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Z Image Turbo ControlNet:支持 LoRA 的结构引导图片到图片生成 | RunComfy

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

使用输入图片引导生成,并可设置 4 种预处理模式、0–1 控制时段、最多 3 个 LoRA 及 1–8 个推理步。

目录

1. 快速开始2. 身份验证3. API 参考提交请求查询请求状态获取请求结果取消请求4. 文件输入托管文件(URL)5. 数据结构输入结构输出结构

1. 快速开始

使用 RunComfy 的 API 运行 tongyi-mai/z-image/turbo/controlnet/lora。 可接受的输入与输出请参阅模型的 数据结构说明。

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. 身份验证

将 YOUR_API_TOKEN 环境变量设置为您的 API 密钥(在 个人资料中管理密钥),并在每个请求的 Authorization 标头中以 Bearer 令牌形式携带: Authorization: Bearer $YOUR_API_TOKEN。

3. API 参考

提交请求

提交异步生成任务,将立即获得 request_id 以及用于查询状态、获取结果和取消的 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
      }
    ]
  }'

查询请求状态

根据 request_id 获取当前状态("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>"

获取请求结果

获取指定 request_id 的最终输出与元数据;若任务未完成,响应会返回当前状态,便于继续轮询。

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

取消请求

通过 request_id 取消排队中的任务;进行中的任务无法取消。

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

4. 文件输入

托管文件(URL)

请提供可公网访问的 HTTPS 地址。确保目标主机允许服务端拉取(无需登录或 Cookie)、未被限流或拦截爬虫。建议:图片 ≤ 50 MB(约 4K),视频 ≤ 100 MB(约 720p 下 2–5 分钟)。私有资源请使用稳定或预签名 URL。

5. 数据结构

输入结构

{
  "type": "object",
  "title": "输入结构",
  "required": [
    "prompt",
    "image_url",
    "loras"
  ],
  "properties": {
    "prompt": {
      "title": "提示词",
      "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": "参考图片",
      "description": "ControlNet 输入图片的 URL。",
      "type": "string",
      "default": "https://playgrounds-storage-public.runcomfy.net/tools/7267/media-files/depth.jpg"
    },
    "loras": {
      "title": "LoRA 列表",
      "description": "要应用的 LoRA 列表,最多 3 项。",
      "type": "array",
      "default": [
        {
          "path": "alibaba-pai/Z-Image-Turbo-Fun-Controlnet-Union",
          "scale": 1
        }
      ],
      "items": {
        "path": {
          "title": "LoRA 路径",
          "description": "LoRA 权重的 URL 或 Hugging Face 仓库 ID(owner/repo)。",
          "type": "string",
          "format": "str",
          "default": ""
        },
        "scale": {
          "title": "LoRA 强度",
          "description": "LoRA 模型的应用强度。",
          "type": "float",
          "format": "float_slider_with_range",
          "minimum": 0,
          "maximum": 4,
          "default": 1
        }
      },
      "maxItems": 3,
      "minItems": 0
    },
    "image_size": {
      "title": "图片尺寸",
      "description": "输出图片的尺寸预设。",
      "type": "string",
      "enum": [
        "square_hd",
        "square",
        "portrait_4_3",
        "portrait_16_9",
        "landscape_4_3",
        "landscape_16_9",
        "auto"
      ],
      "default": "auto"
    },
    "control_scale": {
      "title": "控制强度",
      "description": "ControlNet 条件影响结果的强度。",
      "type": "float",
      "default": 0.9,
      "minimum": 0,
      "maximum": 1
    },
    "control_start": {
      "title": "控制开始位置",
      "description": "ControlNet 条件在生成过程中的开始位置。",
      "type": "float",
      "default": 0,
      "minimum": 0,
      "maximum": 1
    },
    "control_end": {
      "title": "控制结束位置",
      "description": "ControlNet 条件在生成过程中的结束位置。",
      "type": "float",
      "default": 0.4,
      "minimum": 0,
      "maximum": 1
    },
    "preprocess": {
      "title": "预处理方式",
      "description": "对 ControlNet 输入图片应用的预处理方式。",
      "type": "string",
      "enum": [
        "none",
        "canny",
        "depth",
        "pose"
      ],
      "default": "none"
    },
    "num_inference_steps": {
      "title": "推理步数",
      "description": "生成时使用的推理步数。",
      "type": "integer",
      "default": 8,
      "minimum": 1,
      "maximum": 8
    },
    "seed": {
      "title": "随机种子",
      "description": "用于改变或复现结果的随机种子。",
      "type": "integer",
      "default": 0
    },
    "enable_prompt_expansion": {
      "title": "提示词扩展",
      "description": "启用时自动扩展提示词。",
      "type": "boolean",
      "default": false
    },
    "output_format": {
      "title": "输出格式",
      "description": "生成文件的输出格式。",
      "type": "string",
      "enum": [
        "jpeg",
        "png",
        "webp"
      ],
      "default": "png"
    }
  }
}

输出结构

{
  "output": {
    "type": "object",
    "properties": {
      "image": {
        "type": "string",
        "format": "uri",
        "description": "单张图片 URL"
      },
      "video": {
        "type": "string",
        "format": "uri",
        "description": "单个视频 URL"
      },
      "images": {
        "type": "array",
        "description": "多张图片 URL",
        "items": {
          "type": "string",
          "format": "uri"
        }
      },
      "videos": {
        "type": "array",
        "description": "多个视频 URL",
        "items": {
          "type": "string",
          "format": "uri"
        }
      }
    }
  }
}
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