Maintained by Geekatplay Studio — the console logs and node helpers now surface the Geekatplay branding so you can spot them quickly in shared setups.

This repo is cleaned to a focused setup:

four production workflows
checkpoint + LoRA flow
flux split-component flow (diffusion model + VAE + text encoders)
image-guided variants using Ollama vision analysis

model_registry.json is intentionally kept as the long-term reference registry.

Included Nodes

Exported custom nodes:

OllamaPromptPlanner
OllamaVisionStylePlanner
DynamicCheckpointLoader
DynamicLoraStack
PreviewTextMerge
LiveStatus

Workflows

All workflows are in workflows/:

workflows/ollama_text_checkpoint_lora.json
workflows/ollama_text_flux_split_lora.json
workflows/ollama_image_checkpoint_lora.json
workflows/ollama_image_flux_split_lora.json

Details are documented in docs/WORKFLOWS.md.

Install

Start Ollama and ensure your model is available (for example qwen2.5:7b and llava:7b).
Run:

install.bat

The installer will show all checkpoints/VAEs/text encoders/LoRAs from install_manifest.json with descriptions and NSFW flags. Pick what you want via the checkbox selector (Out-GridView) or the console fallback.
If gated Hugging Face models are required, set:

set HF_TOKEN=your_hf_token

Installer behavior and model paths are documented in docs/INSTALL.md.

Notes

Flux split workflows expect:
- diffusion model in models/diffusion_models/
- VAE in models/vae/
- text encoders in models/text_encoders/
LoRA loading uses models/loras/.
DynamicCheckpointLoader fallback now respects per-model folder_type from model_registry.json.
Console logging is prefixed with Geekatplay Studio | OllamaRouter to make routing messages easy to spot.