AUTO docusaurus 20231002

.github/scripts/download_pretrained.py

@@ -52,7 +52,7 @@ def get_model_name_and_weights_from_config(
             if model_name not in model_class_dict:
                 raise KeyError(
                     f"'{model_name}' not a valid model name. Choose from "
-                    f"{str(list(model_class_dict.keys()))} or create"
+                    f"{list(model_class_dict.keys())!s} or create"
                     f"a new class inheriting from this class to support your model."
                 )
 

.github/tests/test_download_pretrained.py

@@ -23,7 +23,9 @@ def test_download_pretrained_lmf_exists_with_model_name():
     config = yaml.load(CONFIG_FPATH)
 
     steps = config.get("pipeline", [])
-    step = list(filter(lambda x: x["name"] == download_pretrained.COMP_NAME, steps))[0]
+    step = list(  # noqa: RUF015
+        filter(lambda x: x["name"] == download_pretrained.COMP_NAME, steps)
+    )[0]
     step["model_name"] = "roberta"
     step["cache_dir"] = "/this/dir"
 
@@ -41,7 +43,9 @@ def test_download_pretrained_unknown_model_name():
     config = yaml.load(CONFIG_FPATH)
 
     steps = config.get("pipeline", [])
-    step = list(filter(lambda x: x["name"] == download_pretrained.COMP_NAME, steps))[0]
+    step = list(  # noqa: RUF015
+        filter(lambda x: x["name"] == download_pretrained.COMP_NAME, steps)
+    )[0]
     step["model_name"] = "unknown"
 
     with tempfile.NamedTemporaryFile("w+") as fp:
@@ -56,7 +60,9 @@ def test_download_pretrained_multiple_model_names():
     config = yaml.load(CONFIG_FPATH)
 
     steps = config.get("pipeline", [])
-    step = list(filter(lambda x: x["name"] == download_pretrained.COMP_NAME, steps))[0]
+    step = list(  # noqa: RUF015
+        filter(lambda x: x["name"] == download_pretrained.COMP_NAME, steps)
+    )[0]
     step_new = deepcopy(step)
     step_new["model_name"] = "roberta"
     steps.append(step_new)
@@ -74,7 +80,9 @@ def test_download_pretrained_with_model_name_and_nondefault_weight():
     config = yaml.load(CONFIG_FPATH)
 
     steps = config.get("pipeline", [])
-    step = list(filter(lambda x: x["name"] == download_pretrained.COMP_NAME, steps))[0]
+    step = list(  # noqa: RUF015
+        filter(lambda x: x["name"] == download_pretrained.COMP_NAME, steps)
+    )[0]
     step["model_name"] = "bert"
     step["model_weights"] = "bert-base-uncased"
 
@@ -91,7 +99,9 @@ def test_download_pretrained_lmf_doesnt_exists():
     config = yaml.load(CONFIG_FPATH)
 
     steps = config.get("pipeline", [])
-    step = list(filter(lambda x: x["name"] == download_pretrained.COMP_NAME, steps))[0]
+    step = list(  # noqa: RUF015
+        filter(lambda x: x["name"] == download_pretrained.COMP_NAME, steps)
+    )[0]
     steps.remove(step)
 
     with tempfile.NamedTemporaryFile("w+") as fp:

docs/docs/reference/rasa/api.md

@@ -7,8 +7,8 @@ title: rasa.api
 ```python
 def run(model: "Text",
         endpoints: "Text",
-        connector: "Text" = None,
-        credentials: "Text" = None,
+        connector: "Optional[Text]" = None,
+        credentials: "Optional[Text]" = None,
         **kwargs: "Dict[Text, Any]") -> None
 ```
 

docs/docs/reference/rasa/core/channels/channel.md

@@ -18,7 +18,7 @@ Includes the channel the responses should be sent to.
 def __init__(text: Optional[Text] = None,
              output_channel: Optional["OutputChannel"] = None,
              sender_id: Optional[Text] = None,
-             parse_data: Dict[Text, Any] = None,
+             parse_data: Optional[Dict[Text, Any]] = None,
              input_channel: Optional[Text] = None,
              message_id: Optional[Text] = None,
              metadata: Optional[Dict] = None,

docs/docs/reference/rasa/core/channels/rocketchat.md

@@ -15,7 +15,7 @@ async def send_text_message(recipient_id: Text, text: Text,
                             **kwargs: Any) -> None
 ```
 
-Send message to output channel
+Send message to output channel.
 
 ## RocketChatInput Objects
 

docs/docs/reference/rasa/core/channels/socketio.md

@@ -58,7 +58,7 @@ async def send_image_url(recipient_id: Text, image: Text,
                          **kwargs: Any) -> None
 ```
 
-Sends an image to the output
+Sends an image to the output.
 
