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For more information about the new data format see :ref:`training-data-format`.
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Improvements
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------------
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- `#2224 <https://github.com/rasahq/rasa/issues/2224>`_: Suppressed ``pika`` logs when establishing the connection. These log messages
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mostly happened when Rasa X and RabbitMQ were started at the same time. Since RabbitMQ
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can take a few seconds to initialize, Rasa X has to re-try until the connection is
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established.
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In case you suspect a different problem (such as failing authentication) you can
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re-enable the ``pika`` logs by setting the log level to ``DEBUG``. To run Rasa Open
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Source in debug mode, use the ``--debug`` flag. To run Rasa X in debug mode, set the
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environment variable ``DEBUG_MODE`` to ``true``.
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- `#3419 <https://github.com/rasahq/rasa/issues/3419>`_: 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.
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- `#5544 <https://github.com/rasahq/rasa/issues/5544>`_: Add confusion matrix and "confused_with" to response selection evaluation
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If you are using ResponseSelectors, they now produce similiar outputs during NLU evaluation. Misclassfied responses are listed in a "confused_with" attribute in the evaluation report. Similiarily, a confusion matrix of all responses is plotted.
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- `#5578 <https://github.com/rasahq/rasa/issues/5578>`_: Added ``socketio`` to the compatible channels for :ref:`reminders-and-external-events`.
- `#5627 <https://github.com/rasahq/rasa/issues/5627>`_: All Rasa Open Source images are now using Python 3.7 instead of Python 3.6.
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- `#5635 <https://github.com/rasahq/rasa/issues/5635>`_: Update dependencies based on the ``dependabot`` check.
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- `#5636 <https://github.com/rasahq/rasa/issues/5636>`_: Add dropout between ``FFNN`` and ``DenseForSparse`` layers in ``DIETClassifier``,
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``ResponseSelector`` and ``EmbeddingIntentClassifier`` controlled by ``use_dense_input_dropout`` config parameter.
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- `#5646 <https://github.com/rasahq/rasa/issues/5646>`_: ``DIETClassifier`` only counts as extractor in ``rasa test`` if it was actually trained for entity recognition.
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- `#5669 <https://github.com/rasahq/rasa/issues/5669>`_: Remove regularization gradient for variables that don't have prediction gradient.
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- `#5672 <https://github.com/rasahq/rasa/issues/5672>`_: 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.
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- `#5690 <https://github.com/rasahq/rasa/issues/5690>`_: Add ``full_retrieval_intent`` property to ``ResponseSelector`` rankings
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- `#5717 <https://github.com/rasahq/rasa/issues/5717>`_: 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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Bugfixes
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--------
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- `#5230 <https://github.com/rasahq/rasa/issues/5230>`_: 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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- `#5475 <https://github.com/rasahq/rasa/issues/5475>`_: One word can just have one entity label.
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If you are using, for example, ``ConveRTTokenizer`` words can be split into multiple tokens.
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Our entity extractors assign entity labels per token. So, it might happen, that a word, that was split into two tokens,
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got assigned two different entity labels. This is now fixed. One word can just have one entity label at a time.
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- `#5509 <https://github.com/rasahq/rasa/issues/5509>`_: An entity label should always cover a complete word.
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If you are using, for example, ``ConveRTTokenizer`` words can be split into multiple tokens.
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Our entity extractors assign entity labels per token. So, it might happen, that just a part of a word has
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an entity label. This is now fixed. An entity label always covers a complete word.
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- `#5574 <https://github.com/rasahq/rasa/issues/5574>`_: Fixed an issue that happened when metadata is passed in a new session.
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Now the metadata is correctly passed to the ActionSessionStart.
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- `#5672 <https://github.com/rasahq/rasa/issues/5672>`_: Updated Python dependency ``ruamel.yaml`` to ``>=0.16``. We recommend to use at least
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``0.16.10`` due to the security issue
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`CVE-2019-20478 <https://nvd.nist.gov/vuln/detail/CVE-2019-20478>`_ which is present in
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@@ -215,6 +215,7 @@ Releasing a new version is quite simple, as the packages are build and distribut
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- Once the tag with the new Rasa SDK release is pushed and the package appears on [pypi](https://pypi.org/project/rasa-sdk/), the dependency in the rasa repository can be resolved (see below).
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2. Switch to the branch you want to cut the release from (`master` in case of a major / minor, the current feature branch for patch releases)
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- Update the `rasa-sdk` entry in `pyproject.toml` with the new release version and run `poetry update`. This creates a new `poetry.lock` file with all dependencies resolved.
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- Commit the changes with `git commit -am "bump rasa-sdk dependency"` but do not push them. They will be automatically picked up by the following step.
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3. Run `make release`
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4. Create a PR against master or the release branch (e.g. `1.2.x`)
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5. Once your PR is merged, tag a new release (this SHOULD always happen on master or release branches), e.g. using
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