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Z Image Turbo ControlNet:支援 LoRA 的結構引導圖片轉圖片生成 | RunComfy

tongyi-mai/z-image/turbo/controlnet/lora

使用輸入圖片引導產生,並可設定 4 種預處理模式、0–1 控制時段、最多 3 個 LoRA 及 1–8 個推理步。

目錄

1. 快速開始2. 身分驗證3. API 參考提交請求查詢請求狀態取得請求結果取消請求4. 檔案輸入託管檔案(URL)5. 資料結構輸入結構輸出結構

1. 快速開始

使用 RunComfy 的 API 執行 tongyi-mai/z-image/turbo/controlnet/lora。 可接受的輸入與輸出請參閱模型的 資料結構說明。

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
      }
    ]
  }'

2. 身分驗證

將 YOUR_API_TOKEN 環境變數設為您的 API 金鑰(在 個人資料中管理金鑰),並在每個請求的 Authorization 標頭中以 Bearer 權杖形式攜帶: Authorization: Bearer $YOUR_API_TOKEN。

3. API 參考

提交請求

提交非同步生成工作後,將立即取得 request_id 以及用於查詢狀態、取得結果與取消的 URL。

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
      }
    ]
  }'

查詢請求狀態

依 request_id 取得目前狀態(「in_queue」、「in_progress」、「completed」或「cancelled」)。

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

取得請求結果

取得指定 request_id 的最終輸出與中繼資料;若工作尚未完成,回應會回傳目前狀態,方便繼續輪詢。

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

取消請求

透過 request_id 取消排隊中的工作;進行中的工作無法取消。

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

4. 檔案輸入

託管檔案(URL)

請提供可公開存取的 HTTPS 位址。確保目標主機允許伺服器端抓取(無需登入或 Cookie)、未被限流或阻擋機器人。建議:圖片 ≤ 50 MB(約 4K),影片 ≤ 100 MB(約 720p 下 2–5 分鐘)。私人資產請使用穩定或預先簽署 URL。

5. 資料結構

輸入結構

{
  "type": "object",
  "title": "輸入結構",
  "required": [
    "prompt",
    "image_url",
    "loras"
  ],
  "properties": {
    "prompt": {
      "title": "提示詞",
      "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": "參考圖片",
      "description": "ControlNet 輸入圖片的 URL。",
      "type": "string",
      "default": "https://playgrounds-storage-public.runcomfy.net/tools/7267/media-files/depth.jpg"
    },
    "loras": {
      "title": "LoRA 列表",
      "description": "要應用的 LoRA 列表,最多 3 項。",
      "type": "array",
      "default": [
        {
          "path": "alibaba-pai/Z-Image-Turbo-Fun-Controlnet-Union",
          "scale": 1
        }
      ],
      "items": {
        "path": {
          "title": "LoRA 路徑",
          "description": "LoRA 權重的 URL 或 Hugging Face 倉庫 ID(owner/repo)。",
          "type": "string",
          "format": "str",
          "default": ""
        },
        "scale": {
          "title": "LoRA 強度",
          "description": "LoRA 模型的應用強度。",
          "type": "float",
          "format": "float_slider_with_range",
          "minimum": 0,
          "maximum": 4,
          "default": 1
        }
      },
      "maxItems": 3,
      "minItems": 0
    },
    "image_size": {
      "title": "圖片尺寸",
      "description": "輸出圖片的尺寸預設。",
      "type": "string",
      "enum": [
        "square_hd",
        "square",
        "portrait_4_3",
        "portrait_16_9",
        "landscape_4_3",
        "landscape_16_9",
        "auto"
      ],
      "default": "auto"
    },
    "control_scale": {
      "title": "控制強度",
      "description": "ControlNet 條件影響結果的強度。",
      "type": "float",
      "default": 0.9,
      "minimum": 0,
      "maximum": 1
    },
    "control_start": {
      "title": "控制開始位置",
      "description": "ControlNet 條件在產生過程中的開始位置。",
      "type": "float",
      "default": 0,
      "minimum": 0,
      "maximum": 1
    },
    "control_end": {
      "title": "控制結束位置",
      "description": "ControlNet 條件在產生過程中的結束位置。",
      "type": "float",
      "default": 0.4,
      "minimum": 0,
      "maximum": 1
    },
    "preprocess": {
      "title": "預處理方式",
      "description": "對 ControlNet 輸入圖片應用的預處理方式。",
      "type": "string",
      "enum": [
        "none",
        "canny",
        "depth",
        "pose"
      ],
      "default": "none"
    },
    "num_inference_steps": {
      "title": "推理步數",
      "description": "產生時使用的推理步數。",
      "type": "integer",
      "default": 8,
      "minimum": 1,
      "maximum": 8
    },
    "seed": {
      "title": "隨機種子",
      "description": "用於改變或重現結果的隨機種子。",
      "type": "integer",
      "default": 0
    },
    "enable_prompt_expansion": {
      "title": "提示詞擴寫",
      "description": "啟用時自動擴寫提示詞。",
      "type": "boolean",
      "default": false
    },
    "output_format": {
      "title": "輸出格式",
      "description": "產生檔案的輸出格式。",
      "type": "string",
      "enum": [
        "jpeg",
        "png",
        "webp"
      ],
      "default": "png"
    }
  }
}

輸出結構

{
  "output": {
    "type": "object",
    "properties": {
      "image": {
        "type": "string",
        "format": "uri",
        "description": "單張圖片 URL"
      },
      "video": {
        "type": "string",
        "format": "uri",
        "description": "單一影片 URL"
      },
      "images": {
        "type": "array",
        "description": "多張圖片 URL",
        "items": {
          "type": "string",
          "format": "uri"
        }
      },
      "videos": {
        "type": "array",
        "description": "多個影片 URL",
        "items": {
          "type": "string",
          "format": "uri"
        }
      }
    }
  }
}
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