Generate Images with KOLORS

April 24, 2025

Table of contents

  1. Request Headers
  2. Request Body
  3. Responses
  4. Model
  5. Examples
  6. Try It

This endpoint generates images using Kling’s KOLORS AI image generation system. It supports both KOLORS v1.5 (for face and subject references) and KOLORS v2.0 (for text-to-image and restyle), allowing for various reference-based image generation approaches.

https://api.useapi.net/v1/kling/images/kolors

Request Headers 
Authorization: Bearer {API token}
Content-Type: application/json
# Alternatively you can use multipart/form-data
# Content-Type: multipart/form-data
Request Body 
{
  "email": "[email protected]",
  "prompt": "Portrait of a woman with blue eyes, detailed, photorealistic",
  "reference": "face",
  "imageReference": "https://example.com/face.jpg",
  "faceStrength": 65,
  "faceNo": 1,
  "aspect_ratio": "16:9",
  "imageCount": 1
}

  • email is optional when only one account configured.
    However, if you have multiple accounts configured, this parameter becomes required.

  • prompt is required, the text description of the image to generate.
    Maximum length: 2500 characters.

  • reference is optional, the type of reference to use.
    Supported values:
    • none (default, uses KOLORS v2.0)
    • subject (uses KOLORS v1.5)
    • face (uses KOLORS v1.5)
    • restyle (uses KOLORS v2.0)

  • imageReference is required if reference is not none, the URL of the reference image.
    You can upload images using POST /assets and use the returned URL here.

  • aspect_ratio is optional, the aspect ratio of the generated image. Not supported by restyle reference type.
    Supported values: 1:1, 16:9 (default), 4:3, 3:2, 2:3, 3:4, 9:16, 21:9.

  • imageCount is optional, the number of images to generate.
    Range: 1 to 9. Default: 1.

  • faceStrength is optional, the strength of face similarity for both face and subject reference types.
    Range: 1 to 100. Default: 65.

  • subjectStrength is optional, the strength of subject similarity for subject reference type.
    Range: 1 to 100. Default: 50.

  • faceNo is optional, the index of the face to use in multi-face images for face reference type.
    Default: 1. You can use POST /images/recognize-faces to detect faces in an image.

  • maxJobs is optional, range from 1 to 10.
    Specifies the maximum number of concurrent jobs.

  • replyUrl is optional, a callback URL to receive generation progress and result.
    See GET /tasks/task_id for response model.

  • replyRef is optional, a reference identifier for the callback.
Responses

  • 200 OK

    {
  "task": {
    "id": 123456789,
    "userId": 12345,
    "type": "mmu_img2img_aiweb",
    "scene": "NORMAL_CREATION",
    "status": 5,
    "status_name": "submitted",
    "status_final": false,
    "taskInfo": {
      "type": "mmu_img2img_aiweb",
      "inputs": [
        {
          "name": "input",
          "inputType": "URL",
          "token": null,
          "blobStorage": null,
          "url": "https://example.com/face.jpg",
          "cover": null,
          "fromWorkId": null
        },
        {
          "name": "feature",
          "inputType": "URL",
          "token": null,
          "blobStorage": null,
          "url": "https://s21-kling.klingai.com/....jpg",
          "cover": null,
          "fromWorkId": null
        }
      ],
      "arguments": [
        {
          "name": "prompt",
          "value": "Portrait of a woman with blue eyes, detailed, photorealistic"
        },
        {
          "name": "aspect_ratio",
          "value": "16:9"
        },
        {
          "name": "imageCount",
          "value": "1"
        },
        {
          "name": "kolors_version",
          "value": "1.5"
        },
        {
          "name": "fidelity",
          "value": "0.65"
        },
        {
          "name": "style",
          "value": "默认"
        },
        {
          "name": "faceBound",
          "value": "{\"x\":120,\"y\":80,\"width\":200,\"height\":240}"
        },
        {
          "name": "referenceType",
          "value": "mmu_img2img_aiweb_v15_character"
        },
        {
          "name": "biz",
          "value": "klingai"
        }
      ],
      "extraArgs": {},
      "callbackPayloads": [
        {
          "name": "face_count",
          "value": "1"
        },
        {
          "name": "referenceImageWidth",
          "value": "724"
        },
        {
          "name": "referenceImageHeight",
          "value": "1268"
        }
      ],
      "scene": "NORMAL_CREATION"
    },
    "favored": false,
    "deleted": false,
    "viewed": false,
    "createTime": 1745376611075,
    "updateTime": 1745376611075
  },
  "works": [],
  "status": 5,
  "status_name": "submitted",
  "status_final": false,
  "message": "",
  "limitation": {
    "type": "mmu_img2img_aiweb",
    "remaining": 10000,
    "limit": 10000
  },
  "userPoints": {
    "points": [],
    "total": 0
  },
  "userTickets": {
    "ticket": []
  },
  "editProject": null
}

