Tuzi Multimodel Image Generation

Tuzi Multi-model Image Generation

Use the bundled Python script to call the synchronous Tuzi image endpoint and save the returned images locally.

Security

• Prefer the standard TUZI_API_KEY environment variable.
• Allow a deployment to set TUZI_API_KEY_ENV to the name of its generated credential variable. If neither is set, allow exactly one injected COZE_TUZI_API_* variable.
• Allow TUZI_API_KEY_FILE only for a runtime-mounted secret file that is not bundled in the Skill.
• For a local Codex or desktop Agent, allow the user to run scripts/configure_key.py once. Store the Key in the current user's private configuration directory, never in the Skill directory.
• Never request that the user paste the key into chat, a prompt, or a command argument.
• Never print, log, or return the Key. Store it only in the current user's private credential location or the Agent platform's secret manager.
• If no credential is injected, stop and ask the user to configure it as a secret in the current Agent runtime. Never add a real key to a source file or ZIP.

Workflow

1. Read references/models.md when selecting a model or using model-specific options. Read references/runtime.md when configuring credentials or diagnosing an Agent sandbox.

2. If a local desktop runtime reports that no Key exists, run the configuration script. Let the user type into the hidden GUI or terminal prompt; never ask them to send the Key in chat:

   python3 <skill-directory>/scripts/configure_key.py
   

   In a remote or deployed Agent, use the platform's secret credential UI instead.

3. Use the user's requested model when supported. Otherwise choose:

   • seedream-5.0 for ordinary text-to-image generation.
   • seedream-4.5 for multiple reference images.
   • gpt-image-1 for quality, output format, or transparent-background controls.
   • nano-banana-2 for Gemini/Nano Banana text-to-image generation.
   • flux-kontext-pro for one reference image, an explicit seed, or a native aspect ratio.

4. Run scripts/generate_image.py. Pass an absolute output directory when the runtime requires files in a specific workspace; otherwise let the script create a temporary directory.

5. Check the JSON result. Treat code: 0 as success and use saved_files as the deliverables.

6. Return the saved images to the user. Do not claim success when no file was saved.

Command

python3 <skill-directory>/scripts/generate_image.py \
  --prompt "一只蓝色兔子，白色背景，扁平插画" \
  --model seedream-5.0 \
  --size 2K

Common optional arguments:

--aspect-ratio 16:9
--reference-image https://example.com/reference.png
--max-images 2
--watermark
--quality high
--output-format png
--background transparent
--seed 42
--output-dir /absolute/path/to/generated-images

Repeat --reference-image for multiple Seedream reference images. Do not pass both --size and --aspect-ratio.

Failure handling

• Report the returned msg concisely when code is nonzero.
• Do not silently remove unsupported parameters; rerun only after selecting a compatible model or option.
• If outbound HTTPS or local script execution is unavailable, state that the runtime cannot execute this Skill and do not fabricate an image.
• A development sandbox may omit deployment credentials. Treat that as an unverified live path, not as an API failure; retry after deployment or with a locally configured secret.
• Do not substitute an arbitrary base URL or an unlisted model.