I tried searching for the resolution and been stuck on this problem for a few days. I am using actions-on-google (nodeJS) and dialogflow to make a chatbot
Here is a sequence:
1. Choose between food and drinks
2. If food:
----------- does it have to be gluten free?
----------- does it have to vegeterian
----------- Confirm order
----------- Would you like a drink with it?
----------- If yes, go to drink intent and pass food params too. (This is the step I am basically stuck at)
3. If drink,
----------- If coming from food, add it to order
----------- which drink?
----------- confirm order
4. Order placed successfully.
I am unable to move from followups to main intent. Is there a way to do so? conv.followup only worked for child followups.
Intents represent what the user says or does and not how you respond to what they're saying. So in this case, it doesn't really make sense to say that you want to "trigger" the drink Intent.
Instead, you'd ask if they want a drink and, if they say "yes", you would prompt them for the drink they want. Similarly, if they just said up front that they wanted a drink, you'd prompt them for their drink selection. These are two different Intents, but they get the same response and then continue down the same path.
You can't "pass parameters" the way you might be thinking, but you can store values in the parameters of a Context (or in the session storage, if you're developing an Action). One good technique is to build the order and store it in a Context as you go, and then when you're all done, get the values from the Context to confirm and place the order.
Contexts are also commonly used to choose a scope for processing answers - Intents with an Input Context require that Context to be set in order to be triggered. Followup Intents use this to limit when that Intent becomes valid, so you can set that Context yourself during Fulfillment.
(You also don't need to use the Followup Intent Contexts - you can handle this using Contexts you manage yourself.)
Related
Consider a small task where we ask the user to add fruits to the basket one by one in a loop
I have created a small agent for this task with the following intents
Intent: basket
Intent: basket-yes (follow up)
Intent: basket-no (follow up)
In the intent basket user have to provide a fruit name and quantity. Then
If the user says "no" then basket-no (follow up) intent is triggered and the cart is finished
If the user says "yes" then basket-yes (follow up) intent is triggered which should trigger basket intent to allow the user to add more fruits
I have set the input/output context for intents as per the above requirement but the conversation is not moving towards basket intent. I don't know if it's the correct way to do it or even if it's possible to do it with Dialogflow.
First, remember that the Input and Output Contexts don't indicate which Intents will be triggered, they indicate which Intents can be triggered. Intents are only triggered based on what the user says or does. So you never "trigger" an Intent by changing the Context - you can just evaluate which Intents may be valid at any time.
Intents can only be triggered if all of their Input Contexts are currently valid and the user says something that matches a training phrase. So your "basket" Intent will only be triggered if the basket-repeat Context is currently valid and the user says one of the phrases (which you did not show in your screen shots).
Intents are not like state machines, although the Contexts sometimes help you model them that way.
You can do "loops", of a sort, although the user is ultimately in control of how you advance through those loops. While you can't loop through Intents, you can loop through Contexts or state, which influence which Intents may be acceptable at a given moment. And your prompts should certainly reflect the looping nature of what you expect from the user.
I think what is happening is that the basket-repeat Context is never set in the first place, so the basket Intent can never be matched.
I've got a few intents. They all just use a single fallback intent and this fallback intent has the webhook enabled.
In the fallback function what I was hoping to do is switch on the output context and then determine what should happen next depending on which intent the fallback came from.
But the line
var context = request.body.queryResult.outputContexts;
When debugged to the console gets output:
[ { name: 'projects/xxxxproj-xxxx/agent/sessions/xxxxxx-xxxxxx-xxxxx-xxxxx/contexts/xxxxxxx-context' } ]
For the switch statement i just want the last bit with the xxxxx-context. Am I going to have to split that up to get the output context?
In the "Diagnostic Info" section I am a bit surprised there is no reference to the intent from which the fallback came and the only way to work it out seems to be using the outputcontext but as show above that is quite a long string.
Thanks
Yes, the context name is just the last part of that path. Most libraries will take care of that for you, but if you're working with the JSON directly, you need to do this yourself.
There is no reference to "the Intent from which the fallback came" because this isn't quite the model of what an Intent is. Intents represent what the user has said or done, not the current state of the conversation or where you are in the conversation. That current state is represented by Contexts, should you choose to set them.
In that sense, how you use the contexts can vary. They can store parameters, so are a good way to keep information between rounds of a conversation, and you can use them the way you are - to see what state the conversation is in general. But they also take on additional uses when defining Intents.
In an Intent definition, the Intent will only be triggered if all the Contexts listed in the Input Context field are set (ie - have a lifespan greater than 0). Dialogflow uses this when it makes followup Intents, for example, and it is common so you can do things such as have "help" trigger different Intents based on Context. In an Output Context, it will automatically capture all of the parameters specified in the Intent, including those filled in by the user's response, so this can be an easy way to remember what the user has said from round to round.