 #### send\_text\_with\_buttons
 
@@ -87,7 +87,7 @@ async def send_custom_json(recipient_id: Text, json_message: Dict[Text, Any],
                            **kwargs: Any) -> None
 ```
 
-Sends custom json to the output
+Sends custom json to the output.
 
 #### send\_attachment
 

docs/docs/reference/rasa/core/channels/telegram.md

@@ -63,7 +63,7 @@ Sends a message with a custom json payload.
 class TelegramInput(InputChannel)
 ```
 
-Telegram input channel
+Telegram input channel.
 
 #### get\_output\_channel
 

docs/docs/reference/rasa/core/evaluation/marker_base.md

@@ -101,6 +101,7 @@ Instantiates a marker.
   applies if and only if the non-negated marker does not apply)
 - `description` - an optional description of the marker. It is not used
   internally but can be used to document the marker.
+
 
 **Raises**:
 
@@ -352,6 +353,7 @@ Instantiates a marker.
   conversion of this marker
 - `description` - an optional description of the marker. It is not used
   internally but can be used to document the marker.
+
 
 **Raises**:
 

docs/docs/reference/rasa/core/evaluation/marker_tracker_loader.md

@@ -39,7 +39,7 @@ Represents a wrapper over a `TrackerStore` with a configurable access pattern.
 ```python
 def __init__(tracker_store: TrackerStore,
              strategy: str,
-             count: int = None,
+             count: Optional[int] = None,
              seed: Any = None) -> None
 ```
 

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

@@ -67,7 +67,7 @@ Fingerprint the container.
 #### messages
 
 ```python
-def messages(key_attribute: Text = None) -> ValuesView
+def messages(key_attribute: Optional[Text] = None) -> ValuesView
 ```
 
 Returns a view of all messages.

docs/docs/reference/rasa/core/tracker_store.md

@@ -653,8 +653,8 @@ def get_db_url(dialect: Text = "sqlite",
                host: Optional[Text] = None,
                port: Optional[int] = None,
                db: Text = "rasa.db",
-               username: Text = None,
-               password: Text = None,
+               username: Optional[Text] = None,
+               password: Optional[Text] = None,
                login_db: Optional[Text] = None,
                query: Optional[Dict] = None) -> Union[Text, "URL"]
 ```

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

@@ -160,10 +160,11 @@ Add routes to serve the conversation visualization files.
 #### run\_interactive\_learning
 
 ```python
-def run_interactive_learning(file_importer: TrainingDataImporter,
-                             skip_visualization: bool = False,
-                             conversation_id: Text = uuid.uuid4().hex,
-                             server_args: Dict[Text, Any] = None) -> None
+def run_interactive_learning(
+        file_importer: TrainingDataImporter,
+        skip_visualization: bool = False,
+        conversation_id: Text = uuid.uuid4().hex,
+        server_args: Optional[Dict[Text, Any]] = None) -> None
 ```
 
 Start the interactive learning with the model of the agent.

docs/docs/reference/rasa/nlu/extractors/extractor.md

@@ -96,7 +96,7 @@ def convert_predictions_into_entities(
     text: Text,
     tokens: List[Token],
     tags: Dict[Text, List[Text]],
-    split_entities_config: Dict[Text, bool] = None,
+    split_entities_config: Optional[Dict[Text, bool]] = None,
     confidences: Optional[Dict[Text, List[float]]] = None
 ) -> List[Dict[Text, Any]]
 ```

docs/docs/reference/rasa/nlu/utils/hugging_face/transformers_pre_post_processors.md

@@ -221,7 +221,7 @@ def xlm_embeddings_post_processor(
         sequence_embeddings: np.ndarray) -> Tuple[np.ndarray, np.ndarray]
 ```
 
-Post process embeddings from XLM models
+Post process embeddings from XLM models.
 
 by taking a mean over sequence embeddings and returning that as sentence
 representation. Remove first and last time steps

docs/docs/reference/rasa/shared/core/conversation.md

@@ -8,7 +8,7 @@ title: rasa.shared.core.conversation
 class Dialogue()
 ```
 
-A dialogue comprises a list of Turn objects
+A dialogue comprises a list of Turn objects.
 
 #### \_\_init\_\_
 

docs/docs/reference/rasa/shared/core/trackers.md

@@ -456,7 +456,7 @@ Dump the tracker as a story to a file.
 def get_last_event_for(
     event_type: Union[Type["EventTypeAlias"], Tuple[Type["EventTypeAlias"],
                                                     ...]],
-    action_names_to_exclude: List[Text] = None,
+    action_names_to_exclude: Optional[List[Text]] = None,
     skip: int = 0,
     event_verbosity: EventVerbosity = EventVerbosity.APPLIED
 ) -> Optional["EventTypeAlias"]

docs/docs/reference/rasa/shared/core/training_data/story_writer/story_writer.md

@@ -28,6 +28,7 @@ Turns Story steps into an string.
   the existing story file.
 - `is_test_story` - Identifies if the stories should be exported in test stories
   format.
+
 
 **Returns**:
 

docs/docs/reference/rasa/shared/nlu/training_data/message.md

@@ -78,7 +78,7 @@ Retrieve message property.
 def as_dict_nlu() -> dict
 ```
 
-Get dict representation of message as it would appear in training data
+Get dict representation of message as it would appear in training data.
 
 #### as\_dict
 
@@ -146,7 +146,7 @@ Builds a Message from `UserUttered` data.
 def get_full_intent() -> Text
 ```
 
-Get intent as it appears in training data
+Get intent as it appears in training data.
 
