chore: reorganize workflow assets and remove unused files

- Move example images to their respective workflow directories
- Remove unused COMFYUI_MODELS.md (content consolidated elsewhere)
- Remove fix_workflows.py script (no longer needed)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
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2025-11-23 12:01:38 +01:00
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# ComfyUI Models & Nodes - Usage Guide
This document explains how to use the extended playbook.yml for installing ComfyUI models and custom nodes.
## What's Been Added
### Model Categories
**Image Generation Models:**
- FLUX.1 Schnell (23GB, essential) - Fast 4-step inference
- FLUX.1 Dev (23GB, optional) - Balanced quality/speed
- SDXL Base 1.0 (7GB, essential) - Industry standard
- SDXL Refiner 1.0 (6GB, optional) - Enhances base output
- SD 3.5 Large (18GB, optional) - Latest Stability AI
**Video Generation Models:**
- CogVideoX-5B (20GB, essential) - Professional text-to-video
- SVD (8GB, essential) - 14 frame image-to-video
- SVD-XT (8GB, optional) - 25 frame image-to-video
**Audio Generation Models:**
- MusicGen Small (3GB, optional) - Fast generation
- MusicGen Medium (11GB, essential) - Balanced quality
- MusicGen Large (22GB, optional) - Highest quality
**Support Models:**
- CLIP H (2GB, essential) - For SD 1.5 IP-Adapter
- CLIP G (7GB, essential) - For SDXL IP-Adapter
- SigLIP (2GB, essential) - For FLUX models
### Custom Nodes
**Essential Nodes (installed by default):**
- ComfyUI-Manager - Install/manage custom nodes and models
- ComfyUI-VideoHelperSuite - Video operations
- ComfyUI-AnimateDiff-Evolved - Video generation
- ComfyUI_IPAdapter_plus - Style transfer
- ComfyUI-Impact-Pack - Auto face enhancement
- comfyui-sound-lab - Audio generation
**Optional Nodes:**
- ComfyUI-CogVideoXWrapper - CogVideoX integration
- Comfyui-Inspire-Pack - Additional tools
- ComfyUI-Advanced-ControlNet - Advanced control
- ComfyUI-3D-Pack - 3D asset generation
## Usage Examples
### Quick Setup (Essential Only)
Install ComfyUI with only essential models and nodes:
```bash
ansible-playbook playbook.yml --tags comfyui-essential
```
This downloads:
- Image: FLUX Schnell (23GB) + SDXL Base (7GB)
- Video: CogVideoX-5B (20GB) + SVD (8GB)
- Audio: MusicGen Medium (11GB)
- Support: All 3 CLIP models (11GB)
- **Total: ~80GB**
### Selective Installation
#### Install ComfyUI Base Only
```bash
ansible-playbook playbook.yml --tags comfyui
```
#### Install All Image Models
```bash
ansible-playbook playbook.yml --tags comfyui-models-image
```
#### Install All Video Models
```bash
ansible-playbook playbook.yml --tags comfyui-models-video
```
#### Install All Audio Models
```bash
ansible-playbook playbook.yml --tags comfyui-models-audio
```
#### Install Support Models (CLIP, IP-Adapter)
```bash
ansible-playbook playbook.yml --tags comfyui-models-support
```
#### Install Custom Nodes
```bash
ansible-playbook playbook.yml --tags comfyui-nodes
```
### Combined Installation
#### Full ComfyUI Setup
```bash
ansible-playbook playbook.yml --tags comfyui,comfyui-models-all,comfyui-nodes
```
#### ComfyUI + Image + Video Only
```bash
ansible-playbook playbook.yml --tags comfyui,comfyui-models-image,comfyui-models-video,comfyui-nodes
```
## Adding New Models
### Add Image Model
Edit `playbook.yml` and append to `comfyui_image_models`:
```yaml
- name: "author/model-name"
type: "checkpoint"
category: "image"
size_gb: 15
vram_gb: 18
format: "fp16"
description: "Model description"
essential: false # Set to true for default installs
```
### Add Custom Node
Append to `comfyui_custom_nodes`:
```yaml
- name: "NodeName"
repo: "https://github.com/author/repo.git"
category: "image" # or video, audio, control, etc.
