Migration Guide

This page contains information about changes between major versions and how you can migrate from one version to another.

0.13.x to 0.14.0

Warning

This is a release breaking backwards compatibility. action_restart will not work with your old models, as this is now part of the MappingPolicy. Please make sure to retrain a model before trying to use it with this improved version.

General

  • The MappingPolicy is now included in default_config.yml. If you are using a custom policy configuration make sure to update it appropriately.

Function Naming

  • renamed train_dialogue_model to train. Please use train from now on.
  • renamed rasa_core.evaluate to rasa_core.test. Please use test from now on.

0.12.x to 0.13.0

Warning

Python 2 support has now been completely dropped: to upgrade to this version you must use Python 3. As always, make sure you retrain your models when switching to this version

General

  • Support for Python 2 has now been completely removed from Rasa Core, please upgrade to Python 3.5 or 3.6 to continue using the software
  • If you were using the deprecated intent/entity format (_intent[entity1=val1, entity=val2]), then you will have to update your training data to the standard format (/intent{"entity1": val1, "entity2": val2} because it is no longer supported

0.11.x to 0.12.0

Warning

This is major new version with a lot of changes under the hood as well as on the API level. Please take a careful look at the mentioned before updating. Please make sure to retrain your models when switching to this version.

Train script

  • You must pass a policy config flag with -c/--config now when training a model, see Configuring polices using a configuration file. There is a default config file in the documentation Default configuration.
  • Interactive learning is now started with python -m rasa_core.train interactive rather than the --interactive flag
  • All policy configuration related flags have been removed (--epochs, --max_history, --validation_split, --batch_size, --nlu_threshold, --core_threshold, --fallback_action_name), specify these in the policy config file instead, see Configuring polices using a configuration file

Visualisation script

Evaluation script

  • The --output flag now takes one argument: the name of the folder any files generated from the script should be written to
  • The --failed flag was removed, as this is part of the --output flag now

Forms

  • Forms were completely reworked, please follow Slot Filling for instructions how to use them.
  • FormField class and its subclasses were removed, overwrite FormAction.slot_mapping() method to specify the mapping between user input and requested slot in the form utilizing helper methods FormAction.from_entity(...), FormAction.from_intent(...) and FormAction.from_text(...)
  • stories for forms need to be written differently, it is recommended to use interactive learning to create form stories
  • functionality of FormAction.get_other_slots(...) was moved to FormAction.extract_other_slots(...)
  • functionality of FormAction.get_requested_slot(...) was moved to FormAction.extract_requested_slot(...)
  • overwrite FormAction.validate(...) method to validate user input against the slot requested by the form

0.10.x to 0.11.0

Warning

This is major new version with a lot of changes under the hood as well as on the API level. Please take a careful look at the mentioned before updating. Please make sure to retrain your models when switching to this version.

General

Note

TL;DR these are the most important surface changes. But if you have a second please take a minute to read all of them.

  • If you have custom actions, you now need to run a separate server to execute them. If your actions are written in python (in a file called actions.py) you can do this by running python -m rasa_core_sdk.endpoint --actions actions and specifying the action endpoint in the endpoints.yml For more information please read Actions.
  • For your custom actions, the imports have changed from from rasa_core.actions import Action to from rasa_core_sdk import Action and from from rasa_core.events import * to from rasa_core_sdk.events import *
  • The actions list in the domain now needs to always contain the actions names instead of the classpath (e.g. change actions.ActionExample to action_example)
  • utter templates that should be used as actions, now need to start with utter_, otherwise the bot won’t be able to find the action

HTTP Server endpoints

  • We removed /parse and /continue endpoints used for running actions remotely. This has been replaced by the action server that allows you to run your action code in any language. There are no replacement endpoints for these two, as the flow of information has been changed: Instead of you calling Rasa Core to update the tracker and receive the next action to be executed, Rasa Core will call your action server once it predicted an action. More information can be found in the updated docs for Actions.

Webhooks

  • The endpoints for the webhooks changed. All webhooks are now at /webhooks/CHANNEL_NAME/webhook. For example, the webhook to receive facebook messages on a local instance is now http://localhost:5005/webhooks/facebook/webhook.

  • format of the credentials.yml used in the run and server scripts has changed to allow for multiple channels in one file:

    The new format now contains the channels name first, e.g. for facebook:

    facebook:
  verify: "rasa-bot"
  secret: "3e34709d01ea89032asdebfe5a74518"
  page-access-token: "EAAbHPa7H9rEBAAuFk4Q3gPKbDedQnx4djJJ1JmQ7CAqO4iJKrQcNT0wtD"

Changes to Input and Output Channels

  • ConsoleOutputChannel and ConsoleInputChannel have been removed. Either use the run script to run your bot on the cmdline, or adapt the serve_application function to run from a python script.

  • rasa_core.channels.direct output channel package removed. CollectingOutputChannel moved to rasa_core.channels.channel

  • HttpInputComponent renamed to InputChannel & moved to rasa_core.channels.channel.InputChannel

  • If you wrote your own custom input channel, make sure to inherit from InputChannel instead of HttpInputComponent.

  • CollectingOutput channel will no properly collect events for images, buttons, and attachments. The content of the collected messages has changed, data is now called buttons.

