#Rasa chitchat download#

You need to use the / symbol to separate the main intent and its sub-intent. This helps a lot when building for small talk as it reduces overhead in your stories.

In the old version, retrieval intent is an experimental feature in which an intent can be categorized into smaller sub-intents. nlu: - intent: greet examples: - text: | hi metadata: sentiment: neutral - text: | hello Retrieval intents You can declare the metadata individually for each example. As a result, all of the examples contain the metadata. In the example given above, metadata is declared at the intent level. For example, you can declare it as follows: nlu: - intent: greet metadata: sentiment: neutral examples: - text: | hi - text: | hello metadata is accessible by your custom components. In fact, you can now declare additional metadata which contains arbitrary key-value pairs. NLUįor NLU training data, the new structure for version 2.0 is as follows: version: '2.0' nlu: - intent: greet examples: | - Hey - Hi - hello - intent: goodbye examples: | - Goodbye - bye bye NLU metadata You can delete this as a source file.One of the major breaking changes in version 2.0 is the training data format. Your specific chit-chat source is listed as a file, with the selected personality name. Select your KB, and navigate to the Settings page. To ensure the ranker understands that this is chit-chat, add the metadata key/value pair 'Editorial: chitchat', as seen in the following image: When you add any new chit-chat QnA, it gets added to your Editorial source. Ensure that you are not duplicating a QnA pair that is already covered in the chit-chat set. You can add a new chit-chat QnA pair that is not in the predefined data set. Add additional chit-chat questions and answers To view the metadata, select View Options in the toolbar, then select Show metadata. You can now add altered questions or edit the responses, just like with any other source. When you edit your KB, you will see a new source for chit-chat, based on the personality you selected.

#Rasa chitchat download#

Make sure not to edit the format or the metadata when you download and upload the file.Įdit your chit-chat questions and answers Download the personality you want, then upload it as a file source. There is a link to all the chit-chat datasets in the appropriate. If you do not want to add chit-chat, or if you already have chit-chat support in your data sources, choose None. Choose the personality that you want as your chit-chat base. You can see all the personality datasets along with details of the personalities.įor the user query of When is your birthday?, each personality has a styled response: PersonalityĬhit-chat data sets are supported in the following languages: Languageĭuring knowledge base creation, after adding your source URLs and files, there is an option for adding chit-chat. Some examples of the different personalities are below. Given a user query, QnA Maker tries to match it with the closest known chit-chat QnA. Choose the persona that most closely resembles your bot's voice. This dataset has about 100 scenarios of chit-chat in the voice of multiple personas, like Professional, Friendly and Witty. For information on migrating existing QnA Maker knowledge bases to question answering, consult the migration guide. Starting 1st October, 2022 you won’t be able to create new QnA Maker resources. For question answering capabilities within the Language Service, see question answering. A newer version of the question and answering capability is now available as part of Azure Cognitive Service for Language. The QnA Maker service is being retired on the 31st of March, 2025.