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Add knowledge to a prompt

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Prompts enable makers to use generative AI models addressing various types of content generation scenarios. These models use their default knowledge included in their training data to answer. However, this knowledge isn't sufficient to deal with use cases requiring business specific data context.

This point is where data Retrieval Augmented Generation (RAG) allows you to provide external information to augment the knowledge of the model. This augmentation can result in getting the answers you need.

Add knowledge and filter

This section describes how to add knowledge to a prompt and filter it.

  1. Type / or select Add content to choose a data source object from the Knowledge section.

    Screenshot of how to select a data source.

  2. Navigate the data source and select one or more columns. These are added as knowledge objects in the prompt.

    Screenshot of selected column.

  3. Filter the retrieved knowledge by selecting the knowledge object, then select Filter attribute, and choose the field to filter in Filter attribute. Enter a free-form text or a prompt input in Filter value.

    Screenshot of how to filter column value.

  4. Filter using an input. Create a prompt that retrieves all accounts using the value of an input named Question.

    Screenshot of how to use the input to filter knowledge

    The prompt automatically filters all knowledge objects using the value of this input, expressed in natural language.

Example of scenarios

The number of scenarios enabled by this capability is limited only by your creativity. The following list provides some examples.

  • Create a summary of the account named Name using only these columns: Account.Name, Account.Description, Account.Orders (Order).Name, Account.Orders (Order).Amount.
  • Classify the Email into one of these Category.Name matching based on Category.Description.
  • Draft a reply to this Problem matching data from FAQ.Topic and getting inspiration from FAQ.Solution.
  • Get answers to the Question by providing information about Account.Account Name, Account.Account Number, Account.Address 1, and Account.Address 1: City.

Limitations

The following list describes the limitations of using your own data in a prompt.

  • Data source is limited to Dataverse tables.

  • Dataverse environment languages supported: English US, French, Japanese, Danish, Dutch, German, Italian, Brazilian Portuguese, Spanish, Simplified Chinese, Danish Norwegian, and Turkish.

  • Virtual table use isn't yet supported.

  • You can use only one table as the data source. However, you can reference fields from multiple relationships of this table.

  • Only the columns with the following data types are available to insert in the prompt and filter: text, number, date and time, choice, currency, and unique identifier.

  • We support only English US formats for filtering values. For example, Filter value=121.5 is supported, while 121,5 isn't. Filter value=2024-12-25 is supported while 25/12/2024 isn't.

  • You can only use direct relationships of the table added as data source.

    For example, you can use Account.'Company Name (Contact)'.Name and Account.'Preferred User (User)'.'Last Name' but not Account.'Company Name (Contact)'.'Connected To (Connection)'.'Connection Name'.

  • The total number of records that can be retrieved is limited to 1,000.

Training: Create AI Builder prompts using your own Dataverse data (module)