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/images/edits

LiteLLM provides image editing functionality that maps to OpenAI's /images/edits API endpoint.

FeatureSupportedNotes
Cost Tracking✅Works with all supported models
Logging✅Works across all integrations
End-user Tracking✅
Fallbacks✅Works between supported models
Loadbalancing✅Works between supported models
Supported operationsCreate image edits
Supported LiteLLM Versions1.63.8+
Supported LLM providersOpenAICurrently only openai is supported

Usage​

LiteLLM Python SDK​

Basic Image Edit​

OpenAI Image Edit
import litellm

# Edit an image with a prompt
response = litellm.image_edit(
model="gpt-image-1",
image=open("original_image.png", "rb"),
prompt="Add a red hat to the person in the image",
n=1,
size="1024x1024"
)

print(response)

Image Edit with Mask​

OpenAI Image Edit with Mask
import litellm

# Edit an image with a mask to specify the area to edit
response = litellm.image_edit(
model="gpt-image-1",
image=open("original_image.png", "rb"),
mask=open("mask_image.png", "rb"), # Transparent areas will be edited
prompt="Replace the background with a beach scene",
n=2,
size="512x512",
response_format="url"
)

print(response)

Async Image Edit​

Async OpenAI Image Edit
import litellm
import asyncio

async def edit_image():
response = await litellm.aimage_edit(
model="gpt-image-1",
image=open("original_image.png", "rb"),
prompt="Make the image look like a painting",
n=1,
size="1024x1024",
response_format="b64_json"
)
return response

# Run the async function
response = asyncio.run(edit_image())
print(response)

Image Edit with Custom Parameters​

OpenAI Image Edit with Custom Parameters
import litellm

# Edit image with additional parameters
response = litellm.image_edit(
model="gpt-image-1",
image=open("portrait.png", "rb"),
prompt="Add sunglasses and a smile",
n=3,
size="1024x1024",
response_format="url",
user="user-123",
timeout=60,
extra_headers={"Custom-Header": "value"}
)

print(f"Generated {len(response.data)} image variations")
for i, image_data in enumerate(response.data):
print(f"Image {i+1}: {image_data.url}")

LiteLLM Proxy with OpenAI SDK​

First, add this to your litellm proxy config.yaml:

OpenAI Proxy Configuration
model_list:
- model_name: gpt-image-1
litellm_params:
model: gpt-image-1
api_key: os.environ/OPENAI_API_KEY

Start the LiteLLM proxy server:

Start LiteLLM Proxy Server
litellm --config /path/to/config.yaml

# RUNNING on http://0.0.0.0:4000

Basic Image Edit via Proxy​

OpenAI Proxy Image Edit
from openai import OpenAI

# Initialize client with your proxy URL
client = OpenAI(
base_url="http://localhost:4000", # Your proxy URL
api_key="your-api-key" # Your proxy API key
)

# Edit an image
response = client.images.edit(
model="gpt-image-1",
image=open("original_image.png", "rb"),
prompt="Add a red hat to the person in the image",
n=1,
size="1024x1024"
)

print(response)

cURL Example​

cURL Image Edit Request
curl -X POST "http://localhost:4000/v1/images/edits" \
-H "Authorization: Bearer your-api-key" \
-F "model=gpt-image-1" \
-F "image=@original_image.png" \
-F "mask=@mask_image.png" \
-F "prompt=Add a beautiful sunset in the background" \
-F "n=1" \
-F "size=1024x1024" \
-F "response_format=url"

Supported Image Edit Parameters​

ParameterTypeDescriptionRequired
imageFileTypesThe image to edit. Must be a valid PNG file, less than 4MB, and square.✅
promptstrA text description of the desired image edit.✅
modelstrThe model to use for image editingOptional (defaults to dall-e-2)
maskstrAn additional image whose fully transparent areas indicate where the original image should be edited. Must be a valid PNG file, less than 4MB, and have the same dimensions as image.Optional
nintThe number of images to generate. Must be between 1 and 10.Optional (defaults to 1)
sizestrThe size of the generated images. Must be one of 256x256, 512x512, or 1024x1024.Optional (defaults to 1024x1024)
response_formatstrThe format in which the generated images are returned. Must be one of url or b64_json.Optional (defaults to url)
userstrA unique identifier representing your end-user.Optional

Response Format​

The response follows the OpenAI Images API format:

Image Edit Response Structure
{
"created": 1677649800,
"data": [
{
"url": "https://example.com/edited_image_1.png"
},
{
"url": "https://example.com/edited_image_2.png"
}
]
}

For b64_json format:

Base64 Response Structure
{
"created": 1677649800,
"data": [
{
"b64_json": "iVBORw0KGgoAAAANSUhEUgAA..."
}
]
}