  • 400 Bad Request

    {
  "error": "reference \"face\" does not support subjectStrength"
}

  • 401 Unauthorized

    {
  "error": "Unauthorized",
  "code": 401
}

When successful, the response includes a task ID which can be used to check the status using GET /tasks/task_id.

Model 
{ // TypeScript, all fields are optional
    task: {
        id: number
        userId: number
        type: string
        scene: string
        status: number
        status_name: 'submitted' | 'failed' | 'processing' | 'succeed'
        status_final: boolean
        taskInfo: {
            type: string
            inputs: Array<{
                name: string
                inputType: string
                token: string | null
                blobStorage: any | null
                url: string
                cover: string | null
                fromWorkId: number | null
            }>
            arguments: Array<{
                name: string
                value: string
            }>
            extraArgs: Record<string, any>
            callbackPayloads: any[]
            scene: string
        }
        favored: boolean
        deleted: boolean
        viewed: boolean
        createTime: number
        updateTime: number
        viewTime: number
    }
    works: Array<any>
    status: number
    status_name: 'submitted' | 'failed' | 'processing' | 'succeed'
    status_final: boolean
    message: string
    limitation: {
        type: string
        remaining: number
        limit: number
    }
    userPoints: {
        points: Array<{
            orderId: string
            type: string
            amount: number
            balance: number
            startTime: number
            endTime: number
        }>
        total: number
    }
    userTickets: {
        ticket: Array<{
            orderId: string
            type: string
            packageType: string
            amount: number
            balance: number
            startTime: number
            endTime: number
        }>
    }
    editProject: any | null
}
Examples 
  • curl -X POST "https://api.useapi.net/v1/kling/images/kolors" \
   -H "Content-Type: application/json" \
   -H "Authorization: Bearer …" \
   -d '{
     "email": "[email protected]",
     "prompt": "Portrait of a woman with blue eyes, detailed, photorealistic",
     "reference": "face",
     "imageReference": "https://example.com/face.jpg",
     "faceStrength": 65,
     "faceNo": 1
   }'

  • const token = "API token";
const email = "Previously configured account email";
const apiUrl = "https://api.useapi.net/v1/kling/images/kolors"; 
const response = await fetch(apiUrl, {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    "Authorization": `Bearer ${token}`,
  },
  body: JSON.stringify({
    email: email,
    prompt: "Portrait of a woman with blue eyes, detailed, photorealistic",
    reference: "face",
    imageReference: "https://example.com/face.jpg",
    faceStrength: 65,
    faceNo: 1
  })
});
const result = await response.json();
console.log("response", {response, result});

  • import requests
token = "API token"
email = "Previously configured account email"
apiUrl = "https://api.useapi.net/v1/kling/images/kolors"
headers = {
    "Content-Type": "application/json", 
    "Authorization" : f"Bearer {token}"
}
data = {
    "email": email,
    "prompt": "Portrait of a woman with blue eyes, detailed, photorealistic",
    "reference": "face",
    "imageReference": "https://example.com/face.jpg",
    "faceStrength": 65,
    "faceNo": 1
}
response = requests.post(apiUrl, headers=headers, json=data)
print(response, response.json())
Try It