In chatbot conversational flow how and where to define the dependency flow.
should that be handled at the coding level or
can we define in the intents.json file itself.
I have the following intents file
intents.json
{
"tag": "movie_genure",
"patterns": [
"list of available movie genures",
"different genures available"
],
"responses": [
"action movies",
"adventure movies",
"mystery movies"]
}
i want the chatbot flow in the following way
user: provide the list of available movie genures
bot: action movies
adventure movies
mystery movies
user: list of action movies
bot : movie A
movie B
...
movie Z
Example 1: conversational flow structure
Example 2: conversational flow in IBM watson
In Watson Assistant, based on your JSON the patterns would map to your intents, and the responses would map to entities.
In the dialog tree you would look for the intent. For example #ListActionMovies.
You would then check to see if an entity was referenced and if not ask the user. For example: #MovieGenre:mystery
Your UI is the old version of Watson Assistant. I recommend to switch to the new experience, as it's much easier to use.
Related
I have been trying to make my own chatbot with dialogflow CX,
I cant see to find enough DOC about this tool.
I am trying to make the bot start the conversation when i join the session but i cant find a way to do it.
Right now my chatbot needs a "hello" or some training word to start the dialog, but i want the chatbot to start this.
I think you can do it with "Custom payload" but i cant find an example of how to do it.
Also i know in DialogFlow ES you had a "Suggestion Chip" option where you could put in a button the answer options,
but i cant find it on CX, do i have to code it now?, can any kind hearth give me an example or extra documentation about how to code this bot?
Pd: I am new and learning how to do this chatbot, google cloud and object programming need advice in general, thanks!
Right now i am using https://cloud.google.com/dialogflow/cx/docs official doc
custom buttons with hints/suggestions as you outline in your question are only available in Dialogflow CX for integrated services. You can find information about which service is supported on this page. Otherwise, if you are able, you can develop your own integration through their API, i'm using the Python one.
If you decide, for example, to activate the Messenger integration to make your bot available via FB Messenger, you can visit the specific page and find, for example, that buttons can be set up this way.
There are many other response types, you can browse them in the same page (list, button, description, image, card): for each of them google provides a sample code to put in the "Custom Payload" box for the fulfillment. For example a box to www.yoursite.org would work like this:
{
"richContent": [
[
{
"type": "button",
"icon": {
"type": "chevron_right",
"color": "#FF9800"
},
"text": "Button text",
"link": "https://yoursite.org",
"event": {
"name": "",
"languageCode": "en",
"parameters": {}
}
}
]
]
}
by specifying "parameters" or "event" you can trigger Dialogflow events to manage the conversation flow.
Hope this made things clearer for you!
I want to know whether IBM Watson Assistant has the feature of calling webhook.
It means when an intent of workspace is matched Watson Assistant need to send a post request to an external server including the intent in the request body.
Example for a webhook:
https://123.456.789.12:7788/myWebhook/testMethod
IBM Watson Assistant need to send a Post request to this service and that service will return a text string. Watson Assistant should get that text and show it to the user.
That is my usecase. Will it work with Watson Assistant?
i found the below documentation from IBM site.
https://console.bluemix.net/docs/services/conversation/dialog-actions.html
It says to update the json response. i.e. add another key value pair to json object as "action". in the action json array there is "name" parameter. I added above url to name parameter and checked by calling the intent whether a request comes to my web service but it didn't.
following is my json response. i assumed once the intent is matched a post request should go to my web service. but i checked my web service by printing the request body on the console. but no any request came to it. could you please tell me where did i miss?
{
"context": {
"skip_user_input": true
},
"output": {
"text": {
"values": [
"your current outstanding balance is $my_balance ."
],
"selection_policy": "sequential"
}
},
"actions": [
{
"name": "https://123.456.789.12:7788/myWebhook/testMethod",
"type": "client",
"parameters": {
"body": "$body"
},
"result_variable": "context.my_balance"
}
]
}
You found the correct method, i.e. dialog actions, to implement webhooks.
Watson Assistant supports server- or client-side actions:
For the server-side action you would set up an action with IBM Cloud Functions. That action would call the webhook.
For client side, you would pass the information similar to what you show in the question to the app (client). Your app would need to react and to call the webhook.
From what I read about your case I recommend checking out the server-side action. This tutorial about a database-driven bot implements a couple of those actions. Instead of calling the database, you would call out the webhook.
As of August 2019, there is now an integrated webhook feature in Watson Assistant.
Go to "Options" in the Assistant dialog and enable webhook. Paste the url you got after creating an action from cloud functions. Don't forget to add ".json" to the url you paste in the assistant webhook page. See more information here:
https://cloud.ibm.com/docs/assistant?topic=assistant-dialog-webhooks
I created a chatbot on Dialogflow which informs the user about the names of the members of my (extended) family and about where they are the living. I have created a small database with MySQL which has these data stored and I fetch them with a PHP script whenever this is appropriate depending on the interaction of the user with the chatbot.
