Remove LTX sampler options and reorganize README by family
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GenorTG
@@ -1,8 +1,75 @@
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# ComfyUI PromptForge
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Prompt enhancement split into three focused nodes: model/config, prompt generation, and a standalone config finder.
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One pack for three model families: **Krea 2**, **MOSS Image** and **MiniMax H3**, plus shared prompt, loader,
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sampler and video tooling. Each family has its own workflows, presets and setup notes below; the shared node
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reference follows them.
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## Nodes
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- **Krea 2** — realistic and anime text-to-image, identity edit, and face transfer.
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- **MOSS Image** — text-to-image and reference edit, with optional DMD accelerators.
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- **MiniMax H3** — text/reference to video with sound, action presets, endless multi-part generation.
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- **Shared** — loader, sampler with model-aware presets, enhancer, action library, image/video loaders, savers.
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## Krea 2
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Required extras: `comfyui-krea2edit`, `krea2-nag` (only for the transfer workflow) and the Krea 2 models you
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own. The LoRA node starts with the identity LoRA selected in the edit workflow.
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### Workflows
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- `KREA2_T2I_v2.json` — text to image at 1.5 MP. Write in `prompt_text`, pick an action or switch `use_action`
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off, then queue.
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- `KREA2_EDIT_v8.json` — identity edit from `LoadImage`; the face comes from the picture. Write only the change
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(pose, framing, expression) in `prompt_text`.
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- `KREA TRANSFER.json` — face transfer between a source and a target picture.
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### Settings
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Use the `Krea` presets in the sampler list: FinePorn 8-10 steps, cfg 1, `euler`/`simple`; turbo checkpoints
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8 steps. Krea edit keeps identity best at 8-10 steps because the identity LoRA does the work, not more steps.
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### Negative prompts at cfg 1
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`use_negative` on the encode node is the NAG switch. Off: the negative is ignored and the run takes the fast
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cfg-1 path. On: the sampler runs the uncond pass and applies normalized attention guidance at cfg 1, without
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changing cfg. Krea edit no longer uses a separate NAG node; the encoder and sampler handle it.
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## MOSS Image
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Required extras: ComfyUI with MOSS support, `ComfyUI-MOSS-Toolkit`, `moss_image_edit_lora_rank_64_bf16.safetensors`
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for edit, and the MOSS models. Edit always keeps one reference image and `denoise 1`: the reference is
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conditioning, not an img2img latent.
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### Workflows
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- `MOSS_T2I_v2.json` — text to image at 1.5 MP.
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- `MOSS_EDIT_v3.json` — reference edit; pick the picture in `LoadImage`, write the change.
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### Settings and DMD
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Use the `MOSS` presets, matched to the model. Editing keeps the face at `image_strength` 1.5-2.0 with 20 steps,
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cfg 2, `euler`/`normal`. The DMD LoRAs (`lodestones-8-steps`, `sft-4-steps`) run at 8 steps, cfg 1,
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`er_sde`/`simple`; on PrimeLust use 12 steps and cfg 1.5. A denoise below 0.8 tiles the edit result.
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## MiniMax H3
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Required extras: the H3 model, its VAE and an audio VAE. The `PromptForge_H3_AllInOne_Modes_v5.json` workflow
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covers all modes; switch them in the Modes node.
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### Action node and roles
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57 acts, each with an explicit who-is-where description and a recommended 9:16 or 16:9 frame. Every role has
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its own picture picker (Woman, Man, Partner): choose the reference slot, the first frame, none and only a
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description, or `disabled`. Subject 3 defaults to `disabled`; pictures left unassigned become anatomy/detail
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references, not extra people. See the [H3 Action reference](#promptforge-h3-action-adult-presets).
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### Writer and API
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The writer settings (template, style, sampling, retries) are described under the
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[Prompt Enhancer](#promptforge-enhancer-promptforge_promptenhancer). For headless use,
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`PromptForge_H3_AllInOne_Modes_v5.api.json` is already in `/prompt` format; the normal workflow stores the
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image picker as an extra leading widget, which order-based converters must skip.
