API Reference

OpenAI Image Edit

POST https://api.tu-zi.com/v1/images/edits

Preview guide

Paste into an AI assistant to help with integration. Documentation and examples only; no real credentials.

# OpenAI Image Edit

OpenAI Image Edit

## Endpoint and authentication

`POST https://api.tu-zi.com/v1/images/edits`

Transport: multipart

Use an inference API key. Examples contain placeholders; read credentials from environment variables.

```http
Authorization: Bearer YOUR_API_KEY
```

## Body parameters

| Field | Type | Required | Description / constraints |
| --- | --- | --- | --- |
| model | string | Yes | Image editing model identifier. |
| image | file | Yes | Original image file to edit. |
| mask | file | No | Optional PNG mask; transparent areas indicate regions to edit. |
| prompt | string | Yes | Image editing instructions. Example: 保留主体，将背景替换为晴朗海滩。 |
| size | string | No | Output image dimensions. Form initial value (not an upstream default): "1024x1024" Values: "1024x1024", "1536x1024", "1024x1536" |
| n | integer | No | Number of images to generate. Form initial value (not an upstream default): 1 Range in this definition: 1 ~ 10 |

## Minimal request example

```json
{
  "model": "YOUR_MODEL",
  "prompt": "Add a blue background",
  "image": "@input.png"
}
```

## Before running

Replace https://api.tu-zi.com with this site origin (do not append /v1 twice), and YOUR_MODEL with the exact marketplace model ID. Install requests for Python; use Node.js 20+ and save JavaScript as .mjs. WebSocket samples list their own dependencies.

Create an inference key on the site and set API_KEY in the environment; replace YOUR_API_KEY in cURL. Prepare local input.png/input.wav files for upload examples.

Start with a minimal request, then read the result using the response fields below. For async APIs, a returned task ID requires polling; acceptance does not mean generation has finished.

## Code examples

### curl

```bash
curl --request POST 'https://api.tu-zi.com/v1/images/edits' \
  --header 'Authorization: Bearer YOUR_API_KEY' \
  --form 'model=YOUR_MODEL' \
  --form 'prompt=Add a blue background' \
  --form 'image=@input.png'
```

### python

```python
import json
import os
import requests

url = "https://api.tu-zi.com/v1/images/edits"
headers = json.loads("{\"Authorization\":\"Bearer YOUR_API_KEY\"}")
headers["Authorization"] = "Bearer " + os.environ["API_KEY"]
from contextlib import ExitStack
data = json.loads("{\"model\":\"YOUR_MODEL\",\"prompt\":\"Add a blue background\"}")
with ExitStack() as stack:
    files = {}
    files["image"] = stack.enter_context(open("input.png", "rb"))
    response = requests.request("POST", url, headers=headers, data=data, files=files, timeout=120)
response.raise_for_status()
result = response.json()
if isinstance(result, dict) and (result.get("success") is False or result.get("error")):
    raise RuntimeError(json.dumps(result, ensure_ascii=False))
print(result)  # Also inspect protocol-specific status/code fields.
```

### javascript

```javascript
import { readFile } from 'node:fs/promises';
// Node.js 20+
const url = "https://api.tu-zi.com/v1/images/edits";
const headers = {
  "Authorization": "Bearer YOUR_API_KEY"
};
headers.Authorization = 'Bearer ' + process.env.API_KEY;
const body = new FormData();
body.append("model", "YOUR_MODEL");
body.append("prompt", "Add a blue background");
body.append("image", new Blob([await readFile("input.png")]), "input.png");
const response = await fetch(url, { method: "POST", headers, body });
if (!response.ok) throw new Error(await response.text());
const result = await response.json();
if (result?.success === false || result?.error) throw new Error(JSON.stringify(result));
console.log(result); // Also inspect protocol-specific status/code fields.
```

## Response fields

| Field | Type | Description / constraints |
| --- | --- | --- |
| data[].url | string | Image URL in URL output mode. |
| data[].b64_json | string | Base64 image when that output mode is supported. |

Illustrative response; some endpoints show essential fields only. Optional fields may be absent.

```json
{
  "created": 1793491200,
  "data": [
    {
      "url": "https://example.com/result.png"
    }
  ]
}
```

## Errors and retries

Check HTTP status and protocol-specific errors; do not mix error formats across protocols. For 401/403 check credentials and permissions, for 429 back off, and for 5xx check gateway/upstream status. Error bodies may contain error/message/code depending on the protocol.

Use bounded exponential backoff for reads. Do not blindly retry task creation, generation, or key mutations, to avoid duplicate billing or execution.

## Constraints

This page describes the base protocol. Use the selected model quick start for supported fields, enums, limits and asynchronous behavior. Replace YOUR_MODEL. Form initial values are not upstream defaults. Inspect every item in data[]: url is an image download URL; b64_json is Base64-encoded image bytes to decode and save, not a URL. Handle either form. HTTP 200, empty data[] or text alone does not prove image generation succeeded. Do not send the site API key when downloading result URLs. Save and validate the actual image format/MIME; renaming an extension does not convert an image. image=@input.png is cURL local file-upload syntax. Use files in Python or FormData/Blob in JavaScript; never send @input.png or a local path as a JSON string. Let the client library set the multipart Content-Type and boundary; do not set application/json. Use multiple images, masks, sizes and output formats only when explicitly supported by the selected model.

