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Added documentation on `ambiguity_threshold` parameter in Fallback Actions page. |
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Added template name to the metadata of bot utterance events. | ||
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`BotUttered` event contains a `template_name` property in its metadata for any | ||
new bot message. |
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Fixed a bug in the `CountVectorsFeaturizer` which resulted in the very first | ||
message after loading a model to be processed incorrectly due to the vocabulary | ||
not being loaded yet. |
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Added a `--num-threads` CLI argument that can be passed to `rasa train` | ||
and will be used to train NLU components. |
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Fixed Rasa shell skipping button messages if buttons are attached to a message previous to the latest. | ||
Fixed Rasa shell skipping button messages if buttons are attached to | ||
a message previous to the latest. |
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Stack level for `FutureWarning` updated to level 2. |
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If custom utter message contains no value or integer value, then it fails | ||
returning custom utter message. Fixed by converting the template to type string. |
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`DIETClassifier` now also assigns a confidence value to entity predictions. |
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You can now define what kind of features should be used by what component | ||
(see [Choosing a Pipeline](/docs/nlu/choosing-a-pipeline)). | ||
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You can set an alias via the option `alias` for every featurizer in your pipeline. | ||
The `alias` can be anything, by default it is set to the full featurizer class name. | ||
You can then specify, for example, on the | ||
[DIETClassifier](/docs/nlu/components#diet-classifier) what features from which | ||
featurizers should be used. | ||
If you don't set the option `featurizers` all available features will be used. | ||
This is also the default behavior. | ||
Check [Components](/docs/nlu/components) to see what components have the option | ||
`featurizers` available. | ||
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Here is an example pipeline that shows the new option. | ||
We define an alias for all featurizers in the pipeline. | ||
All features will be used in the `DIETClassifier`. | ||
However, the `ResponseSelector` only takes the features from the | ||
`ConveRTFeaturizer` and the `CountVectorsFeaturizer` (word level). | ||
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``` | ||
pipeline: | ||
- name: ConveRTTokenizer | ||
- name: ConveRTFeaturizer | ||
alias: "convert" | ||
- name: CountVectorsFeaturizer | ||
alias: "cvf_word" | ||
- name: CountVectorsFeaturizer | ||
alias: "cvf_char" | ||
analyzer: char_wb | ||
min_ngram: 1 | ||
max_ngram: 4 | ||
- name: RegexFeaturizer | ||
alias: "regex" | ||
- name: LexicalSyntacticFeaturizer | ||
alias: "lsf" | ||
- name: DIETClassifier: | ||
- name: ResponseSelector | ||
epochs: 50 | ||
featurizers: ["convert", "cvf_word"] | ||
- name: EntitySynonymMapper | ||
``` | ||
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:::caution | ||
This change is model-breaking. Please retrain your models. | ||
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::: |
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Added behavior to the `rasa --version` command. It will now also list information | ||
about the operating system, python version and `rasa-sdk`. This will make it easier | ||
for users to file bug reports. |
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Fixed DIET breaking with empty spaCy model. |
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Update `rasa shell` documentation to explain how to recreate external | ||
channel session behavior. |
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Pinned the library version for the Azure | ||
[Cloud Storage](/docs/user-guide/cloud-storage) to 2.1.0 since the | ||
persistor is currently not compatible with later versions of the azure-storage-blob | ||
library. |
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Remove ``clean_up_entities`` from extractors that extract pre-defined entities. | ||
Remove `clean_up_entities` from extractors that extract pre-defined entities. | ||
Just keep the clean up method for entity extractors that extract custom entities. |
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To avoid the problem of our entity extractors predicting entity labels for | ||
just a part of the words, we introduced a cleaning method after the prediction | ||
was done. We should avoid the incorrect prediction in the first place. | ||
To achieve this we will not tokenize words into sub-words anymore. | ||
We take the mean feature vectors of the sub-words as the feature vector of the word. | ||
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:::caution | ||
This change is model breaking. Please, retrain your models. | ||
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::: |
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Removed previously deprecated packages `rasa_nlu` and `rasa_core`. | ||
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Use imports from `rasa.core` and `rasa.nlu` instead. |
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Removed previously deprecated classes: | ||
- event brokers (`EventChannel` and `FileProducer`, `KafkaProducer`, | ||
