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.
Related
I am trying to transition between intents. I have welcome intent and based on user response, I want to either redirect to Search intent or to CheckInternet intent.
I have given output context as search and interconnection in Welcome intent and then given them as input context in relevant intents. But still not able to chain them together.
Unfortunately, I don't have knowledge of Dialogflow yet, as using this for hackathon first time to check its capabilities. Any help would be great
Intents in Dialogflow aren't nodes in a state machine. You don't "transition" between them. Intents reflect what the user says or does.
So, to give your example:
When they start the agent, the welcome Intent is triggered based on the welcome event.
If, at any point, they say "search", then the training phrases in the Search Intent might match, so the webhook or responses for it would be triggered.
Or, if they said "check", then the training phrases in the CheckIntent Intent might match, so the webhook or responses for it would be triggered instead.
If you need to limit under what circumstances these phrases would be accepted by an Intent, you can add a Context and make sure that Context is valid. But you usually only want to add that once you get it responding in the more general case.
You would have to add both Search and CheckInternet as "Follow-up Intents". To do so, create two new Intents and assign the contexts search and interconnection to them respectively as Input Context.
When the user says something that should lead to Search, set search as output context and for the next utterance Search Intent will be considered (if sample utterance match).
I hope that's clear enough, I'm happy to explain that in detail, too. This way I configured a nicely working Chatbot with 20+ Intents once :)
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'm trying to make a simple dialogflow conversation. I have made a simple conversation to ask a person who they are trying to call and then says if a person is available / unavailable, which is just a text reply. When a person is unavailable I have potentially 3 actions the user can do, leave a voicemail, redirect to a colleague or wait until the person is available.
The message I would return is
"I'm sorry nameOfPerson is not available, would you like to leave a voicemail message, redirect to a colleague or wait until nameOfPerson is available?"
Which works, but how can I make it so that lets say there is no voicemail the intent only response with, "I'm sorry nameOfPerson is not available, would you like to redirect to a colleague or wait until nameOfPerson is available?"
Currently the only way I see to fix this is making 7 intents with all different contexts like:
Intent1: voicemailContext
Intent2: redirectContext
Intent3: voicemailContext, redirectContext
Intent4: waitingContext
Intent5: WaitingContext, redirectContext
Intent6: waitingContext, voicemailContext
intent7: waitingContext,redirectContext, voicemailContext
All that work for just a small adjustment seems way to complicated. Also currently I'm sending those options in a call which I would much rather not since people could also just say those options and get a match
Dialogflow is very poor at handling logic. You can sorta do it, as you've seen, but this does lead to overly complicated models. One thing to remember that might help with this is that Intents are good at modeling what the user says, but that you're still responsible for what you do with that.
Better in many cases is to put the logic in a fulfillment webhook. This lets your code determine what the best response is and send that response. Depending how you want to structure your replies, you have a few other options:
You can send a context back in the reply. This would limit which Intents can get triggered when the user replies.
Another approach is to only have one Intent for the reply, but to use Entities to represent what sorts of things they can do. Then have your fulfillment, again, determine if they have given you a valid or invalid reply and respond accordingly.
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?
I know that i can make a none intent to cover some of these, however we cannot just create every nonsense question a person could ask.
Or even if someone types in a 50 word statement. The bigger problem is that if we get a query to LUIS, it is assigning it an intent that is not correct, without even having identified any entities either.
What to do?
To handle these cases, it would be better to add more labeled utterances to your other intents and occasionally add the stray utterances to the None intent. When the model is better for predicting your non-None intents, the better predicting of None intents also accompany this (LUIS attempts to match to an intent rather than cutting intents out).
If intents are triggering without any entities being recognized (and thus you believe the wrong intent has been triggered), this should be handled at an application level, where you would then disambiguate the intents back to your users. If you've set the verbose flag to true, then you could take the top three scoring intents and present those back as options to your user. Then you can move back into the proper dialog.
After you've moved into the intent/dialog they meant to access, you can conduct a programmatic API call to add that utterance to the intent. Individually adding labeled utterances can be problematic (the programmatic API key has a limit of 100,000 transactions per month, and a rate of 10 transactions per second), so you can instead aggregate the utterances and conduct batch labeling. An additional bit of info; there is a limit of 100 labeled utterance per batch upload.
Adding to the Steven's answer - in the intent window, you have the Suggested Utternaces tab - this is also a hint for the algorithm, kind of reinforced learning approach.