L’interface est localisée ; les présentations et documents des Skills sont traduits automatiquement par IA dans votre langue. Le code, les commandes, chemins et termes techniques restent en version originale, et le document de l’auteur fait foi.
Explorer les Skills
Productivité · SKILL.md

prompt-and-image-conditioning

prompt-and-image-conditioning

Route HunyuanImage-3.0 system prompts, recaption and think modes, DeepSeek rewrite, text rendering, image size, and multi-image conditioning decisions.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: prompt-and-image-conditioning description: "Route HunyuanImage-3.0 system prompts, recaption and think modes, DeepSeek rewrite, text rendering, image size, and multi-image conditioning decisions." metadata: disco-role: operating disable-model-invocation: true license: NOASSERTION

Prompt and Image Conditioning

Use this sub-skill when a task is about how to phrase prompts or how to choose use_system_prompt, bot_task, --rewrite, image, image_size, or infer_align_image_size for HunyuanImage-3.0 generation.

Do not use this sub-skill for raw model architecture, tokenizer template internals, checkpoint loading internals, full local command walkthroughs, Gradio launch, or vLLM deployment. For those, route to sibling skills:

Operating route

  1. Read prompt modes to choose the prompt path:
    • manual prompt writing,
    • model self-rewrite with recaption or think_recaption,
    • external DeepSeek PE rewrite,
    • direct multi-image conditioning.
  2. Read troubleshooting before diagnosing failures, especially for credentials, network, dynamic mode, image lists, text rendering, or the known args.sys_deepseek_prompt rewrite typo.
  3. Optionally run prompt-mode validator to check a proposed mode combination without loading model weights or calling any network service.

Fast recommendations

  • For HunyuanImage-3.0-Instruct or Instruct-Distil image editing, multi-image fusion, or sparse prompts: prefer use_system_prompt="en_unified" with bot_task="think_recaption". Pass conditional images as an ordered list in the API or comma-separated paths in the CLI.
  • For direct text-to-image with an already detailed prompt: use bot_task="image"; use image_size="auto" when the model should infer a ratio, or a fixed HxW / W:H value when composition must be constrained.
  • For the base pretrain checkpoint: do not assume local model self-rewrite. Write a rich manual prompt, or use the DeepSeek PE rewrite path only when Tencent credentials and network access are intentionally available.
  • For UI, poster, logo, or text rendering: every visible text string must be explicit and enclosed in double quotes; preserve the language and spelling of user-specified text.
  • Avoid use_system_prompt="dynamic" with the local CLI's bot_task="think_recaption": the source resolver maps dynamic mode for think, recaption, and image, but not for think_recaption.

Safety constraints

  • This sub-skill does not call DeepSeek, Tencent Cloud, model checkpoints, or repo launch scripts.
  • Treat PE/deepseek.py as reference-only because it is credential and network bound.
  • Treat PE/system_prompt.py as distilled guidance, not as a runnable dependency for the generated skill.
  • Keep future guidance self-contained; do not require the original repository checkout to remain available.
Skills enregistrées