Eric's Prompt Enhancers for ComfyUI

A comprehensive suite of 5 AI-powered prompt enhancement nodes for ComfyUI using local LLMs (LM Studio or Ollama). Transform simple prompts into detailed, platform-optimized descriptions for video and image generation.

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📦 Quick Start

cd ComfyUI/custom_nodes/
git clone https://github.com/EricRollei/Local_LLM_Prompt_Enhancer.git video_prompter
cd video_prompter
pip install -r requirements.txt

Restart ComfyUI. All nodes will appear under: Add Node → Eric Prompt Enhancers

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🎯 The 5 Nodes

Find all nodes under the "Eric Prompt Enhancers" category in ComfyUI.

1. 🎬 Video Prompt Expander

Simple video prompt expansion with style presets.

• 4 Detail Levels: Concise, Moderate, Detailed, Exhaustive
• 6 Style Presets: Cinematic, Surreal, Action, Stylized, Noir, Random
• Auto-Variation: Generate up to 3 unique variations
• Best for: Quick video prompt expansion from short ideas

2. 🎬 Video Prompt Expander (Advanced) ⭐ NEW v1.8

Granular control over video aesthetics with 50+ detailed settings.

NEW in v1.8:

• 4 Operation Modes:
  • expand_from_idea - Expand short concepts
  • refine_existing - Polish existing prompts
  • modify_style - Change aesthetic while keeping subject
  • add_details - Enrich existing prompts
• Clear Detail Levels: Concise, Moderate, Detailed, Exhaustive (with tooltips!)
• Optional Image Input: Analyze images with Qwen3-VL for image-to-video workflows
• Auto Mode Detection: Automatically switches to image-to-video when image provided

Controls:

• Lighting: Light source (10 options), Lighting type (13 options), Time of day (9 options)
• Camera: Shot size (10 options), Composition (8 options), Lens (6 options), Angle (10 options), Movement (17 options)
• Visual: Color tone (7 options), Visual style (15 options), Visual effects (11 options)
• Character: Emotion (13 options)

Best for: Professional video generation with precise aesthetic control

3. 🖼️➡️🎬 Image-to-Video Prompt Expander

Vision model analyzes images and adds motion descriptions for video generation.

• Automatic Scene Understanding: Qwen3-VL vision analysis
• Motion Description Generation: AI-generated movement and action
• Style Integration: Combines visual analysis with expansion tiers
• Best for: Converting static images into video prompts

4. 🖼️➡️🖼️ Image-to-Image Prompt Expander

Platform-aware image-to-image prompt generation.

• 5 Platforms: Flux Redux, SDXL Img2Img, Hunyuan Img2Img, Qwen Edit, Wan Edit
• Transformation Controls: Style transfer, detail level, creativity settings
• Vision Analysis: Understands source image characteristics
• Best for: Image transformation and editing workflows

5. 📝➡️🖼️ Text-to-Image Prompt Enhancer (v1.7)

Advanced multi-platform image prompt enhancement with extensive creative controls.

• 8 Platforms: Flux, SDXL, Pony Diffusion, Illustrious XL, Chroma, Qwen Image, Qwen Edit, Wan Image
• Reference Images: Optional 1-2 image inputs with visual analysis
• Genre Styles: 22 styles (cinematic, horror, cyberpunk, steampunk, noir, fantasy, etc.)
• Prompt Length: 6 options (very_short to very_long, 20-400 tokens)
• Subject Controls: Framing (14 options), Pose (17 options)
• Advanced Settings: Camera angle, composition, lighting (source/quality), weather, time, color mood
• Special Syntax: Emphasis (keyword:1.5) and Alternation {a|b|c} support
• Best for: Professional image generation with platform-specific optimization

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✨ Key Features

🤖 Local LLM Support

• LM Studio: OpenAI-compatible API (recommended)
• Ollama: Simple CLI-based LLM server
• Qwen3-VL (Optional): Local vision model for image analysis
• Privacy: All processing happens locally, no data sent to cloud

🎨 Platform-Specific Optimization

Each platform has unique requirements and prompting styles:

