File size: 20,143 Bytes
1e3b872
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
__author__ = "receyuki"
__filename__ = "comfyui.py"
__copyright__ = "Copyright 2023"
__email__ = "receyuki@gmail.com"

import json

from ..format.base_format import BaseFormat
from ..utility import remove_quotes, merge_dict


class ComfyUI(BaseFormat):
    # comfyui node types
    KSAMPLER_TYPES = ["KSampler", "KSamplerAdvanced"]
    VAE_ENCODE_TYPE = ["VAEEncode", "VAEEncodeForInpaint"]
    CHECKPOINT_LOADER_TYPE = [
        "CheckpointLoader",
        "CheckpointLoaderSimple",
        "unCLIPCheckpointLoader",
        "Checkpoint Loader (Simple)",
    ]
    CLIP_TEXT_ENCODE_TYPE = [
        "CLIPTextEncode",
        "CLIPTextEncodeSDXL",
        "CLIPTextEncodeSDXLRefiner",
    ]
    SAVE_IMAGE_TYPE = ["SaveImage", "Image Save", "SDPromptSaver"]

    SETTING_KEY = [
        "ckpt_name",
        "sampler_name",
        "",
        "cfg",
        "steps",
        "",
    ]

    def __init__(
        self, info: dict = None, raw: str = "", width: int = None, height: int = None
    ):
        super().__init__(info, raw, width, height)
        self._comfy_png()

    def _comfy_png(self):
        prompt = self._info.get("prompt", {})
        workflow = self._info.get("workflow", {})
        prompt_json = json.loads(prompt)

        # find end node of each flow
        end_nodes = list(
            filter(
                lambda item: item[-1].get("class_type")
                in ["SaveImage"] + ComfyUI.KSAMPLER_TYPES,
                prompt_json.items(),
            )
        )
        longest_flow = {}
        longest_nodes = []
        longest_flow_len = 0

        # traverse each flow from the end
        for end_node in end_nodes:
            flow, nodes = self._comfy_traverse(prompt_json, str(end_node[0]))
            if len(nodes) > longest_flow_len:
                longest_flow = flow
                longest_nodes = nodes
                longest_flow_len = len(nodes)

        if not self._is_sdxl:
            self._raw = "\n".join(
                [
                    self._positive.strip(),
                    self._negative.strip(),
                ]
            ).strip()
        else:
            sdxl_keys = ["Clip G", "Clip L", "Refiner"]
            self._raw = "\n".join(
                [
                    self._positive_sdxl.get(key).strip()
                    for key in sdxl_keys
                    if self._positive_sdxl.get(key)
                ]
                + [
                    self._negative_sdxl.get(key).strip()
                    for key in sdxl_keys
                    if self._negative_sdxl.get(key)
                ]
            )
        self._raw += "\n" + str(prompt)
        if workflow:
            self._raw += "\n" + str(workflow)

        add_noise = (
            f"Add noise: {remove_quotes(longest_flow.get('add_noise'))}"
            if longest_flow.get("add_noise")
            else ""
        )

        seed = (
            f"Seed: {longest_flow.get('seed')}"
            if longest_flow.get("seed")
            else f"Noise seed: {longest_flow.get('noise_seed')}"
        )

        start_at_step = (
            f"Start at step: {longest_flow.get('start_at_step')}"
            if longest_flow.get("start_at_step")
            else ""
        )

        end_at_step = (
            f"End at step: {longest_flow.get('end_at_step')}"
            if longest_flow.get("end_at_step")
            else ""
        )

        return_with_left_over_noise = (
            f"Return with left over noise: {longest_flow.get('return_with_left_over_noise')}"
            if longest_flow.get("return_with_left_over_noise")
            else ""
        )

        denoise = (
            f"Denoise: {longest_flow.get('denoise')}"
            if longest_flow.get("denoise")
            else ""
        )

        upscale_method = (
            f"Upscale method: {remove_quotes(longest_flow.get('upscale_method'))}"
            if longest_flow.get("upscale_method")
            else ""
        )