`PikaProducer`, `SQLProducer`) | ||
- intent classifier `EmbeddingIntentClassifier` | ||
- policy `KerasPolicy` | ||
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Removed previously deprecated methods: | ||
- `Agent.handle_channels` | ||
- `TrackerStore.create_tracker_store` | ||
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Removed support for pipeline templates in `config.yml` | ||
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Removed deprecated training data keys `entity_examples` and `intent_examples` from | ||
json training data format. |
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Move option `case_sensitive` from the tokenizers to the featurizers. | ||
- Remove the option from the `WhitespaceTokenizer` and `ConveRTTokenizer`. | ||
- Add option `case_sensitive` to the `RegexFeaturizer`. |
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Don't set roles and groups to `O` (nothing found) when constructing entities | ||
from model predictions. |
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Fixed issue where the `DucklingHTTPExtractor` component would | ||
not work if its `url` contained a trailing slash. |
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Creating a `Domain` using `Domain.fromDict` can no longer alter the input dictionary. | ||
Previously, there could be problems when the input dictionary was re-used for other | ||
things after creating the `Domain` from it. |
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The debug-level logs when instantiating an | ||
[SQLTrackerStore](/docs/api/tracker-stores#sql-tracker-store) | ||
no longer show the password in plain text. Now, the URL is displayed with the password | ||
hidden, e.g. `postgresql://username:***@localhost:5432`. |
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Changed to variable `CERT_URI` in `hangouts.py` to a string type |
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Event brokers documentation should say `url` instead of `host`. |
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Removed `restaurantbot` example as it was confusing and not a great way to build a bot. |
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Added `--port` commandline argument to the interactive learning mode to allow | ||
changing the port for the Rasa server running in the background. |
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Shorten the information in tqdm during training ML algorithms based on the log | ||
level. If you train your model in debug mode, all available metrics will be | ||
shown during training, otherwise, the information is shorten. |
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Remove option `token_pattern` from `CountVectorsFeaturizer`. | ||
Instead all tokenizers now have the option `token_pattern`. | ||
If a regular expression is set, the tokenizer will apply the token pattern. |
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Ignore conversation test directory `tests/` when importing a project | ||
using `MultiProjectImporter` and `use_e2e` is `False`. | ||
Previously, any story data found in a project subdirectory would be imported | ||
as training data. |
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Update `rasa init` documentation to include `tests/conversation_tests.md` | ||
in the resulting directory tree. |
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Introduced a new `YAML` format for Core training data and implemented a parser | ||
for it. Rasa Open Source can now read stories in both `Markdown` and `YAML` format. |
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`WhitespaceTokenizer` does not remove vowel signs in Hindi anymore. |
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`rasa data split nlu` now makes sure that there is at least one example per | ||
intent and response in the test data. |
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Convert entity values coming from `DucklingHTTPExtractor` to string | ||
during evaluation to avoid mismatches due to different types. |
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We updated the way how we save and use features in our NLU pipeline. | ||
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The message object now has a dedicated field, called `features`, to store the | ||
features that are generated in the NLU pipeline. We adapted all our featurizers in a | ||
way that sequence and sentence features are stored independently. This allows us to | ||
keep different kind of features for the sequence and the sentence. For example, the | ||
`LexicalSyntacticFeaturizer` does not produce any sentence features anymore as our | ||
experiments showed that those did not bring any performance gain just quite a lot of | ||
additional values to store. | ||
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We also modified the DIET architecture to process the sequence and sentence | ||
features independently at first. The features are concatenated just before | ||
the transformer. | ||
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We also removed the `__CLS__` token again. Our Tokenizers will not | ||
add this token anymore. | ||
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:::caution | ||
This change is model-breaking. Please retrain your models. | ||
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::: |
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Update `FeatureSignature` to store just the feature dimension instead of the | ||
complete shape. This change fixes the usage of the option `share_hidden_layers` | ||
in the `DIETClassifier`. |