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##Looks like we found a thief monkey By the way, I liked the trick how you reached till here. You have a good sense of humor. You will improve a lot if you join our course with this passion.
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00:00:02 Let's use the API route we created in the last lesson to generate an answer and use it on the front end.
00:00:08 We can start by modifying the question details page.
00:00:11 That is the one with the question ID that we have been on for the last couple of modules.
00:00:16 Here, right at the bottom in the answer form, we can also pass a question title equal to question.title as well as a question content.
00:00:28 equal to question.content.
00:00:31 Then make sure you're using the latest version of the MDX editor.
00:00:36 At the time of the recording, we're looking at 3.21. I think I'm on one, but we need to have the version four.
00:00:43 So just make sure that it is four or higher, and then I'll just run npm install one more time to install this newer version that I just typed in,
00:00:51 because previous versions of this package had an issue with the code editor.
00:00:55 Then let's move over into the answer form and let's generate the answer.
00:01:00 First, I'll accept these new props for passing into it, such as the question title, as well as the question content.
00:01:09 Now I can turn this into an actual interface of props, which we can define right here at the top.
00:01:16 interface props, and it'll have a question ID, question title, and question content.
00:01:22 Next, let's make sure that only authenticated users are able to generate AI answers, not to rack up our bill.
00:01:29 We can do that by saying const session is equal to use session coming from NextAuth React.
00:01:36 Next, let's head over into our handle submit form.
00:01:40 And below if results success, below this toast, let's say if.
00:01:45 editorRef.current, then we can clear the markdown by saying editorRef.current.setMarkdown to be equal to an empty string.
00:01:57 And finally, we can create a new function called const generateAIAnswer, which will be equal to an async function where we'll first check if a session
00:02:10 status is not equal to authenticated, And if that is the case, we'll simply return a toast with a title of please log in and a description of you need
00:02:23 to be logged in to be able to use this feature.
00:02:26 In the future, if you want to implement some kind of payment functionalities in your app, this would be the perfect use case to start charging for pro
00:02:34 features of your app, such as generating AI answers.
00:02:37 So only pro users can then leave AI generator responses.
00:02:41 And we can also set, is AI submitting to true?
00:02:45 Because if we don't return out of this, that means that we are authenticated.
00:02:50 So let's open up a try and catch block.
00:02:53 In the catch, I'll simply return a toast that'll have a title equal to error.
00:03:01 It'll have a description of something like error.message.
00:03:06 And finally, a variant will be set to destructive.
00:03:09 And we can also add a finally clause.
00:03:13 Where will set AI is submitting to false, whatever happens.
00:03:17 Oh, and it looks like I forgot to close this if statement right here.
00:03:20 The rest of the code should happen below the if statement.
00:03:23 Now we can see a type error with this description.
00:03:26 So we can say if error is an instance of error, then we can render the error message.
00:03:35 Else we can simply say something like there was a problem with your request.
00:03:42 There we go.
00:03:44 And we are ready to implement the try part of the block where we are ready to call this API.
00:03:50 In here, we can say await API.ai.getAnswer.
00:03:58 Yep, it is that simple.
00:03:59 And to it, you have to pass two params, the question title, as well as the question content.
00:04:08 I told you that later on, we'll be passing the answer that you currently have typed into it.
00:04:13 So bear with me, we'll do that very soon.
00:04:15 But for now, let's make the AI generate its own answer.
00:04:20 Now, where are we going to get this API from?
00:04:22 From lib API, of course.
00:04:25 And we're going to get some response out of this request.
00:04:28 So let's say const and destructure the success state, the data and the error and make it equal to the await call that we just made right here.
00:04:39 We can then check if there is no success.
00:04:42 In that case, we can return a toast and give it a title of error, a description of something like error.message and a variant of destructive.
00:04:55 And if we have a successful response, then we can generate a formatted answer by saying const formatted answer is equal to data.replace And basically we
00:05:09 want to replace every break tag that looks something like this globally across the entire file with an empty space.
00:05:17 So break replaced by a space.
00:05:19 We want to put it to a string.
00:05:22 and we wanna trim it in case there are some extra spaces.
00:05:26 Finally, we wanna check if we have access to the editor ref dot current.
00:05:32 That means the actual editor where we're typing the response.
00:05:35 If we do have access to it, then we can say editor ref dot current dot set markdown to the formatted answer.
00:05:43 We can also validate that content field automatically by saying form dot set value of the content to the formatted answer and we can do the same thing
00:05:56 with form.trigger the validation for the content.
00:06:00 This way we'll automatically know that it has been validated.
00:06:03 We don't have a lot of reason to manually validate the fields because typically they're validated when you type, but here you're not actually typing.
00:06:10 You get the AI to do typing for you.
00:06:13 Oh, and I just noticed that this was supposed to be within this if statement right here.
00:06:17 So let's put it there.
00:06:19 And then let's exit this if statement and let's render a toast with a title of success.
00:06:26 and a description of AI answer has been generated.
00:06:31 Perfect.
00:06:32 Finally, back in the form right below where we say generate AI answer.
00:06:37 I think that's here.
00:06:38 Right here, we have a button that generates that AI answer.
00:06:42 So let's make it do its thing.
00:06:44 Let's give it an on-click listener and make it equal to generate AI answer.
00:06:50 And that's it.
00:06:51 So we are ready to test it out.
00:06:53 Back in the browser, we are ready to test it out.
00:06:55 So head down below a specific question and click the magic generate AI answer button.
00:07:01 It'll say generating, these requests typically do take some time.
00:07:06 But this time we got an error message saying signal is aborted without reason.
00:07:11 This happens because we set a five second limit for the fetch requests.
00:07:16 And we've done that within our handlers fetch.ts.
00:07:21 See this timeout right here under options?
00:07:24 Well, we need to increase it to a bit of a higher number because it can take some time for AI to generate its answers, which means that we have to extend
00:07:31 the time window.
00:07:32 So instead of 5,000, let's actually make this 100,000 to give it enough time to generate its answer.
00:07:38 Once you do that, we are ready to test it out one more time.
00:07:41 So click generate AI answer.
00:07:43 This time you'll see it'll say generating for a bit of a longer time.
00:07:47 but hopefully it comes up with something nice.
00:07:50 And there we go, success.
00:07:51 AI generated answer has been generated, and you can see the full markdown response right here.
00:07:57 Understanding the data renderer component, it's a versatile tool in the web development.
00:08:02 How it works is it accepts specific data inputs, data detections, rendering logic, and it even provides a perfectly formatted example code within an MDX
00:08:13 code block.
00:08:14 How cool is that?
00:08:15 And you can even post an answer right here in a matter of seconds.
00:08:20 It took us a lot of time to write this with proper formatting and everything, but AI did it in a matter of seconds, providing us the perfect response to
00:08:29 this person's question.
00:08:30 But our app would be kind of funny.
00:08:33 And since people are too lazy when providing answers, nobody would actually type anything.
00:08:38 They would just click this button and give the response to get all the clout.
00:08:42 And that would kind of render our app useless.
00:08:45 Proper questions, but AI-generated answers, which is what nobody likes to see.
00:08:50 So in the next lesson, alongside the question title and the question content, will pass the current answer that you as the user or the person answering
00:09:00 the question have typed in already and then it'll take your answer into account alongside the question title and question content to generate the final answer.
00:09:10 Basically to enhance the answer that you already wrote and return it in a nicely formatted way.
00:09:17 So let's do that in the next lesson.