        upscaler = (
            f"Upscaler: {remove_quotes(longest_flow.get('upscaler'))}"
            if longest_flow.get("upscaler")
            else ""
        )

        self._setting = ", ".join(
            list(
                filter(
                    lambda item: item != "",
                    [
                        f"Steps: {longest_flow.get('steps')}",
                        f"Sampler: {remove_quotes(longest_flow.get('sampler_name'))}",
                        f"CFG scale: {longest_flow.get('cfg')}",
                        add_noise,
                        seed,
                        f"Size: {self._width}x{self._height}",
                        f"Model: {remove_quotes(longest_flow.get('ckpt_name'))}",
                        f"Scheduler: {remove_quotes(longest_flow.get('scheduler'))}",
                        start_at_step,
                        end_at_step,
                        return_with_left_over_noise,
                        denoise,
                        upscale_method,
                        upscaler,
                    ],
                )
            )
        )

        for p, s in zip(super().PARAMETER_KEY, ComfyUI.SETTING_KEY):
            match p:
                case k if k in ("model", "sampler"):
                    self._parameter[p] = str(remove_quotes(longest_flow.get(s)))
                case "seed":
                    self._parameter[p] = (
                        str(longest_flow.get("seed"))
                        if longest_flow.get("seed")
                        else str(longest_flow.get("noise_seed"))
                    )
                case "size":
                    self._parameter["size"] = str(self._width) + "x" + str(self._height)
                case _:
                    self._parameter[p] = str(longest_flow.get(s))

        if self._is_sdxl:
            if not self._positive and self.positive_sdxl:
                self._positive = self.merge_clip(self.positive_sdxl)
            if not self._negative and self.negative_sdxl:
                self._negative = self.merge_clip(self.negative_sdxl)

    @staticmethod
    def merge_clip(data: dict):
        clip_g = data.get("Clip G").strip(" ,")
        clip_l = data.get("Clip L").strip(" ,")

        if clip_g == clip_l:
            return clip_g
        else:
            return ",\n".join([clip_g, clip_l])

    def _comfy_traverse(self, prompt, end_node):
        flow = {}
        node = [end_node]
        inputs = {}
        try:
            inputs = prompt[end_node]["inputs"]
        except:
            print("node error")
            return flow, node
        match prompt[end_node]["class_type"]:
            case node_type if node_type in ComfyUI.SAVE_IMAGE_TYPE:
                try:
                    last_flow, last_node = self._comfy_traverse(
                        prompt, inputs["images"][0]
                    )
                    flow = merge_dict(flow, last_flow)
                    node += last_node
                except:
                    print("comfyUI SaveImage error")
            case node_type if node_type in ComfyUI.KSAMPLER_TYPES:
                try:
                    seed = None
                    flow = inputs
                    last_flow1, last_node1, last_flow2, last_node2 = {}, [], {}, []
                    for key, value in inputs.items():
                        match key:
                            case "model":
                                traverse_result = self._comfy_traverse(prompt, value[0])
                                if isinstance(traverse_result, tuple):
                                    last_flow1, last_node1 = traverse_result
                                elif isinstance(traverse_result, dict):
                                    flow.update({key: traverse_result.get("ckpt_name")})
                            case "latent_image":
                                last_flow2, last_node2 = self._comfy_traverse(
                                    prompt, value[0]
                                )
                            case "positive":
                                positive = self._comfy_traverse(prompt, value[0])
                                if isinstance(positive, str):
                                    self._positive = positive
                                elif isinstance(positive, dict):
                                    if positive_prompt := positive.get("positive"):
                                        self._positive = positive_prompt
                                    else:
                                        self._positive_sdxl.update(positive)
                            case "negative":
                                negative = self._comfy_traverse(prompt, value[0])
                                if isinstance(negative, str):
                                    self._negative = negative
                                elif isinstance(negative, dict):
                                    if negative_prompt := negative.get("negative"):
                                        self._negative = negative_prompt
                                    else:
                                        self._negative_sdxl.update(negative)
                            case key_name if key_name in ("seed", "noise_seed"):
                                # handle "CR Seed"
                                if isinstance(value, list):
                                    traverse_result = self._comfy_traverse(
                                        prompt, value[0]
                                    )
                                    if isinstance(traverse_result, dict):
                                        seed = {key_name: traverse_result.get("seed")}
                                    else:
                                        seed = {key_name: traverse_result}
                                if seed:
                                    flow.update(seed)
                            case _ as key_name:
                                if isinstance(value, list):
                                    traverse_result = self._comfy_traverse(
                                        prompt, value[0]
                                    )
                                    if isinstance(traverse_result, dict):
                                        flow.update(
                                            {key_name: traverse_result.get(key_name)}
                                        )

