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The next thing we want to add is the capability to filter on dietary restrictions. This will require extensions to your Dialogflow agent for NLU but also require the implementation of new logic in Prolog for filtering the recipe database on these restrictions.
Dialogflow
As a first step, use the following CSV file to upload the dietaryRestiction entity:
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To make your Dialogflow agent extract this entity, you again need to add more training phrases, and annotate these phrases for the dietaryRestrction entity, and extend the addFilter intent with these phrases. You can use the test console of your agent to verify that it is able to recognize addFilter intents with dietary restrictions and extract the entity entries you just added.
Prolog and Patterns
In the previous capabilities that we implemented for filtering the recipe database, we often could simply use the facts that are part of that database to implement the filtering process (the applyFilter/4 rules). For example, for Capability 5: Filter Recipes by Ingredients and Cuisine we could use the ingredient/2 and cuisine/2 facts, and for Capability 6: Filter by Number of Ingredients & Recipe Steps, we could use time/2 for the cooking duration of a recipe and servings/2 for the number of servings. For computing the number of ingredients and recipe instructions steps, we had to do a bit more work, but these could also be computed quite straightforwardly from these basic facts.
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Even though some of the recipe features that we have looked at require careful analysis, those that require more work than simply inspecting basic facts in the recipe database were all based on reasoning about individual ingredients. That is, we verified whether an ingredient is of a particular type, either a type of food or a type of dietary restriction. If you like a challenge, you can also consider other recipe features that consider more global features of a recipe, such as a recipe being low-carb or cheap. How would you define the logic for such filters? What kind of information would you need to add to the database to be able to define features like these?
Visuals
Nothing we ask you to do here for this capability. It’s up to youYou can update the visuals based on what you think will help the user the most. Think about how you can support the implemented capability visually.
Test it Out
Try to ask your conversational agent to add dietary restrictions for, for example, vegan recipes. Try various types of restrictions to see how that works. What can you say about how consistent the logic that is defined for these restrictions is? You may want to think about how to improve that (and, if you have any ideas that you did not implement, reflect on that in your report, for example).
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