 #### separate\_intent\_response\_key
 

docs/docs/reference/rasa/shared/nlu/training_data/training_data.md

@@ -231,7 +231,7 @@ Calculates the number of examples per entity.
 def sort_regex_features() -> None
 ```
 
-Sorts regex features lexicographically by name+pattern
+Sorts regex features lexicographically by name+pattern.
 
 #### nlu\_as\_json
 

docs/docs/reference/rasa/shared/nlu/training_data/util.md

@@ -10,7 +10,7 @@ def transform_entity_synonyms(
         known_synonyms: Optional[Dict[Text, Any]] = None) -> Dict[Text, Any]
 ```
 
-Transforms the entity synonyms into a text->value dictionary
+Transforms the entity synonyms into a text->value dictionary.
 
 #### get\_file\_format\_extension
 
@@ -29,6 +29,7 @@ same known format, return it's extension
 **Arguments**:
 
 - `resource_name` - The name of the resource, can be a file or a folder.
+
 
 **Returns**:
 

docs/docs/reference/rasa/utils/endpoints.md

@@ -9,7 +9,7 @@ def read_endpoint_config(filename: Text,
                          endpoint_type: Text) -> Optional["EndpointConfig"]
 ```
 
-Read an endpoint configuration file from disk and extract one
+Read an endpoint configuration file from disk and extract one.
 
 config.
 

docs/docs/reference/rasa/utils/tensorflow/crf.md

@@ -149,6 +149,7 @@ Computes the unary scores of tag sequences.
 - `tag_indices` - A [batch_size, max_seq_len] matrix of tag indices.
 - `sequence_lengths` - A [batch_size] vector of true sequence lengths.
 - `inputs` - A [batch_size, max_seq_len, num_tags] tensor of unary potentials.
+
 
 **Returns**:
 
@@ -168,6 +169,7 @@ Computes the binary scores of tag sequences.
 - `tag_indices` - A [batch_size, max_seq_len] matrix of tag indices.
 - `sequence_lengths` - A [batch_size] vector of true sequence lengths.
 - `transition_params` - A [num_tags, num_tags] matrix of binary potentials.
+
 
 **Returns**:
 
@@ -191,6 +193,7 @@ Computes the unnormalized score for a tag sequence.
   we compute the unnormalized score.
 - `sequence_lengths` - A [batch_size] vector of true sequence lengths.
 - `transition_params` - A [num_tags, num_tags] transition matrix.
+
 
 **Returns**:
 
@@ -239,6 +242,7 @@ Computes the normalization for a CRF.
   to use as input to the CRF layer.
 - `sequence_lengths` - A [batch_size] vector of true sequence lengths.
 - `transition_params` - A [num_tags, num_tags] transition matrix.
+
 
 **Returns**:
 
@@ -266,6 +270,7 @@ Computes the log-likelihood of tag sequences in a CRF.
 - `sequence_lengths` - A [batch_size] vector of true sequence lengths.
 - `transition_params` - A [num_tags, num_tags] transition matrix,
   if available.
+
 
 **Returns**:
 

docs/docs/reference/rasa/utils/tensorflow/layers.md

@@ -449,7 +449,7 @@ def f1_score(tag_ids: tf.Tensor, pred_ids: tf.Tensor,
              mask: tf.Tensor) -> tf.Tensor
 ```
 
-Calculates f1 score for train predictions
+Calculates f1 score for train predictions.
 
 ## DotProductLoss Objects
 

docs/docs/sources/rasa_interactive___help.txt

@@ -39,7 +39,7 @@ options:
   --conversation-id CONVERSATION_ID
                         Specify the id of the conversation the messages are
                         in. Defaults to a UUID that will be randomly
-                        generated. (default: d8274dd1c0b743279c3d5754cf8d4701)
+                        generated. (default: c7b0c8957e9b4ade97e3a6bf4d87a4dd)
   --endpoints ENDPOINTS
                         Configuration file for the model server and the
                         connectors as a yml file. (default: endpoints.yml)

docs/docs/sources/rasa_shell___help.txt

@@ -30,7 +30,7 @@ options:
   -h, --help            show this help message and exit
   --conversation-id CONVERSATION_ID
                         Set the conversation ID. (default:
-                        368875d2e6844d0d9e7cd66da0fb02fb)
+                        d2436920ecba4b0e80992625be3a2fd8)
   -m MODEL, --model MODEL
                         Path to a trained Rasa model. If a directory is
                         specified, it will use the latest model in this