I Built a Calorie-Tracking App with ChatGPT + Lovable in Under 20 Minutes (No Code, No Dev Skills)

0:00 Okay. So, what we're going to do today 0:03 is we're going to be building an app 0:06 using chat 0:08 GPT and Lovable. So, if you haven't 0:11 already seen, uh, Lovable allows you to 0:15 build apps. You don't have to be a 0:17 developer. Uh, it's a no code, just a 0:20 chatbased developer, and it's pretty 0:22 cool. So, let's go ahead and get right 0:25 into it. All right. So, um, I'm going to 0:28 build 0:30 uh an 0:32 app measures 0:39 calories. Uh and the reason why we want 0:41 to do this is because if you've seen uh 0:43 this kid just made, let's 0:51 see, a 0:53 $1.12 million a month app and he's 17 0:57 years old. So, if that doesn't motivate 1:00 you or you a little 1:04 bit, then I hope this video will. So, um 1:08 that's exactly what we're going to do is 1:10 we're going to just go ahead and build 1:11 this stuff out. I'm 1:15 using as a senior 1:18 developer. Give me 1:22 the overview. 1:28 Okay, so let's go ahead and get right 1:30 into it. And this is because I'm not a 1:32 developer, right? We're just 1:35 gonna make an app that measures calories 1:38 at Cal Cali. And it's going to go right 1:40 into, of course, we're in chat, so you 1:42 might be familiar with it. I'm using the 1:44 40 model right now. And it gives me some 1:47 good, you know, instructions. It says, 1:49 "Build a custom calorie app." Okay, you 1:52 got to know your core tech. I mean, 1:54 we're going to be using AIG uh for 1:56 vision or any kind of vision for the 1:59 food recognition. Of course, we want to 2:01 have some kind of nutrition database and 2:02 then AI personalization and then user 2:04 interface things like that, right? So, 2:06 how are we going to turn this app and 2:09 make it so? So, 2:15 see, I'm going to go ahead and plug this 2:17 in right hereable. And let's go ahead 2:19 and see what it 2:22 does. Okay. And of course, here's a 2:24 bystep 2:36 road and uh I've already done a couple 2:39 of apps before but I'm just kind of 2:40 reading through this. So it says we have 2:42 to uh first define the app structure 2:45 pages to build in lovable like it 2:48 mentions the homepage the camera input 2:51 page the meal recognition result log 2:53 book the profile and this is great for a 2:55 setup uh if you haven't built an app 2:57 before and this is a little bit 2:59 confusing uh basically anytime you have 3:01 an app you're going to want to have the 3:02 different pages so that's what that's 3:03 all about there in step two um AI and 3:07 API for food recognition we want to 3:09 teach the AI or have the right 3:11 containers. So that way when the AI 3:14 recognizes the food, we're able to 3:16 properly analyze it, add it up, and 3:19 calculate the response. And uh step 3:22 three is to map the foods to nutrition. 3:24 I think that is a good uh idea. That way 3:27 we don't have to run a web search or a 3:30 web AI response every single time. We 3:32 could have a database for this. And then 3:34 uh meal logging and user dashboard. So 3:37 create a data structure uh is also a 3:40 very good step and easy to do. And then 3:43 number five would be to add some 3:46 personalization and AI feedback which is 3:48 an optional layer but I think that that 3:50 would be great. So and there's some 3:53 other things that we can do as well. 3:54 Let's go ahead and see what Lovable has 3:56 come up with so far. So you can see it 3:59 is already in the process of building uh 4:04 this app and it isn't done. It's 4:06 already, you know, built coded quite a 4:09 lot. Uh, as you can see, it's already 4:13 got to a lot of work. And this lovable 4:17 site, by the way, has already improved 4:19 so much uh since I've already started to 4:22 use it. But I can give you a little bit 4:23 better idea right 4:27 now. Okay. Okay. So, I'm going to come 4:29 back over here to chat GBT and uh let's 4:32 write out some of the exact prompts in 4:34 the steps that I need to and include any 4:36 of the vision prompts as well. So, now 4:39 Chad's going to work. Let's check back 4:41 over here with level. And that is 4:45 amazing. I mean, it it's not done, but 4:48 literally with 4:50 one prompt, and it wasn't even a a good 4:54 prompt, right? We're already able to see 4:56 a dashboard. This is highlighting. Um, 5:00 it actually works. My goodness, I didn't 5:02 think that that was all going to work. 5:04 Okay, so the the settings don't work 5:05 yet, but the home and the history do. 5:09 Uh, you know, these don't really pull up 5:10 all the way, but this is amazing. Right. 5:13 So, you can add a meal manually. Uh, we 5:16 got to get that functionality working. 5:18 You know, you can add a picture, right? 