# SDXL Turbo model is used, but LoRA LCM was also fast
import bpy
import json
import requests
import random
# ComfyUI server address
comfyui_address = "http://127.0.0.1:8188"
def queue_prompt(prompt_workflow):
p = {"prompt": prompt_workflow}
# Convert prompt workflow to JSON
workflow_json = json.dumps(p).encode('utf-8')
# Send POST request to ComfyUI server
response = requests.post(comfyui_address + "/prompt", data=workflow_json)
# Check if request was successful
if response.status_code != 200:
print("Error sending prompt to ComfyUI:", response.status_code)
print(response.text)
else:
print("Prompt successfully sent to ComfyUI")
# Read workflow API data from file and convert it into dictionary
prompt_workflow = json.load(open("/Users/jimmygunawan/Downloads/inter_combine_workflow6.json"))
# Create a list of prompts
#prompt_list = []
# Access the text block and append for ComfyUI
# Get the text datablock
#text_datablock = bpy.data.texts['MonkeyRobot']
# Get the text content
#text_content = text_datablock.lines
#if text_datablock:
# Read the contents of the text block
#for i in text_content:
#print(i.body)
#prompt_list.append(i.body)
#else:
#print(f"Text block '{text_block_name}' not found.")
#prompt_list = []
#prompt_list.append("photo of a bearded man Mario wearing a red hat sitting alone in a cafe")
#prompt_list.append("oil painting of a llama standing in the middle of a busy street")
#prompt_list.append("water colour art of a fish sitting in a tree")
#prompt_list.append("beautiful mushroom glass bottle landscape, purple galaxy bottle")
#prompt_list.append("princess peach on abandoned castle reading book at night, fireflies")
#prompt_list.append("head totem of monkey head, made of mecha garbage recycle, in the middle of empty park")
# Give some easy-to-remember names to the nodes
load_image_node1 = prompt_workflow["48"]
load_image_node2 = prompt_workflow["49"]
prompt_pos_node = prompt_workflow["6"]
#seed_node = prompt_workflow["4"]
#save_image_node = prompt_workflow["1"]
#empty_latent_img_node = prompt_workflow["1"]
# Set image dimensions and batch size in EmptyLatentImage node
#empty_latent_img_node["inputs"]["width"] = 512
#empty_latent_img_node["inputs"]["height"] = 640
#empty_latent_img_node["inputs"]["num_images"] = 1
# For every prompt in prompt_list...
for i in range(166):
load_image_node1["inputs"]["skip_first_frames"] = i
load_image_node2["inputs"]["skip_first_frames"] = i
# Text prompt positive assign
prompt_pos_node["inputs"]["text"] = "(solo) cyborg woman (fox ears:1.1), (blonde hair:1.0), messy hair, sky clouds, standing in a grass field, (chibi), blue eyes"
queue_prompt(prompt_workflow)
#for index, prompt in enumerate(prompt_list):
# Set the text prompt for positive CLIPTextEncode node
#prompt_pos_node["inputs"]["text"] = prompt + " made of garbage, waste recycles, wabisabi, imperfect"
# Set a random seed in KSampler node
#seed_node["inputs"]["noise_seed"] = random.randint(1, 18446744073709551614)
# Set filename prefix to be the same as prompt
# (truncate to first 100 chars if necessary)
#fileprefix = prompt
#if len(fileprefix) > 100:
# fileprefix = fileprefix[:100]
#save_image_node["inputs"]["filename_prefix"] = fileprefix
# Everything set, add entire workflow to queue.
#queue_prompt(prompt_workflow)