Content Comparison

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[TBU]Greet, and Self-Identify

3. Request a Random Recipe Recommendation

Summary Description

The second capability will enable the agent to recommend a recipe when a user does not care (to refine) what kind of recipe they are looking for (see the example conversational pattern below). A new pattern will be introduced to this purpose for selecting a recipe, and a new intent should be added to your Dialogflow agent to enable understanding user requests for recommending “just some recipe”. Quite some work will need to be done for introducing the first code needed for retrieving recipes from the recipe database. The first versions of two new pages will also need to be created. One page for making clear to the user that they should inform the agent about features of recipes that help refine the selection of recipes and clarify what the user is looking for. Another page for asking a user to (dis)confirm that the recipe that the agent has selected and recommends to the user is what the user is looking for.

Implementation Tasks Overview

Instructions

Select Recipes by Name

Summary Description

Instead of leaving it up to the agent to suggest a recipe and choose one out of all remaining recipes, a user also can mention a specific recipe themselves and ask the agent to present that. This means that the Dialogflow agent should have knowledge of all of the recipes that are in the database too. We will make this available to that agent by adding a recipe entity (type). That will also enable the agent to recognize these recipes in user expressions.

A: What recipe would you like to cook?

U: I'd like to make ____ *.

A: ____* is a great choice!

• insert name of a recipe from the recipe database here, such as “artichoke and pine nut pasta”

Implementation Tasks Overview

Instructions

Tasks Focused on Dialogue Patterns

1. Implement Recipe Selection Pattern

   • Define the a50recipeSelect pattern in patterns.pl with these moves:

     • [agent, specifyGoal]: Agent asks the user what recipe they want.

     • [user, requestRecommendation]: User requests a random recipe.

     • [agent, recommend]: Agent suggests a recipe.

   • Add [agent, insert(a50recipeConfirm)] to direct the agent to the recipe confirmation pattern.

2. Implement Recipe Confirmation Pattern

   • Define the a50recipeConfirm pattern in patterns.pl to allow users to confirm or disconfirm a recipe.

3. Specify Agent Responses

   • Add responses in responses.pl:

     • text(specifyGoal, "..."): Agent asks about recipe preferences.

     • text(recommend, "..."): Agent suggests a random recipe.

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Tasks Focused on Recipe Filtering

1. Add Recipes to the Database

   • Each team member adds one favorite recipe to recipe_database.pl, ensuring unique recipe IDs and consistent ingredient names.

2. Implement Recipe Selection Logic

   • Add rules in recipe_selection.pl:

     • currentRecipe(RecipeID): Retrieves the selected recipe from memory.

     • recipeIDs(RecipeIDs): Collects all recipe IDs from the database.

     • recipesFiltered(RecipeIDs): Filters recipes based on user preferences or constraints.

3. Update Conversational Memory

   • Add a rule in dialog_update.mod2g to update the memory with the randomly selected recipe when a user requests a recommendation.

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Tasks Focused on Visual Support

1. Design Recipe Recommendation Page

   • Define page(a50recipeSelect, _, Html) in html.pl to display:

     • A simple heading asking for user preferences.

     • A microphone button for user input.

2. Design Recipe Confirmation Page

   • Define page(a50recipeConfirm, _, Html) in html.pl to display:

     • The recommended recipe name and image.

     • A microphone button for user confirmation.

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Tasks Focused on Debugging and Testing

1. Test Recipe Recommendation

   • Add a50recipeSelect to the agenda in dialog_init.mod2g and verify the agent's ability to:

     • Ask for recipe preferences.

     • Respond with a random recipe recommendation.

2. Test Recipe Confirmation

   • Ensure the agent correctly displays the recommended recipe and allows user confirmation.

Instructions

[TBU]Request a Recommendation

4. Select Recipes by Name

Summary Description

Instead of leaving it up to the agent to suggest a recipe and choose one out of all remaining recipes, a user also can mention a specific recipe themselves and ask the agent to present that. This means that the Dialogflow agent should have knowledge of all of the recipes that are in the database too. We will make this available to that agent by adding a recipe entity (type). That will also enable the agent to recognize these recipes in user expressions.

Implementation Tasks Overview

Tasks Focused on Dialogue Patterns

1. Add a New Recipe Request Pattern

   • Define a variant of the a50recipeSelect pattern in patterns.pl with these moves:

     • [agent, specifyGoal]: Agent asks what recipe the user wants to cook.

     • [user, recipeRequest]: User requests a specific recipe by name.

     • [agent, recipeChoiceReceipt]: Agent acknowledges the selected recipe.

     • [agent, insert(a50recipeConfirm)]: Move to the confirmation phase.

2. Specify the Agent’s Recipe Acknowledgment Response

   • In responses.pl, define a rule for text(recipeChoiceReceipt, Txt) to construct the response dynamically.

   • Retrieve the recipe name from memory using currentRecipe/1 and construct the acknowledgment (e.g., "Artichoke and pine nut pasta is a great choice!") using string_concat/3.

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Tasks Focused on Visual Support

1. Update Visuals for Recipe Request

   • Adjust the recipe recommendation page (page(a50recipeSelect, _, Html)) in html.pl to clearly guide users toward selecting a recipe by name.

   • Ensure the page is engaging and displays useful instructions or examples for specifying a recipe.

2. Support Alternate Input Methods

   • Uncomment the chatbox code in the footer/1 predicate in html.pl to allow users to type their recipe request as an alternative to voice input.

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Tasks Focused on Debugging and Testing

1. Test Recipe Request Handling

   • Add the new pattern to the agent’s agenda in dialog_init.mod2g after the c10 pattern.

   • Test the interaction flow:

     • Agent asks for a recipe.

     • User requests a specific recipe.

     • Agent acknowledges the recipe choice and moves to the confirmation phase.

2. Verify Intent Recognition

   • Check the Dialogflow Training Tool to confirm the recipeRequest intent is recognized.

   • Verify the SIC server logs show the correct intent and transcript.

3. Handle ASR Failures

   • Use the chatbox feature to avoid ASR failures and ensure the agent can handle specific recipe requests reliably.

Instructions

[TBU]Select Recipes by Name

5. Filter Recipes by Ingredients, Cuisines and Meal Types

Implementing this capability will involve implementing some of the conversational and reasoning competences that a conversational recipe recommendation agent should have. It will enable users to request recipes which use specific ingredient (types) or ask for recipes from a specific cuisine. This one of the capabilities that requires quite a big amount of work. Some of the bigger challenges will be to make Dialogflow understand ingredients (at least those that are in our database; and cuisines, for that matter, but those are fewer), to implement the logic to filter the recipe database with the feature requests of a user, and to present those in a nice way to the user on a webpage.

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