initial commit

.gitignore

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+.DS_Store

Dockerfile

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+# Use Nvidia CUDA base image
+FROM nvidia/cuda:11.8.0-cudnn8-runtime-ubuntu22.04 as base
+
+# Prevents prompts from packages asking for user input during installation
+ENV DEBIAN_FRONTEND=noninteractive
+# Prefer binary wheels over source distributions for faster pip installations
+ENV PIP_PREFER_BINARY=1
+# Ensures output from python is printed immediately to the terminal without buffering
+ENV PYTHONUNBUFFERED=1 
+
+# Install Python, git and other necessary tools
+RUN apt-get update && apt-get install -y \
+    python3.10 \
+    python3-pip \
+    git \
+    wget
+
+# Clean up to reduce image size
+RUN apt-get autoremove -y && apt-get clean -y && rm -rf /var/lib/apt/lists/*
+
+# Clone ComfyUI repository
+RUN git clone https://github.com/comfyanonymous/ComfyUI.git /ComfyUI
+
+# Change working directory to ComfyUI
+WORKDIR /ComfyUI
+
+# Install ComfyUI dependencies
+RUN pip3 install --no-cache-dir torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121 \
+    && pip3 install --no-cache-dir xformers==0.0.21 \
+    && pip3 install -r requirements.txt
+
+# Install runpod
+RUN pip3 install runpod
+
+# Download Stable Diffusion XL
+# RUN wget -O models/checkpoints/sd_xl_base_1.0.safetensors https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/resolve/main/sd_xl_base_1.0.safetensors
+
+# Add the models
+ADD models/checkpoints/sd_xl_base_1.0.safetensors models/checkpoints/
+ADD models/checkpoints/sdxl_vae.safetensors models/checkpoints/
+
+# Go back to the root
+WORKDIR /
+
+# Add the start and the handler
+ADD src/start.sh src/rp_handler.py ./
+RUN chmod +x /start.sh
+
+# Start the container
+CMD /start.sh

README.md

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+# RunPod Worker Comfy
+
+> ComfyUI via API on [RunPod](https://www.runpod.io/) serverless
+
+<!-- toc -->
+
+- [What](#what)
+
+<!-- tocstop -->
+
+---
+
+## What
+
+* Use ubuntu with cuda driver as base
+* make sure to set the correct options as with a1111 from ashley
+* clone comfy & install dependencies
+* create a start.sh script to start comfy and then the handler
+* use the start.sh as the entrypoint in the dockerfile
+* create a loop to create the image
+* store hte generated image in S3
+* return the URL to the image via API
+* use the network volume

docker-compose.yml

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+version: '3.8'
+
+services:
+  comfyui:
+    image: timpietruskyblibla/runpod-worker-comfy:1.0.0
+    container_name: comfyui-worker
+    environment:
+      - NVIDIA_VISIBLE_DEVICES=all
+    runtime: nvidia
+    volumes:
+      - ./data:/data

src/rp_handler.py

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+import runpod
+
+
+def hello_world(job):
+    job_input = job["input"]
+    greeting = job_input["greeting"]
+
+    if not isinstance(greeting, str):
+        return {"error": "Please provide a String"}
+
+    return f"Hello {greeting}"
+
+
+runpod.serverless.start({"handler": hello_world})

src/start.sh

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+#!/usr/bin/env bash
+
+echo "runpod-worker-comfy: Starting ComfyUI"
+
+# Use libtcmalloc for better memory management
+TCMALLOC="$(ldconfig -p | grep -Po "libtcmalloc.so.\d" | head -n 1)"
+export LD_PRELOAD="${TCMALLOC}"
+
+python /ComfyUI/main.py --disable-auto-launch --disable-metadata > /workspace/logs/comfy.log 2>&1 &
+
+echo "runpod-worker-comfy: Starting RunPod Handler"
+python3 -u /rp_handler.py

test/prompt.py

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+import json
+from urllib import request, parse
+
+# 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
+prompt_text = """
+{
+    "3": {
+        "class_type": "KSampler",
+        "inputs": {
+            "cfg": 8,
+            "denoise": 1,
+            "latent_image": [
+                "5",
+                0
+            ],
+            "model": [
+                "4",
+                0
+            ],
+            "negative": [
+                "7",
+                0
+            ],
+            "positive": [
+                "6",
+                0
+            ],
+            "sampler_name": "euler",
+            "scheduler": "normal",
+            "seed": 8566257,
+            "steps": 20
+        }
+    },
+    "4": {
+        "class_type": "CheckpointLoaderSimple",
+        "inputs": {
+            "ckpt_name": "sd_xl_base_1.0.safetensors"
+        }
+    },
+    "5": {
+        "class_type": "EmptyLatentImage",
+        "inputs": {
+            "batch_size": 1,
+            "height": 512,
+            "width": 512
+        }
+    },
+    "6": {
+        "class_type": "CLIPTextEncode",
+        "inputs": {
+            "clip": [
+                "4",
+                1
+            ],
+            "text": "masterpiece best quality girl"
+        }
+    },
+    "7": {
+        "class_type": "CLIPTextEncode",
+        "inputs": {
+            "clip": [
+                "4",
+                1
+            ],
+            "text": "bad hands"
+        }
+    },
+    "8": {
+        "class_type": "VAEDecode",
+        "inputs": {
+            "samples": [
+                "3",
+                0
+            ],
+            "vae": [
+                "4",
+                2
+            ]
+        }
+    },
+    "9": {
+        "class_type": "SaveImage",
+        "inputs": {
+            "filename_prefix": "ComfyUI",
+            "images": [
+                "8",
+                0
+            ]
+        }
+    }
+}
+"""
+
+
+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)
+
+
+prompt = json.loads(prompt_text)
+# set the text prompt for our positive CLIPTextEncode
+prompt["6"]["inputs"]["text"] = "masterpiece best quality man"
+
+# set the seed for our KSampler node
+prompt["3"]["inputs"]["seed"] = 5
+
+
+queue_prompt(prompt)

test_input.json

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+{
+    "input": {
+        "greeting": "world"
+    }
+}