description: "What it does"
essential: false
```
## VRAM Requirements Summary
For your **24GB GPU**, you can run:
### Simultaneously Loadable Combinations
**Option 1: Image Generation Focus**
- FLUX Schnell FP16 (23GB) → Full model, leaves 1GB for operations
- FLUX Schnell FP8 (12GB) + SDXL (12GB) → Both loaded
- SDXL (12GB) + Refiner (12GB) → Both loaded with room
**Option 2: Video Generation**
- CogVideoX-5B with optimizations (12GB) + SDXL (12GB)
- SVD-XT (20GB) → Good frame count
**Option 3: Multi-Modal**
- SDXL (12GB) + MusicGen Medium (8GB)
- CogVideoX-5B (12GB) + MusicGen Small (4GB)
## Storage Requirements
### Essential Models Only
- Image: 30GB
- Video: 28GB
- Audio: 11GB
- Support: 11GB
- **Total: ~80GB**
### All Models (including optional)
- Image: 54GB
- Video: 36GB
- Audio: 36GB
- Support: 11GB
- **Total: ~137GB**
## Directory Structure Created
```
/workspace/ComfyUI/
├── models/
│ ├── checkpoints/ # FLUX, SDXL, SD3 models
│ ├── unet/ # Diffusion U-Nets
│ ├── vae/ # VAE models
│ ├── loras/ # LoRA adapters
│ ├── clip/ # CLIP text encoders
│ ├── clip_vision/ # CLIP vision models
│ ├── controlnet/ # ControlNet models
│ ├── ipadapter/ # IP-Adapter models
│ ├── embeddings/ # Text embeddings
│ ├── upscale_models/ # Upscalers
│ ├── video_models/ # Video generation models
│ ├── animatediff_models/ # AnimateDiff models
│ ├── audio_models/ # Audio generation models
│ └── configs/ # Model configs
└── custom_nodes/ # Extension nodes
```
## Extending the Playbook
### Add a New Model Category
1. Add variable list in `vars` section:
```yaml
comfyui_new_category_models:
- name: "model-repo-id"
type: "new_type"
category: "new_category"
size_gb: 10
description: "Description"
essential: true
```
2. Create download task section:
```yaml
- name: Download New Category Models
tags: [comfyui-models-newcat, comfyui-models-all]
block:
# Copy pattern from existing model download tasks
```
3. Update tags documentation at top of file
## Model Download Notes
- **Async Downloads**: Large models download asynchronously with 1-hour timeouts
- **Smart Caching**: Models are only downloaded if not already cached
- **HuggingFace Token**: Set `HF_TOKEN` environment variable for gated models
- **Error Handling**: Download failures are ignored to allow partial installations
## Performance Tips
### For 24GB GPU:
1. **Use FP8 Quantized FLUX** when you need multiple models loaded
2. **Use Full FP16 FLUX** when you want maximum quality
3. **Enable CogVideoX Optimizations** to fit in 12GB (edit model config)
4. **Use GGUF variants** for FLUX to save VRAM (manually download)
### Recommended First Install:
```bash
# Essential setup (~80GB, ~1 hour)
ansible-playbook playbook.yml --tags comfyui-essential
```
Then add specific models as needed:
```bash
# Add video models later
ansible-playbook playbook.yml --tags comfyui-models-video
```
## Troubleshooting
### Downloads Failing
Check HuggingFace token:
```bash
export HF_TOKEN="your_token_here"
ansible-playbook playbook.yml --tags comfyui-models-image
```
### Out of Space
Check available storage:
```bash
df -h /workspace
du -sh /workspace/huggingface_cache
```
Remove optional models:
```bash
# Keep only essential models in playbook vars
```
### Custom Node Dependencies
Some nodes require manual intervention:
```bash
cd /workspace/ComfyUI/custom_nodes/NodeName
pip3 install -r requirements.txt
```
## Next Steps
After installation:
1. **Start ComfyUI:**
```bash
cd /workspace/ComfyUI
python3 main.py --listen 0.0.0.0 --port 8188
```
2. **Access via Browser:**
```
http://your-runpod-ip:8188
```
3. **Install Additional Nodes via Manager:**
- ComfyUI Manager provides GUI for installing more nodes
- Browse and install from the manager interface
4. **Download Model Variants:**
- Use ComfyUI Manager to download LoRAs
- Download ControlNet models as needed
- Get additional checkpoints from Civitai
## Support
For issues or questions:
- Check Ansible logs for download status
- Verify HuggingFace token is valid
- Ensure sufficient storage space
- Check VRAM requirements for your GPU

