DrawThings Image Generation
Generate images with DrawThings (Stable Diffusion) via API. Use when creating images from text prompts, running image generation workflows, or batch generating images. DrawThings runs locally on Mac w
Description
name: drawthings description: Generate images with DrawThings (Stable Diffusion) via API. Use when creating images from text prompts, running image generation workflows, or batch generating images. DrawThings runs locally on Mac with MLX/CoreML acceleration. metadata: openclaw: emoji: "🎨" requires: env: ["DRAWTHINGS_URL"]
DrawThings Image Generation
Generate images using DrawThings, a local Stable Diffusion implementation for Mac with MLX/CoreML acceleration. DrawThings exposes an Automatic1111-compatible API for programmatic image generation.
When to Use
Use this skill when you need to:
- Generate images from text prompts
- Create variations of a concept
- Batch generate multiple images
- Test different models/samplers/settings
- Generate images with specific dimensions or quality settings
Configuration
Set the DRAWTHINGS_URL environment variable (defaults to http://127.0.0.1:7860):
export DRAWTHINGS_URL="http://127.0.0.1:7860"
Or configure in OpenClaw:
openclaw config set env.DRAWTHINGS_URL "http://127.0.0.1:7860"
Quick Start
Generate a single image:
python3 scripts/generate.py "a cyberpunk cat in neon city"
With custom settings:
python3 scripts/generate.py "a cyberpunk cat" \
--steps 20 \
--cfg-scale 7.5 \
--width 768 \
--height 768 \
--sampler "DPM++ 2M Karras"
Batch generation (5 variations):
python3 scripts/generate.py "a fantasy landscape" --batch-size 5
Save to specific location:
python3 scripts/generate.py "portrait photo" --output ./outputs/portrait.png
API Usage
The skill provides a Python script that wraps the DrawThings API (Automatic1111-compatible):
Main endpoint: POST /sdapi/v1/txt2img
Common parameters:
prompt- Text description of the imagenegative_prompt- What to avoid in the imagesteps- Number of diffusion steps (8-50, default: 20)sampler_name- Sampler algorithm (default: "DPM++ 2M Karras")cfg_scale- Classifier-free guidance scale (1.0-20.0, default: 7.0)width/height- Image dimensions (default: 512x512)batch_size- Number of images to generate (default: 1)seed- Random seed for reproducibility (-1 for random)
See references/api-reference.md for complete API documentation.
Presets
Fast (8 steps, UniPC Trailing):
python3 scripts/generate.py "your prompt" --preset fast
Quality (30 steps, DPM++ 2M Karras):
python3 scripts/generate.py "your prompt" --preset quality
NFT (optimized for 512x512 with good detail):
python3 scripts/generate.py "your prompt" --preset nft
Workflow Examples
Character variations:
python3 scripts/generate.py "electric sheep, glowing wool, cyberpunk" \
--batch-size 10 \
--steps 20 \
--cfg-scale 7.5
High-res output:
python3 scripts/generate.py "detailed portrait" \
--width 1024 \
--height 1024 \
--steps 30 \
--sampler "DPM++ 2M Karras"
Reproducible generation:
python3 scripts/generate.py "landscape" --seed 42
# Re-run with same seed for identical output
Output
Images are saved as PNG files with metadata embedded:
- Prompt, negative prompt
- Generation parameters (steps, sampler, cfg_scale, etc.)
- Timestamp and seed
Default location: ./drawthings_output_YYYYMMDD_HHMMSS.png
Troubleshooting
"Connection refused"
- Ensure DrawThings is running
- Check the API server is enabled in DrawThings preferences
- Verify the port matches (default: 7860)
"Generation failed"
- Check prompt length (max ~75 tokens per CLIP model)
- Reduce dimensions if out of memory
- Try a different sampler
Slow generation
- Use fewer steps (8-12 for drafts)
- Reduce image dimensions (512x512)
- Use faster samplers (UniPC, Euler A)
Canvas display quirk (visual only)
- DrawThings UI doesn't clear the canvas between generations
- New images appear to render on top of previous ones in the app
- This is purely cosmetic - API outputs are unaffected
Tips
- CFG Scale: Lower (1-3) for creative/artistic, higher (7-12) for prompt adherence
- Steps: 8-12 for drafts, 20-30 for final images, 50+ rarely needed
- Samplers: UniPC/Euler A are fast, DPM++ 2M Karras is quality, LCM for ultra-fast
- Dimensions: Keep to multiples of 64 (512, 768, 1024)
- Batch processing: Use
--batch-sizefor variations, not multiple script calls
Models
DrawThings supports Stable Diffusion models. To change models:
- Open DrawThings app
- Select model from the UI
- The API will use the currently selected model
See references/models.md for recommended models and download sources.
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