Platform	Style	Optimal Length	Specialization
Flux	Natural language	75-150 tokens	Photography, artistic
SDXL	Natural/tags hybrid	40-75 tokens	Versatile, balanced
Pony Diffusion	Booru tags	Tag count	Anime, characters
Illustrious XL	Danbooru tags	Tag count	Detailed anime
Chroma/Meissonic	Detailed natural	100-200 tokens	Complex scenes
Qwen Image	Technical descriptions	Medium	General purpose
Qwen Edit	Edit instructions	Medium	Image editing
Wan Image	Cinematography	60-120 tokens	Professional video stills

🔧 Special Syntax (NEW v1.6.1)

Emphasis (Weight Control)

(keyword:1.5)    # Increase importance 1.5x
(keyword:0.5)    # Decrease importance 0.5x
(red hair:2.0)   # Double the weight

Alternation (Random Selection)

{cat|dog|rabbit}                    # Picks one randomly
{red|blue|green} dress              # Random color
{elegant|casual} woman with (detailed face:1.5)

Combined

A {tall|short} woman with (dark hair:1.4) wearing a {red|blue|green} (dress:1.2)

🎯 Intelligent Features

• Auto-Detection: Analyzes input complexity and selects optimal detail level (Video nodes)
• Multiple Variations: Generate up to 3 unique variations in one run
• Keyword Integration: Automatically include LoRA triggers and custom terms
• Smart Negatives: Platform-optimized negative prompts
• File Export: Save prompts with complete metadata
• Wildcard Support: Random element selection for variety

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🚀 Installation

Prerequisites

• ComfyUI: Installed and working
• Python 3.8+: Usually included with ComfyUI
• LLM Backend: LM Studio or Ollama (see setup below)

Step 1: Install the Node

Method 1: Git Clone (Recommended)

cd ComfyUI/custom_nodes/
git clone https://github.com/EricRollei/Local_LLM_Prompt_Enhancer.git video_prompter
cd video_prompter
pip install -r requirements.txt

Method 2: Manual Install

1. Download this repository as ZIP
2. Extract to ComfyUI/custom_nodes/video_prompter/
3. Install dependencies:

   cd ComfyUI/custom_nodes/video_prompter/
   pip install -r requirements.txt

Step 2: Setup LLM Backend

Choose one of these options:

Option 1: LM Studio (Recommended)

1. Download from: https://lmstudio.ai/
2. Load a model (recommended: Llama 3 8B or similar)
3. Start the server (Settings → Server → Start Server)
4. Default endpoint: http://localhost:1234/v1

Option 2: Ollama

1. Install from: https://ollama.ai/
2. Pull a model: ollama pull llama3
3. Server runs automatically at: http://localhost:11434

Step 3: Restart ComfyUI

All nodes will appear under: Add Node → Eric Prompt Enhancers

Optional: Qwen3-VL Vision Model

For image analysis in Image-to-Video and Image-to-Image nodes:

pip install transformers>=4.42.0 accelerate>=0.30.0 huggingface_hub>=0.23.0 bitsandbytes>=0.43.0

See VISION_BACKEND_GUIDE.md for details.

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📖 Usage Guide

Basic Workflow (Video Prompt Expander)

1. Add Node: Right-click → Eric Prompt Enhancers → Video Prompt Expander
2. Enter Prompt: "A cat playing piano in a cozy room"
3. Select Preset: Choose "cinematic" for film-like quality
4. Choose Detail Level: "detailed" for ~400-500 words
5. Configure LLM:
   • Backend: lm_studio
   • Model: llama3
   • Endpoint: http://localhost:1234/v1
6. Generate: Run the workflow
7. Use Output: Connect positive_prompt_1 to your video generator

Advanced Workflow (Advanced Node)

1. Add Node: Video Prompt Expander (Advanced)
2. Choose Operation Mode:
   • expand_from_idea: For short concepts
   • refine_existing: For polishing existing prompts
   • modify_style: To change aesthetic
   • add_details: To enrich prompts
3. Select Detail Level: Choose based on desired output length
4. Set Aesthetic Controls: Configure camera, lighting, style, etc.
5. Optional: Add reference image for image-to-video mode
6. Generate: Prompts incorporate your specific controls