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## Shared node reference
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### PromptForge Model (`PROMPTFORGE_Model`)
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@@ -13,13 +80,6 @@ Owns model choice and runtime configuration; outputs a `MODEL` bundle and a `REP
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- **Quant fallback**: unsupported combinations warn and use a working option — q5/q6 on safetensors load as q8, q8/q4 on a single-file encoder load in fp16, q8 switches to q4 when free VRAM is insufficient, CPU-offloaded layers are allowed (slower) instead of raising, a missing GGUF quant falls through the available files, and an incompatible KV/flash/SWA choice is retried with the safe value. The report re-checks local availability at run time, so stale `[AVAILABLE]` widget labels still show `[LOCAL]`.
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### Example image workflows
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The pack does not bundle workflows; they live in your ComfyUI `user/default/workflows` folder.
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- `KREA2_T2I_v2.json`, `KREA2_EDIT_v8.json` — Krea 2 text-to-image and identity edit, built on PromptForge Action and Enhancer. Edit needs `comfyui-krea2edit`, `krea2-nag` and the `krea2_identity_edit_v2` LoRA.
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- `MOSS_T2I_v2.json`, `MOSS_EDIT_v3.json` — MOSS-Image text-to-image and image edit. Edit needs ComfyUI 0.43+, `ComfyUI-MOSS-Toolkit` and `moss_image_edit_lora_rank_64_bf16.safetensors`. The edit workflow uses `task = custom` with full-size reference on purpose: the native ComfyUI MOSS model needs a full-size reference.
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### PromptForge Action (`PROMPTFORGE_ImageAction`)
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A pose library for any image model: 90 named actions (portraits, SFW solo and couple poses, nude and
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@@ -156,6 +216,8 @@ The Choose image picker, and an **Images** tab in the left sidebar, share one li
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### Endless Video (category `🔮 PromptForge/Endless Video`)
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Makes a long MiniMax H3 video part by part. One node does the generating (**PromptForge H3 Endless Video**); small nodes plug into it, and every one of them is optional except the Story. The generator saves nothing: it outputs `frames` (IMAGE), `audio`, `prompts` and `report`, so you save them with PromptForge Save Video (or anything else) afterwards. A ready all-in-one workflow (`PromptForge_H3_AllInOne_Modes_v5.json`) is provided separately, in your workflow folder: text to video, image to video, characters / references, voice, extending an existing video, first-pass preview and endless multi-part video in one graph; you switch modes by bypassing the optional nodes (its READ ME note lists which). (The old `H3 Endless` and `H3 Options` nodes are gone; workflows built with them need rewiring.)
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### PromptForge H3 Action (adult presets)
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| Node | What it holds |
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|---|---|
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| **H3 Modes** | What writes the prompt (`prompt_source`: my idea or action preset; the other node is ignored) and what kind of video: **T2V** (text only, empty latent), **I2V** (first frame encoded and anchored at frame 0), **L2V** (last frame anchored at the end), **FL2V** (both), **REF2V** (pictures, videos and sounds encoded as references). Also one clip or several parts, extend an existing video, second stage on/off. Its overview lists the files chosen in the Load nodes with a tick for each; rows the mode does not use are dimmed. Each mode also picks its prompt template (T2VA, I2VA, L2VA, FL2VA, Ref2VA). |
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+1
-1
@@ -1,7 +1,7 @@
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[project]
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name = "ComfyUI-PromptForge"
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description = "ComfyUI prompt enhancement suite: model/config node with GPU-aware auto settings, prompt enhancer with a preset catalog, and a standalone config finder."