5:20 It's pulling up all my pictures. Oh, 5:23 this is incredible. Okay, so let's go 5:25 ahead and get to the next steps right of 5:29 building out cow AI. Let's see what it 5:32 uh brought me here in chat GBT which 5:36 there's two responses that we got to 5:37 choose from. So let's see 5:40 um it says lovable calorie app 5:42 stepbystep building 5:47 prompts. Okay, 5:49 so you know it already created a lot of 5:51 these 5:53 blocks. Uh, 5:56 so I'm gonna go with the one on the 5:59 right because I 6:02 think actually they're both good for 6:04 different reasons. I'm, you know, I'm 6:06 not really sure. So, I'm not really 6:09 [Music] 6:14 uh Okay, let's just go ahead and select 6:16 the first 6:18 one. We're going to just go ahead and 6:20 run this out. 6:40 Okay. Uh, and this is why some people 6:42 call it bite coding. Um, because 6:45 literally it's just keep it's just about 6:49 trying things until it works, right? And 6:52 uh that's really what coding is too. So 6:55 don't let anybody discourage you by 6:57 saying 6:58 that. But let's go ahead and get this 7:00 working. And I think it's already it was 7:03 functional because I was able to 7:08 uh press on the camera button and it was 7:11 pulling up some food. But let's go ahead 7:13 and test it. Right. 7:17 So I'm going to just pull up a meal 7:19 picture. 7:30 This is going to be a little bit more 7:32 simpler. Let's do this 7:42 one. I got the image download. 7:51 Grilled chicken salad. That's awesome. 7:54 So, uh, this one isn't a grilled chicken 7:57 salad. This is a It looks like a quinoa 7:59 or like a chicken rice bowl. So, I'm 8:03 going to press not this and see what 8:05 happens. Oh, it says no problem. Please 8:07 try again or manually add the meal. Aha. 8:10 So, let's go one more time and see what 8:12 happens if I 8:24 Can I try by manually uh doing 8:30 this? Oh, I see. So, I literally have to 8:32 put in everything, which is cool. Okay, 8:34 that's great. Just see how 8:37 far this one goes. It's going to analyze 8:40 and I 8:44 confirm and then let's see if it gets 8:46 added to the 8:48 log. Uh, it didn't really get added to 8:51 the log yet, but you can see this is 8:53 this is great, right? This is literally 8:55 tracking 8:56 um all the calories and things that you 8:59 would think it should do, right? 9:07 So, I'm going to go back over here and 9:08 all you have to do is when you have an 9:11 error is you have to just basically 9:13 press to try to fix it. It's uh not 9:17 rocket science here, folks. And the AI 9:19 is is amazing and incredible enough to 9:22 be able to build code and then also tell 9:24 you when there's an error. Okay, so we 9:26 got that error fixed. I'm going to go up 9:28 and just see if this one's still an 9:30 error. Then we can go ahead and fix this 9:31 one, too. 9:37 Okay, we got both 9:41 those says uh I need to fix the type 9:44 script error and then it fixed it which 9:46 is good. 9:51 It says there's another error here 9:56 uh or something wrong with the macro 9:57 summary and then the 9:59 index and it says that uh the AI was 10:03 able to fix it but it was not able to 10:05 apply the changes because the code 10:07 changes were the same as previous code. 10:09 So, what happens is is uh 10:14 sometimes like when I fix it, I fix it 10:16 in the wrong order. Uh or sometimes when 10:18 you press a new uh prompt, I I find that 10:23 it tends to fix some of the errors just 10:27 automatically without you having to go 10:29 and press all this try to fix it. So, I 10:31 don't know if your uh experience is 10:33 going to be the same for you, but that's 10:34 what I found out. So, let's go ahead and 10:38 take it to the next step. Okay, because 10:40 now we got the cal AI 10:44 working. And then now we can do uh food 10:47 detection. So, it it did it pretty well 10:50 already. Um, but let's see if we can 10:53 improve 11:04 it. 11:06 functionality is 11:08 working. Okay. So, what we're going to 11:10 want to do is make sure the food 11:12 detection functionality is working. Now, 11:14 it's thinking and it's going to go ahead 11:16 and do its job. So, again, while this is 11:20 thinking, I don't know about you, if 11:23 you're watching this, I'm not sure what 11:25 side of the fence you're on. If you are 11:27 a developer already, curious to hear 11:29 your comments or your thoughts on this. 11:31 Um, but if you're not a developer, if 11:33 you're brand new, if you wanted to 11:35 develop or if you thought that coding 11:37 was going to be impossible and something 11:39 that you'd never be able to do, I'm 11:41 really curious to comment down below. 11:42 What do you want to build? What are the 11:44 thoughts that are coming to your mind 11:45 right now? And, you know, what's going 11:47 to make this easier for you? And maybe, 11:50 you know, maybe I already have answer 11:51 some of these questions or maybe we can 11:53 figure that out together. And that's 11:54 really what this is about, right? All of 11:56 AI and automation is so new to most 11:58 people. 