comfyui-tag-rag

By FrostySDXLView on GitHub →

ComfyUI custom node package for tag-based prompt RAG using CSV datasets and local LLM generation.

How much VRAM does comfyui-tag-rag require?

Direct Answer: The ComfyUI node comfyui-tag-rag requires a minimum base VRAM of 256MB and is optimized for GPUs with at least 4GB of VRAM. Low VRAM mode is fully supported for resource-constrained setups.

High (2-4GB)
Base VRAM:
256MB (0.3GB)
Recommended GPU:
4GB+ VRAM
Low VRAM Mode:
✓ Supported
Estimation Confidence:
HIGH

Interactive VRAM Compatibility Estimator

Estimated Total VRAM: 3.00 GBTarget: 8 GB
✅ Comfortable Fit

Your GPU has plenty of headroom. You can run this node safely with your active configurations!

Deploy on High-Performance GPUs

Need more VRAM to run ComfyUI with this node? Rent low-cost, high-performance GPUs on Vast.ai instantly.

🚀 Deploy on Vast.ai

Deploy on Cloud GPUs

Need more VRAM to run ComfyUI with this node? Rent low-cost, high-performance cloud GPUs on RunPod instantly.

🚀 Deploy on RunPod

What Python packages are required for comfyui-tag-rag?

Direct Answer: Running comfyui-tag-rag requires installing the following Python package dependencies: faiss-cpu>=1.7.4, llama-cpp-python>=0.2.0, numpy>=1.24.0, onnxruntime>=1.16.0, pillow>=10.0.0, requests>=2.31.0. Ensure your ComfyUI environment has these packages active before launching.

requirements.txt
faiss-cpu>=1.7.4
llama-cpp-python>=0.2.0
numpy>=1.24.0
onnxruntime>=1.16.0
pillow>=10.0.0
requests>=2.31.0

Interactive Setup & Dependency Resolver

Operating System:
Environment Type:
Run this terminal command in your ComfyUI root folder:
# Loading command...

Related Custom Nodes

The following custom nodes run in the same PyTorch / CUDA environment and share similar categories or workflows:

ComfyUI-Regex-Runner
by orange90256MB VRAM
AIGODLIKE-COMFYUI-TRANSLATION
by AIGODLIKE128MB VRAM
AIRedoon
by purpen256MB VRAM
AITocha Vision
by aitocha128MB VRAM

Frequently Asked Questions

How much VRAM does comfyui-tag-rag require?

comfyui-tag-rag requires a minimum of 256MB (0.3GB) of VRAM for base operation. For optimal performance, a GPU with at least 4GB of VRAM is recommended. This node supports low VRAM mode for resource-constrained setups.

Can I run comfyui-tag-rag on an RTX 3060, RTX 4070, or RTX 4090?

✅ RTX 3060 (12GB): Yes, fully compatible with 10.6GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 10.6GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 14.2GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 21.4GB headroom

What Python packages are required for comfyui-tag-rag?

To run comfyui-tag-rag, you need to install: faiss-cpu>=1.7.4, llama-cpp-python>=0.2.0, numpy>=1.24.0, onnxruntime>=1.16.0, pillow>=10.0.0, requests>=2.31.0. You can install these using pip or add them to your requirements.txt file.

How can I reduce VRAM usage when running comfyui-tag-rag?

comfyui-tag-rag supports low VRAM mode. To reduce memory usage: (1) Enable --lowvram or --medvram flags in ComfyUI, (2) Reduce batch size to 1, (3) Use fp16 or fp8 precision if supported, (4) Close other GPU applications.

How do I install comfyui-tag-rag in ComfyUI?

To install comfyui-tag-rag: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/FrostySDXL/comfyui-tag-rag, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.