Z Image Turbo ControlNet：LoRA対応の構造制御image-to-image生成 | RunComfy

curl --request POST \
  --url https://model-api.runcomfy.net/v1/models/tongyi-mai/z-image/turbo/controlnet/lora \
  --header "Content-Type: application/json" \
  --header "Authorization: Bearer <token>" \
  --data '{
    "prompt": "ultra-realistic interior rendering of a modern minimalist apartment living space with floor-to-ceiling glass windows on the right side, filling the room with soft natural daylight. A sleek light gray sectional sofa and a low rectangular coffee table with a matte finish sit on pale wood flooring. The walls are smooth and painted white, creating a clean and airy aesthetic. In the background, a green indoor plant adds a subtle touch of nature. The composition features high ceilings, long hallway perspective, and a serene, uncluttered atmosphere. Rendered in 8k, photorealistic, global illumination, unreal engine, architectural photography style, shot with a wide-angle lens, soft shadows, natural lighting.",
    "image_url": "https://playgrounds-storage-public.runcomfy.net/tools/7267/media-files/depth.jpg",
    "loras": [
      {
        "path": "alibaba-pai/Z-Image-Turbo-Fun-Controlnet-Union",
        "scale": 1
      }
    ]
  }'

curl --request GET \
  --url https://model-api.runcomfy.net/v1/requests/{request_id}/status \
  --header "Authorization: Bearer <token>"

curl --request GET \
  --url https://model-api.runcomfy.net/v1/requests/{request_id}/result \
  --header "Authorization: Bearer <token>"

curl --request POST \
  --url https://model-api.runcomfy.net/v1/requests/{request_id}/cancel \
  --header "Authorization: Bearer <token>"

{
  "type": "object",
  "title": "入力スキーマ",
  "required": [
    "prompt",
    "image_url",
    "loras"
  ],
  "properties": {
    "prompt": {
      "title": "プロンプト",
      "description": "",
      "type": "string",
      "default": "ultra-realistic interior rendering of a modern minimalist apartment living space with floor-to-ceiling glass windows on the right side, filling the room with soft natural daylight. A sleek light gray sectional sofa and a low rectangular coffee table with a matte finish sit on pale wood flooring. The walls are smooth and painted white, creating a clean and airy aesthetic. In the background, a green indoor plant adds a subtle touch of nature. The composition features high ceilings, long hallway perspective, and a serene, uncluttered atmosphere. Rendered in 8k, photorealistic, global illumination, unreal engine, architectural photography style, shot with a wide-angle lens, soft shadows, natural lighting."
    },
    "image_url": {
      "title": "画像",
      "description": "ControlNet ベースの生成に使用される入力画像の URL。",
      "type": "string",
      "default": "https://playgrounds-storage-public.runcomfy.net/tools/7267/media-files/depth.jpg"
    },
    "loras": {
      "title": "LoRA",
      "description": "適用する LoRA のリスト (最大 3 つ)。",
      "type": "array",
      "default": [
        {
          "path": "alibaba-pai/Z-Image-Turbo-Fun-Controlnet-Union",
          "scale": 1
        }
      ],
      "items": {
        "path": {
          "title": "LoRA パス",
          "description": "URL、HuggingFace リポジトリ ID (所有者/リポジトリ) を lora の重みに変換します。",
          "type": "string",
          "format": "str",
          "default": ""
        },
        "scale": {
          "title": "LoRA スケール",
          "description": "LoRA モデルのスケール。",
          "type": "float",
          "format": "float_slider_with_range",
          "minimum": 0,
          "maximum": 4,
          "default": 1
        }
      },
      "maxItems": 3,
      "minItems": 0
    },
    "image_size": {
      "title": "アスペクト比（幅:高さ）",
      "description": "",
      "type": "string",
      "enum": [
        "square_hd",
        "square",
        "portrait_4_3",
        "portrait_16_9",
        "landscape_4_3",
        "landscape_16_9",
        "auto"
      ],
      "default": "auto"
    },
    "control_scale": {
      "title": "コントロールスケール",
      "description": "ControlNet 条件が出力にどの程度強く影響するかを制御します。",
      "type": "float",
      "default": 0.9,
      "minimum": 0,
      "maximum": 1
    },
    "control_start": {
      "title": "コントロールスタート",
      "description": "生成中の ControlNet コンディショニングの開始点を指定します。",
      "type": "float",
      "default": 0,
      "minimum": 0,
      "maximum": 1
    },
    "control_end": {
      "title": "コントロールエンド",
      "description": "生成中の ControlNet コンディショニングのエンドポイントを指定します。",
      "type": "float",
      "default": 0.4,
      "minimum": 0,
      "maximum": 1
    },
    "preprocess": {
      "title": "前処理",
      "description": "ControlNet 入力画像に適用される前処理 (存在する場合) を定義します。",
      "type": "string",
      "enum": [
        "none",
        "canny",
        "depth",
        "pose"
      ],
      "default": "none"
    },
    "num_inference_steps": {
      "title": "推論ステップ数",
      "description": "生成時の推論ステップ数を指定します。",
      "type": "integer",
      "default": 8,
      "minimum": 1,
      "maximum": 8
    },
    "seed": {
      "title": "シード",
      "description": "",
      "type": "integer",
      "default": 0
    },
    "enable_prompt_expansion": {
      "title": "マジックプロンプト",
      "description": "結果を改善するために自動プロンプト展開を有効にします。リクエストごとにコストが 0.0025 クレジット増加します。",
      "type": "boolean",
      "default": false
    },
    "output_format": {
      "title": "出力形式",
      "description": "出力画像形式を指定します。",
      "type": "string",
      "enum": [
        "jpeg",
        "png",
        "webp"
      ],
      "default": "png"
    }
  }
}