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Dialogflow
Removing feature requests again
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For the deleteParameter intent, you should introduce a new entity type called @filtertype @filterType (with corresponding parameter name) and add as entry entities all the features you have introduced, such as ingredient, cuisine, etc. You may also wish to consider any synonyms that a user might use to refer to any of these features. Again, make sure to include a sufficient number of training phrases to make recognition of this intent robust.
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Recall that we used the agent intent ackFilter to implement the first move in this fragment as part of the a21featureRequest
pattern. If a user complies with the agent’s request, that would trigger another a21featureRequest
pattern. If a user does not comply but rather responds negatively, we can also view that as a disconfirmation move. We argue that we can reuse that intent to capture negative responses to the agent’s request. A user, for that matter, could also simply respond to the agent’s move by saying “No, I won’t” or something similar. We implemented this intent before, but we should extend it to now also cover the variety of user expressions a user could use to say they do not want to add anything else. So, you should add training phrases to make sure these expressions are covered too.
Prolog and Patterns
We will begin with implementing a pattern for allowing a user to express they are done, and then get back to what is still missing to implement requests to remove a filter.
A user does not want to specify more recipe constraints
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A: OK. Here is a list of recipes that you can choose from. [Alternative: Sorry, there are still too many recipes left to show them all. Please add more preferences.]
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But what would granting the user’s request mean? The idea is to somewhat lift our previous restriction of only showing pictures of the list of filtered recipes when there are no more than 15 recipes left. The agent can, for example, show the list of filtered recipes if there are a 100 recipes or fewer left when a user indicates they do not want to provide more information. It does not seem reasonable to show many more recipes, as that does not seem to align well with the ambition to develop a conversational first agent. In other words, our agent should not grant the request if the recipe list still is more than a 100 recipes long. (The exact number, of course, is a bit arbitrary, and it is up to you if you want to argue for changing it.The agent can then allow the user to see the list with the pictureGranted
response, or deny with pictureNotGranted
. If )
We can base the name for the agent intent on our design choice to show more recipe pictures and call the one that grants the user’s request pictureGranted
, and the one that denies the request pictureNotGranted
. Using these labels, you can implement two versions of the a21noMoreFilters
pattern in the patterns.pl
file. And don’t forget to add responses for the agent intents pictureGranted
and pictureNotGranted
to the responses.pl
file. This will require you to define two rules with a different condition on the number of recipes left. Recall that you can use the recipesFiltered/1
predicate to compute a list of the filtered recipes and use that to compute how many recipes are still left after filtering.
There is still one thing missing… Just by talking the agent will not change the page that is displayed. Recall that you have created two pages for the a50recipeSelect
pattern for Capability 5: Filter Recipes by Ingredients and Cuisine. When the agent grants the user’s request we still need to make sure that the second recipe recommendation page showing the recipe pictures is displayed. To make that happen, we need to change the condition for showing that page. We need the store the fact that the user requested this. The idea is to use the conversational memory of the agent for that and update it with this information. Therefore, when the agent grants the user's request, the version of that pattern should end with the agent updating its memory using 'an [agent, update(['show'='true'])]
'. This triggers the showing of recipes by updating the agent's memory.
In responses.pl
we have to make two rules, for 'grantPicture' and 'pictureNotGranted'. The recipesFiltered/1
predicate provides a list of the filtered recipes. Fill in the two rules with the corresponding conditions.
Implement the a21noMoreFilters
pattern actor-intent pair. To change the condition for showing the page in the html.pl
file, we can then use the memoryKeyValue/2
predicate defined in the dialog.pl
file to add an alternative condition for showing this page.
Finishing the implementation for removing filters
Most of the work that needs to be done to remove filters again has already been done. Various patterns implementing the a21removeKeyFromMemory
have already been included in the patterns.pl
file .
Add this predicate to the responses.pl
file in the indicated spot.
Code Block |
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% used in a21removeKeyFromMemory for handling deleteParameter.
text(removedSpecificFilter(DelFilter), Txt) :- convert_to_string(DelFilter, Str1),
string_concat("I removed the ", Str1, Str2),
string_concat(Str2, " requirement.", Txt). |
featureInquiry intent
Multiple text predicates take the argument feature inquiry in responses.pl
. Each feature inquiry response is (check them out to better understand the variants added for this pattern). The specification of the agent response featureInquiry
used in several of these variants, however, is still missing It is up to you to add these in the responses.pl
file. The idea is to define four different types of these responses. Each of these feature inquiry responses should be different based on how many recipes there are still left to filter.after applying all the filters, and will require you to define the conditions for when a response is available:
First Rule for Large Number of Recipes
We want to prompt the user for more specific preferences if there are too many recipes . The rule will left. This version of the response should be triggered when the length of the list of recipes is still large (say greater than 890.800):
Start with the
text/2
predicate, where the first argument isfeatureInquiry
.The For the second argument will be the you can use a response text such as "What kind of recipe would you like?".
Use the
recipesFiltered/1
predicate to get the list of recipes.Use , thelength/2
predicate to determine the number of recipes.Set , and add a condition that the lengthL
must be greater than 890800.
Second Rule for a Moderate Number of Recipes
If there's a moderate number of recipes left (more than 15 but fewer than 891less than or equal to 800), we ask the user to add more preferences unless a certain the memory key-value pair is set.
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Repeat the initial steps of the first rule.
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to show recipes has been set (see above):
Use a response text similar to e.g. "What other preference would you like to add?".
Set the length Add a condition to be less than 891 and greater than 15.Include a condition using
not/1
check that more than 15 but less than 800 recipes are left.Also include a condition to check that the memory does not have the key-value pair
'show', 'true'
.
Third Rule for No Recipes
If there are no recipes left after filtering, we want to inform the user to remove some
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feature requests.
Use the
recipesFiltered/1
predicate again.The a response text will be similar to "There are no recipes, please remove more requirements.".Check that the length
L
is equal to 0 usingL=0
Use therecipesFiltered/1
predicate again to check that no recipes are left.
Fourth Rule for a Small Number of Recipes or a Show Command
This rule handles two scenarios: either there's a small number of recipes, or the user has explicitly asked to show the recipes despite even when the number .
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Start with the text/2
predicate for featureInquiry
.
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is greater than 15.
Use a response text similar to "Here are some recipes that fit your requirements.".
Use the
recipesFiltered/1
predicate to get the filtered list.Create a condition that checks if , and check that the lengthL
is less than 16 but more than 0, or if (use a semicolon;
which represents a logical OR) check that the memory key-value pair '‘show', 'true'
exists. This condition is composed of two parts joined by a semicolon;
, representing a logical OR. is stored in the agent’s conversational memory.
This completes the implementation of all the different cases for the agent’s response. The patterns for removing filters should now work!
Visuals
What you do visually for this capability is up to you.
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