sml-comfyui-prompt-expansion

sml-comfyui-prompt-expansion
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提示词扩展Deepseek 服务Stable DiffusionComfyUI 集成
在 ComfyUI 中通过 Deepseek API 自动扩展并增强 Stable Diffusion 的提示词，提升生成细节与创意表现。
💡 自动生成更丰富的提示词以提升 Stable Diffusion 图像质量。
🍴 4 Forks💻 Python🔄 2025-01-27
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https://pan.quark.cn/s/a1f1f564f19c
📦 requirements.txt
openai
workflow-0.png
workflow-1.png
workflow-flux-pro-ultra.png
📄 README

sml-comfyui-prompt-expansion

Stable Diffusion Prompt Expansion using Deepseek API

  • Create API key at https://platform.deepseek.com
  • Copy config.ini.example to config.ini and put the replicate key there.

    • Installation

    Navigate to where you have installed ComfyUI. For example:

    cd ~/dev/ComfyUI/

    Go to the custom nodes folder:

    cd custom_nodes

    Clone this repo

    git clone https://github.com/smlbiobot/sml-comfyui-prompt-expansion

    Go inside the repo folder

    cd sml-comfyui-prompt-expansion

    Install the requirements

    pip install -r requirements.txt

    Copy the example config config.ini.example to config.ini, then edit the config.ini with the actual Repliate API token.

    cp config.ini.example config.ini

    Start ComfyUI.

    Parameters

  • system_prompt. The system prompt to use.
  • prompt. The prompt to expand.
  • min_char. Minimum number of characters to generate.
  • max_char. Maximum number of characters to generate.

    • Setting min 1000, max 3000 will generate between 1000 and 3000 characters. This prompt length is generally good for models like Flux and SDXL. If you’re working with SD 1.5, you may wish to set this to a lower value.

    This prompt expansion node is not intended for SD 1.5, since SD 1.5 uses a different style of prompt.

    Methodology

    The DeepSeek engine is used to generate the expanded prompt. It has a caching mechanism that would output the same result given the same user prompt. To ensure that the same prompt will in fact output different results, I’ve employed a few tactics through salting:

  • Character count. By using a min and max character count, it asks the LLM to output a prompt with a character length that’s different every time. Thus you should set a range for this.
  • If it detects that you are using the same prompt as last time, it will fetch a few random sentences from the previous output and put that into the prompt you typed. This is mainly to avoid repetition by forcing the LLM to output different results.

    • Examples

    This shows a very simple prompt expanded into a complex paragraph.

    A real example for Flux Pro Ultra output.

    Suggestions

    Please open an issue if you have any suggestions or questions.