DemonGatanjieuandClaude Fable 5.2
d6c2edb1a1
Found in a Gemini Flash exam (recorded in tool-exam.md): - A later step's mask preview (only the character redrawn) was taken for a base; picked, the rest enlarged the mask. A base is the decoded picture itself. - Flash tries run_workflow with no arguments: on a blueprint just built that drew three bases of nothing and spent the three to pick from. A run that draws from an empty latent with every positive prompt empty is refused once. - A Tile refused for not fitting: when the user named the model, the AI is told to ask before changing it. - A decision's rejected option given as a sentence stays one option. Co-Authored-By: Claude Fable 5.2 <noreply@anthropic.com>
117 lines
7.8 KiB
JavaScript
117 lines
7.8 KiB
JavaScript
import assert from 'node:assert/strict';
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import { baseOnly, onKeptBase } from '../web/modules/base_only.js';
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const loaders = {
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1: { class_type: 'UNETLoader', inputs: { unet_name: 'a.safetensors', weight_dtype: 'default' } },
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5: { class_type: 'CLIPLoader', inputs: { clip_name: 'te.safetensors', type: 'stable_diffusion' } },
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8: { class_type: 'VAELoader', inputs: { vae_name: 'vae.safetensors' } },
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2: { class_type: 'CLIPTextEncode', inputs: { text: 'a lake', clip: ['5', 0] } },
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3: { class_type: 'CLIPTextEncode', inputs: { text: '', clip: ['5', 0] } },
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6: { class_type: 'EmptyLatentImage', inputs: { width: 832, height: 1216, batch_size: 1 } },
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};
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const advanced = (model, latent, start, end, leftover) => ({
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class_type: 'KSamplerAdvanced', inputs: {
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model: [model, 0], positive: ['2', 0], negative: ['3', 0], latent_image: [latent, 0], add_noise: 'enable',
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noise_seed: 7, steps: 35, start_at_step: start, end_at_step: end, return_with_leftover_noise: leftover,
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},
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});
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// The two-pass card: the base is decoded and saved, then encoded, enlarged and redrawn by a second model under Tile.
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{
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const output = {
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...loaders, 30: { class_type: 'UNETLoader', inputs: { unet_name: 'b.safetensors', weight_dtype: 'default' } },
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32: advanced('1', '6', 0, 35, 'disable'),
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7: { class_type: 'VAEDecodeTiled', inputs: { samples: ['32', 0], vae: ['8', 0], tile_size: 512 } },
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9: { class_type: 'SaveImage', inputs: { images: ['7', 0], filename_prefix: 'two_pass/base' } },
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10: { class_type: 'VAEEncodeTiled', inputs: { pixels: ['7', 0], vae: ['8', 0] } },
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11: { class_type: 'LatentUpscaleBy', inputs: { samples: ['10', 0], scale_by: 1.5 } },
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18: { class_type: 'AnimaLLLiteApply', inputs: { model: ['30', 0], image: ['7', 0] } },
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19: { class_type: 'KSampler', inputs: { model: ['18', 0], positive: ['2', 0], negative: ['3', 0], latent_image: ['11', 0], seed: 3, denoise: 0.85 } },
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20: { class_type: 'VAEDecodeTiled', inputs: { samples: ['19', 0], vae: ['8', 0] } },
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21: { class_type: 'ColorMatch', inputs: { image_ref: ['7', 0], image_target: ['20', 0] } },
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22: { class_type: 'SaveImage', inputs: { images: ['21', 0], filename_prefix: 'two_pass/upscaled' } },
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};
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const before = JSON.stringify(output);
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const got = baseOnly(output);
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assert.equal(JSON.stringify(output), before, 'the queued prompt is cut down in a copy');
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assert.deepEqual(got.bases, [{ node: '32', type: 'KSamplerAdvanced', names: ['noise_seed'] }]);
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assert.deepEqual(got.shows, ['9']);
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assert.deepEqual(got.saved, ['9'], 'the full run saves this base again: it can be compared');
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assert.equal(got.prefix, 'two_pass/base');
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assert.deepEqual(Object.keys(got.output).sort(), ['1', '2', '3', '32', '5', '6', '7', '8', '9']);
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assert.deepEqual(got.output[9], { class_type: 'PreviewImage', inputs: { images: ['7', 0] } });
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assert.equal(got.output[32], output[32], 'a base that finishes on its own runs as it is: the same picture');
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// The run after the pick: the second pass takes the kept picture wherever it took the base's, the base is not drawn again.
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const kept = onKeptBase(output, 'anomalous_reference_abc.png');
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assert.deepEqual(kept[33], { class_type: 'LoadImage', inputs: { image: 'anomalous_reference_abc.png' } });
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assert.deepEqual([kept[10].inputs.pixels, kept[18].inputs.image, kept[21].inputs.image_ref], [['33', 0], ['33', 0], ['33', 0]]);
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assert.deepEqual(kept[21].inputs.image_target, ['20', 0]);
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assert.deepEqual(Object.keys(kept).sort(), ['10', '11', '18', '19', '2', '20', '21', '22', '3', '30', '33', '5', '8'], 'the base model and its empty latent are not loaded');
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assert.equal(JSON.stringify(output), before, 'the queued prompt is changed in a copy');
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}
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// A later step that previews a mask cut from the base (only the character redrawn): the mask is no base to pick.
