Fix Python linting issues and enhance RunPod network storage

- Fix all whitespace and formatting issues in runpod_handler.py
- Remove trailing whitespace and blank line whitespace
- Add comprehensive RunPod network storage setup
- Enhance start_runpod.py with automatic model mounting
- Update Dockerfile for optimized RunPod deployment
- Add detailed setup documentation in runpod_setup.md
- Improve .dockerignore for faster builds
- Add .env to .gitignore for security

.dockerignore

@@ -1,19 +1,79 @@
+# Git
 .git
-.github
-__pycache__
-*.pyc
-*.pyo
-*.pyd
-.Python
-*.so
-*.egg
-*.egg-info
-dist
-build
-.vscode
-.idea
+.gitignore
+.gitattributes
+
+# Documentation
 *.md
-output
-input
-models/checkpoints/*.safetensors
-models/checkpoints/*.ckpt
+docs/
+
+# Development files
+.env
+.env.local
+.env.example
+
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# Virtual environments
+venv/
+env/
+ENV/
+
+# IDE
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+
+# OS
+.DS_Store
+Thumbs.db
+
+# Logs
+*.log
+logs/
+
+# Temporary files
+temp/
+tmp/
+*.tmp
+
+# Large model files (will be mounted from network storage)
+models/*/
+!models/.gitkeep
+
+# Output files
+output/
+outputs/
+
+# Cache
+.cache/
+cache/
+
+# Node modules (if any)
+node_modules/
+
+# Docker
+Dockerfile.*
+docker-compose*.yml

.gitignore

@@ -24,3 +24,8 @@ web_custom_versions/
 openapi.yaml
 filtered-openapi.yaml
 uv.lock
+
+# Environment files with secrets
+.env
+.env.local
+.env.production

ComfyUI-master/runpod_handler.py

@@ -39,12 +39,12 @@ class ComfyUIServerlessHandler:
         """Start ComfyUI server in background"""
         try:
             logger.info("Starting ComfyUI server...")
-            
+
             # Check if main.py exists
             if not os.path.exists("/workspace/ComfyUI/main.py"):
                 logger.error("main.py not found in /workspace/ComfyUI")
                 raise FileNotFoundError("ComfyUI main.py not found")
-            
+
             # Check if models directory exists (network storage)
             if not os.path.exists("/workspace/ComfyUI/models"):
                 logger.warning("Models directory not found, creating symlink to network storage")
@@ -52,7 +52,7 @@ class ComfyUIServerlessHandler:
                     os.symlink("/runpod-volume/models", "/workspace/ComfyUI/models")
                 else:
                     logger.error("Network storage models not found at /runpod-volume/models")
-            
+
             # Start ComfyUI
             self.comfyui_process = subprocess.Popen([
                 "python3", "main.py",
@@ -60,12 +60,12 @@ class ComfyUIServerlessHandler:
                 "--port", "8000",
                 "--dont-print-server",
                 "--disable-auto-launch"
-            ], cwd="/workspace/ComfyUI", 
-               stdout=subprocess.PIPE, 
+            ], cwd="/workspace/ComfyUI",
+               stdout=subprocess.PIPE,
                stderr=subprocess.PIPE)
-            
+
             logger.info("ComfyUI server started")
-            
+
         except Exception as e:
             logger.error(f"Failed to start ComfyUI: {str(e)}")
             raise

Dockerfile

@@ -18,9 +18,16 @@ RUN pip install --no-cache-dir \
     torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu && \
     pip install --no-cache-dir -r requirements.txt
 
-# Cloud Run PORT environment variable'ını kullan
+# RunPod başlangıç scriptini çalıştırılabilir yap
+RUN chmod +x start_runpod.py
+
+# Environment variables
 ENV PORT=8188
+ENV RUNPOD_NETWORK_STORAGE_PATH=/runpod-volume
+ENV HF_HUB_DISABLE_TELEMETRY=1
+ENV DO_NOT_TRACK=1
+
 EXPOSE 8188
 
-# Başlat - CPU modunda çalıştır
-CMD python main.py --listen 0.0.0.0 --port ${PORT} --cpu
+# RunPod başlangıç scriptini kullan
+CMD ["python", "start_runpod.py"]