## Documentation source

Definition version: 1

Reviewed: 2026-11-02

Source: https://api.tu-zi.com/en/docs/api/reference-relay-image-edit

Related protocol guide: https://api.tu-zi.com/docs/api/images

This export contains documentation and examples only, without real credentials, account data or user requests.

Updated 2026-11-02 · Reviewed 2026-11-02

Endpoint and authentication

POST https://api.tu-zi.com/v1/images/edits

Transport: multipart

Use an inference API key. Examples contain placeholders; read credentials from environment variables.

Authorization: Bearer YOUR_API_KEY

Minimal request example

{
  "model": "YOUR_MODEL",
  "prompt": "Add a blue background",
  "image": "@input.png"
}

Before running

Replace https://api.tu-zi.com with this site origin (do not append /v1 twice), and YOUR_MODEL with the exact marketplace model ID. Install requests for Python; use Node.js 20+ and save JavaScript as .mjs. WebSocket samples list their own dependencies.

Create an inference key on the site and set API_KEY in the environment; replace YOUR_API_KEY in cURL. Prepare local input.png/input.wav files for upload examples.

Start with a minimal request, then read the result using the response fields below. For async APIs, a returned task ID requires polling; acceptance does not mean generation has finished.

Constraints

This page describes the base protocol. Use the selected model quick start for supported fields, enums, limits and asynchronous behavior. Replace YOUR_MODEL. Form initial values are not upstream defaults. Inspect every item in data[]: url is an image download URL; b64_json is Base64-encoded image bytes to decode and save, not a URL. Handle either form. HTTP 200, empty data[] or text alone does not prove image generation succeeded. Do not send the site API key when downloading result URLs. Save and validate the actual image format/MIME; renaming an extension does not convert an image. image=@input.png is cURL local file-upload syntax. Use files in Python or FormData/Blob in JavaScript; never send @input.png or a local path as a JSON string. Let the client library set the multipart Content-Type and boundary; do not set application/json. Use multiple images, masks, sizes and output formats only when explicitly supported by the selected model.

Body parameters

Field	Type	Required	Description / constraints
model	string	Yes	Image editing model identifier.
image	file	Yes	Original image file to edit.
mask	file	No	Optional PNG mask; transparent areas indicate regions to edit.
prompt	string	Yes	Image editing instructions. Example: 保留主体，将背景替换为晴朗海滩。
size	string	No	Output image dimensions. Form initial value (not an upstream default): "1024x1024" Values: "1024x1024", "1536x1024", "1024x1536"
n	integer	No	Number of images to generate. Form initial value (not an upstream default): 1 Range in this definition: 1 ~ 10

Response fields

Field	Type	Description / constraints
data[].url	string	Image URL in URL output mode.
data[].b64_json	string	Base64 image when that output mode is supported.

Illustrative response; some endpoints show essential fields only. Optional fields may be absent.

{
  "created": 1793491200,
  "data": [
    {
      "url": "https://example.com/result.png"
    }
  ]
}

Errors and retries

Check HTTP status and protocol-specific errors; do not mix error formats across protocols. For 401/403 check credentials and permissions, for 429 back off, and for 5xx check gateway/upstream status. Error bodies may contain error/message/code depending on the protocol.

Use bounded exponential backoff for reads. Do not blindly retry task creation, generation, or key mutations, to avoid duplicate billing or execution.

Document information and sources

Documentation source

Definition version: 1

Reviewed: 2026-11-02

Source: https://api.tu-zi.com/en/docs/api/reference-relay-image-edit

Related protocol guide: https://api.tu-zi.com/docs/api/images

This export contains documentation and examples only, without real credentials, account data or user requests.

Request examples

curl --request POST 'https://api.tu-zi.com/v1/images/edits' \
  --header 'Authorization: Bearer YOUR_API_KEY' \
  --form 'model=YOUR_MODEL' \
  --form 'prompt=Add a blue background' \
  --form 'image=@input.png'

import json
import os
import requests

url = "https://api.tu-zi.com/v1/images/edits"
headers = json.loads("{\"Authorization\":\"Bearer YOUR_API_KEY\"}")
headers["Authorization"] = "Bearer " + os.environ["API_KEY"]
from contextlib import ExitStack
data = json.loads("{\"model\":\"YOUR_MODEL\",\"prompt\":\"Add a blue background\"}")
with ExitStack() as stack:
    files = {}
    files["image"] = stack.enter_context(open("input.png", "rb"))
    response = requests.request("POST", url, headers=headers, data=data, files=files, timeout=120)
response.raise_for_status()
result = response.json()
if isinstance(result, dict) and (result.get("success") is False or result.get("error")):
    raise RuntimeError(json.dumps(result, ensure_ascii=False))
print(result)  # Also inspect protocol-specific status/code fields.

import { readFile } from 'node:fs/promises';
// Node.js 20+
const url = "https://api.tu-zi.com/v1/images/edits";
const headers = {
  "Authorization": "Bearer YOUR_API_KEY"
};
headers.Authorization = 'Bearer ' + process.env.API_KEY;
const body = new FormData();
body.append("model", "YOUR_MODEL");
body.append("prompt", "Add a blue background");
body.append("image", new Blob([await readFile("input.png")]), "input.png");
const response = await fetch(url, { method: "POST", headers, body });
if (!response.ok) throw new Error(await response.text());
const result = await response.json();
if (result?.success === false || result?.error) throw new Error(JSON.stringify(result));
console.log(result); // Also inspect protocol-specific status/code fields.