Vito
48b1292115
* feat(nodes): let a link drive the prompt text of every PromptManager node The Focused, Split and Pair editors hide their widgets, and ComfyUI only draws a widget's input socket while the widget is visible. `text` (and the Pair's `negative_text`) therefore had no socket, and a STRING link dropped on the editor fell through to the first free STRING input, `prepend_text`, which is how #342's workflow was wired. - Detach those inputs from their hidden widgets on create and after a workflow load, so they are ordinary sockets in Classic and Nodes 2.0. The schema, widget order and saved values are unchanged. - A STRING link dropped on the editor body fills the main prompt, then the negative, before the frontend's own choice. - Each editor says when its text comes from a link; the typed text is kept for disconnect. The Classic nodes now save the typed text under a link instead of null, and "use prompt" no longer overwrites it while linked. - Real-host tests: mouse drags in both renderers, a workflow saved before this change, and executions proving the linked text is saved, counted, recorded in history and linked to the run's image. Closes #343 * test(coverage): floor for the linked-text module * test(nodes): PromptSearchList text takes a dragged link like a core widget * fix(nodes): linked text review round for #343 - A legacy frontend Primitive linked to an editor's text or the Pair's negative now runs with its value: the graphToPrompt wrapper and the queue hook fill it in (through virtual reroutes), in new and pre-#343 workflows. - Moving a linked text and releasing it on the editor keeps it on `text`: a link being moved counts as free, as the frontend counts it. - A link dropped on a prompt box (or its link note) fills that box's input, so the Pair's Negative prompt box takes `negative_text` (Classic through getInputOnPos, Nodes 2.0 through the box's slot key). - Only exact STRING links are steered; wildcards keep the frontend choice. - A linked Classic text box gives its row back and gets it back on disconnect; the PromptManagerText note uses the theme colour. - The metadata parsers map positional widget values through the widget table when an editor's widget-bound inputs do not line up with it. - Real-host cases for the legacy Primitive (new and saved workflows, a real Run), the moved link, the Negative box, paste/clone/undo and Split. * fix(nodes): resolve a legacy Primitive's text like the host, once per run (#343) - Inputs still bound to their widget (Classic PromptManager/PromptManagerText) are left as the host resolved them; the injection no longer overwrites them. - For the editors' detached text inputs, the Primitive's value goes through its "Run widget replace on values" replacement and the hidden widget's own serializer, so {a|b} wildcards and %date% tokens resolve as on main. - Each queued output is filled once (graphToPrompt wrapper, or the queue hook for an output that did not come through it): a wildcard is drawn once. - Editors inside subgraphs are found under their <subgraph>:<inner> id. - Real-host runPrompt installs its request route before the run starts. - Shared parser case pins the widget-table fallback for a core KSampler. * fix(nodes): pin the Classic wildcard behaviour and match queued ids by type (#343) - Classic PromptManager/PromptManagerText expose _pmTextSerializerReady, settled once their own text serializer is installed; the real-host specs wait on it and assert the Classic text is queued as written, as on main. - The Primitive fill only touches an output entry whose class_type matches the graph node at that id. - TESTING.md notes the host's harmless "Invalid widget" warning per Run.
551 lines
16 KiB
Python
551 lines
16 KiB
Python
"""Named workflow cases shared by the generation-parameter parser tests.
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Each case is the raw metadata records a file would carry, as text, so the cases
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exercise ``parse_js_json`` as well as the tracing. The JS parity test runs every
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case through the legacy browser parser too. Prompt texts and seeds are invented.
