Zenkai-POML for ComfyUI

Bring Microsoft's POML (Prompt Orchestration Markup Language) to your ComfyUI workflows! Create structured, reusable, and powerful prompts with visual node-based editing.

🚀 Quick Start

Prerequisites

• ComfyUI installed and working
• Python 3.8+ (same as ComfyUI)
• pip package manager

Installation

1. Navigate to ComfyUI custom nodes directory

   cd ComfyUI/custom_nodes/
   

2. Create Zenkai-POML folder

   mkdir Zenkai-POML
   cd Zenkai-POML
   

3. Download node files

   • Copy __init__.py → save as __init__.py
   • Copy zenkai_poml.py → save as zenkai_poml.py
   • Copy requirements.txt → save as requirements.txt

4. Install dependencies ⚠️ CRITICAL STEP

   # Standard installation (optimized requirements)
   pip install -r requirements.txt
   
   # Optional: For development/testing
   pip install -r requirements-dev.txt
   
   # Minimal fallback (limited features)
   pip install poml
   

5. Restart ComfyUI

   • Close ComfyUI completely
   • Restart the application
   • Check console for "🚀 Zenkai-POML nodes loaded successfully!"

Dependency Levels

| Level | Installation | Features Available | |-------|-------------|-------------------| | Optimized | pip install -r requirements.txt | All core POML features: official SDK, data processing, PDF/Excel, images, JSON validation | | Development | pip install -r requirements-dev.txt | Additional tools for testing, enhanced processing, ML libraries | | Minimal | pip install poml | Official POML SDK only (basic functionality) | | Fallback | No dependencies | Basic parsing with limited features |

✅ Recommended: Use the optimized requirements.txt for the best balance of features and installation simplicity.

First Use

1. Add POML Processor Node
   • Right-click → Add Node → Zenkai/POML → POML Processor
2. Connect to OpenRouter
   • POML Processor rendered_prompt → OpenRouter text input
3. Test with Sample

   <poml>
   <role>You are an AI assistant specialized in {{ domain }}.</role>
   <task>Help the user understand {{ topic }} in simple terms.</task>
   <output-format>Use clear explanations with examples.</output-format>
   </poml>
   

🎯 Node Reference

ZenkaiPOMLProcessor

Main processing node that converts POML markup to rendered prompts

Inputs:

• poml_template (STRING, required): POML markup text
• render_mode (COMBO, required):
  • standard: Clean, natural prompt rendering
  • optimized: Structured format with clear sections
  • debug: Detailed breakdown with component labels
• variables_json (STRING, optional): JSON object with template variables
• max_length (INT, optional): Maximum prompt length (0 = no limit)

Outputs:

• rendered_prompt (STRING): Final prompt text ready for LLM
• metadata (STRING): JSON with parsing info and statistics

ZenkaiPOMLTemplate

Template library with pre-built POML patterns

Inputs:

• template_name (COMBO): Select from built-in templates
  • Analysis
  • Creative Writing
  • Technical Documentation
  • Customer Support
  • Data Analysis
• template_variables (STRING): JSON with template-specific variables

Outputs:

• poml_template (STRING): Ready-to-use POML template

💡 Usage Examples

Basic Prompt Enhancement

Traditional Prompt:

You are a helpful assistant. Explain quantum computing simply.

POML Version:

<poml>
<role>You are a physics educator with a gift for simple explanations.</role>
<task>Explain quantum computing to a {{ audience }} audience.</task>
<example>
  <input>What is quantum computing?</input>
  <o>Quantum computing is like having a super-calculator that can try many solutions at once, instead of one at a time like regular computers.</o>
</example>
<output-format>Use analogies and avoid jargon. Keep under {{ max_words }} words.</output-format>
</poml>

Variables JSON:

{
  "audience": "high school student", 
  "max_words": 150
}

Data Analysis Workflow

<poml>
<role>You are a business intelligence analyst.</role>
<task>Analyze the sales performance data and identify trends.</task>
<table title="Q4 Sales Data">
Region | Q1 | Q2 | Q3 | Q4
North  | 150k | 180k | 165k | 210k  
South  | 220k | 195k | 235k | 260k
East   | 180k | 175k | 190k | 185k
West   | 250k | 280k | 275k | 295k
</table>
<output-format style="format: executive-summary">
Provide: Key Insights, Performance Trends, Regional Analysis, Recommendations.
</output-format>
</poml>

