payload_from_button_question(button_question: "Question") -> Text
 
 Prompt user with a button question and returns the nlu payload.
 
+#### signal\_handler
+
+```python
+signal_handler(_: int, __: FrameType) -> None
+```
+
+Kills Rasa when OS signal is received.
+

docs/docs/reference/rasa/core/actions/action.md

@@ -268,15 +268,6 @@ Creates action. See docstring of parent class.
 
 Resolve the name of the intent from the action name.
 
-#### action\_name\_from\_intent
-
-```python
- | @staticmethod
- | action_name_from_intent(intent_name: Text) -> Text
-```
-
-Resolve the action name from the name of the intent.
-
 #### run
 
 ```python

docs/docs/reference/rasa/core/agent.md

@@ -187,23 +187,6 @@ the bot wants to respond.
 >>> await agent.handle_text("hello")
 [u'how can I help you?']
 
-#### toggle\_memoization
-
-```python
- | toggle_memoization(activate: bool) -> None
-```
-
-Toggles the memoization on and off.
-
-If a memoization policy is present in the ensemble, this will toggle
-the prediction of that policy. When set to ``False`` the Memoization
-policies present in the policy ensemble will not make any predictions.
-Hence, the prediction result from the ensemble always needs to come
-from a different policy (e.g. ``TEDPolicy``). Useful to test
-prediction
-capabilities of an ensemble when ignoring memorized turns from the
-training data.
-
 #### load\_data
 
 ```python

docs/docs/reference/rasa/core/featurizers/single_state_featurizer.md

@@ -96,3 +96,19 @@ Encode all action from the domain using the given interpreter.
 
   A list of encoded actions.
 
+## BinarySingleStateFeaturizer Objects
+
+```python
+class BinarySingleStateFeaturizer(SingleStateFeaturizer)
+```
+
+Dialogue State featurizer which features the state as binaries.
+
+#### \_\_init\_\_
+
+```python
+ | __init__() -> None
+```
+
+Creates featurizer.
+

docs/docs/reference/rasa/core/lock_store.md

@@ -160,6 +160,14 @@ Create a lock store which uses Redis for persistence.
 - `socket_timeout` - Timeout in seconds after which an exception will be raised
   in case Redis doesn't respond within `socket_timeout` seconds.
 
+#### get\_lock
+
+```python
+ | get_lock(conversation_id: Text) -> Optional[TicketLock]
+```
+
+Retrieves lock (see parent docstring for more information).
+
 ## InMemoryLockStore Objects
 
 ```python

docs/docs/reference/rasa/core/training/__init__.md

@@ -3,6 +3,27 @@ sidebar_label: training
 title: rasa.core.training
 ---
 
+#### extract\_story\_graph
+
+```python
+async extract_story_graph(resource_name: Text, domain: "Domain", use_e2e: bool = False, exclusion_percentage: Optional[int] = None) -> "StoryGraph"
+```
+
+Loads training stories / rules from file or directory.
+
+**Arguments**:
+
+- `resource_name` - Path to file or directory.
+- `domain` - The model domain.
+- `use_e2e` - `True` if Markdown files should be parsed as conversation test files.
+- `exclusion_percentage` - Percentage of stories which should be dropped. `None`
+  if all training data should be used.
+
+
+**Returns**:
+
+  The loaded training data as graph.
+
 #### load\_data
 
 ```python
@@ -34,11 +55,3 @@ Load training data from a resource.
 
   list of loaded trackers
 
-#### persist\_data
-
-```python
-persist_data(trackers: List["DialogueStateTracker"], path: Text) -> None
-```
-
-Dump a list of dialogue trackers in the story format to disk.
-

docs/docs/reference/rasa/core/training/interactive.md

@@ -113,14 +113,6 @@ latest_user_message(events: List[Dict[Text, Any]]) -> Optional[Dict[Text, Any]]
 
 Return most recent user message.
 
-#### all\_events\_before\_latest\_user\_msg
-
-```python
-all_events_before_latest_user_msg(events: List[Dict[Text, Any]]) -> List[Dict[Text, Any]]
-```
-
-Return all events that happened before the most recent user message.
-
 #### is\_listening\_for\_message
 
 ```python
@@ -145,14 +137,6 @@ start_visualization(image_path: Text, port: int) -> None
 
 Add routes to serve the conversation visualization files.
 
-#### wait\_til\_server\_is\_running
-
-```python
-async wait_til_server_is_running(endpoint: EndpointConfig, max_retries: int = 30, sleep_between_retries: float = 1.0) -> bool
-```
-
-Try to reach the server, retry a couple of times and sleep in between.
-
 #### run\_interactive\_learning
 
 ```python

docs/docs/reference/rasa/core/utils.md

@@ -16,16 +16,6 @@ Configure logging to a file.
 - `logger_obj` - Logger object to configure.
 - `log_file` - Path of log file to write to.
 