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"""
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import json
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def _text(value):
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return None if value is None else json.dumps(value)
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def case(prompt=None, workflow=None):
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return {"prompt": _text(prompt), "workflow": _text(workflow)}
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def encoder(text, clip=("4", 1)):
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return {
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"class_type": "CLIPTextEncode",
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"inputs": {"text": text, "clip": list(clip)},
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}
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def ksampler(positive, negative, model=("4", 0), **settings):
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inputs = {
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"seed": 5,
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"steps": 20,
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"cfg": 7,
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"sampler_name": "euler",
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"scheduler": "normal",
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"denoise": 1.0,
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"model": list(model),
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"positive": list(positive),
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"negative": list(negative),
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"latent_image": ["2", 0],
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}
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inputs.update(settings)
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return {"class_type": "KSampler", "inputs": inputs}
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CHECKPOINT = {
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"class_type": "CheckpointLoaderSimple",
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"inputs": {"ckpt_name": "example.safetensors"},
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}
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LATENT = {
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"class_type": "EmptyLatentImage",
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"inputs": {"width": 512, "height": 512, "batch_size": 1},
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}
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def _basic():
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return {
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"4": CHECKPOINT,
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"2": LATENT,
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"6": encoder("a cat on a windowsill"),
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"7": encoder("blurry, watermark"),
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"3": ksampler(("6", 0), ("7", 0)),
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"9": {"class_type": "SaveImage", "inputs": {"images": ["8", 0]}},
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}
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def _prompt_manager(text, prepend="", append=""):
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return {
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"class_type": "PromptManager",
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"inputs": {
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"text": text,
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"category": "",
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"tags": "",
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"search_text": "",
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"prepend_text": prepend,
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"append_text": append,
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"clip": ["4", 1],
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},
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}
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def _shared_prompt_pipeline():
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"""One PromptManager pair feeds a base pass, an upscale pass and a detailer."""
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return {
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"1": CHECKPOINT,
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"5": ksampler(
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("25", 0),
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("26", 0),
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("1", 0),
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seed=111,
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steps=4,
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cfg=1.0,
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sampler_name="lcm",
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latent_image=["20", 0],
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),
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"6": {
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"class_type": "VAEDecode",
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"inputs": {"samples": ["5", 0], "vae": ["1", 2]},
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},
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"11": {
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"class_type": "VAEEncode",
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"inputs": {"pixels": ["6", 0], "vae": ["1", 2]},
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},
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"12": ksampler(
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("25", 0),
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("26", 0),
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("1", 0),
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seed=222,
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steps=6,
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cfg=1.0,
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sampler_name="lcm",
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denoise=0.45,
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latent_image=["11", 0],
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),
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"13": {
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"class_type": "VAEDecode",
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"inputs": {"samples": ["12", 0], "vae": ["1", 2]},
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},
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"17": {
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"class_type": "FaceDetailer",
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"inputs": {
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"seed": 333,
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"steps": 4,
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"cfg": 1.0,
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"sampler_name": "lcm",
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"image": ["13", 0],
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"model": ["1", 0],
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"clip": ["1", 1],
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"vae": ["1", 2],
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"positive": ["25", 0],
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"negative": ["26", 0],
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},
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},
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"20": {
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"class_type": "EmptyLatentImage",
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"inputs": {"width": 640, "height": 1536, "batch_size": 1},
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},
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"25": _prompt_manager("a lighthouse at dusk, oil painting"),
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"26": _prompt_manager("blurry, watermark"),
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"48": {
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"class_type": "KikoSaveImage",
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"inputs": {"filename_prefix": ["49", 0], "images": ["17", 0]},
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},
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"49": {
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"class_type": "KikoProjectFilePath",
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"inputs": {"project_name": "example"},
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},
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}
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def _custom_sampler(guider):
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return {
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"13": CHECKPOINT,
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"20": encoder("a red fox in snow", clip=("13", 1)),
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"21": encoder("lowres", clip=("13", 1)),
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"22": guider,
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"25": {"class_type": "RandomNoise", "inputs": {"noise_seed": 42}},
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"16": {"class_type": "KSamplerSelect", "inputs": {"sampler_name": "dpmpp_2m"}},
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"17": {
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"class_type": "BasicScheduler",
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"inputs": {
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"scheduler": "karras",
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"steps": 8,
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"denoise": 1.0,
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"model": ["13", 0],
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},
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},
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"1300:8": {