I have integrated this chatbot to Facebook Messenger. My question is the following:
Can I directly trigger the Facebook messenger camera to be turned on through Dialogflow (and without using any other front-end camera)?
The reason I want to turn on the camera is to allow the user to take a photo of himself/herself and then I will process the photo with some computer vision libraries to infer if this person at the photo is a family member of mine. Obviously, I can simply create another basic front-end where I will turn on a camera whenever e.g. an intent called 'Camera' is triggered but I was wondering if can do this directly on facebook messenger.
The json response that I am receiving at my back-end from Dialogflow contains only the following UI capabilities:
"surface": {
"capabilities": [
{
"name": "actions.capability.MEDIA_RESPONSE_AUDIO"
},
{
"name": "actions.capability.SCREEN_OUTPUT"
},
{
"name": "actions.capability.AUDIO_OUTPUT"
},
{
"name": "actions.capability.WEB_BROWSER"
}
]
}
therefore my first impression is that turning on a camera directly through Dialoglfow (and Facebook Messenger) is not possible.
Am I right?
Well, you're right... but probably not for the reasons you think.
First, you're not going to be able to turn on the Facebook Messenger camera because you're not using Facebook Messenger. You're using the Google Assistant. Right now, the Google Assistant doesn't define a way to send an image to the Action you're interacting with. (It does work with Google Lens, but at this point, there is no way to get that to you.)
Second, you wouldn't actually "turn on" the camera. If the user sends you an image through the Messenger camera, you can process this by looking at the originalRequest field in the JSON you get on your fulfillment which should contain the message from Facebook which contains the image.
We have a chatbot for our website today, that is not build using Google technology. The bot has a JSON REST API where you can send the question to and which replies with the corresponding answers. So all the intents and entities are being resolved by the existing chatbot.
What is the best way to wrap this functionality in Google Assistant / for Google Home?
To me it seems I need to extract the "original" question from the JSON that is send to our webservice (when I enable fullfilment).
But since context is used to exchange "state" I have to find a way to exchange the context between the dialogflow and our own chatbot (see above).
But maybe there are other ways ? Can it (invoke our chatbot) be done directly (without DialogFlow as man in the middle) ?
This is one of the those responses that may not be enough for someone who doesn't know what I am talking about and too much for someone who does. Here goes:
It sounds to me as if you need to build an Action with the Actions SDK rather than with Dialog flow. Then you implement a text "intent" in your Action - i.e. one that runs every time the user speaks something. In that text intent you ask the AoG platform for the text - see getRawInput(). Now you do two things. One, you take that raw input and pass it to your bot. Two, you return a promise to tell AoG that you are working on a reply but you don't have it yet. Once the promise is fulfilled - i.e. when your bot replies - you reply with the text you got from your bot.
I have a sample Action called the French Parrot here https://github.com/unclewill/french_parrot. As far as speech goes it simply speaks back whatever it hears as a parrot would. It also goes to a translation service to translate the text and return the (loose) French equivalent.
Your mission, should you choose to accept it, is to take the sample, rip out the code that goes to the translation service and insert the code that goes to your bot. :-)
Two things I should mention. One, it is not "idiomatic" Node or JavaScript you'll find in my sample. What can I say - I think the rest of the world is confused. Really. Two, I have a minimal sample of about 50 lines that eschews the translation here https://github.com/unclewill/parrot. Another option is to use that as a base and add code to call your bot and the Promise-y code to wait on it to it.
If you go the latter route remove the trigger phrases from the action package (action.json).
So you already have a Backend that process user inputs and sends responses back and you want to use it to process a new input flow (coming from Google Assistant)?
That actually my case, I've a service as a Facebook Messenger ChatBot and recently started developing a Google Home Action for it.