Dockerfile.serverless

@@ -0,0 +1,93 @@
+# RunPod Serverless ComfyUI Worker
+FROM runpod/pytorch:2.2.0-py3.11-cuda12.1.1-devel-ubuntu22.04
+
+# Set working directory
+WORKDIR /workspace
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    git \
+    wget \
+    curl \
+    unzip \
+    ffmpeg \
+    libsm6 \
+    libxext6 \
+    libxrender-dev \
+    libglib2.0-0 \
+    libgl1-mesa-glx \
+    && rm -rf /var/lib/apt/lists/*
+
+# Install Python dependencies
+RUN pip install --no-cache-dir \
+    runpod \
+    requests \
+    pillow \
+    numpy \
+    torch \
+    torchvision \
+    torchaudio \
+    xformers \
+    accelerate \
+    transformers \
+    diffusers \
+    opencv-python \
+    scipy \
+    scikit-image
+
+# Clone ComfyUI
+RUN git clone https://github.com/bahadirciloglu/ComfyUI.git /workspace/ComfyUI
+
+# Set ComfyUI as working directory
+WORKDIR /workspace/ComfyUI
+
+# Switch to create_image branch
+RUN git checkout create_image
+
+# Install ComfyUI requirements
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Install additional dependencies for new features
+RUN pip install --no-cache-dir \
+    safetensors \
+    transformers[torch] \
+    accelerate \
+    bitsandbytes \
+    optimum
+
+# Copy serverless handler
+COPY runpod_handler.py /workspace/runpod_handler.py
+COPY .env /workspace/.env
+
+# Create necessary directories
+RUN mkdir -p /workspace/ComfyUI/models/checkpoints \
+    /workspace/ComfyUI/models/vae \
+    /workspace/ComfyUI/models/loras \
+    /workspace/ComfyUI/models/controlnet \
+    /workspace/ComfyUI/models/clip_vision \
+    /workspace/ComfyUI/models/upscale_models \
+    /workspace/ComfyUI/input \
+    /workspace/ComfyUI/output \
+    /tmp/inputs \
+    /tmp/outputs \
+    /tmp/comfyui
+
+# Set environment variables
+ENV PYTHONPATH="/workspace/ComfyUI:${PYTHONPATH}"
+ENV COMFYUI_SERVERLESS=true
+ENV NVIDIA_VISIBLE_DEVICES=all
+ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
+
+# Create startup script
+RUN echo '#!/bin/bash\n\
+cd /workspace/ComfyUI\n\
+python main.py --listen 0.0.0.0 --port 8000 --dont-print-server --disable-auto-launch &\n\
+sleep 10\n\
+cd /workspace\n\
+python runpod_handler.py' > /workspace/start.sh && chmod +x /workspace/start.sh
+
+# Expose port
+EXPOSE 8000
+
+# Set the command
+CMD ["/workspace/start.sh"]

