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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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# ComfyUI-AI-Photography-Toolkit
A collection of AI-powered photography and image generation tools for ComfyUI. All nodes are prefixed with `SID_` for easy identification.
AI-powered Z-Image prompt generator for ComfyUI. Analyzes images and generates flowing narrative prompts optimized for Z-Image models.
![Workflow Screenshot](docs/images/workflow-screenshot.png)
## Features
### Current Nodes
#### SID_ZImagePromptGenerator
Agentic multi-stage image analyzer that generates Z-Image compatible narrative prompts. Supports multiple AI providers including Anthropic Claude, Ollama (local), and Grok (xAI).
**Key Features:**
- **6-Stage Agentic Pipeline**: Classification → Metadata → Attribute Mapping → Detailed Analysis → Prompt Composition → Z-Image Optimization
- **Multi-Provider Support**: Anthropic (Claude), Ollama (local models), Grok (xAI)
- **Z-Image Optimized**: Generates flowing narrative prompts (no keyword lists or meta-tags)
- **NSFW Support**: Content detail levels from minimal to explicit
- **Smart Caching**: Persistent disk cache saves API calls
- **56+ Photography Genres**: Across 6 categories (People, Events, Nature, Commercial, Artistic, Lifestyle)
- **11 Shot Framings**: From Extreme Close-Up (ECU) to Very Long Shot (VLS)
### Future Nodes (Planned)
- SID_ZImagePromptEnhancer - Text-to-text prompt enhancement for Z-Image
**Version:** 4.1.0
**Author:** Siddhartha Lahiri
## Installation
### Method 1: Manual Installation (Recommended)
```bash
cd ComfyUI/custom_nodes
git clone https://github.com/slahiri/ComfyUI-AI-Photography-Toolkit.git
```
1. Navigate to your ComfyUI custom_nodes directory:
```bash
cd ComfyUI/custom_nodes
```
Restart ComfyUI. Dependencies install automatically on first load.
2. Clone this repository:
```bash
git clone https://github.com/slahiri/ComfyUI-AI-Photography-Toolkit.git
```
## Nodes
3. Install dependencies:
```bash
cd ComfyUI-AI-Photography-Toolkit
pip install -r requirements.txt
```
### Prompt Generators
4. Restart ComfyUI
| Node | Description |
|------|-------------|
| **SID_ZImagePromptGenerator** | Built-in Anthropic Claude |
| **SID_ZImagePromptGenerator_Advanced** | Connect any LLM provider |
### Method 2: Via ComfyUI Manager
### LLM Providers (for Advanced node)
1. Open ComfyUI Manager
2. Search for "ComfyUI-AI-Photography-Toolkit"
3. Click Install
4. Restart ComfyUI
| Node | Provider | API Key |
|------|----------|---------|
| **SID_Anthropic_LLM** | Anthropic Claude | [console.anthropic.com](https://console.anthropic.com) |
| **SID_OpenAI_Compatible_LLM** | OpenAI / GPT / Together AI / LM Studio | [platform.openai.com](https://platform.openai.com) or local |
| **SID_Grok_LLM** | xAI Grok | [console.x.ai](https://console.x.ai) |
| **SID_GGUF_LLM** | Local GGUF models | Not required |
## Usage
## Quick Start
### SID_ZImagePromptGenerator
### Option 1: Basic Node (Anthropic)
#### 1. Choose Your AI Provider
```
Image → SID_ZImagePromptGenerator → zimage_prompt
```
| Provider | Models | API Key | URL |
|----------|--------|---------|-----|
| **Anthropic** | claude-sonnet-4-5, claude-haiku-4-5, claude-opus-4-1 | Required ([console.anthropic.com](https://console.anthropic.com)) | Auto |
| **Ollama** | llava, moondream, bakllava (local) | Not required | `http://localhost:11434` |
| **Grok** | grok-2-vision, grok-vision-beta | Required ([console.x.ai](https://console.x.ai)) | Auto |
Enter your Anthropic API key in the node.
