Image Editing API Reference

gpt-image-2-all image editing API reference and interactive playground — upload reference images + instructions for single-image editing or multi-image fusion

POST /v1/images/edits

Image editing: edit or fuse reference images with instructions

cURL

curl --request POST \
  --url https://api.apiyi.com/v1/images/edits \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: multipart/form-data' \
  --form model=gpt-image-2-all \
  --form 'prompt=Put the person from image1 into the scene of image2, using the art style of image3' \
  --form 'image=<string>' \
  --form image.items='@example-file'

200

{
  "data": [
    {
      "b64_json": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA..."
    }
  ],
  "created": 1778037127,
  "usage": {
    "input_tokens": 98,
    "output_tokens": 1185,
    "total_tokens": 1283
  }
}

The interactive Playground on the right supports direct local file upload. Enter your API Key in the Authorization field (format: Bearer sk-xxx), select images, fill in prompt and model, then click send.

Scope: This page is for editing or fusing one or more reference images. Requests use multipart/form-data. For pure text-to-image generation, use the Text-to-Image endpoint.

🖥️ Browser Playground limitation (default b64_json mode)

This endpoint defaults to response_format: "b64_json", so the response carries a multi-MB base64 string and the browser Playground may show 请求时发生错误: unable to complete request — the request actually succeeded; the browser just can’t render such a long base64 string.

Recommended workflow:

• Just want to view the image in the Playground? Pass "response_format": "url" explicitly — the response is a single R2 link and renders fine.
• Want base64 or uploading large reference images? Copy the code sample below and run it locally — the code handles upload and decoding automatically.

📎 Multi-image order matters

The image field can be repeated to upload multiple reference images. The order determines how “image1/image2/image3” in the prompt are resolved. We recommend referring to them explicitly, e.g.:

Put the person from image1 into the scene of image2, using the art style of image3

Recommended ≤ 10MB per image, formats png / jpg / webp. Overly large images may hit gateway limits.

🎯 Shape-preserving edits: This endpoint’s output aspect ratio follows whichever reference image the prompt names as the edit target — not necessarily the first one in multi-image scenarios.

For example, with the prompt “modify image2, change image2’s outfit and hat to match image1”, if image2 is 1:1, the output is 1:1 (even if image1 is a landscape 16:9).

Useful for outfit swaps, adding accessories, retouching, and other shape-preserving edits. The size field has no effect on this model (sending any value is silently ignored — for strict size locking, use gpt-image-2-vip). If the prompt doesn’t pick a target, the model decides on its own.

Code Examples

Python

Single-image edit:

import requests

API_KEY = "sk-your-api-key"

with open("photo.png", "rb") as f:
    response = requests.post(
        "https://api.apiyi.com/v1/images/edits",
        headers={"Authorization": f"Bearer {API_KEY}"},
        data={
            "model": "gpt-image-2-all",
            "prompt": "Change the background to a seaside sunset",
            "response_format": "url"
        },
        files=[
            ("image", ("photo.png", f, "image/png"))
        ],
        timeout=300  # conservative — absorbs tail latency + image upload/download time
    ).json()

print(response["data"][0]["url"])

Multi-image fusion:

import requests

with open("ref1.png", "rb") as f1, \
     open("ref2.png", "rb") as f2, \
     open("ref3.png", "rb") as f3:
    response = requests.post(
        "https://api.apiyi.com/v1/images/edits",
        headers={"Authorization": "Bearer sk-your-api-key"},
        data={
            "model": "gpt-image-2-all",
            "prompt": "Put the person from image1 into the scene of image2, using the art style of image3",
            "response_format": "b64_json"
        },
        files=[
            ("image", ("ref1.png", f1, "image/png")),
            ("image", ("ref2.png", f2, "image/png")),
            ("image", ("ref3.png", f3, "image/png"))
        ],
        timeout=300  # conservative — absorbs tail latency + image upload/download time
    ).json()

# b64_json already includes the "data:image/png;base64," prefix
data_url = response["data"][0]["b64_json"]

cURL

Single-image edit:

curl -X POST "https://api.apiyi.com/v1/images/edits" \
  -H "Authorization: Bearer sk-your-api-key" \
  -F "model=gpt-image-2-all" \
  -F "prompt=Change the background to a seaside sunset" \
  -F "response_format=url" \
  -F "image=@./photo.png"