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"class_type": "SamplerCustomAdvanced",
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"inputs": {
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"noise": ["25", 0],
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"guider": ["22", 0],
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"sampler": ["16", 0],
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"sigmas": ["17", 0],
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"latent_image": ["5", 0],
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},
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},
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}
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def _workflow_only():
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return {
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"nodes": [
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{
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"id": 4,
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"type": "CheckpointLoaderSimple",
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"mode": 0,
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"inputs": [],
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"widgets_values": ["example.safetensors"],
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},
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{
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"id": 6,
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"type": "CLIPTextEncode",
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"mode": 0,
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"inputs": [{"name": "clip", "link": 3}],
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"widgets_values": ["a tidepool at noon"],
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},
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{
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"id": 7,
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"type": "CLIPTextEncode",
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"mode": 0,
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"inputs": [{"name": "clip", "link": 5}],
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"widgets_values": ["noisy"],
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},
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{
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"id": 10,
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"type": "Reroute",
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"mode": 0,
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"inputs": [{"name": "", "link": 7}],
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},
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{
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"id": 3,
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"type": "KSampler",
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"mode": 0,
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"inputs": [
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{"name": "model", "link": 1},
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{"name": "positive", "link": 8},
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{"name": "negative", "link": 4},
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{"name": "latent_image", "link": 2},
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],
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"widgets_values": [314, "randomize", 25, 6.5, "dpmpp_2m", "karras", 1],
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},
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{
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"id": 11,
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"type": "CLIPTextEncode",
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"mode": 2,
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"inputs": [],
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"widgets_values": ["muted node text"],
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},
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],
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"links": [
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[1, 4, 0, 3, 0, "MODEL"],
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[3, 4, 1, 6, 0, "CLIP"],
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[5, 4, 1, 7, 0, "CLIP"],
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[7, 6, 0, 10, 0, "CONDITIONING"],
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[8, 10, 0, 3, 1, "CONDITIONING"],
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[4, 7, 0, 3, 2, "CONDITIONING"],
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{
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"id": 2,
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"origin_id": 99,
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"origin_slot": 0,
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"target_id": 3,
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"target_slot": 3,
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"type": "LATENT",
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},
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],
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}
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def _detached_editor_text(pair):
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"""#343: editor text inputs are sockets, not widget inputs; no named values."""
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names = ["text"] + (["negative_text"] if pair else [])
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sockets = [
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{"name": "clip", "link": 3},
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{"name": "prepend_text", "link": None},
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{"name": "append_text", "link": None},
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]
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sockets += [{"name": name, "link": None} for name in names]
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sockets += [
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{"name": name, "widget": {"name": name}, "link": None}
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for name in ("category", "tags", "search_text")
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]
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editor = {
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"id": 6,
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"type": "PromptManagerPair" if pair else "PromptManagerFocused",
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"mode": 0,
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"inputs": sockets,
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"widgets_values": ["a detached positive"]
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+ (["a detached negative"] if pair else [])
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+ ["a category", "a tag", "", "", ""],
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}
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negative = (
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[]
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if pair
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else [
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{
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"id": 7,
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"type": "CLIPTextEncode",
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"mode": 0,
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"inputs": [{"name": "clip", "link": 5}],
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"widgets_values": ["plain negative"],
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}
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]
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)
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return {
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"nodes": [
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{
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"id": 4,
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"type": "CheckpointLoaderSimple",
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"mode": 0,
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"inputs": [],
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"widgets_values": ["example.safetensors"],
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},
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editor,
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*negative,
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{
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"id": 3,
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"type": "KSampler",
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"mode": 0,
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"inputs": [
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{"name": "model", "link": 1},
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{"name": "positive", "link": 8},
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{"name": "negative", "link": 4},
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],
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"widgets_values": [7, "fixed", 12, 5, "euler", "normal", 1],
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},
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],
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"links": [
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[1, 4, 0, 3, 0, "MODEL"],
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[3, 4, 1, 6, 0, "CLIP"],
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[5, 4, 1, 7, 0, "CLIP"],
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[8, 6, 0, 3, 1, "CONDITIONING"],
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[4, 6 if pair else 7, 1 if pair else 0, 3, 2, "CONDITIONING"],
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],
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}
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def _core_widget_input_out_of_order():
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"""#343 review R4: a core KSampler whose only widget input is ``cfg``.