runpod_handler.py

@@ -0,0 +1,245 @@
+#!/usr/bin/env python3
+"""
+RunPod Serverless Worker Handler for ComfyUI
+Optimized for the new ComfyUI features and performance improvements
+"""
+
+import os
+import json
+import time
+import logging
+import tempfile
+import requests
+from typing import Dict, Any, Optional
+import runpod
+
+# Configure logging
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+)
+logger = logging.getLogger(__name__)
+
+class ComfyUIServerlessHandler:
+    def __init__(self):
+        self.comfyui_url = "http://127.0.0.1:8000"
+        self.client_id = "runpod_serverless_worker"
+        self.setup_paths()
+        
+    def setup_paths(self):
+        """Setup required paths for serverless operation"""
+        os.makedirs("/tmp/inputs", exist_ok=True)
+        os.makedirs("/tmp/outputs", exist_ok=True)
+        os.makedirs("/tmp/comfyui", exist_ok=True)
+        
+    def wait_for_comfyui(self, timeout: int = 120) -> bool:
+        """Wait for ComfyUI to be ready"""
+        start_time = time.time()
+        while time.time() - start_time < timeout:
+            try:
+                response = requests.get(f"{self.comfyui_url}/system_stats")
+                if response.status_code == 200:
+                    logger.info("ComfyUI is ready")
+                    return True
+            except requests.exceptions.RequestException:
+                pass
+            time.sleep(2)
+        
+        logger.error(f"ComfyUI not ready after {timeout} seconds")
+        return False
+    
+    def download_input_files(self, input_data: Dict[str, Any]) -> Dict[str, str]:
+        """Download input files and return local paths"""
+        local_files = {}
+        
+        if "input_files" in input_data:
+            for file_key, file_url in input_data["input_files"].items():
+                try:
+                    response = requests.get(file_url, timeout=60)
+                    response.raise_for_status()
+                    
+                    # Create temporary file
+                    with tempfile.NamedTemporaryFile(
+                        delete=False, 
+                        dir="/tmp/inputs",
+                        suffix=os.path.splitext(file_url)[1]
+                    ) as tmp_file:
+                        tmp_file.write(response.content)
+                        local_files[file_key] = tmp_file.name
+                        
+                    logger.info(f"Downloaded {file_key} to {local_files[file_key]}")
+                    
+                except Exception as e:
+                    logger.error(f"Failed to download {file_key}: {str(e)}")
+                    raise
+        
+        return local_files
+    
+    def execute_workflow(self, workflow: Dict[str, Any]) -> Dict[str, Any]:
+        """Execute ComfyUI workflow"""
+        try:
+            # Queue the workflow
+            queue_response = requests.post(
+                f"{self.comfyui_url}/prompt",
+                json={
+                    "prompt": workflow,
+                    "client_id": self.client_id
+                },
+                timeout=30
+            )
+            queue_response.raise_for_status()
+            
+            prompt_id = queue_response.json()["prompt_id"]
+            logger.info(f"Queued workflow with prompt_id: {prompt_id}")
+            
+            # Wait for completion
+            return self.wait_for_completion(prompt_id)
+            
+        except Exception as e:
+            logger.error(f"Failed to execute workflow: {str(e)}")
+            raise
+    
+    def wait_for_completion(self, prompt_id: str, timeout: int = 300) -> Dict[str, Any]:
+        """Wait for workflow completion and return results"""
+        start_time = time.time()
+        
+        while time.time() - start_time < timeout:
+            try:
+                # Check queue status
+                queue_response = requests.get(f"{self.comfyui_url}/queue")
+                queue_data = queue_response.json()
+                
+                # Check if our job is still in queue
+                running = any(item[1]["prompt_id"] == prompt_id for item in queue_data.get("queue_running", []))
+                pending = any(item[1]["prompt_id"] == prompt_id for item in queue_data.get("queue_pending", []))
+                
+                if not running and not pending:
+                    # Job completed, get results
+                    history_response = requests.get(f"{self.comfyui_url}/history/{prompt_id}")
+                    if history_response.status_code == 200:
+                        history_data = history_response.json()
+                        if prompt_id in history_data:
+                            return self.process_results(history_data[prompt_id])
+                
+                time.sleep(2)
+                
+            except Exception as e:
+                logger.error(f"Error checking completion: {str(e)}")
+                time.sleep(5)
+        
+        raise TimeoutError(f"Workflow {prompt_id} timed out after {timeout} seconds")
+    
+    def process_results(self, history_data: Dict[str, Any]) -> Dict[str, Any]:
+        """Process and upload results"""
+        results = {
+            "status": "completed",
+            "outputs": [],
+            "metadata": {}
+        }
+        
+        if "outputs" in history_data:
+            for node_id, node_output in history_data["outputs"].items():
+                if "images" in node_output:
+                    for image_info in node_output["images"]:
+                        # Download image from ComfyUI
+                        image_url = f"{self.comfyui_url}/view"
+                        params = {
+                            "filename": image_info["filename"],
+                            "subfolder": image_info.get("subfolder", ""),
+                            "type": image_info.get("type", "output")
+                        }
+                        
+                        try:
+                            image_response = requests.get(image_url, params=params)
+                            image_response.raise_for_status()
+                            
+                            # Save to temp file for upload
+                            output_path = f"/tmp/outputs/{image_info['filename']}"
+                            with open(output_path, "wb") as f:
+                                f.write(image_response.content)
+                            
+                            results["outputs"].append({
+                                "type": "image",
+                                "filename": image_info["filename"],
+                                "path": output_path,
+                                "node_id": node_id
+                            })
+                            
+                        except Exception as e:
+                            logger.error(f"Failed to process image {image_info['filename']}: {str(e)}")
+        
+        return results
+    
+    def cleanup(self):
+        """Clean up temporary files"""
+        try:
+            import shutil
+            shutil.rmtree("/tmp/inputs", ignore_errors=True)
+            shutil.rmtree("/tmp/outputs", ignore_errors=True)
+            os.makedirs("/tmp/inputs", exist_ok=True)
+            os.makedirs("/tmp/outputs", exist_ok=True)
+            logger.info("Cleaned up temporary files")
+        except Exception as e:
+            logger.error(f"Cleanup failed: {str(e)}")
+
+def handler(job: Dict[str, Any]) -> Dict[str, Any]:
+    """Main serverless handler function"""
+    handler_instance = ComfyUIServerlessHandler()
+    
+    try:
+        # Wait for ComfyUI to be ready
+        if not handler_instance.wait_for_comfyui():
+            return {"error": "ComfyUI failed to start"}
+        
+        # Get job input
+        job_input = job.get("input", {})
+        
+        # Download input files if any
+        local_files = handler_instance.download_input_files(job_input)
+        
+        # Update workflow with local file paths
+        workflow = job_input.get("workflow", {})
+        if local_files and "file_mappings" in job_input:
+            for node_id, mappings in job_input["file_mappings"].items():
+                if node_id in workflow:
+                    for input_key, file_key in mappings.items():
+                        if file_key in local_files:
+                            workflow[node_id]["inputs"][input_key] = local_files[file_key]
+        
+        # Execute workflow
+        results = handler_instance.execute_workflow(workflow)
+        
+        # Upload output files to RunPod storage or return base64
+        output_urls = []
+        for output in results.get("outputs", []):
+            if output["type"] == "image":
+                # For serverless, we typically return base64 or upload to storage
+                with open(output["path"], "rb") as f:
+                    import base64
+                    image_data = base64.b64encode(f.read()).decode()
+                    output_urls.append({
+                        "filename": output["filename"],
+                        "data": image_data,
+                        "node_id": output["node_id"]
+                    })
+        
+        return {
+            "status": "success",
+            "outputs": output_urls,
+            "execution_time": time.time() - job.get("start_time", time.time())
+        }
+        
+    except Exception as e:
+        logger.error(f"Handler error: {str(e)}")
+        return {
+            "error": str(e),
+            "status": "failed"
+        }
+    
+    finally:
+        # Always cleanup
+        handler_instance.cleanup()
+
+if __name__ == "__main__":
+    # Start the serverless worker
+    runpod.serverless.start({"handler": handler})