Multi-image fusion:

curl -X POST "https://api.apiyi.com/v1/images/edits" \
  -H "Authorization: Bearer sk-your-api-key" \
  -F "model=gpt-image-2-all" \
  -F "prompt=Put the person from image1 into the scene of image2, using the art style of image3" \
  -F "response_format=b64_json" \
  -F "image=@./ref1.png" \
  -F "image=@./ref2.png" \
  -F "image=@./ref3.png"

Node.js (native fetch + FormData)

import fs from 'node:fs';

const form = new FormData();
form.append('model', 'gpt-image-2-all');
form.append('prompt', 'Change the background to outer space');
form.append('response_format', 'url');
form.append(
  'image',
  new Blob([fs.readFileSync('./photo.png')]),
  'photo.png'
);

const resp = await fetch('https://api.apiyi.com/v1/images/edits', {
    method: 'POST',
    headers: { 'Authorization': 'Bearer sk-your-api-key' },
    body: form
});
const data = await resp.json();
console.log(data.data[0].url);

Browser JavaScript (File objects)

// <input type="file" id="fileInput" multiple>
const files = document.getElementById('fileInput').files;
const form = new FormData();
form.append('model', 'gpt-image-2-all');
form.append('prompt', 'Fuse these images into one poster');
form.append('response_format', 'url');
for (const f of files) form.append('image', f);

const resp = await fetch('https://api.apiyi.com/v1/images/edits', {
    method: 'POST',
    headers: { 'Authorization': 'Bearer sk-your-api-key' },
    body: form
});
const { data } = await resp.json();
document.getElementById('result').src = data[0].url;

Parameters Quick Reference

Field	Type	Required	Description
model	text	Yes	Fixed: gpt-image-2-all
prompt	text	Yes	Natural-language edit/fusion instruction
image	file	Yes	Reference image; can be repeated
size	text	No	Field has no effect; sending any value is silently ignored. Output aspect ratio follows whichever reference image the prompt names as the edit target (not necessarily the first one in multi-image scenarios). For strict size locking, use gpt-image-2-vip
response_format	text	No	b64_json (default) or url

Multi-turn iteration: Feed the previous output image back as image input with new instructions to iteratively refine the result.

Response Format

Same as the text-to-image endpoint: data[0] returns either url or b64_json — never both (depends on response_format). This endpoint defaults to b64_json.

b64_json mode (default):

{
  "data": [
    {
      "b64_json": "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA..."
    }
  ],
  "created": 1778037127,
  "usage": {
    "input_tokens": 98,
    "output_tokens": 1185,
    "total_tokens": 1283
  }
}

url mode (requires explicit "response_format": "url"):

{
  "data": [
    {
      "url": "https://r2cdn.copilotbase.com/r2cdn2/0e82148a-bec0-4b42-bbca-117c6b42581b.png"
    }
  ],
  "created": 1778037331,
  "usage": {
    "input_tokens": 30,
    "output_tokens": 2074,
    "total_tokens": 2104
  }
}

The b64_json field already contains the data:image/png;base64, prefix and can be used directly. Do not manually prepend the prefix.

Authorizations

Authorization · string · header · required

API Key from the API易 Console

Body

multipart/form-data

model · enum<string> · default: gpt-image-2-all · required

Model name, fixed to gpt-image-2-all

Available options: gpt-image-2-all

prompt · string · required

Edit/fusion instruction. For multi-image fusion, reference upload order as image1/image2/image3

Example:

"Put the person from image1 into the scene of image2, using the art style of image3"

image · file[] · required

Reference images. For a single image, send the field once; for multiple images, repeat the same image field (e.g., -F image=@a.png -F image=@b.png) — upload order maps to image1 / image2 / ... in the prompt. Recommended ≤ 10MB each, formats png / jpg / webp.

response_format · enum<string> · default: b64_json

Response format. b64_json returns a base64 string already prefixed with a data URL header (default); url returns an R2 CDN link

Available options: b64_json, url

Response

200

application/json

Image successfully generated. Defaults to base64 in data[0].b64_json — url is not returned in the same response.

Image editing response. data[0] returns either url or b64_json, never both (depends on response_format; this endpoint defaults to b64_json).

data · object[]

Result array (this model returns 1 image per call)

Show child attributes

created · integer

Unix timestamp (seconds)

usage · object

Token usage statistics

Show child attributes