Image-to-Video Workflow

1. Add Node: Image-to-Video Prompt Expander (or Advanced with image)
2. Connect Image: Link your image to the reference_image input
3. Add Direction: "Camera slowly zooms in on the subject"
4. Generate: Vision model analyzes image and incorporates it into prompt

Text-to-Image Workflow

1. Add Node: Text-to-Image Prompt Enhancer
2. Select Platform: Choose your target platform (Flux, SDXL, etc.)
3. Set Length: Choose prompt length (medium recommended)
4. Configure Controls: Set genre, framing, lighting, etc.
5. Use Syntax: Add emphasis (keyword:1.5) and alternations {a|b}
6. Generate: Get platform-optimized prompts

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📝 Detail Levels Explained

Concise (~150-200 words)

• Essential details only
• Clear subject, basic setting, simple action
• Use when: You want compact prompts or API token savings

Moderate (~250-350 words)

• Good balance of detail
• Subject characteristics, environment description, basic aesthetics
• Use when: Standard detailed descriptions needed

Detailed (~400-500 words) - DEFAULT

• Rich, comprehensive description
• Full cinematography, specific lighting, camera work
• Use when: Professional video generation

Exhaustive (~600-1000 words)

• Maximum detail for cinematic quality
• Director-level descriptions, complete technical details
• Use when: Masterful, film-quality output required

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🎨 Style Presets

Cinematic

Professional film quality with emphasis on lighting, composition, and smooth camera movements.

• Edge lighting, soft lighting, warm colors
• Professional framing, balanced composition

Surreal

Dreamlike, unusual scenes with artistic emphasis.

• Unexpected combinations, creative camera angles
• Artistic lighting, ethereal atmosphere

Action

High-energy motion and dynamic camera work.

• Fast movement, intense action
• Dynamic angles, motion blur

Stylized

Artistic interpretation with strong visual identity.

• Bold choices, distinctive look
• Creative freedom, unique aesthetics

Noir

Dark, moody film noir aesthetic.

• High contrast, dramatic shadows
• Low-key lighting, mystery atmosphere

Random

AI selects random aesthetic elements while respecting your core concept.

• Variety for batch generation
• Creative combinations

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🔧 Configuration

Common Settings

LLM Configuration

• llm_backend: lm_studio or ollama
• model_name: Your loaded model (e.g., "llama3")
• api_endpoint: LLM server URL
• temperature: 0.1-2.0 (0.7 recommended, lower = focused, higher = creative)

Keywords

• positive_keywords: Comma-separated must-include terms (LoRA triggers, style terms)
• negative_keywords: Comma-separated terms to avoid

Output

• num_variations: Generate 1-3 variations
• save_to_file: Save prompts to disk with metadata
• filename_base: Base name for saved files

Node Outputs

All nodes return:

1. positive_prompt_1/2/3: Enhanced prompt variations
2. negative_prompt: Auto-generated platform-specific negatives
3. breakdown/settings_used: Detailed analysis of what was applied
4. status: Success messages, errors, file save location

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📚 Documentation

Quick References

• QUICKSTART.md - Get started in 5 minutes
• QUICK_REFERENCE.md - Fast reference guide
• QUICK_REF_V17.md - Text-to-Image quick reference

Node Guides

• TXT2IMG_GUIDE.md - Text-to-Image node complete guide
• IMG2IMG_GUIDE.md - Image-to-Image workflows
• NODE_COMPARISON.md - Which node to use when
• ADVANCED_NODE_REDESIGN.md - Advanced node v1.8 redesign details

Setup Guides

• LM_STUDIO_SETUP.md - LM Studio configuration
• VISION_BACKEND_GUIDE.md - Qwen3-VL setup for image analysis
• CONFIGURATION.md - Advanced configuration options

Platform & Technical

• WAN_GUIDE_REFERENCE.md - Wan 2.2 video prompt guide
• WILDCARD_GUIDE.md - Wildcard syntax examples