12:00 uh just by even knowing about some of 12:03 these tools, it can completely change 12:05 somebody's life. I know Chad GBT is 12:07 changing a lot of people's life, but 12:09 just like this lovable one, uh there's a 12:11 lot of other softwares that we'll go 12:13 through on this channel. So, by the way, 12:14 if you do like this content or you want 12:17 to see more stuff on AI, automation, and 12:21 how to make your life in personal life, 12:25 work life easier, better, faster, you 12:28 know, more or more results from less 12:30 work actually then go ahead and give me 12:33 a like and uh comment down 12:36 below. Okay, so right now it says let's 12:38 go ahead and implement the GPT4 vision 12:42 based on food 12:43 detection 12:45 and it was able to implement the food 12:48 detection. So it simulates it. All 12:51 right, let's go ahead and try this again 12:53 and see uh if it comes up with something 12:55 different. 12:58 Wow. So, uh, if you notice before it 13:02 just said, um, what was it? Chicken 13:05 breast, uh, grilled chicken breast. But 13:07 now it's coming in a lot more accurately 13:10 with white rice and steamed broccoli. 13:14 So, now we can confirm it's this. It's 13:16 added to the log, but it's not really 13:17 still adding it to the log, but that's 13:19 okay. Let's just go ahead and follow 13:20 along here. 13:24 Um, let's make sure that we have the 13:26 nutrition 13:33 data. Okay. And um, obviously there's a 13:35 lot of ways to do this. This isn't the 13:36 only way, but I'm just showing you how 13:38 with just two apps, Chat GBT and 13:40 Lovable, without being a senior 13:43 developer or really knowing much of 13:44 anything, we can get a working app in 13:49 very short order. And that's what's 13:51 amazing with this. 13:57 Uh I absolutely love Lovable uh and what 14:02 it's able to do because of it. I think 14:03 it's going to absolutely 14:06 change our world. And um I'm all for, 14:11 you know, giving the small guy or the 14:14 underdog the tools to beat the big guy. 14:17 Uh maybe because, you know, I been on 14:20 both sides of the fence. I think it's 14:22 great when you win. Of course, we always 14:23 like to win, but I also think that we 14:25 should let other people win when they 14:27 also have the skills. I have no problem 14:30 winning and then I have no problem 14:33 enjoying other areas of my life. I'll 14:35 put it that way because some people get 14:36 so stuck on you have to win and you have 14:38 to, you know, have this title and 14:41 championship. Um, but anyway, I don't 14:43 want to digress too much, but there 14:45 there's more important, right? 14:47 So, let's go ahead and see 14:50 as lovable gets this work done here. 14:52 Looking at your 14:53 request, you'd like to implement the 14:55 proper nutrition data and it's doing 14:58 that. So, uh it's replacing the current 15:01 mock nutrition database and implementing 15:04 the 15:05 functionality. It already integrated the 15:09 edom API which is amazing. Uh it created 15:13 a new 15:18 function. Let's see. Uh, no, I've left 15:21 the actual API called commented out and 15:23 kept the mock responses for now since 15:25 you would need to provide real API 15:27 credentials. Aha, I see. So, this is if 15:30 I want to actually take it to the next 15:31 step and make that a fully functional um 15:34 app, which I don't need to do right now, 15:36 but we would do before launching 15:38 anything like this. And then let's go 15:41 ahead 15:51 Okay. And then we're going to go ahead 15:52 and create the meal summary 16:02 page. So, as this is thinking for the 16:05 final step, um I there's we're pretty 16:07 much done, right? We can add a 16:08 dashboard, but I think you can kind of 16:11 already get the sense that this is 16:13 amazing. I mean, we can go through this 16:15 or you're more than um welcome to if you 16:19 want. I think they have a free uh 16:21 version of this. So, I'll put the link 16:23 below if you want to try levelable as 16:25 well as um I will share this actual 16:28 project itself if you for whatever 16:30 reason wanted to take uh this project 16:34 and you wanted 16:39 to There we go. Go back. uh if you 16:43 wanted to uh take this on Premiere. I 16:46 made it public so that way you can, you 16:48 know, view it and remix it. So again, 16:51 let me know down in the comments below 16:53 if you uh like this, if you have a 16:55 project in mind that you want to start, 16:56 if you think that there's something 16:58 that's a great idea, or if you just want 17:00 to share uh your feedback or any kind of 17:02 comments you have related to this video 17:04 and what kind of videos, comments 17:09 or softwares you would like me to review 17:12 in the future. Anything have to do with 17:13 AI automation and of course I have a 17:16 passion in health. So, anything on those 17:18 topics, completely open to. Uh, feel 17:22 free to leave a comment 17:23 below, like this video, subscribe to 17:26 this channel if you want to see more 17:27 videos like this, and we'll see you on 17:29 the next one.