It's quite simple. You just need to:
Create an action here https://console.actions.google.com
Download GActions-Cli from here https://developers.google.com/actions/tools/gactions-cli
Create a JSON file action.[fr/en/de/it].json (choose a language). The file is your mean to define your intents and the URL to your webhook (a middleware between your backend and google assistant). It may look like this:
{
"locale": "en",
"actions": [
{
"name": "MAIN",
"description": "Default Welcome Intent",
"fulfillment": {
"conversationName": "app name"
},
"intent": {
"name": "actions.intent.MAIN",
"trigger": {
"queryPatterns": [
"Talk to app name"
]
}
}
}
],
"conversations": {
"app name": {
"name": "app name",
"url": "https://your_nodejs_middleware.com/"
}
}
}
Upload the JSON file using gactions update --action_package action.en.json --project PROJECT_ID
AFAIK, there only a Node.js client library for Actions-on-google https://github.com/actions-on-google/actions-on-google-nodejs that why you need a Node.js middleware before hitting your backend
Now, user inputs will be sent to your Node.js middleware (app.js) hosted at https://your_nodejs_middleware.com/ which may look like:
//require express and all required staff to build a Node.js server,
//look on internet how to build a simple web server in Node.js
//if you a new to this domain. const {
ActionsSdkApp } = require('actions-on-google');
app.post('/', (req, res) => {
req.body = JSON.parse(req.body);
const app = new ActionsSdkApp({
request: req,
response: res
});
// Create functions to handle requests here
function mainIntent(app) {
let inputPrompt = app.buildInputPrompt(false,
'Hey! Welcome to app name!');
app.ask(inputPrompt);
}
function respond(app) {
let userInput = app.getRawInput();
//HERE you get what user typed/said to Google Assistant.
//NOW you can send the input to your BACKEND, process it, get the response_from_your_backend and send it back
app.ask(response_from_your_backend);
}
let actionMap = new Map();
actionMap.set('actions.intent.MAIN', mainIntent);
actionMap.set('actions.intent.TEXT', respond);
app.handleRequest(actionMap); });
Hope that helped!
Thanks for all the help, the main parts of the solution are already given, but I summarize them here
action.json that passes on everything to fullfilment service
man in the middle (in my case IBM Cloud Function) to map JSON between services
Share context/state through the conversationToken property
You can find the demo here: Hey Google talk to Watson
my boss give me the task to creata a chatbot, not made with Telegram or Slack, in which use Watson Conversation service.
More, the chat bot has to be inserted inside a web page, then it has to be embeddable in html as javascript.
Are there anyone who knows other good platforms to performe these tasks?
Thanks for any help.
After replying in comments and I had another look and realised Microsoft Bot Framework could work with minimal dev investment (in the beginning).
https://docs.botframework.com/en-us/support/embed-chat-control2/
This little guy is fun. You should give him a try.
http://www.program-o.com/
I strongly suggest you to build more an assistant than a simple bot, using a language understanding service tool like Microsoft LUIS, that is part of the Microsoft Cognitive Services.
You can then combine this natural language processing tool with bot SDK like MicroSoft Botframework mentioned above, so that you could easily run queries in natural language, parse the response in a dialog in entities and intents, and provide a response in natural language.
By an example, a parsed dialog response will have something like this json
{
"intent": "MusicIntent",
"score": 0.0006564476,
"actions": [
{
"triggered": false,
"name": "MusicIntent",
"parameters": [
{
"name": "ArtistName",
"required": false,
"value": [
{
"entity": "queen",
"type": "ArtistName",
"score": 0.9402311
}
]
}
]
}
]
}
where you can see that this MusicIntent has a entity queen of type ArtistName that has been recognized by the language understanding system.
that is, using the BotFramework like doing
var artistName=BotBuilder.EntityRecognizer.findEntity(args.entities, Entity.Type.ArtistName);
A good modern bot assistant framework should support at least a multi-turn dialog mode that is a dialog where there is an interaction between the two party like
>User:Which artist plays Stand By Me?
(intents=SongIntent, songEntity=`Stand By Me`)
>Assistant:The song `Stand by Me` was played by several artists. Do you mean the first recording?
>User:Yes, that one!
(intents=YesIntent)
>Assistant: The first recording was by `Ben E. King` in 1962. Do you want to play it?
>(User)Which is the first album composed by Ben E.King?
(intents=MusicIntent, entity:ArtistName)
>(Assistant) The first album by Ben E.King was "Double Decker" in 1960.
>(User) Thank you!
(intents=Thankyou)
>(Assistant)
You are welcome!
Some bot frameworks use then a WaterFall model to handle this kind of language models interactions:
self.dialog.on(Intent.Type.MusicIntent,
[
// Waterfall step 1
function (session, args, next)
{
// prompts something to the user...
BotBuilder.Prompts.text(session, msg);
},
// waterfall step 2
function (session, args, next)
{
// get the response
var response=args.response;
// do something...
next();//trigger next interaction
},
// waterfall step 3 (last)
function (session, args)
{
}
]);
Other features to consider are:
support for multi-languages and automatic translations;
3rd party services integration (Slack, Messenger, Telegram, Skype, etc);
rich media (images, audio, video playback, etc);
security (cryptography);
cross-platforms sdk;
I've started to do some work in this space using this open source project called Talkify:
https://github.com/manthanhd/talkify
It is a bot framework intended to help orchestrate flow of information between bot providers like Microsoft (Skype), Facebook (Messenger) etc and your backend services.
I'd really like people's input to see if how it can be improved.