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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🆕 New in 2.0

Version 2.0 keeps every existing node and every saved workflow, and adds three things underneath them. The rest of this README still describes the 1.x nodes and will be brought up to date in a later 2.0.x release; the documents linked here are current.

A real wildcard engine. The Dynamic Prompts / Impact Pack grammar (__name__, {a|b|c}, weights, ranges, variables, tag queries such as __objects[metal AND handheld]__), read straight from ComfyUI/models/wildcards, in every enhancer node. Picks are handed to the LLM as concepts to express, as exact strings that must survive (__=lora_triggers__), or as loose inspiration (__?moods__). New nodes: Wildcard Processor, Semantic Variation (moves picks to semantic neighbours, with named direction axes) and Concept Survival Check. See docs/WILDCARD_GUIDE.md.

Platform profiles. Everything the nodes know about a target model is one YAML file in profiles/: format, length, negative prompt or none, quality tokens or none, how text and dialogue are written, and - where the maker publishes one - the maker's own rewriter prompt, downloaded once and cached. Over 60 models, open and hosted: FLUX.2, Krea 2, Z-Image, Qwen-Image, HunyuanImage 3, Ideogram 4, Illustrious, NoobAI; MiniMax H3, Wan 2.2, LTX-2, HunyuanVideo 1.5; and for API use Seedream 5, Nano Banana, GPT Image, Midjourney V8, Seedance 2.5, Kling 3, Veo 3.1, Wan 3.0 and others. Your own go in profiles_user/. The new Platform Prompt Rewriter node writes for any of them, including the structured formats (MiniMax H3 fields, FLUX.2 and Ideogram JSON, edit instructions). See PLATFORM_NOTES.md.

The video nodes have a target_model. The three video expanders were written around Wan 2.2. They now write for any video profile, and the default is MiniMax H3. Choose wan22_video to get the original behaviour exactly. Note for existing workflows: a workflow saved before 2.0 has no value for this new input, so it loads with the default (MiniMax H3) - set it to wan22_video once and save.

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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: 2.0.1
Last Updated: September 21, 2026
Author: Eric Rollei
Repository: https://github.com/EricRollei/Local_LLM_Prompt_Enhancer