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Frank 55f87fcdce llm: retire the trio service names — fleet services renamed to frank-archon/frank-dragoon/frank-zealot

The 2026-10-09 wire aliases become the service names everywhere:
systemd units, serve scripts, env files and FRANK_* variables,
deploy-plan/deploy-remote service keys, container names, Prometheus
job names + alert rules, Grafana dashboard queries, bats seams,
runbook filenames, homepage/AGENTS lore, and historical prose.
Rollback tags renamed in lockstep. Residue in the tree: zero.
Retired frank-medium/small/npu names are history and stay.

Known casualty: scripts/patches/*.patch context lines were rewritten;
those retired-era vLLM-fork patches no longer apply byte-exact.

2026-10-10 17:03:14 -07:00

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description

ComfyUI Qwen-Image Workflows

Two ready-to-load text-to-image workflows for the Qwen-Image 2.1 payload already on Dankclaw, both proven end-to-end on 2026-10-05 by POSTing to the live API on port 8188 and verifying the rendered PNG. The repo copies are the source of truth; the host copies under /home/dank/comfyui-data/workflows/ are for convenience.

What is on disk

Path (under `/home/dank/comfyui-data/models/`)	Size	Role
`diffusion_models/qwen_image_2.1_int8_convrot.safetensors`	6.8 GB	The one the workflows use — int8-convrot quant, ComfyUI-core native
`diffusion_models/qwen_image_2.1_bf16.safetensors`	14 GB	Full-precision fallback
`diffusion_models/qwen-image-2.1-Q8_0.gguf` (+ `-arch`)	7.1 GB	GGUF alternative (needs ComfyUI-GGUF custom node)
`text_encoders/qwen3vl_8b_w4a8.safetensors`	5.9 GB	The one the workflows use — 4-bit-weights/8-bit-act Qwen3-VL 8B encoder
`text_encoders/qwen3vl_8b_int8_convrot.safetensors`	8.8 GB	Mid quant
`text_encoders/qwen3vl_8b_bf16.safetensors`	17 GB	Full precision
`vae/qwen_image_2.1_vae_bf16.safetensors`	645 MB	2.1 VAE (used)
`vae/qwen_image_vae.safetensors`	243 MB	Smaller VAE

No LoRAs are on disk yet — see Recommended additions.

The workflows

Both are API-format JSON (ComfyUI 0.37 loads them via the UI's Load dialog too): dankclaw/comfyui/workflows/ in the repo, /home/dank/comfyui-data/workflows/ on the host. Node chain in both:

UNETLoader (int8_convrot) ──┐
CLIPLoader (qwen_image, w4a8) ─┤ CLIPTextEncode pos/neg
VAELoader (2.1 bf16) ────────┤
EmptySD3LatentImage ─────────┴─ KSampler ─ VAEDecode ─ SaveImage

Common sampler settings: cfg 1.0 (Qwen-Image 2.1 expects CFG-free sampling), euler + simple, seed fixed in the file.

Workflow	File	Shape	Steps	Made for
Art	`qwen-image-2.1-t2i-art.json`	1024×1024	20	General illustration/prose prompts
Legible text	`qwen-image-2.1-t2i-legible-text.json`	832×1216	25	Posters, captions, any in-image text

Legible-text prompt recipe

Qwen-Image 2.1 is one of the best open-weight text renderers, but only if the prompt is written for it:

Quote the exact strings: large bold white text reading "SOLIDARITY OF THE SOVIET COMPUTER SYSTEMS" — quoted text is rendered literally.
Describe layout, not vibes: say centered / below it / large vs small, the typeface family (sans-serif), and the color.
Say what NOT to draw: end with no other words, no watermark.
Keep the negative side on misspelled, warped letters, extra text (already in the workflow).
More steps help text: the text workflow uses 25 vs 20.

Verified render: SOLIDARITY OF THE SOVIET COMPUTER SYSTEMS + DANKCLAW DANKSERVER EST 2026 came back crisp and correctly spelled at 832×1216 (qwen21-text_00001_.png, 953 KB). One caveat from the same render: a shorter secondary line is where misspellings creep in — proofread the first render before shipping.

Driving it from the API

ComfyUI 0.37 requires the graph wrapped in a prompt key — a bare {node-id: node} body gets {"error": {"type": "no_prompt"}} (verified 2026-10-05):

curl -s -X POST http://127.0.0.1:8188/prompt -H 'Content-Type: application/json' \
  -d "$(python3 -c 'import json;print(json.dumps({"prompt": json.load(open("dankclaw/comfyui/workflows/qwen-image-2.1-t2i-art.json"))}))')"
# -> {"prompt_id": "...", ...}
curl -s http://127.0.0.1:8188/history/<prompt_id>   # status.status_str == "success"

Outputs land in /home/dank/comfyui-data/output/. The queue is FIFO — the two workflows above ran back-to-back unattended.

Note: the container's UI-saved workflows live in the ephemeral /opt/ComfyUI/user layer and do NOT survive an image rebuild — hence the host-side workflows/ dir and the repo copy.

Recommended additions

Quantized preferred, sized for the 8060S iGPU (GTT-backed; the RTX 3090 is frank-zealot's). All repos verified 2026-10-05. None are on disk yet.

#	What	Repo	Grab	Size	Why
1	Lightning 8-step LoRA (T2I speed)	`lightx2v/Qwen-Image-Lightning`	`qwen_image_lightning_8steps_*.safetensors` (LoRA)	~1–2 GB	20 steps → 8 with a `LoraLoader` node; 2–3× faster renders on the iGPU, negligible quality loss
2	Qwen-Image-Edit-2511 GGUF (image editing)	`unsloth/Qwen-Image-Edit-2511-GGUF`	Q4_K_M (~13.2 GB) or Q4_0 (~11.9 GB)	~12–13 GB	Unlocks img2img "edit this photo" workflows — a capability class the fleet has zero of; Q4 keeps it iGPU-friendly
3	DiffSynth ControlNets (structure control)	`Comfy-Org/Qwen-Image-DiffSynth-ControlNets`	`split_files/model_patches/` canny + depth	~2–3 GB each	Pose/edge/depth-guided layouts — pairs with the legible-text workflow for exact poster composition. The `QwenImageDiffsynthControlnet` node is already in the running ComfyUI
4	Wan 2.2 TI2V-5B GGUF (first video model)	`QuantStack/Wan2.2-TI2V-5B-GGUF`	Q4/Q5 GGUF (~6–8 GB)	~6–8 GB	T2V+I2V in one dense 5B model; the gentlest on-ramp into video generation, runs in ComfyUI core (`wan` CLIP type is already in this build's loader enum)

Placement: #1 → models/lora/ (create it), #2 → models/diffusion_models/, #3 → models/controlnet/ (create it), #4 → models/diffusion_models/. Fetch with scripts/download-frank-*.sh discipline (-f + byte-count + sha256 checks) or a plain hf download with the token in the environment — never on the command line.

Skip list: the original city96/Qwen-Image-gguf conversions (superseded by the 2.1 files already on disk), and any BF16 of #2/#4 (the iGPU does not need them at GTT capacity, and they double the disk bill).

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