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import requests
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import json
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import uuid
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import time
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import os
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import subprocess
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import sys
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COMFY_PORT = 8188
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POLL_TIMEOUT = 300
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MODELS = {
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"lineart": {
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"name": "Deliberate_v2.safetensors",
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"url": "https://huggingface.co/XpucT/Deliberate/resolve/main/Deliberate_v2.safetensors",
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},
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"manga": {
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"name": "Deliberate_v2.safetensors",
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"url": "https://huggingface.co/XpucT/Deliberate/resolve/main/Deliberate_v2.safetensors",
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},
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}
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DEFAULT_MODEL_URL = MODELS["manga"]["url"]
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DEFAULT_MODEL_NAME = MODELS["manga"]["name"]
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def base_url(host="127.0.0.1"):
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return f"http://{host}:{COMFY_PORT}"
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def is_ready(host="127.0.0.1", timeout=3):
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try:
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requests.get(f"{base_url(host)}/system_stats", timeout=timeout)
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return True
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except Exception:
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return False
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def find_model(comfy_path, name=None):
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model_dir = os.path.join(comfy_path, "models", "checkpoints")
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if not os.path.isdir(model_dir):
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return None
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if name:
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return name if os.path.exists(os.path.join(model_dir, name)) else None
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for f in os.listdir(model_dir):
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if f.endswith(".safetensors") or f.endswith(".ckpt"):
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return f
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return None
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def download_model(comfy_path, style="manga"):
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model_info = MODELS.get(style, MODELS["manga"])
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model_name = model_info["name"]
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model_url = model_info["url"]
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style_label = "Anything V5 (anime/manga lineart)" if style == "lineart" else "Deliberate v2 (general purpose)"
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model_dir = os.path.join(comfy_path, "models", "checkpoints")
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os.makedirs(model_dir, exist_ok=True)
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dest = os.path.join(model_dir, model_name)
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if os.path.exists(dest):
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return model_name
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print(f"\n Model for --style {style} not found: {model_name}")
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print(f" Recommended model: {style_label}")
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print(f" Source: {model_url}")
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confirm = input("\n Download it now? (~2GB) [Y/n] ").strip().lower()
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if confirm in ("n", "no"):
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print(" Aborted.")
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sys.exit(0)
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print(f"\n Downloading {model_name}...")
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bar_width = 35
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with requests.get(model_url, stream=True) as r:
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r.raise_for_status()
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total = int(r.headers.get("content-length", 0))
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downloaded = 0
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with open(dest, "wb") as f:
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for chunk in r.iter_content(chunk_size=1024 * 1024):
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f.write(chunk)
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downloaded += len(chunk)
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if total:
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pct = downloaded / total
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filled = int(bar_width * pct)
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bar = "\u2588" * filled + "\u2591" * (bar_width - filled)
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mb_done = downloaded / 1024 / 1024
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mb_total = total / 1024 / 1024
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print(f"\r [{bar}] {mb_done:.0f}/{mb_total:.0f} MB ", end="", flush=True)
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print(f"\r Download complete: {dest} ")
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return model_name
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def ensure_model_for_style(comfy_path, style="manga"):
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model_info = MODELS.get(style, MODELS["manga"])
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model_name = model_info["name"]
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existing = find_model(comfy_path, name=model_name)
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if existing:
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return existing
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return download_model(comfy_path, style=style)
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def install_dependencies(comfy_path):
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req_file = os.path.join(comfy_path, "requirements.txt")
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stamp = os.path.join(comfy_path, ".deps_installed")
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if not os.path.exists(req_file):
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return
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if os.path.exists(stamp):
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req_mtime = os.path.getmtime(req_file)
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stamp_mtime = os.path.getmtime(stamp)
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if stamp_mtime >= req_mtime:
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return
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print(" Installing ComfyUI dependencies...")
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subprocess.run(
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[sys.executable, "-m", "pip", "install", "-r", req_file, "--quiet"],
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check=True,
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)
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open(stamp, "w").close()
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def build_workflow(positive, negative, model_name, steps=20, width=768, height=1024, cfg=4.5):
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seed = int(time.time()) % 2**32
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return {
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"3": {
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"class_type": "KSampler",
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"inputs": {
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"seed": seed,
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"steps": steps,
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"cfg": cfg,
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"sampler_name": "euler_ancestral",
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"scheduler": "karras",
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"denoise": 1.0,
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"model": ["4", 0],
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"positive": ["6", 0],
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"negative": ["7", 0],
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"latent_image": ["5", 0],
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},
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},
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"4": {
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"class_type": "CheckpointLoaderSimple",
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"inputs": {"ckpt_name": model_name},
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},
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"5": {
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"class_type": "EmptyLatentImage",
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"inputs": {"width": width, "height": height, "batch_size": 1},
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},
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"6": {
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"class_type": "CLIPTextEncode",
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"inputs": {"text": positive, "clip": ["4", 1]},
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},
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"7": {
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"class_type": "CLIPTextEncode",
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"inputs": {"text": negative, "clip": ["4", 1]},
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},
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"8": {
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"class_type": "VAEDecode",
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"inputs": {"samples": ["3", 0], "vae": ["4", 2]},
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},
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"9": {
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"class_type": "SaveImage",
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"inputs": {"filename_prefix": "manga", "images": ["8", 0]},
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},
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}
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def generate_image(base_url_str, positive, negative, model_name, steps=20, width=768, height=1024, cfg=4.5):
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client_id = str(uuid.uuid4())
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workflow = build_workflow(positive, negative, model_name, steps, width, height, cfg)
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r = requests.post(f"{base_url_str}/prompt", json={"prompt": workflow, "client_id": client_id})
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r.raise_for_status()
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prompt_id = r.json()["prompt_id"]
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deadline = time.time() + POLL_TIMEOUT
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while time.time() < deadline:
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time.sleep(1)
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hist = requests.get(f"{base_url_str}/history/{prompt_id}").json()
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if prompt_id in hist:
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outputs = hist[prompt_id]["outputs"]
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for node_id, node_output in outputs.items():
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if "images" in node_output:
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img_info = node_output["images"][0]
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img_r = requests.get(
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f"{base_url_str}/view",
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params={
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"filename": img_info["filename"],
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"subfolder": img_info.get("subfolder", ""),
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"type": img_info["type"],
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},
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)
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img_r.raise_for_status()
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return img_r.content
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break
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raise RuntimeError(f"ComfyUI: no images returned for prompt_id {prompt_id} within {POLL_TIMEOUT}s")
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