-#### is\_int
-
-```python
-is_int(value: Any) -> bool
-```
-
-Checks if a value is an integer.
-
-The type of the value is not important, it might be an int or a float.
-
 #### one\_hot
 
 ```python
@@ -45,67 +35,6 @@ Create a one-hot array.
 
   One-hot array.
 
-## HashableNDArray Objects
-
-```python
-class HashableNDArray()
-```
-
-Hashable wrapper for ndarray objects.
-
-Instances of ndarray are not hashable, meaning they cannot be added to
-sets, nor used as keys in dictionaries. This is by design - ndarray
-objects are mutable, and therefore cannot reliably implement the
-__hash__() method.
-
-The hashable class allows a way around this limitation. It implements
-the required methods for hashable objects in terms of an encapsulated
-ndarray object. This can be either a copied instance (which is safer)
-or the original object (which requires the user to be careful enough
-not to modify it).
-
-#### \_\_init\_\_
-
-```python
- | __init__(wrapped: np.ndarray, tight: bool = False) -> None
-```
-
-Creates a new hashable object encapsulating an ndarray.
-
-wrapped
-    The wrapped ndarray.
-
-tight
-    Optional. If True, a copy of the input ndaray is created.
-    Defaults to False.
-
-#### \_\_eq\_\_
-
-```python
- | __eq__(other: Any) -> bool
-```
-
-Performs equality of the underlying array.
-
-#### \_\_hash\_\_
-
-```python
- | __hash__() -> int
-```
-
-Return the hash of the array.
-
-#### unwrap
-
-```python
- | unwrap() -> np.ndarray
-```
-
-Returns the encapsulated ndarray.
-
-If the wrapper is "tight", a copy of the encapsulated ndarray is
-returned. Otherwise, the encapsulated ndarray itself is returned.
-
 #### dump\_obj\_as\_yaml\_to\_file
 
 ```python
@@ -158,14 +87,6 @@ Determine whether the number of messages has reached a limit.
 
   `True` if the limit has been reached, otherwise `False`.
 
-#### read\_lines
-
-```python
-read_lines(filename: Union[Path, Text], max_line_limit: Optional[int] = None, line_pattern: Text = ".*") -> Generator[Text, Any, None]
-```
-
-Read messages from the command line and print bot responses.
-
 #### file\_as\_bytes
 
 ```python
@@ -174,48 +95,6 @@ file_as_bytes(path: Text) -> bytes
 
 Read in a file as a byte array.
 
-#### convert\_bytes\_to\_string
-
-```python
-convert_bytes_to_string(data: Union[bytes, bytearray, Text]) -> Text
-```
-
-Convert `data` to string if it is a bytes-like object.
-
-#### get\_file\_hash
-
-```python
-get_file_hash(path: Text) -> Text
-```
-
-Calculate the md5 hash of a file.
-
-#### download\_file\_from\_url
-
-```python
-async download_file_from_url(url: Text) -> Text
-```
-
-Download a story file from a url and persists it into a temp file.
-
-**Arguments**:
-
-- `url` - url to download from
-
-
-**Returns**:
-
-  The file path of the temp file that contains the
-  downloaded content.
-
-#### pad\_lists\_to\_size
-
-```python
-pad_lists_to_size(list_x: List, list_y: List, padding_value: Optional[Any] = None) -> Tuple[List, List]
-```
-
-Compares list sizes and pads them to equal length.
-
 ## AvailableEndpoints Objects
 
 ```python
@@ -242,16 +121,6 @@ Get `AvailableEndpoints` object from specified path.
 
   `AvailableEndpoints` object read from endpoints file.
 
-#### create\_task\_error\_logger
-
-```python
-create_task_error_logger(error_message: Text = "") -> Callable[[Future], None]
-```
-
-Error logger to be attached to a task.
-
-This will ensure exceptions are properly logged and won't get lost.
-
 #### replace\_floats\_with\_decimals
 
 ```python

docs/docs/reference/rasa/nlu/persistor.md

@@ -17,10 +17,10 @@ storages.
 ## Persistor Objects
 
 ```python
-class Persistor()
+class Persistor(abc.ABC)
 ```
 
-Store models in cloud and fetch them when needed
+Store models in cloud and fetch them when needed.
 
 #### persist
 
@@ -38,14 +38,6 @@ Uploads a model persisted in the `target_dir` to cloud storage.
 
 Downloads a model that has been persisted to cloud storage.
 
-#### list\_models
-
-```python
- | list_models() -> List[Text]
-```
-
-Lists all the trained models.
-
 ## AWSPersistor Objects
 
 ```python
@@ -74,15 +66,3 @@ class AzurePersistor(Persistor)
 
 Store models on Azure
 
-#### list\_models
-
-```python
- | list_models() -> List[Text]
-```
-
-Lists models on remote storage.
-
-**Returns**:
-
-  Paths to found models.
-