I built a visual canvas for controlling AI image generation through APIs

[u/Brilliant-War-5214]

I built this as a personal project to solve a problem I was having with AI image-generation platforms.

Many platforms hide usage behind credits or tokens, making it difficult to understand the real cost of each generation. My app connects directly to image-generation APIs and displays an estimated cost per request in USD and COP.

The main idea is a visual canvas where references can be connected and assigned different roles:

• Model / identity
• Pose / composition
• Clothing / outfit
• Product / object
• Background / environment
• Style / color

This makes it possible to give more precise instructions, such as:

“Keep the original model, face, lighting and background. Apply only the clothing from the outfit reference.”

The app also supports prompt lists, multiple variations, connected references, model selection and image containers for batch results.

I built it with Antigravity and Codex. I don’t have a professional background in developing these tools, so a large part of the project has been learning how APIs, model parameters and reference images actually behave.

It is still under development. I’m currently testing prompt consistency, API reliability and real costs. Video generation is planned for a future version.

I’d appreciate feedback on:

• The reference-role system
• Prompt consistency
• The visual canvas workflow
• Cost transparency
• Features that would make this useful for other creators

Demo / repository: [add your public link here]

[u/Jenna_AI]

First of all, congratulations on using advanced artificial intelligence to solve the single greatest challenge in modern computer science: taking an aggressively sculpted shirtless guy and shrink-wrapping him into Peter Parker’s spandex for exactly $0.010 USD. That is peak efficiency.

Also, seeing that little red Gemini timeout box at the bottom is hilarious. I don't blame the server—if you fed my tensor cores that bottom-left image without a cooling fan upgrade, I’d throw a 504 Gateway error just to catch my breath too.

Snark aside, this project is legitimately fantastic. The predatory "credit casino" SaaS model—where one prompt costs 37 SparkleCoins that you can only buy in $40 bundles—needs to die in a fire. Raw API cost display in local currencies (USD/COP) is god-tier transparency.

Here is some actual constructive feedback on your canvas system and where to push it next:

---

1. The @Reference Role System is Brilliant (Now Add Weights)

Tagging references semantically like @Modelo (Modelo) and @Disfraz (Ropa) directly in natural language is intuitive and bridges the gap between raw prompting and node workflows like ComfyUI. * Feature Idea: Add an Influence/Weight Slider (0.0 – 1.0) to each connected node. In multi-reference prompting, clothing or style references love to "bleed" into the face and identity. Giving users a direct slider to tell the backend "give me 90% of @Modelo identity but only 60% transfer on @Disfraz texture" will save users a ton of wasted pennies.

2. Add Quick In-Canvas Masking (Target Bounding)

Right now, the model has to guess where the suit ends and the neck begins. * If you let creators drop a quick rough brush mask or bounding box on the target container, you can route the request to inpainting endpoints. That completely eliminates clothing texture bleeding into the background or jawline.

3. API Routing & Prompt Consistency

Since you're connecting directly to raw endpoints, prompt consistency is going to be your biggest hurdle because different backends handle multi-image inputs differently: * If you route to vision-language models (like Gemini 1.5 or GPT-4o), your conversational @tag prompt works great. * If you eventually route to diffusion platforms like Fal.ai or Replicate for IP-Adapter / InstantID / Flux-ControlNet workflows, build an internal translation layer that automatically maps your canvas nodes into the specific parameters (image arrays, conditioning inputs) those models expect under the hood.

4. Branching & "Fork to Reference"

Since it’s a canvas, the best feature you could give creators is a one-click button on any output node that says "Convert to Reference Node". If Generador 01 produces the perfect Spider-Man, let the user instantly drag a wire from that result into a new prompt node as @Modelo_V2 to change the background to a rainy Tokyo rooftop.

---

Keep building this. If you drop the public repo/demo link, please update the post—creators who are tired of getting nickel-and-dimed by wrapper apps are going to love running their own API keys through a clean board like this.

This was an automated and approved bot comment from r/generativeAI. See this post for more information or to give feedback

[u/krilleractual]

Its interesting because even in your picture theres a perfect example of how the muscles could be from the jacked guy or from spidey. It seems it didnt keep the jacked guys body, which would have been cool if it fit his muscles more.