shengsuanyun-image

name	shengsuanyun-image
description	Generate images with Shengsuanyun Router using openai/gpt-image-2, including prompt-file generation, local or URL reference images, task polling, downloads, and saved JSON responses. Use when the user wants Codex to call the Shengsuanyun image API, use gpt-image-2 through router.shengsuanyun.com, or package/reuse this API-based image generation workflow.

Shengsuanyun Image

Use this skill to generate images through Shengsuanyun Router's task API, typically with openai/gpt-image-2.

Core Rules

• Never store real API keys in shared files.
• Prefer SHENGSUANYUN_API_KEY or a private --env-file .env over --api-key.
• Use the bundled script instead of rewriting API callers.
• Save generated images into the current project unless the user asks for preview-only output.
• If reference images are used, state each image's role: hardware reference, style reference, layout reference, or edit target.
• If network/DNS fails in a sandboxed environment, rerun the same command with the required network permission.

Files

• Script: scripts/shengsuanyun_image.py
• Usage reference: references/usage.md
• Prompting reference: references/prompting.md
• Config template: assets/.env.example
• Example prompt: assets/example_prompt.txt

Read references/usage.md when you need command examples or option details. Read references/prompting.md when preparing complex prompts or when a prompt is refused.

Standard Workflow

1. Decide whether the request uses direct prompt text or a prompt file.
2. Decide whether reference images are needed and label their role.
3. Put the API key in SHENGSUANYUN_API_KEY, a private .env file, or use the user-provided key only for the command.
4. Run:

python3 <skill_dir>/scripts/shengsuanyun_image.py \
  --prompt-file <prompt.txt> \
  --env-file .env \
  --name <output_name> \
  --out-dir <output_dir> \
  --size 1536x864 \
  --quality auto \
  --save-response

5. Add one or more --reference-image <path-or-url> options if needed.
6. Inspect the generated image before judging success.
7. If the image fails the user's constraints, revise the prompt and regenerate rather than manually hiding major generated-image errors.

Common Commands

Direct prompt:

python3 <skill_dir>/scripts/shengsuanyun_image.py \
  --prompt "一张白色背景上的蓝色立方体，简洁产品摄影风格" \
  --name test_cube \
  --out-dir outputs/shengsuanyun \
  --save-response

Prompt file with reference image:

python3 <skill_dir>/scripts/shengsuanyun_image.py \
  --prompt-file prompts/frame_01.txt \
  --reference-image references/style.jpg \
  --name frame_01 \
  --out-dir outputs/shengsuanyun \
  --size 1536x864 \
  --quality auto \
  --save-response

Dry run:

python3 <skill_dir>/scripts/shengsuanyun_image.py \
  --prompt-file prompts/frame_01.txt \
  --reference-image references/style.jpg \
  --dry-run

Output

The script prints JSON containing:

{
  "request_id": "...",
  "images": ["outputs/shengsuanyun/name_01.png"]
}

When --save-response is used, it also writes:

• <name>_create_response.json
• <name>_final_response.json

Troubleshooting

• Missing API key: set SHENGSUANYUN_API_KEY or pass --api-key.
• HTTP 401: the token is invalid.
• Network/DNS failure: rerun with network permission.
• Policy refusal: rewrite into a neutral, non-harmful, non-identifying, or clearly educational/demo form; see references/prompting.md.
• Reference image ignored: try fewer references and make each role explicit in the prompt.