ComfyUI Prompt Manager

A custom node for ComfyUI that allows both saving and generating new prompts using llama.cpp.

(Llama.cpp needs to be installed and accessible from command prompt.)

<div align="center"> <img src="docs/prompt_manager.png" alt="Prompt Manager"> </div>

Key features:

Prompt Manager:

• Category Organization: Create and manage multiple categories to organize your prompts
• Save & Load Prompts: Quickly save and recall your favorite prompts with custom names
• LLM Input Toggle: Connect text outputs from other nodes and toggle between using them or your internal prompts
• LLM Input Toggle: When in use, display of categories and prompt is disabled, allowing user to switch category and save.
• Persistent Storage: All prompts saved in your ComfyUI user folder

Prompt Generator

• Automatic llama.cpp Server Management: Automatically starts llama.cpp server as needed
• Server Control: Toggle to stop server after generation (frees VRAM)
• AI-Powered Prompt Enhancement: Transform basic prompts into detailed, vivid descriptions optimized for image generation
• Local Model Support: Automatically detects and uses first .gguf model found in the models/guff folder.

Prompt Generator Options

• Model Selection: Choose from local models or download from HuggingFace
• Model Auto-Download: Easy download of Qwen3 1.7B, 4B, or 8B from HuggingFace.
• LLM Parameters: Fine-tune temperature, top_k, top_p, min_p, repeat_penalty
• Custom Instructions: Override default system prompt for different enhancement styles

Installation

1. Navigate to your ComfyUI custom nodes directory:

   cd ComfyUI/custom_nodes/
   

2. Clone this repository:

   git clone https://github.com/FranckyB/ComfyUI-Prompt-Manager.git
   

3. Install dependencies:

   cd ComfyUI-Prompt-Manager
   pip install -r requirements.txt
   

4. Install llama.cpp. It can be found here: llama.cpp install

5. If you have them, place your .gguf models in the models/gguf folder. (Create folder if not present)

6. Restart ComfyUI

Usage

Prompt Manager

1. Add the Node: Add Node → Prompt Manager
2. Select a Category: Use the dropdown to choose from your categories
3. Choose a Prompt: Select a saved prompt from the name dropdown
4. Connect prompt output: Connect Prompt Manager output to your clip text encode node.

Prompt Generator

Basic Usage (assuming a model is present in models\gguf):

1. Add the Node: Add Node → Prompt Generator
2. Connect llm_output to prompt manager: If you want to save your generated prompt connect to prompt manager.
3. type your prompt: Type in your basic prompt that will be embelished
4. Save memory: Toggle "stop_server_after" ON to free VRAM after generation, if seed is set to fix, it won't restart unless prompt changes.
5. Run Workflow: Once calculated, the prompt will display in the Prompt Manager window and allow you to save it.

Advanced Usage:

1. Add the Options Node: Add Node → Prompt Generator Options
2. Connect Options: Connect the options node to the Prompt Generator Options input
3. Select from available models: Select from models found in your modeld\gguf folder. Qwen models will be available to download.
4. Adjust settings: Adjust LLM parameters (temperature, top_k, etc.)
5. Customize LLM: Customize the default LLM instructions to modify the responses llama returns.

Size of Qwen models found in options

• Qwen3-1.7B-Q8_0.gguf: Fastest, lowest VRAM (~2GB)
• Qwen3-4B-Q8_0.gguf: Balanced performance (~4GB VRAM)
• Qwen3-8B-Q8_0.gguf: Best quality, highest VRAM (~8GB)

Model Management:

• Place gguf files in models/gguf folder
• Downloaded models are also placed in this folder.

Requirements

• ComfyUI
• Python 3.8+
• requests >= 2.31.0
• huggingface_hub >= 0.20.0
• llama-server (from llama.cpp)

Troubleshooting

Problem: Prompts don't appear in the dropdown

• Solution: Make sure the category has saved prompts. Try creating a new prompt first.

Problem: Changes aren't saved

• Solution: Click the "Save Prompt" button after making changes. Direct edits in the text field are temporary.

Problem: Can't see LLM output in the node

• Solution: Make sure the LLM output is connected to the "llm_input" and run the workflow.

Problem: "llama-server command not found"

• Solution: Install llama.cpp and make sure llama-server is available in command line. See llama.cpp releases

Problem: "No models found"

• Solution: Either place a .gguf file in the models/ folder, or connect the Prompt Generator Option node and select a model size (1.7B, 4B, or 8B) to download from HuggingFace

Problem: Server won't start

• Solution: Check that port 8080 is not in use. Close any existing llama-server processes.

Problem: Model download fails

• Solution: Check your internet connection and HuggingFace availability. Large models may take time to download.

Problem: Generation is slow

• Solution: Either, Use a smaller quantized model (Q4 instead of Q8) or toggle 'stop_server_after' to quit llama.cpp after generating prompt.

Changelog

Version 1.5.1

• LLM output remains avaiable when use llm is off. So it can be edited
• Improved Caching detection, any change to options will be detected and force a new ouput
• Improved some UI quirks

Version 1.5.0

• Added Prompt Generator node with automatic llama.cpp server management
• Added Prompt Generator Options node for model selection and parameters
• Automatic model detection and auto-download from HuggingFace for Qwen3 models.
• VRAM management with optional server shutdown

Version 1.1.0

• Added LLM input toggle for switching between internal and external text
• Made text fields scrollable even when disabled
• Fixed reload bugs with toggle state

Version 1.0.0

• Initial release
• Category and prompt management
• LLM output integration