# Rasa Change Log All notable changes to this project will be documented in this file. This project adheres to [Semantic Versioning](http://semver.org/) starting with version 1.0. ## [1.3.10] - 2019-10-18 ### Added - Can now pass a package as an argument to the `--actions` parameter of the `rasa run actions` command. ### Fixed - Fixed visualization of stories with entities which led to a failing visualization in Rasa X ## [1.3.9] - 2019-10-10 ### Added - Port of 1.2.10 (support for RabbitMQ TLS authentication and `port` key in event broker endpoint config). - Port of 1.2.11 (support for passing a CA file for SSL certificate verification via the –ssl-ca-file flag). ### Fixed - Fixed the hanging HTTP call with `ner_duckling_http` pipeline. - Fixed text processing of `intent` attribute inside `CountVectorFeaturizer`. - Fixed `argument of type 'NoneType' is not iterable` when using `rasa shell`, `rasa interactive` / `rasa run` ## [1.3.8] - 2019-10-08 ### Changed - Policies now only get imported if they are actually used. This removes TensorFlow warnings when starting Rasa X ### Fixed - Fixed error `Object of type 'MaxHistoryTrackerFeaturizer' is not JSON serializable` when running `rasa train core` - Default channel `send_` methods no longer support kwargs as they caused issues in incompatible channels ## [1.3.7] - 2019-09-27 ### Fixed - re-added TLS, SRV dependencies for PyMongo - socketio can now be run without turning on the `--enable-api` flag - MappingPolicy no longer fails when the latest action doesn’t have a policy ## [1.3.6] - 2019-09-21 ### Added - Added the ability for users to specify a conversation id to send a message to when using the `RasaChat` input channel. ## [1.3.5] - 2019-09-20 ### Fixed - Fixed issue where `rasa init` would fail without spaCy being installed ## [1.3.4] - 2019-09-20 ### Added - Added the ability to set the `backlog` parameter in Sanics `run()` method using the `SANIC_BACKLOG` environment variable. This parameter sets the number of unaccepted connections the server allows before refusing new connections. A default value of 100 is used if the variable is not set. - Status endpoint (`/status`) now also returns the number of training processes currently running ### Fixed - Added the ability to properly deal with spaCy `Doc`-objects created on empty strings as discussed [here](https://github.com/RasaHQ/rasa/issues/4445). Only training samples that actually bear content are sent to `self.nlp.pipe` for every given attribute. Non-content-bearing samples are converted to empty `Doc`-objects. The resulting lists are merged with their preserved order and properly returned. - asyncio warnings are now only printed if the callback takes more than 100ms (up from 1ms). - `agent.load_model_from_server` no longer affects logging. ### Changed - The endpoint `POST /model/train` no longer supports specifying an output directory for the trained model using the field `out`. Instead you can choose whether you want to save the trained model in the default model directory (`models`) (default behavior) or in a temporary directory by specifying the `save_to_default_model_directory` field in the training request. ## [1.3.3] - 2019-09-13 ### Fixed - Added a check to avoid training CountVectorizer for a particular attribute of a message if no text is provided for that attribute across the training data. - Default one-hot representation for label featurization inside `EmbeddingIntentClassifier` if label features don’t exist. - Policy ensemble no longer incorrectly wrings “missing mapping policy” when mapping policy is present. - “test” from `utter_custom_json` now correctly saved to tracker when using telegram channel ### Removed - Removed computation of `intent_spacy_doc`. As a result, none of the spacy components process intents now. ## [1.3.2] - 2019-09-10 ### Fixed - SQL tracker events are retrieved ordered by timestamps. This fixes interactive learning events being shown in the wrong order. ## [1.3.1] - 2019-09-09 ### Changed - Pin gast to == 0.2.2 ## [1.3.0] - 2019-09-05 ### Added - Added option to persist nlu training data (default: False) - option to save stories in e2e format for interactive learning - bot messages contain the `timestamp` of the `BotUttered` event, which can be used in channels - `FallbackPolicy` can now be configured to trigger when the difference between confidences of two predicted intents is too narrow - experimental training data importer which supports training with data of multiple sub bots. Please see the [docs](/content/docs/rasa/api/training-data-importers/index.html) for more information. - throw error during training when triggers are defined in the domain without `MappingPolicy` being present in the policy ensemble - The tracker is now available within the interpreter’s `parse` method, giving the ability to create interpreter classes