runpod_setup.md

@@ -0,0 +1,150 @@
+# RunPod Network Storage Setup Guide
+
+## 1. Network Storage Hazırlığı
+
+### RunPod Dashboard'da:
+1. **Network Storage** oluşturun (örn: `comfyui-models`)
+2. Storage boyutunu belirleyin (en az 50GB önerilir)
+3. Storage ID'sini not alın
+
+### Modelleri Network Storage'a Yükleme:
+```bash
+# RunPod pod'unda terminal açın
+cd /runpod-volume
+
+# Models klasörü oluşturun
+mkdir -p models/{checkpoints,loras,vae,controlnet,upscale_models,text_encoders,clip,diffusion_models,unet,embeddings,clip_vision}
+
+# Örnek model indirme (SDXL Base)
+cd models/checkpoints
+wget https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/resolve/main/sd_xl_base_1.0.safetensors
+
+# VAE modeli
+cd ../vae
+wget https://huggingface.co/stabilityai/sdxl-vae/resolve/main/sdxl_vae.safetensors
+
+# ControlNet modeli
+cd ../controlnet
+wget https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/diffusers_xl_canny_mid.safetensors
+```
+
+## 2. RunPod Template Ayarları
+
+### Container Settings:
+- **Docker Image**: `your-registry/comfyui-runpod:latest`
+- **Container Disk**: 20GB (minimum)
+- **Network Storage**: Mount ettiğiniz storage'ı seçin
+
+### Environment Variables:
+```bash
+# Zorunlu
+RUNPOD_NETWORK_STORAGE_PATH=/runpod-volume
+PORT=8188
+
+# Opsiyonel
+LISTEN=0.0.0.0
+COMFYUI_ARGS=--preview-method auto
+DOWNLOAD_MODELS=sdxl-base,sdxl-vae  # Otomatik indirme için
+```
+
+### Ports:
+- **Container Port**: 8188
+- **Expose HTTP Ports**: 8188
+
+## 3. Model Klasör Yapısı
+
+Network storage'da şu yapı oluşturulmalı:
+```
+/runpod-volume/
+└── models/
+    ├── checkpoints/          # Ana modeller (SDXL, SD 1.5, vb.)
+    │   ├── sd_xl_base_1.0.safetensors
+    │   └── sd_xl_refiner_1.0.safetensors
+    ├── loras/               # LoRA modelleri
+    ├── vae/                 # VAE modelleri
+    │   └── sdxl_vae.safetensors
+    ├── controlnet/          # ControlNet modelleri
+    ├── upscale_models/      # Upscaler modeller
+    ├── text_encoders/       # CLIP modelleri
+    ├── clip/               # Legacy CLIP klasörü
+    ├── diffusion_models/    # UNet modelleri
+    ├── unet/               # Legacy UNet klasörü
+    ├── embeddings/         # Textual Inversion
+    └── clip_vision/        # CLIP Vision modelleri
+```
+
+## 4. Popüler Modeller
+
+### Checkpoints:
+```bash
+# SDXL Base
+wget https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/resolve/main/sd_xl_base_1.0.safetensors
+
+# SDXL Refiner
+wget https://huggingface.co/stabilityai/stable-diffusion-xl-refiner-1.0/resolve/main/sd_xl_refiner_1.0.safetensors
+
+# SD 1.5
+wget https://huggingface.co/runwayml/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.safetensors
+```
+
+### VAE:
+```bash
+# SDXL VAE
+wget https://huggingface.co/stabilityai/sdxl-vae/resolve/main/sdxl_vae.safetensors
+
+# SD 1.5 VAE
+wget https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.safetensors
+```
+
+### ControlNet:
+```bash
+# SDXL Canny
+wget https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/diffusers_xl_canny_mid.safetensors
+
+# SDXL Depth
+wget https://huggingface.co/lllyasviel/sd_control_collection/resolve/main/diffusers_xl_depth_mid.safetensors
+```
+
+## 5. Deployment
+
+### Build ve Push:
+```bash
+# Docker image build
+docker build -t your-registry/comfyui-runpod:latest .
+
+# Registry'ye push
+docker push your-registry/comfyui-runpod:latest
+```
+
+### RunPod'da Deploy:
+1. Template oluşturun
+2. Network storage'ı mount edin
+3. Environment variables'ları ayarlayın
+4. Deploy edin
+
+## 6. Monitoring
+
+Container loglarında şunları göreceksiniz:
+```
+2024-11-01 13:15:00 - INFO - RunPod ComfyUI başlatılıyor...
+2024-11-01 13:15:01 - INFO - Network storage hazır
+2024-11-01 13:15:02 - INFO - Models klasörü network storage'a bağlandı
+2024-11-01 13:15:03 - INFO - Model klasörü: checkpoints (2 dosya)
+2024-11-01 13:15:04 - INFO - ComfyUI başlatılıyor...
+```
+
+## 7. Troubleshooting
+
+### Network Storage Mount Edilmezse:
+- Local models klasörü kullanılır
+- Logları kontrol edin: `RUNPOD_NETWORK_STORAGE_PATH` doğru mu?
+
+### Modeller Bulunamazsa:
+- Network storage'da model dosyaları var mı kontrol edin
+- Dosya izinlerini kontrol edin
+- Symlink'in doğru çalıştığını kontrol edin
+
+### Performance İyileştirme:
+- GPU instance kullanın (CPU yerine)
+- Dockerfile'da `--cpu` parametresini kaldırın
+- CUDA support ekleyin