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Older frontends saved only converted or linked widget inputs, so the list
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is not a prefix of the schema and carries no named values; the positional
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values must still land on the schema's names.
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"""
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workflow = _detached_editor_text(False)
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sampler = workflow["nodes"][-1]
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sampler["inputs"] = sampler["inputs"] + [
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{"name": "cfg", "widget": {"name": "cfg"}, "link": None}
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]
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sampler["widgets_values"] = [9, "fixed", 30, 4.5, "dpmpp_2m", "karras", 1]
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return workflow
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def _nested(depth):
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"""A value nested ``depth`` arrays deep, as a crafted file can hold."""
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value = ["leaf", 7]
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for _ in range(depth):
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value = [value, None]
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return value
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def _chain(length):
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graph = {"4": CHECKPOINT, "1": encoder("deep chain text")}
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previous = "1"
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for index in range(length):
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node_id = str(100 + index)
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graph[node_id] = {
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"class_type": "ConditioningPass",
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"inputs": {"conditioning": [previous, 0]},
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}
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previous = node_id
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graph["3"] = ksampler((previous, 0), ("1", 0))
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return graph
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CASES = {
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"basic": case(_basic()),
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"prompt-manager-prepend-append": case(
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{
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"4": CHECKPOINT,
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"6": _prompt_manager("a cat", prepend="masterpiece", append="4k"),
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"7": _prompt_manager(
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"masterpiece, a dog", prepend="masterpiece", append="4k"
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),
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"3": ksampler(("6", 0), ("7", 0)),
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}
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),
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"linked-text-concat": case(
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{
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"4": CHECKPOINT,
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"10": {"class_type": "PrimitiveString", "inputs": {"value": "first part"}},
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"11": {
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"class_type": "StringConcatenate",
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"inputs": {
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"string_a": ["10", 0],
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"string_b": "second part",
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"delimiter": ", ",
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"seed": 3,
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"string_c": " ",
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},
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},
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"6": {
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"class_type": "CLIPTextEncode",
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"inputs": {"text": ["11", 0], "clip": ["4", 1]},
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},
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"7": encoder(""),
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"3": ksampler(("6", 0), ("7", 0)),
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}
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),
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"prompt-manager-pair": case(
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{
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"4": CHECKPOINT,
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"8": {
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"class_type": "PromptManagerPair",
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"inputs": {
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"text": "pair positive",
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"negative_text": "pair negative",
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"prepend_text": "",
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"append_text": "",
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"clip": ["4", 1],
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},
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},
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"3": ksampler(("8", 0), ("8", 1)),
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}
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),
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"conditioning-passthrough": case(
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{
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"4": CHECKPOINT,
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"6": encoder("through a controlnet"),
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"7": encoder("negative through it"),
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"12": {
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"class_type": "ControlNetApplyAdvanced",
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"inputs": {
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"positive": ["6", 0],
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"negative": ["7", 0],
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"control_net": ["13", 0],
