1.10.24

Bugfixes

• #8019: Added group_id parameter back to KafkaEventBroker to fix error when instantiating event broker with a config containing the group_id parameter which is only relevant to the event consumer

2.4.3

Bugfixes

• #8114: Fixes bug where stories could not be retrieved if entities had no start or end.

2.4.2

Bugfixes

• #7835: Fix UnicodeException in is_key_in_yaml.
• #8258: Fixed the bug that events from previous conversation sessions would be re-saved in the SQLTrackerStore or MongoTrackerStore when retrieve_events_from_previous_conversation_sessions was true.

2.4.1

Bugfixes

• #8194: Fix TEDPolicy training e2e entities when no entities are present in the stories
  but there are entities in the domain.
• #8198: Fixed missing model configuration file validation.
• #8223: In Rasa 2.4.0, support for using template in utter_message when handling a custom action was wrongly deprecated. Both template and response are now supported, though note that template will be deprecated at Rasa 3.0.0.

2.4.0

Deprecations and Removals

• #6484: NLG Server

  • Changed request format to send response as well as template as a field. The template field will be removed in Rasa Open Source 3.0.0.

  rasa.core.agent

  • The terminology template is deprecated and replaced by response. Support for template from the NLG response will be removed in Rasa Open Source 3.0.0. Please see here for more details.

  rasa.core.nlg.generator

  • generate() now takes in utter_action as a parameter.
  • The terminology template is deprecated and replaced by response. Support for template in the NaturalLanguageGenerator will be removed in Rasa Open Source 3.0.0.

  rasa.shared.core.domain

  • The property templates is deprecated. Use responses instead. It will be removed in Rasa Open Source 3.0.0.
  • retrieval_intent_templates will be removed in Rasa Open Source 3.0.0. Please use retrieval_intent_responses instead.
  • is_retrieval_intent_template will be removed in Rasa Open Source 3.0.0. Please use is_retrieval_intent_response instead.
  • check_missing_templates will be removed in Rasa Open Source 3.0.0. Please use check_missing_responses instead.

  Response Selector

  • The field template_name will be deprecated in Rasa Open Source 3.0.0. Please use utter_action instead. Please see here for more details.
  • The field response_templates will be deprecated in Rasa Open Source 3.0.0. Please use responses instead. Please see here for more details.

Improvements

• #7022: The following endpoints now require the existence of the conversation for the specified conversation ID, raising an exception and returning a 404 status code.

  • GET /conversations/<conversation_id:path>/story

  • POST /conversations/<conversation_id:path>/execute

  • POST /conversations/<conversation_id:path>/predict

• #7438: Simplify our training by overwriting train_step instead of fit for our custom models.

  This allows us to use the build-in callbacks from Keras, such as the
  Tensorboard Callback,
  which offers more functionality compared to what we had before.

  :::warning
  If you want to use Tensorboard for DIETClassifier, ResponseSelector, or TEDPolicy and log metrics after
  every (mini)batch, please use 'batch' instead of 'minibatch' as 'tensorboard_log_level'.

• #7578: When TED is configured to extract entities rasa test now evaluates them against the labels in the test stories. Results are saved in /results along with the results for the NLU components that extract entities.

• #7680: We're now running integration tests for Rasa Open Source, with initial coverage for SQLTrackerStore (with PostgreSQL),
  RedisLockStore (with Redis) and PikaEventBroker (with RabbitMQ). The integration tests are now part of our
  CI, and can also be ran locally using make test-integration
  (see Rasa Open Source README for more information).

• #7763: Allow tests to be located anywhere, not just in tests directory.

• #7893: Model configuration files are now validated whether they match the expected schema.

• #7952: Speed up YAMLStoryReader.is_key_in_yaml function by making it to check if key is in YAML without
  actually parsing the text file.

• #7953: Speed up YAML parsing by reusing parsers, making the process of environment variable interpolation optional,
  and by not adding duplicating implicit resolvers and YAML constructors to ruamel.yaml

• #7955: Drastically improved finger printing time for large story graphs

• #8000: Remove console logging of conversation level F1-score and precision since these calculations were not meaningful.

  Add conversation level accuracy to core policy results logged to file in story_report.json after running rasa test core or rasa test.

