Edit images with AI models

June 3, 2025 (October 3, 2025)

Table of contents

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

This endpoint edits existing images using FLUX.1 Kontext, FLUX.1 Kontext Max, or Nano Banana / Gemini 2.5 Flash Image based on text prompts and reference images.

Model Capabilities
Parameter FLUX.1 Kontext
flux (default)		 FLUX.1 Kontext Max
flux-premium		 Nano Banana / Gemini 2.5 Flash Image
nano-banana
referenceAssetId ✓ ✓ ✓
referenceAssetId2 ✓ ✓ ✓
referenceAssetId3 ✗ ✓ ✓
aspectRatio ✓ ✓ ✗

https://api.useapi.net/v1/ltxstudio/images/edit

Request Headers 
Authorization: Bearer {API token}
Content-Type: application/json
# Alternatively you can use multipart/form-data
# Content-Type: multipart/form-data
Request Body 
{
  "prompt": "Add golden sunset lighting to the landscape",
  "referenceAssetId": "asset:3b18…-type:image/png",
  "aspectRatio": "16:9",
  "shotType": "wide shot",
  "shotAngle": "eye-level",
  "seed": 123456
}
  • email is optional when only one account configured. However, if you have multiple accounts configured, this parameter becomes required.
  • prompt is required, text description for image editing (max 2000 characters)
  • referenceAssetId is required, asset ID for the source image to edit. Use field fileId from POST assets/?type=reference-image or GET assets/?filter=images.
  • referenceAssetId2 is optional, second reference image asset ID.
  • referenceAssetId3 is optional, third reference image asset ID (see model capabilities table above).
  • location is optional, location description for the image (max 2000 characters).
  • weather is optional, weather conditions description (max 2000 characters).
  • lighting is optional, lighting description (max 2000 characters).
  • aspectRatio is optional, output image aspect ratio (see model capabilities table above).
    Supported values: 16:9, 9:16, 1:1.
    Default: 16:9.
  • shotType is optional, type of shot for the image (e.g., “wide shot”, “close-up”, “medium shot”).
  • shotAngle is optional, camera angle for the shot.
    Supported values: eye-level, low-angle, over-the-shoulder, overhead, birds-eye-view.
  • seed is optional, random seed for reproducible results.
  • model is optional, the AI model to use for image editing.
    Supported values: flux, flux-premium, nano-banana.
    Default: flux.
  • pollForResult is optional, number of polling attempts to wait for completion (each attempt waits 3 seconds, up to 60 seconds total max) before sending job to the scheduler. For example, pollForResult: 5 will poll every 3 seconds for up to 15 seconds total. Supported values: 1-20. Default: immediate return with jobId.
  • maxJobs is optional, override the default maximum number of concurrent jobs.
  • replyUrl is optional, webhook URL for job completion notifications.
    See GET assets/jobId for response model.
  • replyRef is optional, custom reference for webhook identification.
Responses

  • 200 OK (Job Created)

    {
    "jobId": "email:[email protected]:7a34b821-9fd0-205e-d21b-4abc6f7839e7-type:image",
    "generationId": "gen_abc123def456"
}

  • 200 OK (pollForResult completed)

    {
    "status": {
        "type": "completed",
        "progress": 100,
        "artifact": {
            "assetUrl": "https://storage.googleapis.com/lt-infinity-prd/artifacts/vertex-ai/…",
            "expirationDateString": "1748919477350",
            "asset": {
                "type": "artifact",
                "fileId": "asset:3b18…-type:image/png",
                "mimeType": "image/png",
                "artifactSubtype": "vertex-ai"
            }
        }
    },
    "jobId": "email:[email protected]:7a34b821-9fd0-205e-d21b-4abc6f7839e7-type:image",
    "replyRef": "custom-reference-123",
    "replyUrl": "https://webhook.example.com/ltx-callback",
    "code": 200
}

  • 400 Bad Request

    {
  "error": "Error message",
  "code": 400
}

  • 401 Unauthorized

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

  • 402 Payment Required

    {
  "error": "Insufficient credits",
  "code": 402
}
Model

Use GET assets/jobId to retrieve job status and results if they were not provided with the response.

{ // TypeScript, all fields are optional
    status: {
        type: 'active' | 'completed' | 'failed'
        progress?: number
        message?: string
        artifact?: {
            assetUrl: string
            expirationDateString: string
            asset: {
                type: string
                fileId: string
                mimeType: string
                artifactSubtype: string
            }
        }
    }
    jobId?: string
    generationId?: string
    replyRef?: string
    replyUrl?: string
    code?: number
}
Examples 
  • curl "https://api.useapi.net/v1/ltxstudio/images/edit" \
   -H "Authorization: Bearer …" \
   -H "Content-Type: application/json" \
   -d '{
     "prompt": "Add golden sunset lighting to the landscape",
     "referenceAssetId": "asset:3b18…-type:image/png",
     "aspectRatio": "16:9",
     "shotType": "wide shot",
     "shotAngle": "eye-level",
     "pollForResult": 10
   }'

  • const token = "API token";
const apiUrl = "https://api.useapi.net/v1/ltxstudio/images/edit";

const response = await fetch(apiUrl, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${token}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "prompt": "Add golden sunset lighting to the landscape",
    "referenceAssetId": "asset:3b18…-type:image/png",
    "aspectRatio": "16:9",
    "shotType": "wide shot",
    "shotAngle": "eye-level",
    "pollForResult": 10
  })
});
const result = await response.json();
console.log("response", {response, result});

  • import requests
token = "API token"
apiUrl = "https://api.useapi.net/v1/ltxstudio/images/edit"
headers = {
    "Authorization" : f"Bearer {token}",
    "Content-Type": "application/json"
}
data = {
    "prompt": "Add golden sunset lighting to the landscape",
    "referenceAssetId": "asset:3b18…-type:image/png",
    "aspectRatio": "16:9",
    "shotType": "wide shot",
    "shotAngle": "eye-level",
    "pollForResult": 10
}
response = requests.post(apiUrl, headers=headers, json=data)
print(response, response.json())
Try It