The SD 3D Model Generator is an innovative creative tool that bridges the gap between simple text inputs and fully developed 3D assets for game development, visualization, and creative prototyping. Unlike traditional Stable Diffusion (SD) frontends, this application accelerates the entire workflow by integrating advanced Large Language Models (LLMs):
Prompts are automatically optimized, seamless (topic-relevant) environment maps are generated, images of objects or characters are created and transformed into high-quality 3D models – all in an intuitive interface where you can view images as well as 3D models with environment maps.

What sets the tool apart?

• Prompt-to-Asset, End-to-End: Simply enter an object name or concept – the system guides you through the process, optimizing your prompt for Stable Diffusion via LLM, ensuring stylistic consistency, creative details, and optimal formatting.
• Simplified 3D Workflow: Generated images can be converted to 3D models (GLB) with one click. Additionally, a custom panorama environment (HDRI) can be created for each asset, ready to use in Blender or game engines.
• No prompt experience needed: The LLMs in the backend automatically transform rough ideas into professional, detailed prompts – saving time and reducing creative effort.
• Integrated Gallery & Batch Generation: Extensive collections of images and models can be efficiently managed through batch control, page navigation, and comparison view.

Features & User Experience

• Easy input, professional result: A simple object title (“low poly farmer”) is sufficient – the system uses LLMs to automatically optimize the Stable Diffusion prompts and always delivers the best possible image quality, composition, and clarity.
• Real-time streaming: LLM and image generation results are streamed live to the interface – for transparency and quick feedback.
• Intuitive galleries: Separate, tab-based galleries for 2D images and 3D models – assets can be compared, managed in batch, or edited directly. Context menus allow instant export, reuse of generation results, or direct model/HDRI creation.
• Automatic 3D model creation: Each generated image can be directly converted into a 3D GLB model via the UI (through external tools/scripts, flexibly configurable).
• Automatic environment map creation: A custom equirectangular HDRI environment can be generated for each model: LLMs first describe a suitable environment, then SD creates a photorealistic panorama for lighting and reflections.
• Batch control & placeholders: Support for batch image creation, placeholder management, and clear regeneration – keeping the current progress always traceable.
• One-click export to Blender: Models and HDRIs can be opened and further edited directly from the application in Blender.

Technical Overview

• Frontend:
  • Pure HTML/CSS/JavaScript, seamlessly integrated via PyWebview for direct access to the Python backend.
  • Dynamic, responsive UI logic for gallery, tabs, and context menus.
  • Live streaming of LLM outputs and image generation status via Python–JS bridge.
• Backend:
  • Python backend based on PyWebview and a FastAPI-like interface.
  • Integration of Ollama or local LLM servers (e.g., Mistral) for automatic prompt optimization and summarization.
  • Image generation via Stable Diffusion (diffusers library), all parameters (model, VAE, sampler, etc.) are user-configurable or set automatically.
  • External tools/scripts for converting images to 3D (GLB) and creating HDRI panoramas are modular and easily interchangeable.
  • Automatic file management, metadata embedding (JSON in PNG and sidecars), and monitoring of asset folders for live updates in the gallery.
• Extensibility:
  • Each backend process is decoupled and scriptable: The 3D conversion or HDRI creation can easily be replaced with custom pipelines.
  • Easily adaptable for different LLMs, SD models, or 3D workflows.

The SD 3D Model Generator radically simplifies the path from idea to finished asset. By combining LLMs, Stable Diffusion, and automated 3D workflows, artists, designers, and developers can generate, manage, and process high-quality visuals faster, more flexibly, and more creatively.