2023-02-22 17:34:27 +00:00
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import json
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from urllib import request, parse
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import random
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2023-07-19 19:07:12 +00:00
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#This is the ComfyUI api prompt format.
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#If you want it for a specific workflow you can "enable dev mode options"
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#in the settings of the UI (gear beside the "Queue Size: ") this will enable
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#a button on the UI to save workflows in api format.
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2023-02-22 17:34:27 +00:00
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#keep in mind ComfyUI is pre alpha software so this format will change a bit.
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#this is the one for the default workflow
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prompt_text = """
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{
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"3": {
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"class_type": "KSampler",
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"inputs": {
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"cfg": 8,
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"denoise": 1,
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"latent_image": [
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"5",
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0
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],
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"model": [
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"4",
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0
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],
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"negative": [
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"7",
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0
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],
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"positive": [
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"6",
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0
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],
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2023-02-27 06:43:06 +00:00
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"sampler_name": "euler",
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2023-02-22 17:34:27 +00:00
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"scheduler": "normal",
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"seed": 8566257,
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"steps": 20
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}
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},
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"4": {
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2023-03-05 08:00:28 +00:00
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"class_type": "CheckpointLoaderSimple",
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2023-02-22 17:34:27 +00:00
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"inputs": {
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2024-08-29 23:48:48 +00:00
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"ckpt_name": "v1-5-pruned-emaonly.safetensors"
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2023-02-22 17:34:27 +00:00
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}
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},
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"5": {
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"class_type": "EmptyLatentImage",
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"inputs": {
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"batch_size": 1,
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"height": 512,
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"width": 512
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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": {
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"clip": [
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"4",
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1
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],
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"text": "masterpiece best quality girl"
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}
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},
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"7": {
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"class_type": "CLIPTextEncode",
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"inputs": {
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"clip": [
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"4",
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1
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],
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"text": "bad hands"
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}
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},
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"8": {
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"class_type": "VAEDecode",
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"inputs": {
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"samples": [
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"3",
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0
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],
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"vae": [
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"4",
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2
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]
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}
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},
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"9": {
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"class_type": "SaveImage",
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"inputs": {
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"filename_prefix": "ComfyUI",
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"images": [
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"8",
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0
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]
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}
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}
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}
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"""
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def queue_prompt(prompt):
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p = {"prompt": prompt}
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data = json.dumps(p).encode('utf-8')
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req = request.Request("http://127.0.0.1:8188/prompt", data=data)
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request.urlopen(req)
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prompt = json.loads(prompt_text)
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#set the text prompt for our positive CLIPTextEncode
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prompt["6"]["inputs"]["text"] = "masterpiece best quality man"
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#set the seed for our KSampler node
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prompt["3"]["inputs"]["seed"] = 5
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queue_prompt(prompt)
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