A full and comprehensive guide on DialogFlow: how to use it and how to integrate your logic in your chatbot. This article has two goals. The first one is to grasp the global view of how DialogFlow works and, more precisely, how it integrates with a webhook. The second one is to teach you how to create a Go webhook. Its role is to help building chatbots using Machine Learning. All you need to do is provide a set of sentences a user could potentially say, highlight the parameters you want to retrieve and let DialogFlow do its work.
DialogFlow allows you to ask questions to users, display rich messages such as cards, carousels, quick responses, etc and supports a wide range of integrations. You can create a complete conversational chatbot without having to write a single line of code!
How great is that? As stated earlier, DialogFlow supports a wide range of integrations, it knows how to communicate with various services such as Facebook Messenger, Actions on Google, Skype, etc. Every time DialogFlow matches an intent, you have the possibility to ask DialogFlow to send a request to a specific endpoint. That will allow you to retrieve the matched intent, as well as the matched parameters and contexts, and do some useful work with those.
There are loads of tutorials on the internet on how to get started with DialogFlow. So follow one of them and create a new agent. Remember to activate the v2 API before creating the agent! Now that you have your new agent, what should we do? An intent represents what the user is trying to do.
The Random intent will match whenever DialogFlow detects a certain type of sentence. First, the sys. Second, there are two extra entities in the parameters table : alcohol and drink-type. Head to the next section to see how to create them.
Entities are powerful tools used for extracting parameter values from natural language inputs. For example here is the alcohol entity that we saw earlier in our intent definition :. Simple, right? We simply define a set of terms that will match a single value synonyms when our user uses them in a sentence.
For now, you can improve your agent by adding phrases that the user could say and test it out in the console on the right. See if your intent is matched and check if the parameters are filled correctly.To use fulfillment in a production system, you should implement and deploy a webhook service. The detailed processing flow for fulfillment and webhooks is described in the fulfillment overview document. It's important to secure your webhook service, so that only you or your Dialogflow agent are authorized to make requests.
Dialogflow supports the following mechanisms for authentication:. The body of this request is a JSON object with information about the matched intent. See the WebhookRequest reference documentation for details. Once your webhook receives a webhook request, it needs to send a webhook response. The body of this response is a JSON object with the following information:.
See the WebhookResponse reference documentation for details. To enable and manage fulfillment for your agent with the API, see the agent reference. The getFulfillment and updateFulfillment methods can be used to manage fulfillment settings. To enable fulfillment for an intent with the API, see the intents reference. If your webhook service encounters an error, it should return one of the following HTTP status codes:. In any of the following error situations, Dialogflow responds to the end-user with the built-in response configured for the intent currently matched:.
In addition, if the intent match was triggered by a detect intent API callthe status field in the detect intent response contains the webhook error information. For example:. Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.
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Using the text responses from Dialogflow console in your webhook code
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The pin is "validated" at the server end using the Webhook call. That is, "Enable webhook call for this intent" is checked. The method returns a positive message on successful validation. The whole scenario works perfectly as long as I use the Dialogflow console's "Try it Now" window.
But when I try to test it in the Google Assistant Simulator, it responds with:. Intent screen from DialogFlow Agent page. Please note, I have already checked Error "Empty speech response".
It didn't help. When replying with a message for the Google Assistant, you should be using the speech and displayText parameters for the response.
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So the equivalent response would be something like. However, if you're going to be doing additional work with Actions on Google features cards, feature requests, etc or even just keep the conversation open while talking to the user, then you will need to use the data. That might look something like this:. Learn more. Asked 2 years, 1 month ago. Active 2 years, 1 month ago. Viewed 1k times. Your pin has been confirmed. Prisoner Abdullah Abdullah 2 2 silver badges 12 12 bronze badges. Active Oldest Votes.
That's a good question, and the documentation looks a bit unclear about valid responses. We have confirmed your PIN and you can proceed. Prisoner Prisoner It worked.
