Upload install_swarmui.py
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Swarmui_Kaggle/install_swarmui.py
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#!/usr/bin/env python3
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"""
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install_swarmui.py
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Instala SwarmUI en Kaggle con ComfyUI backend, extensiones, modelos y configuraciones.
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"""
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import os
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import subprocess
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from pathlib import Path
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WORK_DIR = Path("/kaggle/working").resolve()
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SWARM_DIR = WORK_DIR / "SwarmUI"
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COMFY_DIR = SWARM_DIR / "dlbackend" / "ComfyUI"
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def _run(cmd: str, cwd: Path | None = None) -> None:
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"""Ejecuta un comando shell."""
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print(f"+ {cmd}")
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subprocess.run(cmd, shell=True, check=False, cwd=cwd)
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def wget(url: str, output: str | None = None, quiet: bool = False, show_progress: bool = False) -> None:
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"""Descarga con wget."""
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cmd = "wget"
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if quiet:
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cmd += " -q"
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if show_progress:
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cmd += " --show-progress"
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if output:
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cmd += f" -O {output}"
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cmd += f" {url}"
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_run(cmd)
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def aria2c(url: str, output: str, cwd: Path | None = None) -> None:
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"""Descarga con aria2c."""
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cmd = (f'aria2c --console-log-level=error -c -x 16 -s 16 -k 1M '
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f'"{url}" -o {output}')
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_run(cmd, cwd=cwd)
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def clone(repo: str, cwd: Path | None = None) -> None:
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"""Clona un repositorio git."""
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_run(f"git clone {repo}", cwd=cwd)
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def main() -> None:
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os.chdir(WORK_DIR)
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# 1. Descargas iniciales y clonar SwarmUI
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wget("https://huggingface.co/datasets/Mightys/SwarmuiColab/resolve/main/scripts/download_magic.py")
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if not SWARM_DIR.exists():
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clone("https://github.com/mcmonkeyprojects/SwarmUI")
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(SWARM_DIR / "Models").mkdir(parents=True, exist_ok=True)
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(SWARM_DIR / "dlbackend").mkdir(parents=True, exist_ok=True)
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_run("pip install aria2 gdown")
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# 2. Configuración de SwarmUI (Data)
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data_dir = SWARM_DIR / "Data"
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data_dir.mkdir(parents=True, exist_ok=True)
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os.chdir(data_dir)
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wget("https://huggingface.co/datasets/Mightys/Notebook_Scripts/resolve/main/Swarmui_Kaggle/Settings.fds",
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quiet=True, show_progress=True)
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wget("https://huggingface.co/datasets/Mightys/Notebook_Scripts/resolve/main/Swarmui_Kaggle/Backends.fds",
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quiet=True, show_progress=True)
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wget("https://huggingface.co/datasets/Mightys/Notebook_Scripts/resolve/main/Swarmui_Kaggle/Users.ldb",
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quiet=True, show_progress=True)
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# Autocompletions
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auto_dir = data_dir / "Autocompletions"
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auto_dir.mkdir(parents=True, exist_ok=True)
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os.chdir(auto_dir)
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wget("https://huggingface.co/datasets/Mightys/SwarmuiColab/resolve/main/Data/Autocompletions/danbooru_e621_merged.csv",
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quiet=True, show_progress=True)
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# 3. Instalar .NET
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os.chdir(WORK_DIR)
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wget("https://dot.net/v1/dotnet-install.sh", output="dotnet-install.sh")
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_run("chmod +x dotnet-install.sh")
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_run("./dotnet-install.sh --channel 8.0")
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# 4. Instalar Cloudflare tunnel
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wget("https://github.com/cloudflare/cloudflared/releases/download/2024.8.2/cloudflared-linux-amd64.deb",
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quiet=True, show_progress=True)
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_run("dpkg -i cloudflared-linux-amd64.deb")
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# 5. Clonar ComfyUI
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os.chdir(SWARM_DIR / "dlbackend")
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if not COMFY_DIR.exists():
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clone("https://github.com/comfyanonymous/ComfyUI.git")
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else:
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_run("git pull", cwd=COMFY_DIR)
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# 6. Dependencias de ComfyUI
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os.chdir(COMFY_DIR)
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_run("uv pip install -r requirements.txt --no-progress")