To answer your question in the comments - it doesn't specifically say which Intents were previously triggered, or which most recently, although if you're consistent in how you use your Output Contexts and what lifespan you give them, you can use it this way. What it does say is in what state your conversation is in, which is generally much better anyway.
Remember - Intents represent what a user has said or done. It doesn't represent anything else about the conversation. Only the state of the system represents that, and one tool we have to control that state is through Contexts.
trying to make an Intent for my first Conversational Assistant with a couple of parameters. Everything is build in Dialogflow and for some of my functionality I use fulfillment.
The easiest way to describe my assistant is as a cinema tickets booking.
I need to store #number_of_tickets, #cinema, #movie. The last two (#cinema and #movie) are very easy to solve with entities, however struggle a lot with #number_of_tickets. All of this parameters should be mandatory.
My goal is to allow such kind of functionality:
Book me a ticket for Star Wars in IMax (ticket = 1 = #number_of_tickets, Star Wars = #movie, IMax = #cinema)
Book me 2 tickets for Star Wars in IMax(2 tickets = 2 = #number_of_tickets, Star Wars = #movie, IMax = #cinema)
Book me tickets for Star Wars in IMax -> How many tickets you want to book?
I tried with composite Entities but it doesn't work as I'm expecting.
How I can enable such kind of functionality in Dialogflow?
Is there a way to require #number_of_tickets to be between 1 and 5?
Above question can be achieved by following below steps:
Solution:
Step 1:
Create Entities for movie and cinema:
Cinema:
Movie:
Step 2:
Create an intent with three parameters:
(If you want alow only from 1 to 5 then you can create an entity like cinema and movies with entries from 1 to 5 and map the number of tickets parameter with the same)
Step 3:
Make all the parameter Mandatory and define prompts for all as below:
Movie Prompts:
Cinema Prompts:
Number of tickets prompts:
Result:
It may not be obvious, but the answer to both of your questions can be addressed by remembering that Intents capture what the user says, and not what you do with what they say. You can have multiple Intents to capture different phrases, and handle them in mostly the same way in your fulfillment. (And these do require that you have some kind of fulfillment webhook behind the scenes.)
How can I assume a default of 1 ticket?
There are a couple of approaches.
The first is that you can setup an Intent to capture phrases that suggest a single ticket and a different Intent that explicitly requires a number. So perhaps one Intent (possibly book.single) with
I'd like to get a ticket for Star Wars in IMax
How about the IMax showing for Star Wars
Let me see the Star Wars for IMax
and so forth. While you'd also have a different Intent (possibly book.multiple) with
I'd like 2 tickets for Star Wars in IMax
2 tickets please for the IMax Star Wars
etc.
In your fulfillment, you might have some function that takes three parameters
bookTickets( num, movie, cinema );
In your Intent handler for book.single, you'd call this with
bookTickets( 1, movieParameter, cinemaParameter );
while in the Intent handler for book.multiple, this would be done with
bookTickets( countParameter, movieParameter, cinemaParameter );
In each case, the fulfillment still ends up calling the same function to do the actual work, but the handler sets the values as appropriate.
How can I limit how many tickets get ordered?
This goes to something that you didn't address - what do you want to happen if they try to order more? Do you want to direct them to a group order conversation? Reject it outright? Whatever you want - make sure you've planned out this path of a conversation before you try to implement it.
In this case, this isn't something you want to enforce in the Dialogflow Intent. Handling it in your fulfillment is easiest. There, you would apply any logic for the various parameters and return a message, prompting them about their next reply.
Logic is best handled in the fulfillment.
There are actually a couple of places this is important in your example. In the first, how would you handle more than 5 tickets requested? In your handler for book.multiple, you would check how many are requested. If between 1 and 5 inclusive, you'd call the book function above. But if not, you might want to just send back a replying saying "I'm sorry, you can only reserve 5 tickets maximum. How many tickets do you want?"
You would also need a new Intent to capture the reply. It could be as simple as just taking a number, but to make sure it only gets applied when you send back this prompt, you may want to set an Output Context indicating you're prompting for the number of tickets and then set this as an Input Context for the Intent that collects a number.
Are there other cases where you might want to apply logic before booking tickets? Plenty - and in each case you will probably want to make sure there is a new Intent that can capture what they want. For example, what if the movie they want to book isn't showing in that cinema? What if you already know that movie is sold out?
But what about Followup Intents?
Followup Intents are generally best avoided in general for exactly the same reason - Intents represent what the user says, and shouldn't try to model your code logic. There is nothing special about a Followup Intent - you can create an Intent at the top level that works the same way, but will be valid only if you prompt for certain things. How? Contexts again!
So if you prompt with possible showtimes ("Do you want the 2:00, 4:00, or 6:00 show?") you could also include a context (say "promptTime", for example) and then have an Intent that expects this as an Input Context and matches the times.