Am surprised these details are not in their official documentation. I may still need to tweak and work a little on the response for my purpose. I tried to edit your reply because there is a missing comma in the json response just before the data. FYI, Google has updated their help page and included details: dialogflow.Throughout the migration process of going from V1 to V2, if you use Dialogflow fulfillment, you'll need to make sure you respond correctly to Dialogflow's V2 webhook requests.
Ultimately, webhook requests you receive from Dialogflow and the responses to those webhook requests will be different between V1 and V2. Dialogflow's fulfillment library and the Action on Google V2 client library for Node. The libraries listed below support both Dialogflow V1 and V2 webhook requests and responses.
Both libraries eliminate the need to maintain fulfillment for both V1 and V2. If you are already using the Dialogflow fulfillment library, or V2 of the Actions on Google client library, your fulfillment is already compatible with Dialogflow V2 webhook requests and responses.
Agents - Exported JSON Fields
For platforms other than Node. If you are currently using Node. The Dialogflow fulfillment library also supports multiple platforms Google Assistant, Slack, Facebook Messenger, and 5 others for building cross-platform fulfillment. You can find the Dialogflow fulfillment library on Github and npm.
Check out the quick start guide or samples to get started. Actions on Google client library V2 supports Dialogflow V1 and V2 and is best for fulfillment when your agent is only utilizing the Google Assistant integration. You can find the Action on Google V2 client library on Github and npm. The HTTP request from Dialogflow contains information about how Dialogflow processed the request as well as information about the original request from Google Assistant, Slack, detect intent API call, or other integration.
Both the request and the expected response have changed from V1 to V2 and must have JSON bodies structured as described in the next two sections. The body of the request will contain JSON structured to provide you information about Dialogflow's evaluation of the request and information about the original request from the user. Please see the context and session section for how sessions have changed from V1 to V2.
Messages defined in Dialogflow's console for an intent are sent in every webhook request that has matched the same intent. These messages can also be sent back to Dialogflow as a response s to the user. All the information previously found in the result attribute of the JSON request has moved to the queryResult attribute in V2. These attributes contain the following information:.
These attributes contain integration specific information like the following:. This information is dependent on the platform the user is currently using i. Google Assistant, Slack, Facebook Messenger, etc. Below is a list of webhook request JSON bodies you can expect for a variety of Dialogflow and Google Assistant requests to help you know what to expect when migrating from V1 to V After receiving a webhook request from Dialogflow, your backend must respond with a correctly formatted response within the timeout limit.
The expected response format differs from V1 and V2. Please see the contexts and session section for how sessions have changed from V1 to V2. Below is a list of webhook response JSON bodies you can send to respond to your users for a variety of circumstances with versions for both V1 and V2 to help you migrate:. You can find the Project ID for your Dialogflow agent in your agent's settings under the General tab. See our Message Objects page for V1 and V2 comparisons.
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4. For details, see the Google Developers Site Policies. Overview Actions on Google.This is another question which came to me from a client, and I think the answer might be helpful for a lot of folks. Here is the challenge: You want to use the text response you write in your Dialogflow console to be available to the webhook code.
Before we can discuss how to use the copy from the Dialogflow console from inside your webhook, you should first understand exactly what is sent to the webhook. For example, the image below shows a Response section of an intent which has two Text Response blocks and one Custom Payload block. The first Text Response block has 2 individual responses, while the second Text Response block has 3 individual responses.
If the webhook is invoked a second time after a few minutes, this is the JSON which is sent over:.
Now that you know the pattern of the JSON coming in to the webhook, you should be able to use this in your webhook code. Have your copy editors write down the responses in the Dialogflow console. In this case, you will use the default speech received by your webhook inside the fulfillment object and simply set it as the speech field coming back in the response JSON.
A good use case for this approach is the following: you have collected some data from the user successfully. After the webhook saves the data, you want to display some appropriate message to the user. Note that in this case, the response coming back from the webhook can use the copy from the console without any modifications. Another possibility is to use a templating language inside your console, such as the Liquid templates that Shopify uses.