start_runpod.py

@@ -0,0 +1,206 @@
+#!/usr/bin/env python3
+"""
+RunPod başlangıç scripti - Network storage mount ve model yönetimi
+"""
+
+import os
+import sys
+import logging
+import subprocess
+import time
+from pathlib import Path
+
+# Logging setup
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s - %(levelname)s - %(message)s'
+)
+logger = logging.getLogger(__name__)
+
+def mount_runpod_storage():
+    """RunPod network storage'ı mount et"""
+    try:
+        # RunPod network storage path (environment variable'dan al)
+        network_storage_path = os.environ.get('RUNPOD_NETWORK_STORAGE_PATH', '/runpod-volume')
+        models_storage_path = os.path.join(network_storage_path, 'models')
+        
+        # Local models klasörü
+        local_models_path = '/app/models'
+        
+        logger.info(f"Network storage path: {network_storage_path}")
+        logger.info(f"Models storage path: {models_storage_path}")
+        
+        # Network storage'da models klasörü var mı kontrol et
+        if os.path.exists(models_storage_path):
+            logger.info("Network storage'da models klasörü bulundu")
+            
+            # Local models klasörünü sil ve symlink oluştur
+            if os.path.exists(local_models_path):
+                if os.path.islink(local_models_path):
+                    os.unlink(local_models_path)
+                else:
+                    import shutil
+                    shutil.rmtree(local_models_path)
+            
+            # Symlink oluştur
+            os.symlink(models_storage_path, local_models_path)
+            logger.info(f"Models klasörü network storage'a bağlandı: {models_storage_path} -> {local_models_path}")
+            
+            # Model klasörlerini kontrol et
+            check_model_folders(local_models_path)
+            
+        else:
+            logger.warning(f"Network storage'da models klasörü bulunamadı: {models_storage_path}")
+            logger.info("Local models klasörü kullanılacak")
+            
+            # Network storage'da models klasörü oluştur
+            os.makedirs(models_storage_path, exist_ok=True)
+            logger.info(f"Network storage'da models klasörü oluşturuldu: {models_storage_path}")
+            
+            # Mevcut local models'i network storage'a taşı
+            if os.path.exists(local_models_path) and not os.path.islink(local_models_path):
+                import shutil
+                shutil.copytree(local_models_path, models_storage_path, dirs_exist_ok=True)
+                shutil.rmtree(local_models_path)
+                logger.info("Local models network storage'a taşındı")
+            
+            # Symlink oluştur
+            os.symlink(models_storage_path, local_models_path)
+            logger.info("Models klasörü network storage'a bağlandı")
+            
+    except Exception as e:
+        logger.error(f"Network storage mount hatası: {e}")
+        logger.info("Local models klasörü kullanılacak")
+        ensure_local_model_folders()
+
+def check_model_folders(models_path):
+    """Model klasörlerinin varlığını kontrol et"""
+    required_folders = [
+        'checkpoints',
+        'loras', 
+        'vae',
+        'controlnet',
+        'upscale_models',
+        'text_encoders',
+        'clip',
+        'diffusion_models',
+        'unet',
+        'embeddings',
+        'clip_vision'
+    ]
+    
+    for folder in required_folders:
+        folder_path = os.path.join(models_path, folder)
+        if not os.path.exists(folder_path):
+            os.makedirs(folder_path, exist_ok=True)
+            logger.info(f"Model klasörü oluşturuldu: {folder}")
+        else:
+            # Klasördeki dosya sayısını kontrol et
+            file_count = len([f for f in os.listdir(folder_path) if os.path.isfile(os.path.join(folder_path, f))])
+            logger.info(f"Model klasörü: {folder} ({file_count} dosya)")
+
+def ensure_local_model_folders():
+    """Local model klasörlerini oluştur"""
+    models_path = '/app/models'
+    check_model_folders(models_path)
+
+def download_essential_models():
+    """Temel modelleri indir (opsiyonel)"""
+    try:
+        models_to_download = os.environ.get('DOWNLOAD_MODELS', '').split(',')
+        models_to_download = [m.strip() for m in models_to_download if m.strip()]
+        
+        if not models_to_download:
+            logger.info("İndirilecek model belirtilmedi")
+            return
+            
+        logger.info(f"İndirilecek modeller: {models_to_download}")
+        
+        # Burada model indirme logic'i eklenebilir
+        # Örnek: huggingface-hub kullanarak
+        
+    except Exception as e:
+        logger.error(f"Model indirme hatası: {e}")
+
+def setup_environment():
+    """Çevre değişkenlerini ayarla"""
+    # ComfyUI için gerekli environment variables
+    os.environ['HF_HUB_DISABLE_TELEMETRY'] = '1'
+    os.environ['DO_NOT_TRACK'] = '1'
+    
+    # RunPod specific
+    if 'RUNPOD_POD_ID' in os.environ:
+        logger.info(f"RunPod Pod ID: {os.environ['RUNPOD_POD_ID']}")
+    
+    # Port ayarı
+    port = os.environ.get('PORT', '8188')
+    os.environ['PORT'] = port
+    logger.info(f"Server port: {port}")
+
+def wait_for_storage():
+    """Network storage'ın hazır olmasını bekle"""
+    max_wait = 30  # 30 saniye
+    wait_interval = 2
+    
+    network_storage_path = os.environ.get('RUNPOD_NETWORK_STORAGE_PATH', '/runpod-volume')
+    
+    for i in range(0, max_wait, wait_interval):
+        if os.path.exists(network_storage_path):
+            logger.info("Network storage hazır")
+            return True
+        
+        logger.info(f"Network storage bekleniyor... ({i}/{max_wait}s)")
+        time.sleep(wait_interval)
+    
+    logger.warning("Network storage timeout - local storage kullanılacak")
+    return False
+
+def main():
+    """Ana başlangıç fonksiyonu"""
+    logger.info("RunPod ComfyUI başlatılıyor...")
+    
+    # Environment setup
+    setup_environment()
+    
+    # Network storage'ı bekle
+    wait_for_storage()
+    
+    # Network storage mount
+    mount_runpod_storage()
+    
+    # Temel modelleri indir (opsiyonel)
+    download_essential_models()
+    
+    # ComfyUI'yi başlat
+    logger.info("ComfyUI başlatılıyor...")
+    
+    # Port ve listen address
+    port = os.environ.get('PORT', '8188')
+    listen = os.environ.get('LISTEN', '0.0.0.0')
+    
+    # ComfyUI command
+    cmd = [
+        sys.executable, 'main.py',
+        '--listen', listen,
+        '--port', port,
+        '--cpu'  # CPU mode for RunPod
+    ]
+    
+    # Extra args
+    if os.environ.get('COMFYUI_ARGS'):
+        extra_args = os.environ['COMFYUI_ARGS'].split()
+        cmd.extend(extra_args)
+    
+    logger.info(f"ComfyUI komutu: {' '.join(cmd)}")
+    
+    # ComfyUI'yi başlat
+    try:
+        subprocess.run(cmd, check=True)
+    except KeyboardInterrupt:
+        logger.info("ComfyUI durduruldu")
+    except Exception as e:
+        logger.error(f"ComfyUI başlatma hatası: {e}")
+        sys.exit(1)
+
+if __name__ == "__main__":
+    main()