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_run("uv pip install torch==2.9.1 torchvision==0.24.1 torchaudio xformers==0.0.33.post2 triton==3.5.1 "
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"--index-url https://download.pytorch.org/whl/cu128 --no-progress")
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_run("uv pip install ultralytics==8.3.216 onnxruntime gdown pickleshare insightface clip rembg numpy==2.3.0 "
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"--no-progress")
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# 7. Extensiones de SwarmUI
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ext_dir = SWARM_DIR / "src" / "Extensions"
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ext_dir.mkdir(parents=True, exist_ok=True)
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os.chdir(ext_dir)
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clone("https://github.com/jtreminio/SwarmUI-PromptBuilderExtension.git")
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clone("https://github.com/yoinked-h/MaHiRon-SwarmUI.git")
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# 8. SageAttention
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os.chdir(WORK_DIR)
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wheel = "sageattention-2.1.2-cp312-cp312-linux_x86_64.whl"
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wget(f"https://huggingface.co/datasets/WhiteAiZ/T4_SageAttention2_For_Google_Colab/resolve/main/python%203.12/{wheel}")
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_run(f"uv pip install {wheel}")
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# 9. Wildcards
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wild_dir = SWARM_DIR / "Data" / "Wildcards"
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wild_dir.mkdir(parents=True, exist_ok=True)
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os.chdir(wild_dir)
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aria2c("https://huggingface.co/datasets/Mightys/Notebook_Scripts/resolve/main/Wildcards/artist_tags_danbooru5000.txt",
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"5000-booru-artist.txt")
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# 10. Modelos YOLO (segmentación/adetailers)
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yolo_dir = SWARM_DIR / "Models" / "yolov8"
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yolo_dir.mkdir(parents=True, exist_ok=True)
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os.chdir(yolo_dir)
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yolo_models = [
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("https://huggingface.co/Anzhc/Anzhcs_YOLOs/resolve/main/Anzhc%20Eyes%20-seg-hd.pt", "Anzhc_Eyes-seg-hd.pt"),
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("https://huggingface.co/Anzhc/Anzhcs_YOLOs/resolve/main/Anzhc%20Face%20seg%20640%20v3%20y11n.pt", "Anzhc_Face_seg_v3_y11n.pt"),
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| 129 |
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("https://huggingface.co/Anzhc/Anzhcs_YOLOs/resolve/main/Anzhc%20Breasts%20Seg%20v1%201024n.pt", "Anzhc_Breasts_Seg_v1_1024n.pt"),
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("https://huggingface.co/Anzhc/Anzhcs_YOLOs/resolve/main/Anzhc%20HeadHair%20seg%20y8n.pt", "Anzhc_HeadHair_seg_y8n.pt"),
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("https://huggingface.co/Nudimmud/adetailers/resolve/main/assdetailer-seg.pt", "assdetailer.pt"),
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("https://huggingface.co/Bingsu/adetailer/resolve/main/face_yolov8n.pt", "face_yolov8n.pt"),
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("https://huggingface.co/Bingsu/adetailer/resolve/main/face_yolov8m.pt", "face_yolov8m.pt"),
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("https://huggingface.co/Bingsu/adetailer/resolve/main/hand_yolov8n.pt", "hand_yolov8n.pt"),
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("https://huggingface.co/Bingsu/adetailer/resolve/main/hand_yolov8m.pt", "hand_yolov8m.pt"),
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]
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for url, out in yolo_models:
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aria2c(url, out)
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# 11. VAE
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vae_dir = SWARM_DIR / "Models" / "VAE"
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vae_dir.mkdir(parents=True, exist_ok=True)
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os.chdir(vae_dir)
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# Nota: %download es una magic de IPython, aquí usamos wget directamente
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wget("https://huggingface.co/madebyollin/sdxl-vae-fp16-fix/resolve/main/sdxl_vae.safetensors",
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quiet=True, show_progress=True)
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# 12. Gradio tunnel
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| 150 |
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gradio_script = SWARM_DIR / "gradio-tunnel.py"
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| 151 |
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if not gradio_script.exists():
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wget("https://huggingface.co/datasets/Mightys/Notebook_Scripts/resolve/main/scripts/gradio-tunnel.py",
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output=str(gradio_script))
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# 13. Parche de memoria (libmimalloc)
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print("🛠️ Instalando parche de memoria (libmimalloc.so.2.1)...")
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mimalloc_path = WORK_DIR / "libmimalloc.so.2.1"
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| 158 |
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if not mimalloc_path.exists():
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wget("https://huggingface.co/datasets/Mightys/Notebook_Scripts/resolve/main/libmimalloc.so.2.1",
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output=str(mimalloc_path))
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print("✅ Parche descargado.")
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else:
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print("✅ Parche listo.")
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_run("pip install -q requests")
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# Limpiar y mensaje final
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os.system("clear" if os.name != "nt" else "cls")
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print("\n" + "=" * 50)
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print("🎉 Instalación completada")
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print("=" * 50)
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if __name__ == "__main__":
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main()
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