curl --request POST \
  --url https://api.omnirelay.ai/v1/images/edits \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: multipart/form-data' \
  --form model=gpt-image-2 \
  --form 'prompt=<string>' \
  --form image=@example-file \
  --form mask=@example-file

import requests

url = "https://api.omnirelay.ai/v1/images/edits"

files = {
    "image": ("example-file", open("example-file", "rb")),
    "mask": ("example-file", open("example-file", "rb"))
}
payload = {
    "model": "gpt-image-2",
    "prompt": "<string>"
}
headers = {"Authorization": "Bearer <token>"}

response = requests.post(url, data=payload, files=files, headers=headers)

print(response.text)

const form = new FormData();
form.append('model', 'gpt-image-2');
form.append('prompt', '<string>');
form.append('image', '<string>');
form.append('mask', '{
  "fileName": "example-file"
}');

const options = {method: 'POST', headers: {Authorization: 'Bearer <token>'}};

options.body = form;

fetch('https://api.omnirelay.ai/v1/images/edits', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

{
  "created": 123,
  "model": "<string>",
  "data": [
    {
      "b64_json": "<string>",
      "revised_prompt": "<string>"
    }
  ],
  "cost_microusd": 123,
  "background": "<string>",
  "output_format": "<string>",
  "quality": "<string>",
  "size": "<string>",
  "usage": {},
  "omnirelay_metadata": {
    "request_id": "<string>",
    "requested": "<string>",
    "model": "<string>",
    "provider": "<string>",
    "mode": "live",
    "strategy": "direct",
    "attempt": 123,
    "attempts": [
      {
        "provider": "<string>",
        "model": "<string>",
        "mode": "<string>"
      }
    ],
    "tags": {},
    "deprecated_header": "<string>"
  },
  "gateway_metadata": {
    "request_id": "<string>",
    "requested": "<string>",
    "model": "<string>",
    "provider": "<string>",
    "mode": "live",
    "strategy": "direct",
    "attempt": 123,
    "attempts": [
      {
        "provider": "<string>",
        "model": "<string>",
        "mode": "<string>"
      }
    ],
    "tags": {},
    "deprecated_header": "<string>"
  }
}

{
  "error": {
    "code": "unsupported_parameter"
  },
  "request_id": "2f6c1d0e9a"
}

{
  "error": {
    "code": "unauthorized"
  }
}

{
  "error": {
    "code": "inference_budget_or_access_denied"
  },
  "request_id": "2f6c1d0e9a"
}

{
  "error": {
    "code": "model_not_allowed"
  },
  "request_id": "2f6c1d0e9a"
}

{
  "error": {
    "code": "model_unavailable"
  },
  "request_id": "2f6c1d0e9a"
}

{
  "error": {
    "code": "payload_too_large"
  },
  "request_id": "2f6c1d0e9a"
}

{
  "error": {
    "code": "rate_limited"
  },
  "request_id": "2f6c1d0e9a"
}

{
  "error": {
    "code": "image_call_held"
  },
  "request_id": "2f6c1d0e9a"
}

{
  "error": {
    "code": "live_provider_unavailable"
  },
  "request_id": "2f6c1d0e9a"
}

{
  "error": {
    "code": "image_call_held"
  },
  "request_id": "2f6c1d0e9a"
}