                    flow = merge_dict(flow, last_flow1)
                    flow = merge_dict(flow, last_flow2)
                    node += last_node1 + last_node2
                except:
                    print("comfyUI KSampler error")
            case node_type if node_type in ComfyUI.CLIP_TEXT_ENCODE_TYPE:
                try:
                    match node_type:
                        case "CLIPTextEncode":
                            # SDXLPromptStyler & SDPromptReader
                            if isinstance(inputs["text"], list):
                                text = int(inputs["text"][0])
                                traverse_result = self._comfy_traverse(
                                    prompt, str(text)
                                )
                                if isinstance(traverse_result, tuple):
                                    self._positive = traverse_result[0]
                                    self._negative = traverse_result[1]
                                elif isinstance(traverse_result, dict):
                                    return traverse_result
                                return
                            elif isinstance(inputs["text"], str):
                                return inputs.get("text")
                        case "CLIPTextEncodeSDXL":
                            # SDXLPromptStyler
                            self._is_sdxl = True
                            if isinstance(inputs["text_g"], list):
                                text_g = int(inputs["text_g"][0])
                                text_l = int(inputs["text_l"][0])
                                prompt_styler_g = self._comfy_traverse(
                                    prompt, str(text_g)
                                )
                                prompt_styler_l = self._comfy_traverse(
                                    prompt, str(text_l)
                                )
                                self._positive_sdxl["Clip G"] = prompt_styler_g[0]
                                self._positive_sdxl["Clip L"] = prompt_styler_l[0]
                                self._negative_sdxl["Clip G"] = prompt_styler_g[1]
                                self._negative_sdxl["Clip L"] = prompt_styler_l[1]
                                return
                            elif isinstance(inputs["text_g"], str):
                                return {
                                    "Clip G": inputs.get("text_g"),
                                    "Clip L": inputs.get("text_l"),
                                }
                        case "CLIPTextEncodeSDXLRefiner":
                            self._is_sdxl = True
                            if isinstance(inputs["text"], list):
                                # SDXLPromptStyler
                                text = int(inputs["text"][0])
                                prompt_styler = self._comfy_traverse(prompt, str(text))
                                self._positive_sdxl["Refiner"] = prompt_styler[0]
                                self._negative_sdxl["Refiner"] = prompt_styler[1]
                                return
                            elif isinstance(inputs["text"], str):
                                return {"Refiner": inputs.get("text")}
                except:
                    print("comfyUI CLIPText error")
            case "LoraLoader":
                try:
                    flow = inputs
                    last_flow, last_node = self._comfy_traverse(
                        prompt, inputs["model"][0]
                    )
                    flow = merge_dict(flow, last_flow)
                    node += last_node
                except:
                    print("comfyUI LoraLoader error")
            case node_type if node_type in ComfyUI.CHECKPOINT_LOADER_TYPE:
                try:
                    return inputs, node
                except:
                    print("comfyUI CheckpointLoader error")
            case node_type if node_type in ComfyUI.VAE_ENCODE_TYPE:
                try:
                    last_flow, last_node = self._comfy_traverse(
                        prompt, inputs["pixels"][0]
                    )
                    flow = merge_dict(flow, last_flow)
                    node += last_node
                except:
                    print("comfyUI VAE error")
            case "ControlNetApplyAdvanced":
                try:
                    positive = self._comfy_traverse(prompt, inputs["positive"][0])
                    if isinstance(positive, str):
                        self._positive = positive
                    elif isinstance(positive, dict):
                        self._positive_sdxl.update(positive)
                    negative = self._comfy_traverse(prompt, inputs["negative"][0])
                    if isinstance(negative, str):
                        self._negative = negative
                    elif isinstance(negative, dict):
                        self._negative_sdxl.update(negative)

