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CHANGELOG.rst

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.. towncrier release notes start
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[1.9.7] - 2020-04-23
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^^^^^^^^^^^^^^^^^^^^
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Improvements
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------------
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- `#4606 <https://github.com/rasahq/rasa/issues/4606>`_: The stream reading timeout for ``rasa shell` is now configurable by using the
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environment variable ``RASA_SHELL_STREAM_READING_TIMEOUT_IN_SECONDS``.
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This can help to fix problems when using ``rasa shell`` with custom actions which run
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10 seconds or longer.
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Bugfixes
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--------
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- `#5709 <https://github.com/rasahq/rasa/issues/5709>`_: Reverted changes in 1.9.6 that led to model incompatibility. Upgrade to 1.9.7 to fix
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``self.sequence_lengths_for(tf_batch_data[TEXT_SEQ_LENGTH][0]) IndexError: list index out of range``
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error without needing to retrain earlier 1.9 models.
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Therefore, all 1.9 models `except for 1.9.6` will be compatible; a model trained on 1.9.6 will need
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to be retrained on 1.9.7.
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[1.9.6] - 2020-04-15
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^^^^^^^^^^^^^^^^^^^^
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changelog/3419.improvement.rst

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Include the source filename of a story in the failed stories
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Include the source filename of a story in the failed stories to make it easier to identify the file which contains the failed story.

changelog/3765.feature.rst

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Add support for entities with roles and grouping of entities in Rasa NLU.
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You can now define a role and/or group label in addition to the entity type for entities.
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Use the role label if an entity can play different roles in your assistant.
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For example, a city can be a destination or a departure city.
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The group label can be used to group multiple entities together.
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For example, you could group different pizza orders, so that you know what toppings goes with which pizza and
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what size which pizza has.
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For more details see :ref:`entities-roles-groups`.
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To fill slots from entities with a specific role/group, you need to either use forms or use a custom action.
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We updated the tracker method ``get_latest_entity_values`` to take an optional role/group label.
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If you want to use a form, you can add the specific role/group label of interest to the slot mapping function
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``from_entity`` (see :ref:`forms``).
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.. note::
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Composite entities are currently just supported by the :ref:``diet-classifier`` and :ref:``CRFEntityExtractor``.

changelog/5230.bugfix.rst

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Fixed issue where posting to certain callback channel URLs would return a 500 error on successful posts due to invalid response format
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Fixed issue where posting to certain callback channel URLs would return a 500 error on successful posts due to invalid response format.

changelog/5465.feature.rst

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Update training data format for NLU to support entities with a role or group label.
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You can now specify synonyms, roles, and groups of entities using the following data format:
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Markdown:
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.. code-block:: none
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[LA]{"entity": "location", "role": "city", "group": "CA", "value": "Los Angeles"}
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JSON:
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.. code-block:: none
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"entities": [
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{
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"start": 10,
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"end": 12,
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"value": "Los Angeles",
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"entity": "location",
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"role": "city",
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"group": "CA",
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}
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]
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The markdown format ``[LA](location:Los Angeles)`` is deprecated. To update your training data file just
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execute the following command on the terminal of your choice:
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``sed -i .deprecated -E 's/\[(.*)\]\((.*):(.*)\)/\[\1\]\{"entity": "\2", "value": "\3"\}/g' nlu.md``
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For more information about the new data format see :ref:`training-data-format`.
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changelog/5669.improvement.rst

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Remove regularization gradient for variables that don't have prediction gradient.

changelog/5672.improvement.rst

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Raise a warning in ``CRFEntityExtractor`` and ``DIETClassifier`` if entities are not correctly annotated in the
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training data, e.g. their start and end values do not match any start and end values of tokens.

changelog/5717.improvement.rst

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Change default values for hyper-parameters in ``EmbeddingIntentClassifier`` and ``DIETClassifier``
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Use ``scale_loss=False`` in ``DIETClassifier``. Reduce the number of dense dimensions for sparse features of text from 512 to 256 in ``EmbeddingIntentClassifier``.
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## intent:affirm
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- yes
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- yep
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- yeah
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- indeed
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- that's right
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- ok
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- great
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- right, thank you
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- correct
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- great choice
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- sounds really good
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## intent:goodbye
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- bye
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- goodbye
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- good bye
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- stop
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- end
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- farewell
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- Bye bye
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- have a good one
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## intent:greet
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- hey
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- howdy
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- hey there
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- hello
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- hi
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- good morning
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- good evening
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- dear sir
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## intent:chitchat
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- What's your name?
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- What can I call you?
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- How's the weather?
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- Is it too hot outside?
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## intent:book_flight
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- i'm looking for a flight
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- I want to book a flight
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- i'm looking for a flight to [Berlin]{"entity": "location", "role": "to"}
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- show me flights from [Amsterdam]{"entity": "location", "role": "from"}
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- show me flights to [London]{"entity": "location", "role": "to"}
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- i am looking for a flight from [SF]{"entity": "location", "value": "San Fransisco", "role": "from"} to [New York]{"entity": "location", "role": "to"}
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- search for flights
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- from [Madrid]{"entity": "location", "role": "from"} to [Munich]{"entity": "location", "role": "to"}
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- any flight to [Liverpool]{"entity": "location", "role": "to"}
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## intent:order_pizza
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- i want a [large]{"entity": "size", "group": "1"} pizza with [tomato]{"entity": "topping", "group": "1"} and a [small]{"entity": "size", "group": "2"} pizza with [bacon]{"entity": "topping", "group": "2"}
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- one [large]{"entity": "size", "group": "1"} with [pepperoni]{"entity": "topping", "group": "1"} and a [medium]{"entity": "size", "group": "2"} with [mushrooms]{"entity": "topping", "group": "2"}
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- I would like a [medium]{"entity": "size", "group": "1"} standard pizza and a [medium]{"entity": "size", "group": "2"} pizza with [extra cheese]{"entity": "topping", "group": "2"}
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- [large]{"entity": "size", "group": "1"} with [onions]{"entity": "topping", "group": "1"} and [small]{"entity": "size", "group": "2"} with [olives]{"entity": "topping", "group": "2"}
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- a pizza with [onions]{"entity": "topping", "group": "1"} in [medium]{"entity": "size", "group": "1"} and one with [mushrooms]{"entity": "topping", "group": "2"} in [small]{"entity": "size", "group": "2"} please

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