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Version: 0.0.37

Suggestions

The Suggestions Tab is designed to enhance the interaction between the model and the user by providing relevant suggestions. These suggestions facilitate ease of use, helping users to understand model capabilities quickly. Automatic suggestions are generated based on the data linked to the model and during semantic training. However, users also have the option to add custom suggestions to guide model interaction.

Introduction to Suggestions​

Suggestions are fundamentally interactive prompts that assist users in getting the most out of the model. When a user selects a model, these suggestions are displayed automatically, serving as a starting point based on pre-linked data and semantic patterns.

Accessing Suggestions​

Consistent access to the Suggestions feature is achieved through:

  1. Navigate to Workspace

    • Access your Lakehousecat workspace.

  2. Select Custom Models

    • From the list of available models, choose the specific Custom Model you wish to manage.

  3. Open the Suggestions Section

    • Click on the 'Suggestions' tab to view existing suggestions or add new ones. This area provides the framework for enhancing user-model interaction.

Managing Suggestions​

In the Suggestions section:

  • View Existing Suggestions: Observe the automatically generated suggestions based on data connections and previous training sessions.
  • Add New Suggestions: Utilize the plus (+) icon to introduce new suggestions. These custom additions help tailor the model interaction to specific organizational needs or user preferences.

Best Practices​

  • Automatic and Custom Suggestions: Balance automatically generated suggestions with custom ones to create a comprehensive guide for users.
  • User-Centric Approach: Craft suggestions that resonate with user queries and typical interactions to optimize system usability.
  • Continuous Update: Regularly review and update suggestions based on evolving data or changes in user needs.

With these strategies, the Suggestions Tab becomes a valuable tool in guiding users through efficient and meaningful interactions with Custom Models in Lakehousecat.