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1tsnakers

OllamaDiffuser Image generation

by 1TSnakers · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install ollamadiffuser
Description
Local AI image generation using OllamaDiffuser. Use this skill when Claude needs to generate, edit (img2img/inpaint), or control (ControlNet) images locally...
README (SKILL.md)

OllamaDiffuser

OllamaDiffuser is a local AI image generation tool that provides an Ollama-like experience for Stable Diffusion and FLUX models. It can be interfaced via CLI, REST API, or MCP.

Setup & Installation

If the tool is not yet installed or needs specific hardware support, use these commands:

  • Standard Installation: pip install ollamadiffuser
  • Full Suite (Recommended): pip install "ollamadiffuser[full]"
  • Low-VRAM/GGUF Support: pip install "ollamadiffuser[gguf]"
  • MCP/Agent Integration: pip install "ollamadiffuser[mcp]"
  • Apple Silicon (Metal): CMAKE_ARGS="-DSD_METAL=ON" pip install stable-diffusion-cpp-python

Authentication: Gated models (e.g., FLUX.1-dev, SD 3.5) require a Hugging Face token.

  • export HF_TOKEN=your_token_here (Add to .bashrc or .zshrc for persistence).

Core Workflows

1. Text-to-Image Generation

Generate an image from a text prompt.

  • Tool/Command: Use the generate_image MCP tool or the REST API /api/generate.
  • Key Parameters:
    • prompt: Detailed description of the image.
    • width / height: Default is usually 1024x1024 for SDXL/FLUX, 512x512 for SD1.5.
    • seed: Optional for reproducibility.
    • response_format: Set to b64_json for agent-friendly base64 responses.

2. Model Management

Manage which models are downloaded and active in VRAM.

  • Listing Models: Use list_models to see installed versions.
  • Pulling Models: Use ollamadiffuser pull \x3Cmodel-name> via shell.
  • Loading Models: Use load_model to switch active models in memory.
  • Recommendations: Use ollamadiffuser recommend to find models that fit the available GPU VRAM.

3. Image-to-Image & Inpainting

Modify existing images.

  • Img2Img: Use /api/generate/img2img. Requires image (file/base64) and strength (0.0-1.0; lower = closer to original).
  • Inpainting: Use /api/generate/inpaint. Requires image and a mask image.

4. Advanced Control (ControlNet)

Use structural guides (Canny, Depth, OpenPose) for precise control.

  • Workflow:
    1. Ensure a ControlNet model is pulled (e.g., ollamadiffuser pull controlnet-canny-sd15).
    2. Use /api/generate/controlnet.
    3. Provide a control_image and specify the preprocessor (e.g., "canny").

Model Selection Guide

Use Case Recommended Model VRAM Note
Highest Quality flux.1-dev 20GB+ Requires HF Token
Fast & High Quality flux.1-schnell 16GB+ No token needed
Budget GPU (6GB) flux.1-dev-gguf-q4ks 6GB GGUF Quantized
Ultra Low VRAM flux.1-dev-gguf-q2k 3GB Entry-level
Classic/Fast stable-diffusion-1.5 4GB+ Great for img2img
Photorealistic realvisxl-v4 6GB+ SDXL based

Technical Notes

  • API Base URL: http://localhost:8000
  • Web UI: http://localhost:8001 (Start with ollamadiffuser --mode ui)
  • HF Tokens: Gated models (FLUX.1-dev, SD 3.5) require export HF_TOKEN=your_token.
  • GGUF Support: Install with pip install "ollamadiffuser[gguf]" for memory-efficient runs.
Usage Guidance
Before installing, confirm you trust the OllamaDiffuser and related Python packages, run installs in an isolated environment, approve any large model downloads, and only persist a Hugging Face token if you need gated models.
Capability Analysis
Type: OpenClaw Skill Name: ollamadiffuser Version: 1.0.0 The skill bundle provides documentation and instructions for 'ollamadiffuser', a local AI image generation tool. The SKILL.md file outlines standard installation procedures via pip, model management, and local API usage (localhost:8000). There are no indicators of malicious intent, data exfiltration, or harmful prompt injection; the mention of Hugging Face tokens (HF_TOKEN) is consistent with standard practices for accessing gated AI models.
Capability Assessment
Purpose & Capability
The instructions align with the stated purpose of generating, editing, and controlling images locally using OllamaDiffuser, Stable Diffusion, FLUX, and related local APIs.
Instruction Scope
The skill tells the agent to use local CLI, REST API, and MCP-style workflows, including package installation and model pulls. These are purpose-aligned, but users should approve installs and large model downloads.
Install Mechanism
There is no install spec, but SKILL.md recommends unpinned pip installs for OllamaDiffuser and related extras. This is expected for the purpose, but the package provenance is not reviewed in the provided artifacts.
Credentials
The skill uses localhost services and local GPU/disk resources, which are proportionate for local image generation, but model pulls and full-suite installs may be large.
Persistence & Privilege
The only persistence guidance is storing an optional Hugging Face token in shell startup files for gated models. This is disclosed and purpose-aligned, but it expands where the token is available.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install ollamadiffuser
  3. After installation, invoke the skill by name or use /ollamadiffuser
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of ollamadiffuser skill. - Provides local AI image generation using OllamaDiffuser with support for Stable Diffusion, FLUX, and GGUF models. - Supports text-to-image, image-to-image (img2img), inpainting, and ControlNet structural guidance workflows. - Allows local model management: install, list, and load models, including VRAM-optimized recommendations. - Integrates with local REST API and command-line interface for flexible usage. - Explains setup, authentication, and hardware-specific installation options.
Metadata
Slug ollamadiffuser
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is OllamaDiffuser Image generation?

Local AI image generation using OllamaDiffuser. Use this skill when Claude needs to generate, edit (img2img/inpaint), or control (ControlNet) images locally... It is an AI Agent Skill for Claude Code / OpenClaw, with 21 downloads so far.

How do I install OllamaDiffuser Image generation?

Run "/install ollamadiffuser" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is OllamaDiffuser Image generation free?

Yes, OllamaDiffuser Image generation is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does OllamaDiffuser Image generation support?

OllamaDiffuser Image generation is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created OllamaDiffuser Image generation?

It is built and maintained by 1TSnakers (@1tsnakers); the current version is v1.0.0.

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