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?
Related
Hi so I have a problem.
In Dialogflow, when I get a response to end the chat, I would like to ask the user for ratings.
so I've created 2 intents, "endchat" and "endchat2."
They both have the same training phrases, but it appears only endchat2 is being used (the most recently created intent)
How do I ensure that the chatbot randomly chooses an intent after a given response, instead of only using one intent? They have the same training phrases.
An alternate idea is in the attachments. The problem lies that I want the custom payload to only to appear after one of the text responses, (that being text response #1,) but not appear, if the chatbot decides to use text response #2. This is the reason I decide to make two separate intents, but it looks like that's not helping out because the bot is only using one intent.
Remember, Intents represent what the user says and does and not how you respond to that. So there is no way to "randomly choose an Intent" to use to respond.
What you can do, however, is setup a webhook for that Intent and determine how you wish to respond to what the user says. In some cases, you can thank them and end the conversation, while in others you can thank them, ask them the followup question, and set a Context so you can expect their reply.
Having the same / similar training phrase in multiple intents is an anti-pattern of bot design. Ultimately this confuses the bot and it leads to undefined behavior.
This should also trigger an warning in "Validation" with something like "Multiple intents share training phrases which are too similar:..." on the intents.
In our chatbot we have a fallback intent but it would be great if I could know if the user was
asking a question
just saying arbitrary things like "cool", "ok", "got it"
complaining (derogatory texts)
I think (3) can be achieved with sentiment analysis, but is there a tool or an additional API that can guess this sort level of categorisation.
These are chat texts so they are super short.
You can achieve your second option by activating smallTalk in Dialogflow. This is specially design and pre-built trained agent to handle such query 'hello, cool' okay, got it, etc.
For the first option asking a question. I am not sure, but before providing an open-end to the user (basically a broad category of the question) I would suggest narrowing down the scope and category with some option and then create an intent for a feature (less open-end scope of conversation the more effective it will be)
Good day,
I am currently trying to create an intent that is able to put out responses depending on the user input. (The chatbot should be implemented on a website later)
Let's say we have an entity called cars with three entries: "Volkswagen" "Audi" "Ford".
Now when the user types in something with e.g. Audi in it, the response will correspond to this. Something like this: If Audi then give this response, if Ford then this response.
I couldn't find anything helpful yet.
Thank you in advance!
Remember that Intents represent what the user says and not how you handle this or how you reply. Although Dialogflow does offer the ability to respond to Intents, these aren't based on specific values that may appear in parameters.
There are, however, a variety of ways you can handle what you're doing, based on the rest of what you're trying to do.
Multiple Intents
One solution is to create an Intent for each type of thing that the user may talk about. You could then put the response you want for each in the response section of that Intent.
This is probably a bad approach, but may be useful in some ways. It requires you to duplicate phrases between the different Intents, which leads to a lot of duplication. On the upside, it does let you vary the replies, and truly represents the Intent of what the user is trying to say.
Using Parameters with Fulfillment
A better approach is to have a single Intent with many phrases representing what the users can ask. These phrases would have parameters of your Entity Type.
You can then enable Fulfillment for this Intent and write a Fulfillment webhook for the Intent that would look a the value of the parameter and send back an appropriate reply.
Using Parameters with DetectIntent
Since your ultimate goal is to embed this on a website, it may be more appropriate to have your website show something different based on what the user has said. (For example to show a picture of the car in another pane or links to different pages, to use your example of cars.)
In this case, your chat client (or a proxy) would be calling the DetectIntent API. You can structure your Intent similar to above, with parameters of the Entity Type, and the reply that is sent to your client would contain the Intent along with the value of the parameter. Your client then can check the value of the parameter and change the display accordingly.
I am trying to make a search algorithm with dialogflow that could take any combination of: first name, address, phone number, zip code or city as input to a search algorithm. The user does not need all of them, but we will refine our search with each additional answer until we only have one result. Basically we are trying to identify which customer we are talking to.
How should this type of intent (or set of intents) be structured? We have tried one intent with multiple parameters, but we do not need all of them to be required. We have also written a JavaScript function for fulfillment but how can we communicate back to dialogflow as to whether we need more information?
Thank you very much for your help.
Slot filling is designed for this purpose.
Hope that helps.
Please post more code/details to help answers be more specific.
First, keep in mind that Intents reflect what the user is saying, and not typically what you're replying with or what other information you need. Slot filling sometimes bends this rule, but only if you have required slots.
Since you don't - you need a different approach.
This can be done with a single intent, although you may find that multiple intents make it easier in some ways. The approach is broadly the same:
When you ask the question, make sure you set an Outgoing Context with a relatively short lifespan (2-3 is good) to indicate you are collecting user info.
Create an Intent (or Intents) that have sample phrases that capture the information you need.
Some of these will have obvious entity types (phone number and zip code) while others will be more difficult (First name has a system entity type, but it doesn't include all possible first names).
You will need to create sample phrases that collect the parameters by themselves, along with phrases that make sense. You're the best judge of this, and you should probably write some sample conversations before you write the phrases.
In your fulfillment, you'll figure out if you have enough information.
If you do, you can reply and clear the Context that was set. (Clearing it is important so Dialogflow doesn't match the information collecting Intent again.)
If you do not, you can add the information you have as parameters to the Context so you can save it for later processing, make sure you reset the Context lifespan (so it doesn't expire), and prompt the user for additional information. Again, having a conversation mocked out ahead of time will help here.
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.