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#!/usr/bin/env python3
"""
ComfyUI Workflow Schema Fixer
Fixes missing schema fields in ComfyUI workflow JSON files:
- Adds missing 'flags', 'order', 'mode', 'properties', 'size' fields to nodes
- Reconstructs 'inputs' and 'outputs' arrays from links
- Builds complete 'links' array
- Updates outdated node names
Usage:
python3 fix_workflows.py <workflow_directory>
"""
import json
import sys
from pathlib import Path
from typing import Dict, List, Any
# Node name mapping (old → new)
NODE_NAME_MAPPING = {
'AnimateDiffLoader': 'AnimateDiffLoaderV1',
'VHSVideoCombine': 'VHS_VideoCombine',
'PreviewVideo': None, # Remove - use VHS_VideoCombine with preview enabled
'SaveVideo': None, # Remove - use VHS_VideoCombine
'IPAdapterApply': 'IPAdapter',
'IPAdapterApplyFace': 'IPAdapterFaceID',
'AudioSave': 'SaveAudio',
'AnimateDiffSampler': 'KSamplerAdvanced', # AnimateDiff uses standard KSampler
'ADE_AnimateDiffSampler': 'KSamplerAdvanced',
'SeedGenerator': 'ImpactInt', # Use Impact Pack integer node for seed generation
'BatchKSampler': 'KSampler', # Standard KSampler can handle batches
'ImageBatchToList': 'GetImageSize', # Placeholder - may need manual adjustment
}
# Default node sizes by category
NODE_SIZES = {
'Loader': {'0': 350, '1': 100},
'Sampler': {'0': 315, '1': 474},
'Encoder': {'0': 400, '1': 200},
'Default': {'0': 315, '1': 100},
}
def get_node_size(node_type: str) -> Dict[str, int]:
"""Get appropriate size for node based on type"""
if 'Loader' in node_type or 'Load' in node_type:
return NODE_SIZES['Loader']
elif 'Sampler' in node_type or 'KSampler' in node_type:
return NODE_SIZES['Sampler']
elif 'Encode' in node_type or 'CLIP' in node_type:
return NODE_SIZES['Encoder']
else:
return NODE_SIZES['Default']
def fix_workflow(workflow_path: Path) -> bool:
"""Fix a single workflow file"""
print(f"\n{'='*60}")
print(f"Processing: {workflow_path.name}")
print(f"{'='*60}")
try:
with open(workflow_path, 'r') as f:
workflow = json.load(f)
except json.JSONDecodeError as e:
print(f"✗ ERROR: Invalid JSON - {e}")
return False
if 'nodes' not in workflow:
print(f"✗ ERROR: No 'nodes' key in workflow")
return False
nodes = workflow['nodes']
links = workflow.get('links', [])
# Track changes
changes = {
'added_flags': 0,
'added_order': 0,
'added_mode': 0,
'added_properties': 0,
'added_size': 0,
'added_inputs': 0,
'added_outputs': 0,
'updated_node_names': 0,
'removed_nodes': 0,
'added_last_link_id': 0,
'added_links': 0,
}
# Build link index for quick lookup
link_index = {}
for link in links:
if len(link) >= 6:
link_id, src_node_id, src_slot, tgt_node_id, tgt_slot, data_type = link[:6]
link_index[link_id] = {
'source': {'node_id': src_node_id, 'slot': src_slot},
'target': {'node_id': tgt_node_id, 'slot': tgt_slot},
'type': data_type
}
# Build node ID index
node_by_id = {node['id']: node for node in nodes}
# Process each node
nodes_to_remove = []
for i, node in enumerate(nodes):
node_id = node.get('id')
node_type = node.get('type', '')
# Update node name if needed
if node_type in NODE_NAME_MAPPING:
new_name = NODE_NAME_MAPPING[node_type]
if new_name is None:
# Mark for removal
nodes_to_remove.append(i)
changes['removed_nodes'] += 1
print(f" Removing deprecated node {node_id}: {node_type}")
continue
else:
print(f" Updating node {node_id}: {node_type}{new_name}")
node['type'] = new_name
node_type = new_name
changes['updated_node_names'] += 1
# Add missing flags
if 'flags' not in node:
node['flags'] = {}
changes['added_flags'] += 1
# Add missing order (will recalculate later based on dependencies)
if 'order' not in node:
node['order'] = i # Temporary order
changes['added_order'] += 1
# Add missing mode (0 = execute, 4 = bypass)
if 'mode' not in node:
node['mode'] = 0
changes['added_mode'] += 1
# Add missing properties
if 'properties' not in node:
node['properties'] = {"Node name for S&R": node_type}
changes['added_properties'] += 1
# Add missing size
if 'size' not in node:
node['size'] = get_node_size(node_type)
changes['added_size'] += 1
# Reconstruct inputs from links
if 'inputs' not in node or not node['inputs']:
