Change Log¶

Added¶

Changed¶

Removed¶

Fixed¶

• force prediction of action_listen after fallback action (this removes the need for a fallback story in your training data)

Fixed¶

• force fallback policy to be invoked over memoization

Fixed¶

• fixed fallback policy data generation

Fixed¶

• handling of max history configuration in policies
• fixed instantiation issues of fallback policy

Fixed¶

• fixed evaluation script
• fixed story file loading (previously some story files with checkpoints could create wrong training data)
• improved speed of data loading

Fixed¶

• added token auth to all endpoints of the core server

Fixed¶

• fix handling of max_history parameter in AugmentedMemoizationPolicy

Fixed¶

• persistence of training data collected during online learning if default file path is used
• the agent() method used in some rasa_core.server endpoints is re-run at every new call of the ensure_loaded_agent decorator
• fixed OR usage of intents

Added¶

• supported loading training data from a folder - loads all stories from all files in that directory
• parameter to specify NLU project when instantiating a RasaNLUInterpreter
• simple /respond endpoint to get bot response to a user message
• /conversations endpoint for listing sender ids of running conversations
• added a Mattermost channel that allows Rasa Core to communicate via a Mattermost app
• added a Twilio channel that allows Rasa Core to communicate via SMS
• FallbackPolicy for executing a default message if NLU or core model confidence is low.
• FormAction class to make it easier to collect multiple pieces of information with fewer stories.
• Dockerfile for rasa_core.server with a dialogue and Rasa NLU model

Changed¶

• moved server from klein to flask
• updated dependency fbmessenger from 4.3.1 to 5.0.0
• updated Rasa NLU to 0.12.x
• updated all the dependencies to the latest versions

Fixed¶

• List slot is now populated with a list
• Slack connector: slack_channel kwarg is used to send messages either back to the user or to a static channel
• properly log to a file when using the run script
• documentation fix on stories

Fixed¶

• pin rasa nlu version to 0.11.4 (0.12.x only works with master)

Fixed¶

• updated google analytics docs survey code

Fixed¶

• pin pykwalify<=1.6.0 as update to 1.6.1 breaks compatibility

Fixed¶

• pin fbmessenger version to avoid major update

Added¶

• script to reload a dumped trackers state and to continue the conversation at the end of the stored dialogue

Changed¶

• minor updates to dependencies

Fixed¶

• fixed datetime serialisation of reminder event

Fixed¶

• removed deque to support python 3.5
• Documentation improvements to tutorials
• serialisation of date time value for ReminderScheduled event

Added¶

• --debug and --verbose flags to scripts (train.py, run.py, server.py) to set the log level
• support for story cycles when using checkpoints
• added a new machine learning policy SklearnPolicy that uses an sklearn classifier to predict actions (logistic regression by default)
• warn if action emits events when using a model that it did never emit in any of the stories the model was trained on
• support for event pushing and endpoints to retrieve the tracker state from the server
• Timestamp to every event
• added a Slack channel that allows Rasa Core to communicate via a Slack app
• added a Telegram channel that allows Rasa Core to communicate via a Telegram bot

Changed¶

• rewrite of the whole FB connector: replaced pymessenger library with fbmessenger
• story file utterance format changed from * _intent_greet[name=Rasa] to * intent_greet{"name": "Rasa"} (old format is still supported but deprecated)
• persist action names in domain during model persistence
• improved travis build speed by not using miniconda
• don’t fail with an exception but with a helpful error message if an utterance template contains a variable that can not be filled
• domain doesn’t fail on unknown actions but emits a warning instead. this is to support reading logs from older conversation if one recently removed an action from the domain

Fixed¶

• proper evaluation of stories with checkpoints
• proper visualisation of stories with checkpoints
• fixed float slot min max value handling
• fixed non integer feature decoding, e.g. used for memoization policy
• properly log to specified file when starting Rasa Core server
• properly calculate offset of last reset event after loading tracker from tracker store
• UserUtteranceReverted action incorrectly triggered actions to be replayed

Fixed¶

• visualisation using Networkx version 2.x
• add output about line of failing intent when parsing story files

Fixed¶

• Pypi readme rendering

Added¶

• log bot utterances to tracker

Fixed¶

• documentation improvements in README
• renamed interpreter argument to rasa core server

Fixed¶

• moodbot example train command in docs

Changed¶

• “sender_id” (and “DEFAULT_SENDER_ID”) keyword consistency issue #56

Fixed¶

• improved moodbot example - more nlu examples as well as better fitting of dialogue model

Changed¶

• added method to tracker to retrieve the latest entities #68

Added¶

• parameter to specify font size when rendering story visualization

Fixed¶

• fixed documentation of story visualization

Added¶

• added facebook bot example
• added support for conditional checkpoints. a checkpoint can be restricted to only allow one to use it if certain slots are set. see docs for details
• utterance templates in domain yaml support buttons and images
• validate domain yaml and raise exception on invalid file
• run script to load models and handle messages from an input channel

Changed¶

• small dropout in standard keras model to decrease reliance on exact intents
• a LOT of documentation improvements

Fixed¶

• fixed http error if action listen is not confirmed. #42

Fixed¶

• issues with restart events. They created wrong a messed up history leading to wrong predictions

Added¶

• support for Rasa Core usage as a server with remote action execution

Changed¶

• switched to max code line length 80
• removed action id - use action.name() instead. if an action implementation overrides the name, it should include the action_ prefix (as it is not automatically added anymore)
• renamed rasa_dm.util to rasa_dm.utils
• renamed the whole package to rasa_core (so rasa_dm is gone!)
• renamed Reminder attribute id to name
• a lot of documentation improvements. docs are now at https://core.rasa.com
• use hashing when writing memorized turns into persistence - requires retraining of all models that are trained with a version prior to this
• changed agent.handle_message(...) interface for easier usage

Added¶

• support for multiple policies (e.g. one memoization and a Keras policy at the same time)
• loading domains from yaml files instead of defining them with python code
• added an api layer (called Agent) for you to use for 95% of the things you want to do (training, persistence, loading models)
• support for reminders

Changed¶

• large refactoring of code base

Added¶

• ScoringPolicy added to policy implementations (less strict than standard default policy)
• RasaNLUInterpreter to run a nlu instance within dm (instead of using the http interface)
• more tests

Changed¶

• UserUtterance now holds the complete parse data from nlu (e.g. to access attributes other than entities or intent)
• Turn has a reference to a UserUtterance instead of directly storing intent & entities (allows access to other data)
• Simplified interface of output channels
• order of actions in the DefaultPolicy in possible_actions (ActionListen now always has index 0)

Fixed¶

• RedisTrackerStore checks if tracker is stored before accessing it (otherwise a None access exception is thrown)
• RegexInterpreter checks if the regex actually matches the message instead of assuming it always does
• str implementation for all events
• Controller can be started without an input channel (e.g. messages need to be fed into the queue manually)