                    last_flow, last_node = self._comfy_traverse(
                        prompt, inputs["image"][0]
                    )
                    flow = merge_dict(flow, last_flow)
                    node += last_node
                except:
                    print("comfyUI ControlNetApply error")
            case "ImageScale":
                try:
                    flow = inputs
                    last_flow, last_node = self._comfy_traverse(
                        prompt, inputs["image"][0]
                    )
                    flow = merge_dict(flow, last_flow)
                    node += last_node
                except:
                    print("comfyUI ImageScale error")
            case "UpscaleModelLoader":
                try:
                    return {"upscaler": inputs["model_name"]}
                except:
                    print("comfyUI UpscaleLoader error")
            case "ImageUpscaleWithModel":
                try:
                    flow = inputs
                    last_flow, last_node = self._comfy_traverse(
                        prompt, inputs["image"][0]
                    )
                    model = self._comfy_traverse(prompt, inputs["upscale_model"][0])
                    flow = merge_dict(flow, last_flow)
                    flow = merge_dict(flow, model)
                    node += last_node
                except:
                    print("comfyUI UpscaleModel error")
            case "ConditioningCombine":
                try:
                    last_flow1, last_node1 = self._comfy_traverse(
                        prompt, inputs["conditioning_1"][0]
                    )
                    last_flow2, last_node2 = self._comfy_traverse(
                        prompt, inputs["conditioning_2"][0]
                    )
                    flow = merge_dict(flow, last_flow1)
                    flow = merge_dict(flow, last_flow2)
                    node += last_node1 + last_node2
                except:
                    print("comfyUI ConditioningCombine error")
            # SD Prompt Reader Node
            case "SDPromptReader":
                try:
                    return json.loads(prompt[end_node]["is_changed"][0])
                except:
                    print("comfyUI SDPromptReader error")
            case "SDParameterGenerator":
                try:
                    return inputs
                except:
                    print("comfyUI SDParameterGenerator error")
            # custom nodes
            case "SDXLPromptStyler":
                try:
                    return inputs.get("text_positive"), inputs.get("text_negative")
                except:
                    print("comfyUI SDXLPromptStyler error")
            case "CR Seed":
                try:
                    return inputs.get("seed")
                except:
                    print("comfyUI CR Seed error")
            case _:
                try:
                    last_flow = {}
                    last_node = []
                    if inputs.get("samples"):
                        last_flow, last_node = self._comfy_traverse(
                            prompt, inputs["samples"][0]
                        )
                    elif inputs.get("image") and isinstance(inputs.get("image"), list):
                        last_flow, last_node = self._comfy_traverse(
                            prompt, inputs["image"][0]
                        )
                    elif inputs.get("model"):
                        last_flow, last_node = self._comfy_traverse(
                            prompt, inputs["model"][0]
                        )
                    elif inputs.get("clip"):
                        last_flow, last_node = self._comfy_traverse(
                            prompt, inputs["clip"][0]
                        )
                    elif inputs.get("samples_from"):
                        last_flow, last_node = self._comfy_traverse(
                            prompt, inputs["samples_from"][0]
                        )
                    elif inputs.get("conditioning"):
                        result = self._comfy_traverse(prompt, inputs["conditioning"][0])
                        if isinstance(result, str):
                            return result
                        elif isinstance(result, list):
                            last_flow, last_node = result
                    flow = merge_dict(flow, last_flow)
                    node += last_node
                except:
                    print("comfyUI bridging node error")
        return flow, node