Updates & Fixes

• CHANGELOG.md - Complete version history
• UPDATE_V17_ENHANCED_CONTROLS.md - v1.7 features
• BUGFIX_ADVANCED_NODE.md - v1.8 bug fixes
• BUGFIX_V161.md - v1.6.1 syntax fixes

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🆕 What's New in v1.8.0

Advanced Prompt Expander Node - Complete Redesign

3 Major Usability Improvements:

1. Operation Modes - Now you can modify existing prompts!

   • expand_from_idea - Original expansion behavior
   • refine_existing - Polish and improve prompts
   • modify_style - Change aesthetic while keeping subject
   • add_details - Add descriptive richness

2. Clear Detail Levels - No more confusing tiers!

   • Renamed to: Concise, Moderate, Detailed, Exhaustive
   • Added tooltips explaining each option
   • Removed confusing "auto" mode

3. Image Input Support - Image-to-video actually works!

   • Optional reference_image input
   • Qwen3-VL vision analysis integration
   • Automatic mode detection (text vs image-to-video)
   • Status shows when image is being used

Bonus: All video nodes now support emphasis (keyword:1.5) and alternation {a|b|c} syntax!

See docs/ADVANCED_NODE_REDESIGN.md for complete details.

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💡 Tips & Best Practices

For Best Results

1. Start Simple: Begin with basic prompts, let the LLM expand
2. Use Presets: They provide consistent, proven aesthetic directions
3. Experiment with Temperature: 0.7 is balanced, 0.3-0.5 for consistency, 0.8-1.2 for variety
4. Leverage Keywords: Add LoRA triggers and style terms to positive_keywords
5. Save Your Prompts: Enable save_to_file to build a library
6. Use Variations: Generate 3 variations to pick the best
7. Platform Matters: Choose the right platform for your model

Common Workflows

Quick Video Prompt

Node: Video Prompt Expander
Input: "cyberpunk street scene"
Preset: stylized
Detail: moderate

Professional Image Generation

Node: Text-to-Image Enhancer
Platform: Flux
Input: "portrait of a (warrior:1.3) with {red|blue|purple} armor"
Length: long
Genre: fantasy

Refine Existing Prompt

Node: Video Prompt Expander (Advanced)
Operation: refine_existing
Input: [Your existing 300-word prompt]
Detail: detailed

Image-to-Video with Direction

Node: Video Prompt Expander (Advanced)
Reference Image: [Your image]
Input: "Camera slowly dollies in while subject looks up"
Operation: expand_from_idea

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🐛 Troubleshooting

LLM Connection Failed

• Check LLM backend is running (LM Studio or Ollama)
• Verify endpoint URL matches your LLM server
• Test in browser: http://localhost:1234/v1 (LM Studio) or http://localhost:11434 (Ollama)

Empty Output

• Check temperature isn't too high (>1.5)
• Verify model is loaded in LLM backend
• Check ComfyUI console for error messages

Emphasis Syntax Not Working

• Make sure you're using parentheses with colon: (keyword:1.5)
• Syntax is preserved in v1.6.1+ for video nodes, v1.7+ for image nodes

Image Analysis Not Working

• Install vision dependencies: pip install transformers accelerate huggingface_hub bitsandbytes
• Check Qwen3-VL model is downloaded
• See VISION_BACKEND_GUIDE.md

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🤝 Contributing

Contributions welcome! Please:

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Test thoroughly
5. Submit a pull request

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📄 License

Dual License:

• Non-Commercial: Free for personal/research use
• Commercial: Contact for licensing

See LICENSE for details.

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🙏 Acknowledgments

• ComfyUI community for the amazing platform
• LM Studio and Ollama teams for excellent LLM backends
• Qwen3-VL team for the vision model
• All users who provided feedback and bug reports

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📞 Support

• Issues: GitHub Issues
• Discussions: GitHub Discussions

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Version: 1.8.0
Last Updated: October 24, 2025
Author: Eric Rollei
Repository: https://github.com/EricRollei/Local_LLM_Prompt_Enhancer