Conclusion
Intents represent what the user says
Your fulfillment code does something with what they've said
You can prompt them for more or different information in your fulfillment
Contexts can shape what replies you expect
Multiple Intent Handlers can call the same functions to do the work
I have created a pizza bot in dialogflow. The scenario is like..
Bot says: Hi What do you want.
User says : I want pizza.
If the user says I want watermelon or I love pizza then dialogflow should respond with error message and ask the same question again. After getting a valid response from the user the bot should prompt the second like
Bot says: What kind of pizza do you want.
User says: I want mushroom(any) pizza.
If the user gives some garbage data like I want icecream or I want good pizza then again bot has to respond with an error and should ask the same question. I have trained the bot with the intents but the problem is validating the user input.
How can I make it possible in dialogflow?
A glimpse of training data & output
If you have already created different training phrases, then invalid phrases will typically trigger the Fallback Intent. If you're just using #sys.any as a parameter type, then it will fill it with anything, so you should define more narrow Entity Types.
In the example Intent you provided, you have a number of training phrases, but Dialogflow uses these training phrases as guidance, not as absolute strings that must be matched. From what you've trained it, it appears that phrases such as "I want .+ pizza" should be matched, so the NLU model might read it that way.
To narrow exactly what you're looking for, you might wish to create an Entity Type to handle pizza flavors. This will help narrow how the NLU model will interpret what the user will say. It also makes it easier for you to understand what type of pizza they're asking for, since you can examine just the parameters, and not have to parse the entire string again.
How you handle this in the Fallback Intent depends on how the rest of your system works. The most straightforward is to use your Fulfillment webhook to determine what state of your questioning you're in and either repeat the question or provide additional guidance.
Remember, also, that the conversation could go something like this:
Bot says: Hi What do you want.
User says : I want a mushroom pizza.
They've skipped over one of your questions (which wasn't necessary in this case). This is normal for a conversational UI, so you need to be prepared for it.
The type of pizzas (eg mushroom, chicken etc) should be a custom entity.
Then at your intent you should define the training phrases as you have but make sure that the entity is marked and that you also add a template for the user's response:
There are 3 main things you need to note here:
The entities are marked
A template is used. To create a template click on the quote symbol in the training phrases as the image below shows. Make sure that again your entity is used here
Make your pizza type a required parameter. That way it won't advance to the next question unless a valid answer is provided.
One final advice is to put some more effort in designing the interaction and the responses. Greeting your users with "what do you want" isn't the best experience. Also, with your approach you're trying to force them into one specific path but this is not how a conversational app should be. You can find more about this here.
A better experience would be to greet the users, explain what they can do with your app and let them know about their options. Example:
- Hi, welcome to the Pizza App! I'm here to help you find the perfect pizza for you [note: here you need to add any other actions your bot can perform, like track an order for instance]! Our most popular pizzas are mushroom, chicken and margarita? Do you know what you want already or do you need help?
Suppose i want to make a pizza ordering DialogFlow agent. To order a pizza we need 3 things: size, type and toppings.
If we want to go with follow-up intents approach rather than using entities then there will be so many combinations in which user might provide the information.
1: i want a pizza -> no info
2: i want small pizza -> size
3: i want small cheese pizza -> size and type
4: i want small cheese pizza with olives -> size, type and toppings
5: i want small pizza with olives -> size and toppings
...
and so on
How to solve this problem?
There will be so many combinations if we have more entities (2^n combinations)
Note 1: cannot take entities and slotfilling option as there are so many problems if we go down that road, like re-prompts loop, validation etc.
Is there any better solution?
Note 2: If we use entities, mark them required, and set prompts then many times if it does not get desired input from user it get stuck in re-prompt loop, i.e it keeps asking user same (or random) prompt for same entity. In my use case, it is bad for user experience. If we use follow-up intents instead, then we can set fallback intents for all those intents which solved this problem. (please note that this is just example of the use case)
This is another example of why I used follow-up intents, it solved my date capturing problem as well. I took #sys.date.recent and set a fallback intent to capture inputs like last week, last month etc, this was not possible using slots.
First, remember that Intents should reflect what the user says, not necessarily what you are doing.
On the surface, it isn't clear why slot filling (either with fulfillment or using built-in prompts) won't meet your needs. Since you've indicated that all three bits of information are necessary (size, type, and toppings), you can mark them as such in your phrases and Dialogflow will prompt for the missing information until it gets everything.
You almost certainly do not want to use Followup Intents. These are good when you always have a specific response that you send that will always have a very narrow set of replies from the user, but are very poor if the response from your action will prompt the user to reply in many different ways.
Instead, I would use a related concept: Contexts. (At least if you're not going to use slot filling.) When you ask the question of what they want, set a Context so you know they are. Then have one or more Intents that have this as an Input Context that accept the various things the user might say. Your webhook should see if you have the information you need and, if not, prompt them what else you're looking for. At the end, prompt for a confirmation, but they may say something that adjusts the order.