• #8100: Improved the lock store debug log message when the process has to
  queue because other messages have to be processed before this item.

Bugfixes

• #4612: Fixed the bug that OR statements in stories would break the check whether a model needs to be retrained

• #7063: Update the spec of POST /model/test/intents and add tests for cases when JSON is provided.

  Fix the incorrect temporary file extension for the data that gets extracted from the payload provided
  in the body of POST /model/test/intents request.

• #7113: Fix for the cli command rasa data convert config when migrating Mapping Policy and no rules.

  Making rasa data convert config migrate correctly the Mapping Policy when no rules are available. It updates the config.yml file by removing the MappingPolicy and adding the RulePolicy instead. Also, it creates the data/rules.yml file even if empty in the case of no available rules.

• #7470: Allow to have slots with values that result to a dictionary under the key slot_was_set (in stories.yml file).

  An example would be to have the following story step in stories.yml:

  - slot_was_set:
      - some_slot:
          some_key: 'some_value'
          other_key: 'other_value'

  This would be allowed if the some_slot is also set accordingly in the domain.yml with type any.

• #7662: Update the fingerprinting function to recognize changes in lookup files.

• #7932: Fixed a bug when interpolating environment variables in YAML files which included $ in their value.
  This led to the following stack trace:

  ValueError: Error when trying to expand the environment variables in '${PASSWORD}'. Please make sure to also set these environment variables: '['$qwerty']'.
  (13 additional frame(s) were not displayed)
  ...
    File "rasa/utils/endpoints.py", line 26, in read_endpoint_config
      content = rasa.shared.utils.io.read_config_file(filename)
    File "rasa/shared/utils/io.py", line 527, in read_config_file
      content = read_yaml_file(filename)
    File "rasa/shared/utils/io.py", line 368, in read_yaml_file
      return read_yaml(read_file(filename, DEFAULT_ENCODING))
    File "rasa/shared/utils/io.py", line 349, in read_yaml
      return yaml_parser.load(content) or {}
    File "rasa/shared/utils/io.py", line 314, in env_var_constructor
      " variables: '{}'.".format(value, not_expanded)
  

• #7949: The REQUESTED_SLOT always belongs to the currently active form.

  Previously it was possible that after form switching, the REQUESTED_SLOT was for the previous form.

• #96: Update the LanguageModelFeaturizer tests to reflect new default model weights for bert, and skip all bert tests
  with default model weights on CI, run bert tests with bert-base-uncased on CI instead.

Miscellaneous internal changes

• #6484, #7737, #7879

2.3.4

Bugfixes

• #8014: Setting model_confidence=cosine in DIETClassifier, ResponseSelector and TEDPolicy is deprecated and will no longer be available. This was introduced in Rasa Open Source version 2.3.0 but post-release experiments suggest that using cosine similarity as model's confidences can change the ranking of predicted labels which is wrong.

  model_confidence=inner is deprecated and is replaced by model_confidence=linear_norm as the former produced an unbounded range of confidences which broke the logic of assistants in various other places.

  We encourage you to try model_confidence=linear_norm which will produce a linearly normalized version of dot product similarities with each value in the range [0,1]. This can be done with the following config:

  - name: DIETClassifier
    model_confidence: linear_norm
    constrain_similarities: True

  This should ease up tuning fallback thresholds as confidences for wrong predictions are better distributed across the range [0, 1].

  If you trained a model with model_confidence=cosine or model_confidence=inner setting using previous versions of Rasa Open Source, please re-train by either removing the model_confidence option from the configuration or setting it to linear_norm.

  model_confidence=cosine is removed from the configuration generated by auto-configuration.

2.3.3

Bugfixes

• #8001: Fixed bug where the conversation does not lock before handling a reminder event.

2.3.2

Bugfixes

• #7972: Fix a bug where, if a user injects an intent using the HTTP API, slot auto-filling is not performed on the entities provided.

1.10.23

Bugfixes

• #7895: Fixed bug where the conversation does not lock before handling a reminder event.

2.3.1

Bugfixes

• #7970: Fixed a YAML validation error which happened when executing multiple validations
  concurrently. This could e.g. happen when sending concurrent requests to server
  endpoints which process YAML training data.