https://github.com/Pablerdo/ComfyUI-ZeptaframePromptMerger
https://github.com/Pablerdo/ComfyUI-ZeptaframePromptMerger
Last synced: 19 days ago
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- Host: GitHub
- URL: https://github.com/Pablerdo/ComfyUI-ZeptaframePromptMerger
- Owner: Pablerdo
- License: gpl-3.0
- Created: 2025-03-21T02:20:27.000Z (27 days ago)
- Default Branch: main
- Last Pushed: 2025-03-21T03:04:35.000Z (27 days ago)
- Last Synced: 2025-03-21T03:26:18.779Z (27 days ago)
- Language: Python
- Size: 15.6 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-comfyui - **ComfyUI-ZeptaframePromptMerger** - specific prompts (All Workflows Sorted by GitHub Stars)
README
# ComfyUI ZeptaframePromptMerger
A ComfyUI custom node for merging different types of text prompts into a cohesive, structured prompt for text-to-video generation systems. This node uses LLama to intelligently combine general descriptions, subject-specific prompts, and system-generated captions with proper emphasis on the most important elements.
## Features
- Intelligently merges multiple prompt components with specified importance weighting
- Prioritizes subject descriptions and movements over general descriptions
- Uses LLama for natural language understanding and generation
- Easy integration with ComfyUI workflows
## Installation
1. Clone this repository into your ComfyUI custom_nodes directory:
```bash
cd ComfyUI/custom_nodes
git clone https://github.com/your-username/ComfyUI-ZeptaframePromptMerger.git
```
2. Install the required packages:
```bash
pip install llama-cpp-python
```
3. Download a LLama GGUF model:
- Recommended: llama-2-7b-chat.Q8_0.gguf for high quality on GPU systems
- Place the model in a directory named `zepta` in your ComfyUI directory
## Usage
The node takes three inputs:
1. **generalSa2VAPrompt** (String, JSON): System-generated video caption
- Importance: Low (2/10)
- Provides background context
2. **generalTextPrompt** (String, JSON): User-generated general description
- Importance: Medium-High (7/10)
- Describes the overall video content/scene
3. **subjectTextPrompts** (String, JSON): Subject-specific descriptions
- Importance: Highest (8/10)
- Describes how specific subjects should move or appear
- Format: JSON object with subjects as keys and movement descriptions as values
### Example Input
```json
// subjectTextPrompts
{
"bear near creek": "walking fast",
"bear near tree": "walking slow",
"fish jumping in the river": "flapping around"
}
// generalTextPrompt
"A serene forest scene with wildlife by a flowing creek"
// generalSa2VAPrompt
"Nature documentary showing wildlife interaction in a forest environment"
```
## Configuration
You can modify the model path in the `nodes/text_nodes.py` file if you want to use a different LLama model:
```python
model_path = "zepta/llama-2-7b-chat.Q8_0.gguf" # Change this to your preferred model
```
Other parameters you can adjust:
- `n_ctx`: Context window size (default: 4096)
- `max_tokens`: Maximum tokens in generation (default: 512)
- `temperature`: Higher values = more creative output (default: 0.7)
- `top_p`: Nucleus sampling parameter (default: 0.95)
## Requirements
- ComfyUI
- llama-cpp-python
- A LLama GGUF model file (recommended: llama-2-7b-chat.Q8_0.gguf)
- CUDA-capable GPU recommended for faster inference