ap-canvas-creation-module-old/04_stable_diffusion/sd_comfy_api.py

import json
from urllib import request, parse
import random
import sys
import ast
import base64
import uuid

# This is the ComfyUI api prompt format.

# If you want it for a specific workflow you can "enable dev mode options"
# in the settings of the UI (gear beside the "Queue Size: ") this will enable
# a button on the UI to save workflows in api format.

# keep in mind ComfyUI is pre alpha software so this format will change a bit.

# this is the one for the default workflow

# load the prompt from a workflow_api_test.json file


def convert_base64_string_to_object(base64_string):
    bytes = base64.b64decode(base64_string)
    string = bytes.decode("ascii")

    return json.loads(string)


server_address = "127.0.0.1:8188"
client_id = str(uuid.uuid4())

with open(
    "D://Git//ap-canvas-creation-module//04_stable_diffusion//workflows//canvas_3d_to_img_standard_V1.json",
    "r",
) as f:
    prompt_text_json = f.read()


def queue_prompt(prompt):
    p = {"prompt": prompt}
    data = json.dumps(p).encode("utf-8")
    req = request.Request("http://127.0.0.1:8188/prompt", data=data)
    request.urlopen(req)


def find_node(json_obj, title):
    for key, value in json_obj.items():
        if isinstance(value, dict):
            if value.get("_meta", {}).get("title") == title:
                return value
            else:
                result = find_node(value, title)
                if result:
                    return result
    return None


def set_filename(json_obj, title, new_prefix):
    for key, value in json_obj.items():
        if isinstance(value, dict):
            if value.get("_meta", {}).get("title") == title:
                if "inputs" in value and "filename_prefix" in value["inputs"]:
                    value["inputs"]["filename_prefix"] = new_prefix
                else:
                    result = set_filename(value, title, new_prefix)
                    if result:
                        return result
    return None


def main():
    # main code here

    argv = sys.argv

    try:

        argv = argv[argv.index("--") + 1 :]

        ai_scene_info = convert_base64_string_to_object(argv[0])

        print("loading scene data", ai_scene_info)

    except Exception as e:
        print("Error:", e)

    positive_text = ai_scene_info["ai_scene"]["settings"]["positive_prompt"]
    negative_text = ai_scene_info["ai_scene"]["settings"]["negative_prompt"]

    image_path = "D://Git//ap-canvas-creation-module//03_blender//sd_blender//sample_scene//Renders//15a314a1-8ba1-4e0e-ad0c-f605b06f89f8//"

    image_base_path = image_path + "base0001.jpg"
    image_alpha_products_path = image_path + "alpha_products0001.jpg"
    # image_depth_path = image_path + "depth0001.png"

    prompt = json.loads(prompt_text_json)
    set_filename(prompt, "Save Image", "custom/basic_api_example")

    ksampler_main = find_node(prompt, "KSampler")
    ksampler_main["inputs"]["noise_seed"] = random.randint(0, 1000000)

    ksampler_main = find_node(prompt, "KSampler")
    ksampler_main["inputs"]["steps"] = 30

    prompt_positive = find_node(prompt, "positive_CLIPTextEncodeSDXL")
    prompt_positive["inputs"]["text_g"] = positive_text

    prompt_positive["inputs"]["text_l"] = positive_text

    prompt_negative = find_node(prompt, "negative_CLIPTextEncodeSDXL")
    prompt_negative["inputs"]["text_g"] = negative_text
    prompt_negative["inputs"]["text_l"] = negative_text

    image_base = find_node(prompt, "image_base")
    image_base["inputs"]["image"] = image_base_path

    image_base = find_node(prompt, "image_product_mask")
    image_base["inputs"]["image"] = image_alpha_products_path

    image_base = find_node(prompt, "image_depth")
    # image_base["inputs"]["image"] = image_depth_path

    queue_prompt(prompt)


if __name__ == "__main__":
    main()