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},
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},
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"3": ksampler(("12", 0), ("12", 1)),
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}
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),
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"first-sampler-in-js-key-order": case(
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{
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"4": CHECKPOINT,
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"6": encoder("from sampler twelve"),
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"7": encoder("from sampler five"),
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"x": ksampler(("6", 0), ("6", 0)),
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"12": ksampler(("6", 0), ("6", 0), seed=12),
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"5": ksampler(("7", 0), ("7", 0), seed=55),
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}
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),
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"custom-sampler-cfg-guider": case(
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_custom_sampler(
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{
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"class_type": "CFGGuider",
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"inputs": {
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"model": ["13", 0],
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"positive": ["20", 0],
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"negative": ["21", 0],
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"cfg": 3.5,
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},
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}
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)
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),
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"custom-sampler-basic-guider": case(
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_custom_sampler(
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{
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"class_type": "BasicGuider",
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"inputs": {"model": ["13", 0], "conditioning": ["20", 0]},
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}
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)
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),
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"no-sampler-loose-settings": case(
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{
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"4": CHECKPOINT,
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"3": {
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"class_type": "MyKSamplerVariant",
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"inputs": {
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"noise_seed": 9,
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"steps": 12,
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"cfg": 2,
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"sampler_name": "ddim",
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},
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},
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}
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),
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"primitive-seed": case(
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{
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"4": CHECKPOINT,
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"6": encoder("seeded"),
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"30": {
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"class_type": "Seed (rgthree)",
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"inputs": {"other": "x", "seed": 77},
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},
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"3": ksampler(("6", 0), ("6", 0), seed=["30", 0]),
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}
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),
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"workflow-only": case(workflow=_workflow_only()),
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"workflow-only-detached-editor-text": case(workflow=_detached_editor_text(False)),
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"workflow-only-detached-pair-text": case(workflow=_detached_editor_text(True)),
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"workflow-only-core-widget-input-out-of-order": case(
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workflow=_core_widget_input_out_of_order()
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),
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"overwritten-prompt-manager-text": case(
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{
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"4": CHECKPOINT,
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|
"25": _prompt_manager("same saved text"),
|
|
"26": _prompt_manager("same saved text"),
|
|
"3": ksampler(("25", 0), ("26", 0)),
|
|
},
|
|
{
|
|
"nodes": [
|
|
{
|
|
"id": 25,
|
|
"type": "PromptManager",
|
|
"widgets_values": ["the real positive"],
|
|
},
|
|
{
|
|
"id": 26,
|
|
"type": "PromptManager",
|
|
"widgets_values": ["the real negative"],
|
|
},
|
|
],
|
|
"links": [],
|
|
},
|
|
),
|
|
"conditioning-cycle": case(
|
|
{
|
|
"4": CHECKPOINT,
|
|
"20": {
|
|
"class_type": "ConditioningCombine",
|
|
"inputs": {"conditioning_1": ["21", 0]},
|
|
},
|
|
"21": {
|
|
"class_type": "ConditioningCombine",
|
|
"inputs": {"conditioning_1": ["20", 0]},
|
|
},
|
|
"3": ksampler(("20", 0), ("21", 0)),
|
|
}
|
|
),
|
|
"chain-within-visit-limit": case(_chain(450)),
|
|
"chain-beyond-visit-limit": case(_chain(600)),
|
|
"chain-at-last-visit": case(_chain(499)),
|
|
"chain-one-past-last-visit": case(_chain(500)),
|
|
"blank-text-and-zero-seed": case(
|
|
{
|
|
"4": CHECKPOINT,
|
|
"6": encoder(" "),
|
|
"7": encoder("kept negative"),
|
|
"3": ksampler(("6", 0), ("7", 0), seed=0),
|
|
}
|
|
),
|
|
"shared-prompt-pipeline": case(_shared_prompt_pipeline()),
|
|
"null-workflow-node": case(_basic(), {"nodes": [None], "links": []}),
|
|
"unparsable-records": {"prompt": '{"3": NaN}', "workflow": "not json"},
|
|
"seed-beyond-double-precision": case(
|
|
{
|
|
"4": CHECKPOINT,
|
|
"6": encoder("x"),
|
|
"3": ksampler(("6", 0), ("6", 0), cfg=1.0, seed=4974052037430000001),
|
|
}
|
|
),
|
|
"deeply-nested-values": case(
|
|
{
|
|
"4": CHECKPOINT,
|
|
"6": encoder("nested neighbours"),
|
|
"3": ksampler(("6", 0), ("6", 0)),
|
|
"8": {"class_type": _nested(900), "inputs": {"text": "x"}},
|
|
},
|
|
{"nodes": [{"id": _nested(900), "type": _nested(900)}], "links": []},
|
|
),
|
|
"nothing": case(),
|
|
}
|