I Added Unlimited Image Generation To Claude Code (Nano Banana)

There's one thing getting in the way of AI agents  like Claude Code becoming truly amazing. The ability to generate images until now. I'm going  to show you a simple Python script that Claude Code can understand to always generate images when  you need them for designing websites, iconography, or anything else. You can even use this to change  specific elements of an image like how this rocket ship here can be changed easily into a checkered  flag. All without messing up the rest of the image. claw code is now going to be able to use  nano banana directly and that's going to become your super team. So let's see how it works. Well,  I can show you by first manually calling this code with UV run Python. I'm going to generate a 3D  cube on a black background which uses the API version of nanobanana. Now you will see that  the image is already generated and it saved it to output.png. Pretty cool. Just a random cube,  but it shows you that it works. Now the great part about this is that I can make Claude Code do  this for me. If I open up claw code in here, I can simply drag the readme that instructs the model on  how to use it and then say generate a 3D cube for me. And then what it will do is it will understand  how to call all the right Python scripts in here and generate an image whenever I need to. This  can be useful in so many different ways. If you're generating a front end with Claude code, you can  first brainstorm a couple of different styles without having to just rely on textbased input,  which can often lead to super generic, obviously vibecoded UI designs. But this way, you can  actually generate all kinds of reference images for Claude Code to use when designing websites  or applications. While Claude Code is thinking, I just wanted to let you know that this repository  is available for free in a link in the description below. But don't click on it yet because I first  want to explain how everything works. In this case, we're just creating a simple 3D cube. And  you can see that it's created it like so. But you can see how these two very much differ in style,  right? So, how do we get that consistent? Well, this repository allows you to determine a specific  style that must be used for every single image generation. In this case, I actually have one  style defined here, which will create blue glass 3D objects. Some examples of those are this  one, this one, this one. They're pretty cool 3D objects, right? So now let's try and generate an  image using that style. So I can just say use the blue glass style and claude code will understand  that it needs to now reference this markdown file when it's calling the Python script. You can  see it does it automatically. I didn't even tell it that the markdown file exists but it still  knows where to find it. Now it's going to generate another cube but it's not going to determine  any styling itself. It's simply going to pass along this markdown file which contains a bunch  of style parameters. Now, when we have the new cube 3D image, you can see that it looks pretty  similar to the same style as these previously generated images. What's even better is that you  can even create a new image using one of these images as a reference. This is one of the great  parts of modern image generation using AI, which is something that was not possible years ago. If  you're coding with AI, it's very easy to just go back and and fix things with Git, right? But with  image generation, if something here is messed up or I want to change something like how I might  want to change this rocket emoji to something else, you often will find that AI generation will  mess up the image and just change it completely. With Nano Banana, you can actually make varants  on a specific image and make sure that only the aspect of the image is changed that you actually  want to change. So let me give you an example. I'm going to say going to pass in this image. Change  this image by making nano banana remove the rocket ship replacing it with a finish flag emoji in the  same style. And now you will see that it's going to properly read that image using its own image  OCR capabilities. And then what's going to do is it's going to prompt that same Python file  with the directive to remove the rocket ship. But what's most important to understand here is  that it doesn't just call that API without passing the reference image. No, it's actually passing  4.png as a reference image to Google so that the AI model knows what kind of image it needs to take  as inspiration. Now, if you go to the edited file, you will see that it's pretty much the same thing  and it's properly replaced this one icon with the new flag. funnily enough, it doesn't even know  what nano banana is because it's not that aware of the script. It just knows how to call the  script and it will handle it from there. So, let's have a look at the code so you can actually  understand what is going on here. In main.py, we're using the Gemini 3 Pro image preview API,  which is basically the latest Nano Banana API, and you can change this whatever you want. But  the most important thing to understand here is that we use a bunch of different parameters that  really customize this experience. For example, you can pass your own style, which is just a  markdown file, but you can also pass an edit flag with an input image. And that's basically  what Claude Code did for me to make sure that this edited image uses the exact same style  and just replaces one part of the image. Now, I want to give you a super secret pro tip that  has taken me dozens of hours to understand. So, make sure to pay attention to this. You want  to avoid generating complex gradients in your images because the problem with gradients is that  they make it very difficult for these AI models to edit images without losing a lot of quality.  Here's an example. I have a decently highquality image here with a Python and TypeScript logo  with a nice little gradient. Now, I've asked Gemini to redo this style and change the gradient.  With the first iteration, you can already see, you know, it's changing the gradient properly,  but things are getting a little bit lower quality. I'm actually just going to zoom it in so you  can see the differences more clearly. You can see here that it's starting to get a lot more  grainy, right? And this is only the beginning. With the second iteration, it's starting to  look even worse. The gradient has changed, but the Python logo is looking quite fuzzy. And  in the third iteration, it looks even worse. This is basically unusable if you wanted a high  quality asset. And once your image is this kind of poor quality, it will be very difficult to  rework it using Nano Banana. So that's why you want to avoid creating gradients and instead let  it generate the iconography that you want. Then using something like Canva or Photoshop, you want  to add complex gradients afterwards. In my case, I also generate a bunch of backgrounds that  I simply edit using those tools. And when it comes to text, if you want to, you can add them  at the very end or you can just add them using something like Photoshop because even though  Nano Banana is pretty good at adding text, if you ask it to do many things at once, it will  be pretty poor at doing so. So go ahead and grab the repository in the link in the description  below and know that you can extend it to make it a skill that can be called anywhere or even turn  it into an MCP server. It's all up to you, but I want you to go ahead and try it because that's  the only way that you can actually master this.

🎁 FREE AI Image Agent Repo: https://zenvanriel.com/ai-image-starter-kit ⚡ Master AI and become a high-paid AI Engineer: https://aiengineer.community/join AI agents like Claude Code, Copilot and Cursor have always been missing one crucial ability: generating images. In this video I show you a Python repository that lets Claude Code use Google's Nano Banana API directly. This Claude Code tutorial covers how to generate images, maintain consistent styles across generations, and edit specific parts of images without destroying the rest. This is how AI-assisted design should work. Timestamps: 0:00 AI Agents with Image Generation 0:32 How Python and Claude is used to generate with Nano Banana 1:45 How To Get Consistent Image Style Generation 3:16 Create New Variants of Images 5:05 Pro tip: Avoid gradients for quality Sponsorships & Business Inquiries: business@aiengineer.community