test_workflow.json

@@ -0,0 +1,63 @@
+{
+  "input": {
+    "workflow": {
+      "3": {
+        "inputs": {
+          "seed": 42,
+          "steps": 20,
+          "cfg": 7.0,
+          "sampler_name": "euler",
+          "scheduler": "normal",
+          "denoise": 1.0,
+          "model": ["4", 0],
+          "positive": ["6", 0],
+          "negative": ["7", 0],
+          "latent_image": ["5", 0]
+        },
+        "class_type": "KSampler"
+      },
+      "4": {
+        "inputs": {
+          "ckpt_name": "sd_xl_base_1.0.safetensors"
+        },
+        "class_type": "CheckpointLoaderSimple"
+      },
+      "5": {
+        "inputs": {
+          "width": 1024,
+          "height": 1024,
+          "batch_size": 1
+        },
+        "class_type": "EmptyLatentImage"
+      },
+      "6": {
+        "inputs": {
+          "text": "a beautiful landscape with mountains and a lake, highly detailed, 8k",
+          "clip": ["4", 1]
+        },
+        "class_type": "CLIPTextEncode"
+      },
+      "7": {
+        "inputs": {
+          "text": "blurry, low quality, distorted",
+          "clip": ["4", 1]
+        },
+        "class_type": "CLIPTextEncode"
+      },
+      "8": {
+        "inputs": {
+          "samples": ["3", 0],
+          "vae": ["4", 2]
+        },
+        "class_type": "VAEDecode"
+      },
+      "9": {
+        "inputs": {
+          "filename_prefix": "ComfyUI",
+          "images": ["8", 0]
+        },
+        "class_type": "SaveImage"
+      }
+    }
+  }
+}