#### 2. Ollama Models by VRAM
### Option 2: Advanced Node (Any Provider)
| VRAM Tier | Models | Memory Required |
|-----------|--------|-----------------|
| **Low** | `ollama/moondream`, `ollama/llava:7b`, `ollama/bakllava` | ~4-8GB |
| **Mid** | `ollama/llava:13b`, `ollama/llava-llama3` | ~12-16GB |
| **High** | `ollama/llava:34b`, `ollama/llama3.2-vision` | ~24GB+ |
```
SID_Anthropic_LLM ─┐
├→ SID_ZImagePromptGenerator_Advanced → zimage_prompt
Image ─────┘
```
#### 3. Node Configuration
## Setup by Provider
**API Settings:**
- `ai_provider`: Select provider (auto-detected from model)
- `api_key`: Your API key (leave empty for Ollama)
- `model`: Select model (provider auto-detected from prefix)
- `api_url`: Override URL (optional, defaults provided)
### Anthropic Claude
**Analysis Options:**
- `detail_level`: Quick (1 LLM call), Standard (2 calls), Deep (3 calls)
- `focus_override`: Force specific genre (Portrait, Landscape, Product, etc.)
- `content_detail`: minimal, standard, detailed, explicit (NSFW)
1. Get API key: [console.anthropic.com](https://console.anthropic.com)
2. Use **SID_ZImagePromptGenerator** or **SID_Anthropic_LLM**
**Prompt Direction:**
- `user_prompt`: Optional guidance text
- `prompt_mode`:
- "Image Only" - Analyze image, ignore prompt
- "Prompt Guides Analysis" - Image primary, prompt guides emphasis
- "Prompt First, Image Fills Gaps" - Prompt primary, image supplements
- "Prompt Dominates" - Prompt foundation, minimal image details
### OpenAI / GPT-4
**Focus Toggles:**
- `focus_subject`: Include subject description
- `focus_environment`: Include background/environment
- `focus_lighting`: Include lighting analysis
- `focus_colors`: Include colors and materials
- `focus_mood`: Include mood/atmosphere
- `include_text_quotes`: Quote visible text with "quotes"
1. Get API key: [platform.openai.com](https://platform.openai.com)
2. Use **SID_OpenAI_Compatible_LLM**
3. Models: `gpt-4o`, `gpt-4o-mini`, `gpt-4-turbo`
**Generation Settings:**
- `max_tokens`: Target prompt length (50-500)
- `temperature`: Creativity (0.0=focused, 1.0=creative)
- `seed`: Reproducibility seed
- `seed_mode`: fixed, randomize, increment, decrement
- `cache_prompt`: Enable persistent disk caching
### xAI Grok
#### 4. Outputs
1. Get API key: [console.x.ai](https://console.x.ai)
2. Use **SID_Grok_LLM**
### LM Studio / Local Server
1. Start LM Studio server
2. Use **SID_OpenAI_Compatible_LLM**
3. Set `api_url`: `http://localhost:1234/v1`
4. Leave `api_key` empty
### Local GGUF Models
1. Install llama-cpp-python (see below)
2. Use **SID_GGUF_LLM**
3. Models auto-download to `ComfyUI/models/LLM/GGUF/`
**Available Models:**
| Model | VRAM |
|-------|------|
| moondream2-q4_k_m | ~4GB |
| llava-v1.5-7b-q4_k_m | ~8GB |
| minicpm-v-2_6-q4_k_m | ~10GB |
| llava-v1.5-13b-q4_k_m | ~16GB |
**Install llama-cpp-python:**
```bash
# NVIDIA CUDA 12.1
pip install llama-cpp-python --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/cu121
# NVIDIA CUDA 12.2+
pip install llama-cpp-python --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/cu122
# CPU only
pip install llama-cpp-python
# AMD ROCm
CMAKE_ARGS="-DGGML_HIPBLAS=on" pip install llama-cpp-python
```
## Node Settings
| Setting | Options |
|---------|---------|
| detail_level | Quick (1 call), Standard (2), Deep (3) |
| focus_override | Auto-detect, Portrait, Landscape, etc. |
| content_detail | minimal, standard, detailed, explicit |
| prompt_mode | Image Only, Prompt Guides, Prompt First, Prompt Dominates |
## Outputs
| Output | Description |
|--------|-------------|
| `image` | Pass-through of input image |
| `zimage_prompt` | Z-Image compatible narrative prompt |
| `width` | Image width in pixels |
| `height` | Image height in pixels |
| `structured_data` | JSON with classification and attributes |
| `image_metadata` | JSON with Z-Image recommendations |
| `debug_log` | Stage-by-stage processing details |
### Example Workflow
```
Image Input → SID_ZImagePromptGenerator → zimage_prompt → Z-Image Model
↓
structured_data → (optional) Further processing
```
### Z-Image Best Practices
Z-Image-Turbo (6B parameter model) works best with:
- **Narrative prompts**: Flowing descriptions, not keyword lists
- **No meta-tags**: Avoid "8K, masterpiece, best quality"
- **No negative prompts**: Z-Image doesn't use them (guidance_scale=0.0)