Creative Writing with Templates

1. Use ZenkaiPOMLTemplate node
2. Select "Creative Writing"
3. Set variables:

   {
     "genre": "science fiction",
     "content_type": "short story opening",
     "theme": "AI consciousness",
     "tone": "mysterious",
     "length": "200 words",
     "style": "literary",
     "audience": "adult readers"
   }
   

🔄 Workflow Patterns

Pattern 1: Enhanced Single Prompt

Text Input → POML Processor → OpenRouter → Output

Use Case: Transform plain prompts into structured, optimized versions

Pattern 2: Template-Based Generation

POML Template → POML Processor → OpenRouter → Multiple Outputs

Use Case: Consistent prompt formatting across different scenarios

Pattern 3: Multi-Variant Testing

Same Context → Multiple POML Templates → Batch Processing → Compare Results

Use Case: A/B test different prompt structures and styles

Pattern 4: Dynamic Content Integration

File Input → POML Processor (with data) → OpenRouter → Analysis

Use Case: Incorporate external documents or data into prompts

Pattern 5: Conversational Workflows

POML Template → Context Injection → Multi-Turn Chain → Refined Outputs

Use Case: Build sophisticated conversation flows with consistent prompting

🎨 Advanced Features

Variable Templating

Dynamic Role Assignment:

<role>You are a {{ profession }} with {{ years }} years of experience in {{ specialty }}.</role>

Conditional Content:

<task>
{{ base_task }}
{{ expertise_level == 'expert' ? 'Include technical details and citations.' : 'Keep explanations simple.' }}
</task>

Multi-Modal Integration

<poml>
<role>You are a visual content analyst.</role>
<task>Analyze the provided image and data together.</task>
<img src="chart.png" alt="Sales performance bar chart showing quarterly trends" />
<table title="Raw Data">
  <!-- table content -->
</table>
<output-format>Correlate visual and numerical insights.</output-format>
</poml>

Template Libraries

Create reusable patterns:

<!-- Base Analysis Template -->
<poml>
<role>You are a {{ domain }} analyst.</role>
<task>Analyze {{ subject }} focusing on {{ aspects }}.</task>
<output-format style="format: {{ report_type }}; verbosity: {{ detail_level }}">
Present findings with actionable insights.
</output-format>
</poml>

🔧 Troubleshooting

Installation Issues

Problem: Nodes Don't Appear After Installation

1. Check console output when starting ComfyUI:

   python main.py
   # Look for Zenkai-POML loading messages or errors
   

2. Verify file structure:

   ComfyUI/custom_nodes/Zenkai-POML/
   ├── __init__.py          ✅ Required
   ├── zenkai_poml.py       ✅ Required  
   ├── requirements.txt     ✅ Required
   └── README.md           📝 Optional
   

3. Check dependencies installation:

   cd ComfyUI/custom_nodes/Zenkai-POML
   pip install -r requirements.txt
   

Problem: Import/Dependency Errors

| Error Message | Solution | |--------------|----------| | ModuleNotFoundError: No module named 'poml' | pip install poml | | ModuleNotFoundError: No module named 'pandas' | pip install pandas |
| ModuleNotFoundError: No module named 'PyPDF2' | pip install PyPDF2 | | ModuleNotFoundError: No module named 'PIL' | pip install Pillow | | ModuleNotFoundError: No module named 'requests' | pip install requests |

Problem: POML Features Not Working

The node provides graceful degradation. Check the metadata output to see which features are available:

{
  "dependencies_status": {
    "poml": true,           // Official POML SDK
    "pandas": false,        // Advanced table processing  
    "pypdf2": true,         // PDF document support
    "pillow": false,        // Image processing
    "requests": true,       // External data fetching
    "jsonschema": false     // JSON validation
  },
  "features_available": {
    "official_poml_sdk": true,
    "advanced_tables": false,
    "pdf_processing": true,
    "image_processing": false,
    "external_data": true,
    "json_validation": false
  }
}

POML Syntax Issues

Problem: Parsing Errors

1. Check XML syntax:

   • All tags must be properly closed: <role>...</role>
   • Use self-closing for empty tags: <img src="file.png" />
   • Escape special characters: < > &

