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Dialogflow
As a first step towards recipe recommendation, we want a user to be able to ask for a random recipe recommendation. The idea is that the agent would randomly select one of the recipes from its database and recommend that to its user. This may not seem particularly useful at this stage, when you only have implemented Capability 1: Greet, and Self-Identify. A user cannot yet have made any requests for specific features of a recipe. However, at a later stage, when a user can also already have made such specific feature requests, adding this capability makes more sense. In these cases, a user simply may not want to add any other feature requests and ask the agent to recommend an arbitrary recipe from those that satisfy the requests they have made thus far. We want to prepare the agent for doing just that already now. The first thing to do to enable this is to create another intent in your Dialogflow agent for requesting a (random) recipe recommendation. To create such an intent, you should follow the same steps as before:
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Test that your intent is correctly recognizing user requests by using the microphone button in the Dialogflow test console. Try various phrases and check whether what you say is classified as your recipe recommendation intent. |
Prolog and Patterns
This section is about implementing the dialog management capabilities of the conversational agent but also about implementing the domain logic that the agent needs to be able to perform its task. As our conversational agent is a task-based agent for recipe recommendation, the conversational competence of our agent focuses on patterns and responses for recipe recommendation. The logic that we need to implement concerns the capabilities our agent needs to reason about user requests about recipes that are available in the agent’s database. We will first focus on adding some conversational capabilities for our agent to respond to a user request to provide a (random) recipe. As before, the approach to dialog management that we use here will require the definition of a pattern and the specification of a (textual) response to the user request. When we have completed that part, we will continue with the part focusing on implementing the reasoning capabilities for extracting such a recipe from the database in Prolog. This will require the definition of several rules for extracting a suitable recipe from the agent’s recipe database.
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This clause specifies that if there are no filters to apply (i.e., the filter list is empty), the output of this filtering of a list of RecipeIDs thus remains unchanged and is that same list of recipe identifiers RecipeIDs.
Visuals
Recipe recommendation page
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We have introduced the bare essentials for these pages but you should feel free to modify it in any way you like to make it look more appealing. However, please note that the a50recipeConfirm page is extended later to include recipe information. More information about these extensions can be found here: https://socialrobotics.atlassian.net/wiki/spaces/PM2/pages/2229600267/Capability+6+Filter+by+Number+of+Ingredients#Visuals.
It is important that you make sure that the requirements marked in bold in the text are met.
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