- **Visible elements only**: Describe what's actually in the image
## Configuration
### Ollama Setup (Local Models)
1. Install Ollama: https://ollama.ai
2. Pull a vision model:
```bash
ollama pull llava:7b # Low VRAM
ollama pull llava:13b # Mid VRAM
ollama pull llava:34b # High VRAM
```
3. Ollama runs on `http://localhost:11434` by default
### API Key Security
**Important:** Never commit your API key to version control!
Options for storing your API key:
1. Enter it directly in the node (least secure)
2. Use environment variables (recommended)
3. Use a secrets management system (production)
## Troubleshooting
### "ERROR: anthropic library not installed"
```bash
pip install anthropic>=0.39.0
```
### "ERROR: openai library not installed" (for Grok)
```bash
pip install openai
```
### "Ollama connection refused"
- Ensure Ollama is running: `ollama serve`
- Check URL is correct: `http://localhost:11434`
- Verify model is pulled: `ollama list`
### "API Error (AuthenticationError)"
- Verify API key is correct
- Check API key has not expired
- Ensure account has credits
### Empty or Invalid Prompts
- Try increasing `max_tokens`
- Check the debug_log output
- Ensure image is valid
## Requirements
- ComfyUI (latest version recommended)
- Python 3.10+
- API key for chosen provider (except Ollama)
| zimage_prompt | Generated narrative prompt |
| structured_data | JSON classification |
| debug_log | Processing details |
## Dependencies
- `anthropic>=0.39.0` - Anthropic Claude API
- `openai` - Grok API (OpenAI-compatible)
- `requests` - Ollama API
- `pyyaml>=6.0` - Configuration loading
- `pillow>=10.0.0` - Image processing
- `numpy>=1.24.0` - Array operations
**Auto-installed:**
- `anthropic` - Claude API
- `openai` - OpenAI/Grok API
- `pyyaml` - Config
- `requests` - HTTP
## Changelog
### Version 4.0.0 (2025-01-XX) - Z-IMAGE & MULTI-PROVIDER
**New Node: SID_ZImagePromptGenerator**
- Complete rewrite for Z-Image compatibility
- 6-stage agentic pipeline for intelligent image analysis
- Generates flowing narrative prompts (not keyword lists)
- No meta-tags, no negative prompts (Z-Image optimized)
**Multi-Provider Support**
- **Anthropic**: Claude Sonnet 4.5, Haiku 4.5, Opus 4.1
- **Ollama**: Local vision models with VRAM tiers
- Low (~4-8GB): moondream, llava:7b, bakllava
- Mid (~12-16GB): llava:13b, llava-llama3
- High (~24GB+): llava:34b, llama3.2-vision
- **Grok**: xAI vision models (grok-2-vision, grok-vision-beta)
**Smart Features**
- Persistent disk caching (saves API calls)
- 56+ photography genres across 6 categories
- 11 shot framing types (ECU to VLS)
- Content detail levels (minimal to explicit/NSFW)
- Seed modes: fixed, randomize, increment, decrement
- 4 prompt modes for user prompt integration
**Outputs**
- Image pass-through
- Z-Image prompt
- Width/height
- Structured data (JSON)
- Image metadata with Z-Image recommendations
- Debug log
**Breaking Changes**
- Removed old SID_AIPromptGenerator node
- New node uses different output structure
### Previous Versions
See git history for changelog of versions 1.0.0 - 3.0.1.
## Credits
Created by Siddhartha Lahiri
Special thanks to:
- ComfyUI team for the amazing framework
- Anthropic, Ollama, and xAI for AI APIs
- The ComfyUI community
## Contributing
Contributions are welcome! Please:
1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request
## Roadmap
- [x] Z-Image optimized prompt generation
- [x] Multi-provider support (Anthropic, Ollama, Grok)
- [x] Persistent caching
- [x] NSFW content support
- [ ] SID_ZImagePromptEnhancer (text-to-text)
- [ ] Batch processing
- [ ] More AI providers (Gemini, etc.)
**Manual (for GGUF):**
- `llama-cpp-python`
## License
MIT License - See LICENSE file for details
---
**Generate better Z-Image prompts with AI!**
MIT License