  • removed package rasa_core.channels.rest, please use rasa_core.channels.RestInput instead

  • remove file input channel rasa_core.channels.file.FileInputChannel

  • signature of agent.handle_channel got renamed and the signature changed. here is an up to date example:

    from rasa_core.channels.facebook import FacebookInput

input_channel = FacebookInput(fb_verify="VERIFY",
                              fb_secret="SECRET",
                              fb_access_token="ACCESS_TOKEN")
agent.handle_channels([input_channel], port=5005, serve_forever=True)

  • If you wrote your own custom output channel, make sure to split messages on double new lines if you like (the InputChannel you inherit from doesn’t do this anymore), e.g.:

    def send_text_message(self, recipient_id, message):
    # type: (Text, Text) -> None
    """Send a message through this channel."""

    for message_part in message.split("\n\n"):
      # self.send would be the actual communication to e.g. facebook
      self.send(recipient_id, message_part)

0.9.x to 0.10.0

Warning

This is a release breaking backwards compatibility. You can no longer load old models with this version, due to the addition of the default action ActionDefaultFallback. Please make sure to retrain your model before using this version

There have been some API changes to classes and methods:

  • if you use dispatcher.utter_template or dispatcher.utter_button_template in your custom actions run code, they now need the tracker as a second argument, e.g. dispatcher.utter_template("utter_greet", tracker)

  • all input and output channels should have a name. If you are using a custom channel, make sure to implement a class method that returns the name. The name needs to be added to the input channel and the output channel. You can find examples in rasa_core.channels.direct.CollectingOutputChannel:

    @classmethod
def name(cls):
    """Every channel needs a name"""
    return "collector"

  • the RasaNLUHttpInterpreter when created now needs to be passed an instance of EndpointConfig instead of server and token, e.g.:

    from rasa_core.utils import EndpointConfig

endpoint = EndpointConfig("http://localhost:500", token="mytoken")
interpreter = RasaNLUHttpInterpreter("mymodelname", endpoint)

0.8.x to 0.9.0

Warning

This is a release breaking backwards compatibility. Unfortunately, it is not possible to load previously trained models (as the stored file formats have changed as well as the configuration and metadata). Please make sure to retrain a model before trying to use it with this improved version.

  • loading data should be done either using:

    from rasa_core import training

training_data = training.load_data(...)

    or using an agent instance:

    training_data = agent.load_data(...)
agent.train(training_data, ...)

    It is deprecated to pass the training data file directly to agent.train. Instead, the data should be loaded in one of the above ways and then passed to train.

  • ScoringPolicy got removed and replaced by AugmentedMemoizationPolicy which is similar, but is able to match more states to states it has seen during trainer (e.g. it is able to handle slots better)

  • if you use custom featurizers, you need to pass them directly to the policy that should use them. This allows the policies to use different featurizers. Passing a featurizer is optional. Accordingly, the max_history parameter moved to that featurizer:

    from rasa_core.featurizers import (MaxHistoryTrackerFeaturizer,
                                   BinarySingleStateFeaturizer)

featurizer = MaxHistoryTrackerFeaturizer(BinarySingleStateFeaturizer(),
                                         max_history=5)

agent = Agent(domain_file,
              policies=[MemoizationPolicy(max_history=5),
                        KerasPolicy(featurizer)])

    If no featurizer is passed during policy creation, the policies default featurizer will be used. The MemoizationPolicy allows passing in the max_history parameter directly, without creating a featurizer.

  • the ListSlot now stores a list of entities (with the same name) present in an utterance

0.7.x to 0.8.0

  • Credentials for the facebook connector changed. Instead of providing:

    # OLD FORMAT
verify: "rasa-bot"
secret: "3e34709d01ea89032asdebfe5a74518"
page-tokens:
  1730621093913654: "EAAbHPa7H9rEBAAuFk4Q3gPKbDedQnx4djJJ1JmQ7CAqO4iJKrQcNT0wtD"

    you should now pass the configuration parameters like this:

    # NEW FORMAT
verify: "rasa-bot"
secret: "3e34709d01ea89032asdebfe5a74518"
page-access-token: "EAAbHPa7H9rEBAAuFk4Q3gPKbDedQnx4djJJ1JmQ7CAqO4iJKrQcNT0wtD"

    As you can see, the new facebook connector only supports a single page. Same change happened to the in code arguments for the connector which should be changed to:

    from rasa_core.channels.facebook import FacebookInput

FacebookInput(
      credentials.get("verify"),
      credentials.get("secret"),
      credentials.get("page-access-token"))

  • Story file format changed from * _intent_greet[name=Rasa] to * intent_greet{"name": "Rasa"} (old format is still supported but deprecated). Instead of writing:

    ## story_07715946                     <!-- name of the story - just for debugging -->
* _greet
   - action_ask_howcanhelp
* _inform[location=rome,price=cheap]
   - action_on_it                     <!-- user utterance, in format _intent[entities] -->
   - action_ask_cuisine

    The new format looks like this:

    ## story_07715946                     <!-- name of the story - just for debugging -->
* greet
   - action_ask_howcanhelp
* inform{"location": "rome", "price": "cheap"}
   - action_on_it                     <!-- user utterance, in format _intent[entities] -->
   - action_ask_cuisine

Have questions or feedback?

We have a very active support community on Rasa Community Forum that is happy to help you with your questions. If you have any feedback for us or a specific suggestion for improving the docs, feel free to share it by creating an issue on Rasa Core GitHub repository.