The copy editors will specify the template, and the webhook might fetch the values from a data store and populate the fields in the template. Suppose your webhook does a lookup of a product code and finds that the code is invalid. Or perhaps the product is not in stock. At the same time, you might also have specified a template for the response as described in the previous section if the product was found. Here we have a situation where we might choose to use the first Text Response block for the success case, and a second Text Response block to write out the error message.
If the product lookup code fails to fetch the product, it will look at the response in the second element of the messages array and use it to show an appropriate failure message.
In response to the question left in the comments section: the basic ideas discussed in this article still hold for API v2. The main difference is the structure of the JSON sent to the webhook. Sometimes as you are debugging your bot you might notice something perplexing. The exact same question gets two completely different….
This is a post about where to host your webhook. However, this is not a post about cloud service providers. Hi, I create simple web site with node. Thank you. You mean a website chatbot right? I have written about it here.
I have updated the post to answer your question. The main thing that you need to understand is the structure of the JSON sent over to your webhook, and the rest will fall in place. Another related question is about the data you can send from the webhook to the web chatbot.
Do you think, is it the correct way to send information from webhook to web chatbot? Thank you! It depends on your end goal. Given that it is a website chatbot, generally speaking, it would be easier for you to use the Google Assistant response types because they give you a way to preview your content right inside the Dialogflow console, plus it means your JSON received by website chatbot is already correctly formatted.
I have written about the basic idea here. Also consider that if you actually end up putting raw HTML into your custom payload, you may need to escape it and it will make the text harder to read. Could you please help me out on this?GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together.
If nothing happens, download GitHub Desktop and try again. If nothing happens, download Xcode and try again. If nothing happens, download the GitHub extension for Visual Studio and try again. We have also published a new repo to showcase examples of creating different responses using this library. We are working to add more responses in the future. Please give your feedback and do contribute if you like.
Skip to content. Dismiss Join GitHub today GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together. Sign up. Python Branch: master. Find file. Sign in Sign up. Go back. Launching Xcode If nothing happens, download Xcode and try again. Latest commit Fetching latest commit…. Using this libray you can build the JSON objects with few line. You signed in with another tab or window.
Reload to refresh your session. You signed out in another tab or window. Revert "added to pypi". Oct 15, Intents have a built-in response handler that can return responses after the intent is matched.
This feature only supports static responses, though you can use parameter references in these responses to make them somewhat dynamic. This is helpful for recapping information provided by the end-user. In some cases, this is all you need. In cases where your code needs to take some action or build a more dynamic response, you should use one of the dynamic response options below.
Agents typically use a combination of static and dynamic responses. Multiple types of responses can be provided. The basic response type is a text response. Other types of responses are available image, audio, synthesized speech, and so onsome of which are platform-specific. If you define more than one response variation for an intent, your agent will select a response at random. You should add several response variations to make your agent more conversational. When building an agent, you should provide response data for each intent.
When you use the API or fulfillment to interact with Dialogflow, you technically may not need to provide response data, because both of these methods can dynamically generate any response. However, if you want to use the simulator for testing or define intents that have a simple response, you should provide response data. As a general rule, your intent responses should prompt the end-user to provide an expression that will match another intent.
Your responses should also guide the end-user to provide specific data. For example, a question like "What city were you born in? When building an agent, it is most common to use the Dialogflow Console visit documentationopen console.
The instructions below focus on using the console. To access intent response data:. If you are building an agent using the API instead of the console, see the Intents reference. The API field names are similar to the console field names. The instructions below highlight any important differences between the console and the API.
If you are not using an integration, all of your responses can use the default platform. If you are using integrations, each integration can have a unique response, or it can be configured to use the default response. For more information on platform-specific responses, see Rich response messages. Using fulfillment, you can create dynamic responses. See the fulfillment documents for more information.
Using the API, you can create dynamic responses. See the API overview for more information. For example:. If your intent has a parameter that can resolve to an empty value, you must provide at least one response variant that does not use that parameter.
For example, if your intent has 2 parameters p1 and p2and either or both could be empty, you should provide at least four response variants:.