that use the tracker state (e.g. slot values) during the parsing of the message. More details on motivation of this change see issues/3015. - add example bot `knowledgebasebot` to showcase the usage of `ActionQueryKnowledgeBase` - `softmax` starspace loss for both `EmbeddingPolicy` and `EmbeddingIntentClassifier` - `balanced` batching strategy for both `EmbeddingPolicy` and `EmbeddingIntentClassifier` - `max_history` parameter for `EmbeddingPolicy` - Successful predictions of the NER are written to a file if `--successes` is set when running `rasa test nlu` - Incorrect predictions of the NER are written to a file by default. You can disable it via `--no-errors`. - New NLU component `ResponseSelector` added for the task of response selection - Message data attribute can contain two more keys - `response_key`, `response` depending on the training data - New action type implemented by `ActionRetrieveResponse` class and identified with `response_` prefix - Vocabulary sharing inside `CountVectorsFeaturizer` with `use_shared_vocab` flag. If set to True, vocabulary of corpus is shared between text, intent and response attributes of the message - Added an option to share the hidden layer weights of text input and label input inside `EmbeddingIntentClassifier` using the flag `share_hidden_layers` - New type of training data file in NLU which stores response phrases for response selection task. - Add flags `intent_split_symbol` and `intent_tokenization_flag` to all `WhitespaceTokenizer`, `JiebaTokenizer` and `SpacyTokenizer` - Added evaluation for response selector. Creates a report `response_selection_report.json` inside `--out` directory. - argument `--config-endpoint` to specify the URL from which `rasa x` pulls the runtime configuration (endpoints and credentials) - `LockStore` class storing instances of `TicketLock` for every `conversation_id` - environment variables `SQL_POOL_SIZE` (default: 50) and `SQL_MAX_OVERFLOW` (default: 100) can be set to control the pool size and maximum pool overflow for `SQLTrackerStore` when used with the `postgresql` dialect - Add a `bot_challenge` intent and a `utter_iamabot` action to all example projects and the rasa init bot. - Allow sending attachments when using the socketio channel - `rasa data validate` will fail with a non-zero exit code if validation fails ### Changed - added character-level `CountVectorsFeaturizer` with empirically found parameters into the `supervised_embeddings` NLU pipeline template - NLU evaluations now also stores its output in the output directory like the core evaluation - show warning in case a default path is used instead of a provided, invalid path - compare mode of `rasa train core` allows the whole core config comparison, naming style of models trained for comparison is changed (this is a breaking change) - pika keeps a single connection open, instead of open and closing on each incoming event - `RasaChatInput` fetches the public key from the Rasa X API. The key is used to decode the bearer token containing the conversation ID. This requires `rasa-x>=0.20.2`. - more specific exception message when loading custom components depending on whether component’s path or class name is invalid or can’t be found in the global namespace - change priorities so that the `MemoizationPolicy` has higher priority than the `MappingPolicy` - substitute LSTM with Transformer in `EmbeddingPolicy` - `EmbeddingPolicy` can now use `MaxHistoryTrackerFeaturizer` - non-zero `evaluate_on_num_examples` in `EmbeddingPolicy` and `EmbeddingIntentClassifier` is the size of holdout validation set that is excluded from training data - defaults parameters and architectures for both `EmbeddingPolicy` and `EmbeddingIntentClassifier` are changed (this is a breaking change) - evaluation of NER does not include ‘no-entity’ anymore - `--successes` for `rasa test nlu` is now boolean values. If set incorrect/successful predictions are saved in a file. - `--errors` is renamed to `--no-errors` and is now a boolean value. By default incorrect predictions are saved in a file. If `--no-errors` is set predictions are not written to a file. - Remove `label_tokenization_flag` and `label_split_symbol` from `EmbeddingIntentClassifier`. Instead move these parameters to `Tokenizers`. - Process features of all attributes of a message, i.e. - text, intent and response inside the respective component itself. For e.g. - intent of a message is now tokenized inside the tokenizer itself. - Deprecate `as_markdown` and `as_json` in favor of `nlu_as_markdown` and `nlu_as_json` respectively. - pin python-engineio >= 3.9.3 - update python-socketio req to >= 4.3.1 ### Fixed - `rasa test nlu` with a folder of configuration files - `MappingPolicy` standard featurizer is set to `None` - Removed `text` parameter from send_attachment function in slack.py to avoid duplication of text