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{
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const output = {
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...loaders,
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32: advanced('1', '6', 0, 35, 'disable'),
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7: { class_type: 'VAEDecode', inputs: { samples: ['32', 0], vae: ['8', 0] } },
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9: { class_type: 'SaveImage', inputs: { images: ['7', 0], filename_prefix: 'picture' } },
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40: { class_type: 'InspyrenetRembg', inputs: { image: ['7', 0] } },
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41: { class_type: 'MaskToImage', inputs: { mask: ['40', 1] } },
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42: { class_type: 'PreviewImage', inputs: { images: ['41', 0] } },
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43: { class_type: 'VAEEncode', inputs: { pixels: ['7', 0], vae: ['8', 0] } },
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44: { class_type: 'SetLatentNoiseMask', inputs: { samples: ['43', 0], mask: ['40', 1] } },
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45: { class_type: 'KSampler', inputs: { model: ['1', 0], positive: ['2', 0], negative: ['3', 0], latent_image: ['44', 0], seed: 5, denoise: 0.7 } },
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46: { class_type: 'VAEDecode', inputs: { samples: ['45', 0], vae: ['8', 0] } },
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47: { class_type: 'SaveImage', inputs: { images: ['46', 0], filename_prefix: 'upscaled_character' } },
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};
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const got = baseOnly(output);
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assert.deepEqual(got.shows, ['9'], 'the base alone, not the mask preview');
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assert.deepEqual(Object.keys(got.output).sort(), ['1', '2', '3', '32', '5', '6', '7', '8', '9'], 'nothing is cut out for a base to pick');
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const kept = onKeptBase(output, 'kept.png');
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assert.deepEqual([kept[40].inputs.image, kept[43].inputs.pixels], [['48', 0], ['48', 0]], 'the rest cuts and redraws the kept picture');
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assert.ok(kept[42] && kept[47] && !kept[32] && !kept[9], 'the mask preview is the rest\'s, the base is not drawn again');
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}
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// The mid-way switch: the first model hands its unfinished latent to the second; the base is finished and decoded to show.
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{
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const output = {
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...loaders, 30: { class_type: 'UNETLoader', inputs: { unet_name: 'b.safetensors', weight_dtype: 'default' } },
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32: advanced('1', '6', 0, 21, 'enable'), 33: { ...advanced('30', '32', 21, 10000, 'disable') },
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7: { class_type: 'VAEDecodeTiled', inputs: { samples: ['33', 0], vae: ['8', 0], tile_size: 512 } },
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9: { class_type: 'SaveImage', inputs: { images: ['7', 0], filename_prefix: 'relay' } },
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};
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output[33].inputs.add_noise = 'disable';
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const got = baseOnly(output);
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assert.deepEqual(got.bases.map(base => base.node), ['32']);
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assert.deepEqual(got.shows, ['35']);
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assert.deepEqual(got.saved, [], 'the full run never shows this base');
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assert.equal(got.prefix, '');
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assert.deepEqual(got.output[34], { class_type: 'VAEDecodeTiled', inputs: { samples: ['32', 0], vae: ['8', 0], tile_size: 512 } },
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'decoded as the canvas decodes');
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assert.deepEqual(got.output[35], { class_type: 'PreviewImage', inputs: { images: ['34', 0] } });
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assert.equal(got.output[32].inputs.end_at_step, 10000);
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assert.equal(got.output[32].inputs.return_with_leftover_noise, 'disable');
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assert.equal(output[32].inputs.end_at_step, 21, 'the canvas prompt keeps its switch');
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assert.equal(onKeptBase(output, 'kept.png'), null, 'a latent handed on cannot come from a picture: drawn again from its seed');
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assert.deepEqual(Object.keys(got.output).sort(), ['1', '2', '3', '32', '34', '35', '5', '6', '8']);
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}
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// One pass only: the whole picture, shown and not saved.
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{
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const output = {
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...loaders, 4: { class_type: 'KSampler', inputs: { model: ['1', 0], positive: ['2', 0], negative: ['3', 0], latent_image: ['6', 0], seed: 1 } },
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7: { class_type: 'VAEDecode', inputs: { samples: ['4', 0], vae: ['8', 0] } },
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9: { class_type: 'SaveImage', inputs: { images: ['7', 0], filename_prefix: 'ComfyUI' } },
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};
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const got = baseOnly(output);
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assert.deepEqual(got.bases, [{ node: '4', type: 'KSampler', names: ['seed'] }]);
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assert.equal(got.output[9].class_type, 'PreviewImage');
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assert.equal(onKeptBase(output, 'kept.png'), null, 'nothing after the base');
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}
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assert.throws(() => baseOnly({ ...loaders }), /No sampler/);
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console.log('base_only: ok');
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