Generate image edit ​

POST https://openqiao.com/api/v1/images/edits

The Generate image edit endpoint is compatible with OpenAI's Create image edit endpoint and creates edited or extended images from one or more source images and a prompt.

You can call this endpoint in two ways:

• multipart/form-data: upload binary files through image and, optionally, mask.
• application/json: reference images through images and, optionally, mask, using image_url or file_id.

Note that JSON requests use the images array, not the image field used by multipart requests.

Request headers ​

Authorization string * ​

Bearer Token authentication, formatted as Bearer $OPENQIAO_API_KEY.

Content-Type string * ​

The request content type. Use application/json when referencing image URLs or file IDs; use multipart/form-data when uploading local files.

Request body ​

images array * ​

References to the input images to edit. GPT image models support up to 16 images.

file_id string Optional ​

The uploaded image File API ID to use as input.

image_url string Optional ​

A fully qualified URL or a base64-encoded data URL.

prompt string * ​

Text description of the desired image edit result.

background string Optional ​

The background behavior for the generated image output.

Possible values:

• transparent
• opaque
• auto

input_fidelity string Optional ​

Controls fidelity to the original input image.

Possible values:

• high
• low

mask object Optional ​

References an input image as the mask through a URL or uploaded file ID. You must provide exactly one of image_url or file_id.

file_id string Optional ​

The uploaded image File API ID to use as the mask.

image_url string Optional ​

A fully qualified URL or a base64-encoded data URL.

model string Optional ​

The model to use for image editing. Visit the 开桥 model catalog to check the currently available models.

moderation string Optional ​

The moderation level for GPT image models.

Possible values:

• low
• auto

n number Optional ​

The number of edited images to generate.

output_compression number Optional ​

The compression level for jpeg or webp output.

output_format string Optional ​

The output image format. GPT image models support this parameter.

Possible values:

• png
• jpeg
• webp

partial_images number Optional ​

The number of partial images to generate. This parameter is used for streaming responses that return partial images. The value must be between 0 and 3. When set to 0, the response returns a single image in one streaming event.

If the complete image is generated faster, the final image may be sent before all requested partial images have been produced.

quality string Optional ​

The output quality for GPT image models.

Possible values:

• low
• medium
• high
• auto

size string Optional ​

The requested output image size.

Possible values:

• auto
• 1024x1024
• 1536x1024
• 1024x1536

stream boolean Optional ​

Return partial image results as an event stream.

user string Optional ​

A unique identifier representing your end user, which can help with monitoring and abuse detection.

Response ​

Returns the response object from the image generation endpoint.

created number ​

The Unix timestamp (in seconds) when the image was created.

background string Optional ​

The background parameter used during image generation. May be transparent or opaque.

data array Optional ​

The list of generated images.

b64_json string Optional ​

The base64-encoded JSON for the generated image. GPT image models currently supported by 开桥 return this field by default.

revised_prompt string Optional ​

Returned by some models. Represents the rewritten prompt actually used to generate the image.

url string Optional ​

May contain a generated image URL for models that return URLs. GPT image models currently supported by 开桥 usually return b64_json.

output_format string Optional ​

The output format of the generated image. May be png, webp, or jpeg.

quality string Optional ​

The generated image quality. May be low, medium, or high.

size string Optional ​

The generated image size. May be 1024x1024, 1024x1536, or 1536x1024.

usage object Optional ​

Token usage information for GPT image model image generation.

• input_tokens number: The number of image and text tokens in the input prompt.
• input_tokens_details object: Input token details.
  • image_tokens number: The number of image tokens in the input prompt.
  • text_tokens number: The number of text tokens in the input prompt.
• output_tokens number: The number of output tokens generated by the model.
• total_tokens number: The total number of tokens used for this image generation.
• output_tokens_details object Optional: Output token details.
  • image_tokens number: The number of generated image output tokens.
  • text_tokens number: The number of generated text output tokens.

{
  "created": 0,
  "background": "transparent",
  "data": [
    {
      "b64_json": "b64_json",
      "revised_prompt": "revised_prompt",
      "url": "https://example.com"
    }
  ],
  "output_format": "png",
  "quality": "low",
  "size": "1024x1024",
  "usage": {
    "input_tokens": 0,
    "input_tokens_details": {
      "image_tokens": 0,
      "text_tokens": 0
    },
    "output_tokens": 0,
    "total_tokens": 0,
    "output_tokens_details": {
      "image_tokens": 0,
      "text_tokens": 0
    }
  }
}

Edit image ​

curl -s -D >(grep -i x-request-id >&2) \
  -o >(jq -r '.data[0].b64_json' | base64 --decode > gift-basket.png) \
  -X POST "https://openqiao.com/api/v1/images/edits" \
  -H "Authorization: Bearer $OPENQIAO_API_KEY" \
  -F "model=openai/gpt-image-2" \
  -F "image[]=@body-lotion.png" \
  -F "image[]=@bath-bomb.png" \
  -F "image[]=@incense-kit.png" \
  -F "image[]=@soap.png" \
  -F 'prompt=Create a lovely gift basket with these four items in it'

import fs from "fs";
import OpenAI, { toFile } from "openai";

const client = new OpenAI({
  baseURL: "https://openqiao.com/api/v1", 
  apiKey: process.env.OPENQIAO_API_KEY, 
});

const imageFiles = [
  "bath-bomb.png",
  "body-lotion.png",
  "incense-kit.png",
  "soap.png",
];

const images = await Promise.all(
  imageFiles.map(async (file) =>
    await toFile(fs.createReadStream(file), null, {
      type: "image/png",
    }),
  ),
);

const rsp = await client.images.edit({
  model: "gpt-image-2",
  image: images,
  prompt: "Create a lovely gift basket with these four items in it",
});

// Save the image to a file
const image_base64 = rsp.data[0].b64_json;
const image_bytes = Buffer.from(image_base64, "base64");
fs.writeFileSync("basket.png", image_bytes);

import base64
import os

from openai import OpenAI

client = OpenAI(
    base_url="https://openqiao.com/api/v1",  
    api_key=os.environ["OPENQIAO_API_KEY"],  
)

prompt = """
Generate a photorealistic image of a gift basket on a white background
labeled 'Relax & Unwind' with a ribbon and handwriting-like font,
containing all the items in the reference pictures.
"""

result = client.images.edit(
    model="gpt-image-2",
    image=[
        open("body-lotion.png", "rb"),
        open("bath-bomb.png", "rb"),
        open("incense-kit.png", "rb"),
        open("soap.png", "rb"),
    ],
    prompt=prompt,
)

image_base64 = result.data[0].b64_json
image_bytes = base64.b64decode(image_base64)

# Save the image to a file
with open("gift-basket.png", "wb") as f:
    f.write(image_bytes)