2. Test with minimal example:

   <poml>
   <role>Assistant</role>
   <task>Help user</task>  
   </poml>
   

3. Use debug mode:

   • Set render_mode to "debug"
   • Check metadata for parsing details

Problem: Variables Not Working

1. Check JSON syntax:

   {
     "user_name": "Alice",
     "topic": "AI",
     "max_words": 150
   }
   

2. Verify variable names match template:

   <role>You are helping {{ user_name }} learn about {{ topic }}.</role>
   

3. Check metadata for variable status:

   "variables_used": ["user_name", "topic", "max_words"]
   

Performance Issues

Problem: Slow Processing

1. Optimize templates:

   • Reduce nested loops and conditionals
   • Use simpler variable substitutions
   • Limit data file sizes

2. Check dependency status:

   • Official POML SDK is faster than fallback parser
   • pandas processing is more efficient for large tables
   • Consider file size limits for documents/tables

Problem: Memory Usage

1. Limit data size:
   • Use max_length parameter to truncate output
   • Process large files externally before POML
   • Split large tables into smaller chunks

Common Solutions

| Problem | Quick Fix | |---------|-----------| | Empty output | Ensure POML has <role> and <task> | | Variables not substituting | Check JSON syntax and variable names | | Table not loading | Verify file path and install pandas | | PDF not processing | Install PyPDF2: pip install PyPDF2 | | Performance slow | Use "optimized" render mode | | Features missing | Check metadata dependencies_status |

Dependency Verification Script

Create test_dependencies.py to check your installation:

def check_dependencies():
    deps = {}
    
    try:
        import poml
        deps['poml'] = '✅ Available'
    except ImportError:
        deps['poml'] = '❌ Missing - pip install poml'
    
    try:
        import pandas
        deps['pandas'] = '✅ Available'  
    except ImportError:
        deps['pandas'] = '❌ Missing - pip install pandas'
        
    try:
        import PyPDF2
        deps['PyPDF2'] = '✅ Available'
    except ImportError:
        deps['PyPDF2'] = '❌ Missing - pip install PyPDF2'
        
    try:
        from PIL import Image
        deps['Pillow'] = '✅ Available'
    except ImportError:
        deps['Pillow'] = '❌ Missing - pip install Pillow'
    
    for name, status in deps.items():
        print(f"{name}: {status}")

if __name__ == "__main__":
    check_dependencies()

Run with: python test_dependencies.py

🚀 Performance Tips

Optimization Strategies

1. Template Reuse: Create base templates and modify with variables
2. Render Mode Selection: Use "optimized" for structured LLM input
3. Length Limits: Set max_length for token budget control
4. Variable Preprocessing: Prepare complex data outside the node

ComfyUI Integration

1. Caching: ComfyUI caches node outputs - leverage for repeated prompts
2. Batching: Process multiple variations efficiently
3. Workflow Optimization: Group POML processing early in pipeline
4. Memory Management: Use length limits for large templates

📊 Comparison: Before vs After

| Aspect | Plain Text Prompts | POML Enhanced | |--------|-------------------|---------------| | Structure | Unorganized text blob | Semantic components | | Reusability | Copy-paste with manual edits | Template + variables | | Consistency | Varies with manual writing | Standardized format | | Data Integration | Manual text insertion | Native data components | | Maintainability | Difficult to update | Modular components | | Testing | Hard to A/B test variations | Easy template swapping | | Collaboration | Unclear prompt structure | Self-documenting markup |

🤝 Contributing

Found a bug or want to add features?

1. Report Issues: Describe the problem with example POML
2. Feature Requests: Explain the use case and expected behavior
3. Code Contributions: Fork, implement, test, and submit PR
4. Template Sharing: Contribute useful POML templates

📚 Resources

Learn POML

• Official POML Documentation
• POML Research Paper
• GitHub Repository

ComfyUI Resources

• ComfyUI GitHub
• Custom Node Development
• Workflow Sharing

Community

• POML Discord
• ComfyUI Reddit

📄 License

MIT License - see LICENSE file for details.

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Ready to revolutionize your ComfyUI prompt workflows? Install Zenkai-POML and experience the power of structured prompt engineering! 🚀