output to slackbot - server `/status` endpoint reports status when an NLU-only model is loaded ### Removed - Removed `--report` argument from `rasa test nlu`. All output files are stored in the `--out` directory. ## [1.2.11] - 2019-10-09 ### Added - Support for passing a CA file for SSL certificate verification via the –ssl-ca-file flag ## [1.2.10] - 2019-10-08 ### Added - Added support for RabbitMQ TLS authentication. The following environment variables need to be set: `RABBITMQ_SSL_CLIENT_CERTIFICATE` - path to the SSL client certificate (required) `RABBITMQ_SSL_CLIENT_KEY` - path to the SSL client key (required) `RABBITMQ_SSL_CA_FILE` - path to the SSL CA file (optional, for certificate verification) `RABBITMQ_SSL_KEY_PASSWORD` - SSL private key password (optional) - Added ability to define the RabbitMQ port using the `port` key in the `event_broker` endpoint config. ## [1.2.9] - 2019-09-17 ### Fixed - Correctly pass SSL flag values to x CLI command ## [1.2.8] - 2019-09-10 ### Fixed - SQL tracker events are retrieved ordered by timestamps. This fixes interactive learning events being shown in the wrong order. Backport of `1.3.2` patch (PR #4427). ## [1.2.7] - 2019-09-02 ### Fixed - Added `query` dictionary argument to `SQLTrackerStore` which will be appended to the SQL connection URL as query parameters. ## [1.2.6] - 2019-09-02 ### Fixed - fixed bug that occurred when sending template `elements` through a channel that doesn’t support them ## [1.2.5] - 2019-08-26 ### Added - SSL support for `rasa run` command. Certificate can be specified using `--ssl-certificate` and `--ssl-keyfile`. ### Fixed - made default augmentation value consistent across repo - `'/restart'` will now also restart the bot if the tracker is paused ## [1.2.4] - 2019-08-23 ### Fixed - the `SocketIO` input channel now allows access from other origins (fixes `SocketIO` channel on Rasa X) ## [1.2.3] - 2019-08-15 ### Changed - messages with multiple entities are now handled properly with e2e evaluation - `data/test_evaluations/end_to_end_story.md` was rewritten in the restaurantbot domain ## [1.2.2] - 2019-08-07 ### Fixed - `UserUttered` events always got the same timestamp ## [1.2.1] - 2019-08-06 ### Added - Docs now have an `EDIT THIS PAGE` button ### Fixed - `Flood control exceeded` error in Telegram connector which happened because the webhook was set twice ## [1.2.0] - 2019-08-01 ### Added - add root route to server started without `--enable-api` parameter - add `--evaluate-model-directory` to `rasa test core` to evaluate models from `rasa train core -c ` - option to send messages to the user by calling `POST /conversations/{conversation_id}/execute` ### Changed - `Agent.update_model()` and `Agent.handle_message()` now work without needing to set a domain or a policy ensemble - Update pytype to `2019.7.11` - new event broker class: `SQLProducer`. This event broker is now used when running locally with Rasa X - API requests are no longer logged to `rasa_core.log` by default in order to avoid problems when running on OpenShift (use `--log-file rasa_core.log` to retain the old behavior) - `metadata` attribute added to `UserMessage` ### Fixed - `rasa test core` can handle compressed model files - rasa can handle story files containing multi-line comments - template will retain { if escaped with {. e.g. {{“foo”: {bar}}} will result in {“foo”: “replaced value”} ## [1.1.8] - 2019-07-25 ### Added - `TrainingFileImporter` interface to support customizing the process of loading training data - fill slots for custom templates ### Changed - `Agent.update_model()` and `Agent.handle_message()` now work without needing to set a domain or a policy ensemble - update pytype to `2019.7.11` ### Fixed - interactive learning bug where reverted user utterances were dumped to training data - added timeout to terminal input channel to avoid freezing input in case of server errors - fill slots for image, buttons, quick_replies and attachments in templates ## [1.1.7] - 2019-07-18 ### Added - added optional pymongo dependencies `[tls, srv]` to `requirements.txt` for better mongodb support - `case_sensitive` option added to `WhiteSpaceTokenizer` with `true` as default. ### Fixed - validation no longer throws an error during interactive learning - fixed wrong cleaning of `use_entities` in case it was a list and not `True` - updated the server endpoint `/model/parse` to handle also messages with the intent prefix - fixed bug where “No model found” message appeared after successfully running the bot - debug logs now print to `rasa_core.log` when running `rasa x -vv` or `rasa run -vv` ## [1.1.6] - 2019-07-12 ### Added - rest channel supports setting a message’s input_channel through a field `input_channel` in the request body ### Changed - recommended syntax for empty `use_entities` and `ignore_entities` in the domain file has been