We want our bot to activate as soon as we say something along the lines of:Let’s fill that in.
After that, scroll down to the “Responses” tab.
You can see some generic welcome messages are provided.
Get rid of them, and put in something more personalized to our bot, as follows:Now, this does a couple of things.
Firstly, it lets the user know that they’re using our bot.
It also guides the user to the next point in the conversation.
Here, it is an “or” question.
Hit “Save” and let’s move on.
Creating a Custom EntityBefore we start playing around with Intents, I want to set up a Custom Entity real quick.
If you remember, Entities are what we extract from user’s input to process further.
I’m going to call our Entity “content”.
As the user request will be content — either a joke or a fact.
Let’s go ahead and create that.
Click on the “Entities” tab on left-sidebar and click “Create Entity”.
Fill in the following details:As you can see, we have 2 values possible for our content: “joke” and “fact”.
We also have entered synonyms for each of them, so that if the user says something like “I want to hear something funny”, we know he wants a “joke” content.
Click “Save” and let’s proceed to the next section!Attaching our new Entity to the IntentCreate a new Intent called “say-content”.
Add the phrase “Let’s hear a joke” in the “User Says” section, like so:Right off the bat, we notice a couple of interesting things.
Dialogflow parsed this input and associated the entity content to it, with the correct value (here, “joke”).
Let’s add a few more inputs:PS: Make sure all the highlighted words are in the same color and have associated the same entity.
Dialogflow’s NLU isn’t perfect and sometimes assigns different Entities.
If that’s the case, just remove it, double-click the word and assign the correct Entity yourself!Let’s add a placeholder text response to see it work.
To do that, scroll to the bottom section “Response”, and fill it like so:The “$content” is a variable having a value extracted from user’s response that we saw above.
Let’s see this in action.
On the right side of every page on Dialogflow’s platform, you see a “Try It Now” box.
Use that to test your work at any point in time.
I’m going to go ahead and type in “Tell a fact” in the box.
Notice that the “Tell a fact” phrase wasn’t present in the samples that we gave earlier.
Dialogflow keeps training using it’s NLU modules and can extract data from similarly structured sentences:A Webhook to process requestsTo keep things simple I’m gonna write a JS app that fulfills the request by querying the Reddit’s website and returning the appropriate content.
Luckily for us, Reddit doesn’t need authentication to read in JSON format.
Here’s the code:'use strict';const http = require('https');exports.
appWebhook = (req, res) => { let content = req.
body.
result.
parameters['content']; getContent(content).
then((output) => { res.
setHeader('Content-Type', 'application/json'); res.
send(JSON.
stringify({ 'speech': output, 'displayText': output })); }).
catch((error) => { // If there is an error let the user know res.
setHeader('Content-Type', 'application/json'); res.
send(JSON.
stringify({ 'speech': error, 'displayText': error })); });};function getSubreddit (content) { if (content == "funny" || content == "joke" || content == "laugh") return {sub: "jokes", displayText: "joke"}; else { return {sub: "todayILearned", displayText: "fact"}; }}function getContent (content) { let subReddit = getSubreddit(content); return new Promise((resolve, reject) => { console.
log('API Request: to Reddit'); http.
get(`https://www.
reddit.
com/r/${subReddit["sub"]}/top.
json?sort=top&t=day`, (resp) => { let data = ''; resp.
on('data', (chunk) => { data += chunk; }); resp.
on('end', () => { let response = JSON.
parse(data); let thread = response["data"]["children"][(Math.
floor((Math.
random() * 24) + 1))]["data"]; let output = `Here's a ${subReddit["displayText"]}: ${thread["title"]}`; if (subReddit['sub'] == "jokes") { output += " " + thread["selftext"]; } output += "!.What do you want to hear next, a joke or a fact?" console.
log(output); resolve(output); }); }).
on("error", (err) => { console.
log("Error: " + err.
message); reject(error); }); });}Now, before going ahead, follow the steps 1–5 mentioned here religiously.
NOTE: For step 1, select the same Google Project that you created/used, when creating the agent.
Now, to deploy our function using gcloud:$ gcloud beta functions deploy appWebHook — stage-bucket BUCKET_NAME — trigger-httpTo find the BUCKET_NAME, go to your Google project’s console and click on Cloud Storage under the Resources section.
After you run the command, make note of the httpsTrigger URL mentioned.
On the Dialoglow platform, find the “Fulfilment” tab on the sidebar.
We need to enable webhooks and paste in the URL, like this:Hit “Done” on the bottom of the page, and now the final step.
Visit the “say_content” Intent page and perform a couple of steps.
Make the “content” parameter mandatory.
This will make the bot ask explicitly for the parameter to the user if it’s not clear:2.
Notice a new section has been added to the bottom of the screen called “Fulfilment”.
Enable the “Use webhook” checkbox:Click “Save” and that’s it!.Time to test this Intent out!Reddit’s crappy humor aside, this looks neat.
Our replies always drive the conversation to places (Intents) that we want it to.
Adding Context to our BotEven though this works perfectly fine, there’s one more thing I’d like to add quickly.
We want the user to be able to say, “More” or “Give me another one” and the bot to be able to understand what this means.
This is done by emitting and absorbing contexts between intents.
First, to emit the context, scroll up on the “say-content” Intent’s page and find the “Contexts” section.
We want to output the “context”.
Let’s say for a count of 5.
The count makes sure the bot remembers what the “content” is in the current conversation for up to 5 back and forths.
Now, we want to create new content that can absorb this type of context and make sense of phrases like “More please”:Finally, since we want it to work the same way, we’ll make the Action and Fulfilment sections look the same way as the “say-content” Intent does:And that’s it!.Your bot is ready.
IntegrationsDialogflow provides integrations with probably every messaging service in Silicon Valley, and more.
But we’ll use the Web Demo.
Go to “Integrations” tab from the sidebar and enable “Web Demo” settings.
Your bot should work like this:And that’s it!.Your bot is ready to face a real person!.Now, you can easily keep adding more subreddits, like news, sports, bodypainting, dankmemes or whatever your hobbies in life are?.Or make it understand a few more parameters.
For example, “A joke about Donald Trump”.
Consider that your homework.
You can also add a “Bye” intent, and make the bot stop.
Our bot currently isn’t so great with goodbyes, sort of like real people.
Debugging and TipsIf you’re facing issues with no replies from the Reddit script, go to your Google Project and check the Errors and Reporting tab to make sure everything’s fine under the hood.
If outbound requests are throwing an error, you probably don’t have billing enabled.
Also, one caveat I found is that the entities can take up any value from the synonyms that you’ve provided.
This means you HAVE to hardcode them in your business app as well.
Which sucks right now, but maybe DialogFlow will provide a cleaner solution in the near future!*******************************************************************Velotio Technologies is an outsourced software product development partner for technology startups and enterprises.
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