ai-toolkit-trainer
Train custom LoRAs with ostris AI-Toolkit. Covers WAN 2.2/2.1 (people, styles, video motion) and Z-Image (Turbo & Base, low-VRAM image LoRAs). Use when the…
Build Krea 2 Turbo txt2img workflows with the native krea2 CLIPLoader, Qwen3-VL encoder, Qwen image VAE, 8-step turbo settings, and Ideogram-style JSON prompting
$ npx -y skills add artokun/comfyui-mcp --skill krea2-txt2img --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/krea2-txt2imgContext preview
The summary Claude sees to decide when to auto-load this skill.
Build Krea 2 Turbo txt2img workflows with the native krea2 CLIPLoader, Qwen3-VL encoder, Qwen image VAE, 8-step turbo settings, and Ideogram-style JSON prompting
name: krea2-txt2img description: Build Krea 2 Turbo txt2img workflows with the native krea2 CLIPLoader, Qwen3-VL encoder, Qwen image VAE, 8-step turbo settings, and Ideogram-style JSON prompting globs: - "**/*.json"
Krea 2 is a **12B-parameter Diffusion Transformer** from Krea.ai (released June 2026, weights open-sourced under the Krea 2 Community License, free commercial use up to 50 seats). Two variants:
1. **Krea 2 Raw** is the base checkpoint before extra post-training. For fine-tuning / maximum fidelity, more steps. 2. **Krea 2 Turbo** is post-trained and **distilled**; it generates in **~8 steps at cfg 1**. This is what the krea2 txt2img packs ship.
Sliced from the **KREA2 ULTRA V2** monolith into standalone single-pipeline packs. Pick by how you prompt and what you want:
(`Ideogram4PromptBuilderKJ`).
refine (denoise 0.3), with the krea2 **turbo LoRA** @0.2 on both passes plus the optional **IdeoKrea** LoRA. JSON/Ideogram-style prompting; saves both passes to compare.
Each pack's one prompt source is active (no prompt-mode bypass to flip). `ImageSharpenKJ` runs before `SaveImage`. **V2** adds the `Krea2T-Enhancer` MODEL detail-boost patch (ships **active**) and drops v1's `ConditioningKrea2Rebalance`. `RBG_Smart_Seed_Variance` ships **bypassed** (optional, see below).
Krea 2 has **native ComfyUI support** (`comfy/text_encoders/krea2.py`, ComfyUI ≥ v0.26.0). The `CLIPLoader` uses **`type=krea2`**, with a **Qwen3-VL 4B** text encoder and the **Qwen image VAE**. The Qwen3-VL encoder drives strong prompt adherence and structured-JSON prompts.
| Slot | File | Notes | |---|---|---| | `diffusion_models/` | `krea2_turbo_fp8.safetensors` | 12B Turbo, fp8 — RTX 4000/3000/2000 | | `diffusion_models/` | `krea2_turbo_mxfp8.safetensors` | RTX 5000 (Blackwell) native fp8 | | `text_encoders/` | `qwen3vl_4b_fp8_scaled.safetensors` | Qwen3-VL 4B encoder | | `vae/` | `qwen_image_vae.safetensors` | Qwen image VAE | | `loras/` | `krea2_turbo_lora_rank_64_bf16.safetensors` | turbo LoRA — **combo** only, @0.2 both passes | | `loras/` | `IdeoKrea-test.safetensors` | OPTIONAL Ideogram-style LoRA (`Aitrepreneur/IdeoKrea`) — combo add-in |
(qwen_image_vae), wired via KJNodes `SetNode`/`GetNode` buses into a subgraph (`CLIPTextEncode` → `KSampler` → `VAEDecode`). An rgthree `Any Switch` sits in front of the encoder; in each pack only that pack's prompt source is wired to it (manual node in `-manual`, JSON builder in `-json`).
detail-boost patch, wired in the model path (PowerLora → Krea2T-Enhancer → sampler). Ships **active**; bypass to compare against the un-boosted result.
**bypassed** in the positive-conditioning loop.
VAE-roundtrip resize).
prompt-mode bypass to flip.
sits inline in the model path and ships **active** in all three packs. Widgets are `[on, strength, …]`; bypass it (or toggle `on`) to A/B the boost.
FIRST PASS (8 steps, `er_sde`, denoise 1) → VAE roundtrip → SECOND PASS (4 steps, `euler`, denoise **0.3**), with the **turbo LoRA** @0.2 on both passes. It SAVES BOTH passes so you can see the boost. The **IdeoKrea** LoRA is downloaded but NOT wired by default. Drop it into the Power Lora Loader's empty slot (start ~0.5 to 1.0; it's a test LoRA) for the turbo + IdeoKrea Ideogram-style combo.
All packs leave `RBG_Smart_Seed_Variance` in the positive-conditioning loop **bypassed** (passthrough). Un-bypass on the live canvas with `panel_set_node_mode` (or in the UI) for controlled variations of the same prompt without changing the composition. Set its seed mode to `randomize` and tune the variance mode (e.g. `🌿 Balanced`) / strength widgets. Leave bypassed for a deterministic result.
Like Ideogram 4, Krea 2's Qwen3-VL encoder reads structured prompts (per-region desc + bounding boxes + palettes). For structured prompting use the **`krea2-txt2img-json`** pack; its `Ideogram4PromptBuilderKJ` drives the encoder directly (no bypass to flip). After the render, VERIFY the image matches the JSON you set (view it) BEFORE continuing; if it doesn't, a field is probably stale. Fix and rerun. Gotchas learned the hard way:
`technical`, `style`, `lighting` (widgets 3/5/6/7). Leaving stale values leaks content (a leftover celebrity portrait bled into a tea still-life).
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This project is no longer maintained. ComfyUI now ships official agent and MCP tooling — Comfy Agent and Comfy MCP — built and supported by the Comfy-Org team with deeper integration than a community project can match.
Repo: artokun/comfyui-mcp
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Core ComfyUI knowledge covering workflow format, node types, pipeline patterns, and MCP tool usage