updated from `False` or `None` to an empty list (`[]`) ### Fixed - `rasa run` without `--enable-api` does not require a local model anymore - using `rasa run` with `--enable-api` to run a server now prints “running Rasa server” instead of “running Rasa Core server” - actions, intents, and utterances created in `rasa interactive` can no longer be empty ## [1.1.5] - 2019-07-10 ### Added - debug logging now tells you which tracker store is connected - the response of `/model/train` now includes a response header for the trained model filename - `Validator` class to help develop by checking if the files have any errors - project’s code is now linted using flake8 - `info` log when credentials were provided for multiple channels and channel in `--connector` argument was specified at the same time - validate export paths in interactive learning ### Changed - deprecate `rasa.core.agent.handle_channels(...)`. Please use `rasa.run(...)` or `rasa.core.run.configure_app` instead. - `Agent.load()` also accepts `tar.gz` model file ### Removed - revert the stripping of trailing slashes in endpoint URLs since this can lead to problems in case the trailing slash is actually wanted - starter packs were removed from Github and are therefore no longer tested by the Travis script ### Fixed - all temporal model files are now deleted after stopping the Rasa server - `rasa shell nlu` now outputs unicode characters instead of `\uxxxx` codes - fixed PUT /model with model_server by deserializing the model_server to EndpointConfig. - `x in AnySlotDict` is now `True` for any `x`, which fixes empty slot warnings in interactive learning - `rasa train` now also includes NLU files in other formats than the Rasa format - `rasa train core` no longer crashes without a `--domain` arg - `rasa interactive` now looks for endpoints in `endpoints.yml` if no `--endpoints` arg is passed - custom files, e.g. custom components and channels, load correctly when using the command line interface - `MappingPolicy` now works correctly when used as part of a PolicyEnsemble ## [1.1.4] - 2019-06-18 ### Added - unfeaturize single entities - added agent readiness check to the `/status` resource ### Changed - removed leading underscore from name of ‘_create_initial_project’ function. ### Fixed - fixed bug where facebook quick replies were not rendering - take FB quick reply payload rather than text as input - fixed bug where training_data path in metadata.json was an absolute path ## [1.1.3] - 2019-06-14 ### Fixed - fixed any inconsistent type annotations in code and some bugs revealed by type checker ## [1.1.2] - 2019-06-13 ### Fixed - fixed duplicate events appearing in tracker when using a PostgreSQL tracker store ## [1.1.1] - 2019-06-13 ### Fixed - fixed compatibility with Rasa SDK - bot responses can contain `custom` messages besides other message types ## [1.1.0] - 2019-06-13 ### Added - nlu configs can now be directly compared for performance on a dataset in `rasa test nlu` ### Changed - update the tracker in interactive learning through reverting and appending events instead of replacing the tracker - `POST /conversations/{conversation_id}/tracker/events` supports a list of events ### Fixed - fixed creation of `RasaNLUHttpInterpreter` - form actions are included in domain warnings - default actions, which are overridden by custom actions and are listed in the domain are excluded from domain warnings - SQL `data` column type to `Text` for compatibility with MySQL - non-featurizer training parameters don’t break SklearnPolicy anymore ## [1.0.9] - 2019-06-10 ### Changed - revert PR #3739 (as this is a breaking change): set `PikaProducer` and `KafkaProducer` default queues back to `rasa_core_events` ## [1.0.8] - 2019-06-10 ### Added - support for specifying full database URLs in the `SQLTrackerStore` configuration - maximum number of predictions can be set via the environment variable `MAX_NUMBER_OF_PREDICTIONS` (default is 10) ### Changed - default `PikaProducer` and `KafkaProducer` queues to `rasa_production_events` - exclude unfeaturized slots from domain warnings ### Fixed - loading of additional training data with the `SkillSelector` - strip trailing slashes in endpoint URLs ## [1.0.7] - 2019-06-06 ### Added - added argument `--rasa-x-port` to specify the port of Rasa X when running Rasa X locally via `rasa x` ### Fixed - slack notifications from bots correctly render text - fixed usage of `--log-file` argument for `rasa run` and `rasa shell` - check if correct tracker store is configured in local mode ## [1.0.6] - 2019-06-03 ### Fixed - fixed backwards incompatible utils changes ## [1.0.5] - 2019-06-03 ### Fixed - fixed spaCy being a required dependency (regression) ## [1.0.4] - 2019-06-03 ### Added - automatic creation of index on the `sender_id` column when using an SQL tracker store. If you have existing data and you