node_inputs = []
for link_id, link_data in link_index.items():
if link_data['target']['node_id'] == node_id:
# This link targets this node
# We need to know the input name, but we don't have it
# For now, create a placeholder
node_inputs.append({
'name': f'input_{link_data["target"]["slot"]}',
'type': link_data['type'],
'link': link_id
})
if node_inputs:
node['inputs'] = node_inputs
changes['added_inputs'] += 1
# Reconstruct outputs from links
if 'outputs' not in node or not node['outputs']:
node_outputs = {}
for link_id, link_data in link_index.items():
if link_data['source']['node_id'] == node_id:
slot = link_data['source']['slot']
if slot not in node_outputs:
node_outputs[slot] = {
'name': f'output_{slot}',
'type': link_data['type'],
'links': [],
'slot_index': slot
}
node_outputs[slot]['links'].append(link_id)
if node_outputs:
node['outputs'] = list(node_outputs.values())
changes['added_outputs'] += 1
# Remove deprecated nodes
for i in reversed(nodes_to_remove):
del nodes[i]
# Recalculate execution order based on dependencies
if changes['added_order'] > 0 or changes['removed_nodes'] > 0:
calculate_execution_order(nodes, link_index)
# Add missing links array
if 'links' not in workflow:
workflow['links'] = []
changes['added_links'] = 1
# Add missing last_link_id
if 'last_link_id' not in workflow:
# Calculate from existing links
max_link_id = 0
if workflow.get('links'):
for link in workflow['links']:
if link and len(link) > 0:
max_link_id = max(max_link_id, link[0])
workflow['last_link_id'] = max_link_id
changes['added_last_link_id'] = 1
# Update workflow
workflow['nodes'] = nodes
# Print summary
print(f"\nChanges made:")
for key, value in changes.items():
if value > 0:
print(f"{key.replace('_', ' ').title()}: {value}")
total_changes = sum(changes.values())
if total_changes == 0:
print(f" ✓ No changes needed - workflow already valid")
return True
# Save fixed workflow
try:
with open(workflow_path, 'w') as f:
json.dump(workflow, f, indent=2)
print(f"\n✓ Successfully fixed and saved workflow")
return True
except Exception as e:
print(f"\n✗ ERROR saving workflow: {e}")
return False
def calculate_execution_order(nodes: List[Dict], link_index: Dict):
"""Calculate execution order based on node dependencies"""
# Build dependency graph
dependencies = {}
node_by_id = {node['id']: node for node in nodes}
for node in nodes:
node_id = node['id']
dependencies[node_id] = set()
# Find all nodes this node depends on (inputs)
for link_id, link_data in link_index.items():
if link_data['target']['node_id'] == node_id:
# This node depends on the source node
dependencies[node_id].add(link_data['source']['node_id'])
# Topological sort to determine execution order
visited = set()
order_counter = [0]
def visit(node_id):
if node_id in visited:
return
visited.add(node_id)
# Visit dependencies first
for dep_id in dependencies.get(node_id, []):
if dep_id in node_by_id: # Skip if dependency not in current nodes
visit(dep_id)
# Assign order
if node_id in node_by_id:
node_by_id[node_id]['order'] = order_counter[0]
order_counter[0] += 1
# Visit all nodes
for node_id in node_by_id.keys():
visit(node_id)
def main():
if len(sys.argv) < 2:
print("Usage: python3 fix_workflows.py <workflow_directory>")
sys.exit(1)
workflow_dir = Path(sys.argv[1])
if not workflow_dir.exists():
print(f"Error: Directory {workflow_dir} does not exist")
sys.exit(1)
# Find all JSON files recursively
workflow_files = list(workflow_dir.rglob('*.json'))
if not workflow_files:
print(f"No workflow JSON files found in {workflow_dir}")
sys.exit(1)
print(f"\nFound {len(workflow_files)} workflow files")
# Process each workflow
success_count = 0
for workflow_path in sorted(workflow_files):
if fix_workflow(workflow_path):
success_count += 1
# Summary
print(f"\n{'='*60}")
print(f"SUMMARY")
print(f"{'='*60}")
print(f"Total workflows: {len(workflow_files)}")
print(f"Successfully fixed: {success_count}")
print(f"Failed: {len(workflow_files) - success_count}")
print(f"{'='*60}\n")
if __name__ == '__main__':
main()

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