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version = "1.28.16"
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version = "1.28.17"
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license = { file = "LICENSE" }
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dependencies = [
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"transformers",
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+12
-23
@@ -4,7 +4,7 @@ It runs ComfyUI's own `comfy.sample.sample`, so every sampler, scheduler, model
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the stock nodes. On top of that:
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* `scheduler = auto` picks the family's schedule (LTX Video's token-count dependent one, otherwise simple),
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* sigmas can come from a SIGMAS input, a typed list, or the LTXV schedule with its parameters,
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* sigmas can come from a SIGMAS input or a typed list,
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* `runs` samples several seeds in one go and returns them as one batch,
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* settings can be saved as named presets, and recommended settings come from the model's sidecar and family
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(see sampler_defaults.py).
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@@ -22,12 +22,11 @@ import comfy.samplers
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import comfy.utils
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import folder_paths
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import latent_preview
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from comfy_extras import nodes_easycache, nodes_lt
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from comfy_extras import nodes_easycache
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from . import families, sampler_defaults
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AUTO = "auto"
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LTXV = "ltxv"
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PRESET_FIELDS = ("steps", "cfg", "sampler_name", "scheduler", "denoise", "runs", "step_cache", "cache_threshold")
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# step caching skips whole model calls, which only pays off (and only stays clean) with enough steps
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AUTO_CACHE_MIN_STEPS = 15
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@@ -110,11 +109,6 @@ def parse_sigmas(text):
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return torch.tensor(values, dtype=torch.float32)
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def trim_for_denoise(sigmas, steps):
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"""Keep the last `steps` intervals, which is what denoise < 1 means for a schedule computed at steps / denoise."""
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return sigmas[-(steps + 1):]
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class PROMPTFORGE_Sampler:
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@classmethod
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def INPUT_TYPES(cls):
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@@ -128,7 +122,7 @@ class PROMPTFORGE_Sampler:
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"steps": ("INT", {"default": 20, "min": 1, "max": 10000}),
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"cfg": ("FLOAT", {"default": 4.0, "min": 0.0, "max": 100.0, "step": 0.1, "round": 0.01}),
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"sampler_name": (comfy.samplers.KSampler.SAMPLERS, {"default": "euler"}),
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"scheduler": ([AUTO, LTXV] + comfy.samplers.KSampler.SCHEDULERS, {"default": AUTO, "tooltip": "auto: the family's schedule (ltxv for LTX Video, otherwise simple). ltxv: LTX Video's token-count dependent schedule."}),
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"scheduler": ([AUTO] + comfy.samplers.KSampler.SCHEDULERS, {"default": AUTO, "tooltip": "auto uses a simple schedule."}),
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"denoise": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}),
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"runs": ("INT", {"default": 1, "min": 1, "max": 64, "tooltip": "Samples this many seeds (seed, seed+1 ...) and returns them as one batch."}),
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},
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@@ -143,9 +137,6 @@ class PROMPTFORGE_Sampler:
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"start_at_step": ("INT", {"default": 0, "min": 0, "max": 10000, "advanced": True}),
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"end_at_step": ("INT", {"default": 10000, "min": 0, "max": 10000, "advanced": True}),
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"add_noise": ("BOOLEAN", {"default": True, "advanced": True}),
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"ltxv_max_shift": ("FLOAT", {"default": 2.05, "min": 0.0, "max": 100.0, "step": 0.01, "advanced": True}),
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"ltxv_base_shift": ("FLOAT", {"default": 0.95, "min": 0.0, "max": 100.0, "step": 0.01, "advanced": True}),
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"ltxv_terminal": ("FLOAT", {"default": 0.1, "min": 0.0, "max": 0.99, "step": 0.01, "advanced": True}),
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"preview": (["default", "taesd", "latent2rgb", "none"], {"default": "default", "tooltip": "Live preview while sampling. default follows ComfyUI's --preview-method; taesd uses the model's tiny decoder when it is in models/vae_approx (taeh3 for MiniMax H3) and latent2rgb otherwise."}),
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},
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}
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@@ -164,21 +155,17 @@ class PROMPTFORGE_Sampler:
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family = families.family_from_config(type(config).__name__) if config is not None else None
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return family.key if family else ""
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def _sigmas(self, model, sampler_name, scheduler, steps, denoise, latent_image, sigmas, custom_sigmas, shifts):
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"""The sigmas to sample with: an input, a typed list, the LTXV schedule, or the named scheduler's."""