are running into performance issues, please make sure to add an index manually using `CREATE INDEX event_idx_sender_id ON events (sender_id);`. ### Changed - NLU evaluation in cross-validation mode now also provides intent/entity reports, confusion matrix, etc. ## [1.0.3] - 2019-05-30 ### Fixed - non-ascii characters render correctly in stories generated from interactive learning - validate domain file before usage, e.g. print proper error messages if domain file is invalid instead of raising errors ## [1.0.2] - 2019-05-29 ### Added - added `domain_warnings()` method to `Domain` which returns a dict containing the diff between supplied {actions, intents, entities, slots} and what’s contained in the domain ### Fixed - fix lookup table files failed to load issues/3622 - buttons can now be properly selected during cmdline chat or when in interactive learning - set slots correctly when events are added through the API - mapping policy no longer ignores NLU threshold - mapping policy priority is correctly persisted ## [1.0.1] - 2019-05-21 ### Fixed - updated installation command in docs for Rasa X ## [1.0.0] - 2019-05-21 ### Added - added arguments to set the file paths for interactive training - added quick reply representation for command-line output - added option to specify custom button type for Facebook buttons - added tracker store persisting trackers into a SQL database (`SQLTrackerStore`) - added rasa command line interface and API - Rasa HTTP training endpoint at `POST /jobs`. This endpoint will train a combined Rasa Core and NLU model - `ReminderCancelled(action_name)` event to cancel given action_name reminder for the current user - Rasa HTTP intent evaluation endpoint at `POST /intentEvaluation`. This endpoint performs an intent evaluation of a Rasa model - option to create template for new utterance action in interactive learning - you can now choose actions previously created in the same session in interactive learning - add formatter ‘black’ - channel-specific utterances via the `- "channel":` key in utterance templates - arbitrary json messages via the `- "custom":` key in utterance templates and via `utter_custom_json()` method in custom actions - support to load sub skills (domain, stories, nlu data) - support to select which sub skills to load through `import` section in `config.yml` - support for spaCy 2.1 - a model for an agent can now also be loaded from a remote storage - log level can be set via the environment variable `LOG_LEVEL` - add `--store-uncompressed` to train command to not compress Rasa model - log level of libraries, such as tensorflow, can be set via environment variable `LOG_LEVEL_LIBRARIES` - if no spaCy model is linked upon building a spaCy pipeline, an appropriate error message is now raised with instructions for linking one ### Changed - renamed all CLI parameters containing any `_` to use dashes `-` instead (GNU standard) - renamed `rasa_core` package to `rasa.core` - for interactive learning only include manually annotated and ner_crf entities in nlu export - made `message_id` an additional argument to `interpreter.parse` - changed removing punctuation logic in `WhitespaceTokenizer` - `training_processes` in the Rasa NLU data router have been renamed to `worker_processes` - created a common utils package `rasa.utils` for nlu and core, common methods like `read_yaml` moved there - removed `--num_threads` from run command (server will be asynchronous but running in a single thread) - the `_check_token()` method in `RasaChat` now authenticates against `/auth/verify` instead of `/user` - removed `--pre_load` from run command (Rasa NLU server will just have a maximum of one model and that model will be loaded by default) - changed file format of a stored trained model from the Rasa NLU server to `tar.gz` - train command uses fallback config if an invalid config is given - test command now compares multiple models if a list of model files is provided for the argument `--model` - Merged rasa.core and rasa.nlu server into a single server. See swagger file in `docs/_static/spec/server.yaml` for available endpoints. - `utter_custom_message()` method in rasa_core_sdk has been renamed to `utter_elements()` - updated dependencies. as part of this, models for spacy need to be reinstalled for 2.1 (from 2.0) - make sure all command line arguments for `rasa test` and `rasa interactive` are actually used, removed arguments that were not used at all (e.g. `--core` for `rasa test`) ### Removed - removed possibility to execute `python -m rasa_core.train` etc. (e.g. scripts in `rasa.core` and `rasa.nlu`). Use the CLI for rasa instead, e.g. `rasa train core`. - removed `_sklearn_numpy_warning_fix` from the `SklearnIntentClassifier` - removed `Dispatcher` class from core - removed projects: the Rasa NLU server now has a maximum of one model at a time loaded.