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def _sigmas(self, model, sampler_name, scheduler, steps, denoise, sigmas, custom_sigmas):
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"""The sigmas to sample with: an input, a typed list, or the named scheduler's."""
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if sigmas is not None:
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return sigmas
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if custom_sigmas.strip():
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return parse_sigmas(custom_sigmas)
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if scheduler == LTXV:
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total = max(steps, int(steps / denoise)) if denoise > 0 else steps
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schedule = nodes_lt.LTXVScheduler.execute(total, shifts[0], shifts[1], True, shifts[2], {"samples": latent_image}).args[0]
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return trim_for_denoise(schedule, steps)
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return comfy.samplers.KSampler(model, steps=steps, device=model.load_device, sampler=sampler_name, scheduler=scheduler, denoise=denoise, model_options=model.model_options).sigmas
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def sample(self, model, positive, negative, latent_image, seed, steps, cfg, sampler_name, scheduler, denoise, runs,
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pipe=None, sigmas=None, custom_sigmas="", step_cache="off", cache_threshold=0.2, cache_start=0.15, cache_end=0.95,
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start_at_step=0, end_at_step=10000, add_noise=True, ltxv_max_shift=2.05, ltxv_base_shift=0.95, ltxv_terminal=0.1, preview="default"):
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start_at_step=0, end_at_step=10000, add_noise=True, preview="default"):
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family = self._family(model, pipe)
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if cfg <= 1.0 and any(len(cond) > 1 and cond[1].get("promptforge_use_negative") for cond in negative):
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# the negative is real: force the uncond pass and guide with NAG instead of changing cfg
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@@ -191,17 +178,18 @@ class PROMPTFORGE_Sampler:
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if step_cache != "off":
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model = CACHES[step_cache].execute(model, cache_threshold, cache_start, cache_end, False).args[0]
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if scheduler == AUTO:
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scheduler = LTXV if family == "ltxv" else "simple"
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scheduler = "simple"
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samples = comfy.sample.fix_empty_latent_channels(model, latent_image["samples"], latent_image.get("downscale_ratio_spacial"), latent_image.get("downscale_ratio_temporal"))
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used = self._sigmas(model, sampler_name, scheduler, steps, denoise, samples, sigmas, custom_sigmas, (ltxv_max_shift, ltxv_base_shift, ltxv_terminal))
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used = self._sigmas(model, sampler_name, scheduler, steps, denoise, sigmas, custom_sigmas)
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if runs > 1 and not isinstance(samples, torch.Tensor):
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raise ValueError("[PromptForge] runs > 1 needs a plain latent; this model uses a combined audio+video latent.")
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device = comfy.model_management.get_torch_device()
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if device.type == "cuda":
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torch.cuda.reset_peak_memory_stats(device)
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latent_preview.set_preview_method(None if preview == "default" else preview)
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if preview != "default":
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latent_preview.set_preview_method(preview)
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try:
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try:
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callback = latent_preview.prepare_callback(model, steps)
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@@ -221,7 +209,8 @@ class PROMPTFORGE_Sampler:
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last_step=end_at_step if end_at_step < steps else None, force_full_denoise=end_at_step >= steps,
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noise_mask=latent_image.get("noise_mask"), sigmas=used, callback=callback, disable_pbar=not progress, seed=current))
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finally:
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latent_preview.set_preview_method()
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if preview != "default":
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latent_preview.set_preview_method()
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merged = results[0] if runs == 1 else torch.cat(results)
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out = latent_image.copy()
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