Azure AI Image Editing

Azure AI provides powerful image editing capabilities using FLUX models from Black Forest Labs to modify existing images based on text descriptions.

Overview

Property	Details
Description	Azure AI Image Editing uses FLUX models to modify existing images based on text prompts.
Provider Route on LiteLLM	azure_ai/
Provider Doc	Azure AI FLUX Models ↗
Supported Operations	/images/edits

Setup

API Key & Base URL & API Version

# Set your Azure AI API credentials
import os
os.environ["AZURE_AI_API_KEY"] = "your-api-key-here"
os.environ["AZURE_AI_API_BASE"] = "your-azure-ai-endpoint"  # e.g., https://your-endpoint.eastus2.inference.ai.azure.com/
os.environ["AZURE_AI_API_VERSION"] = "2025-04-01-preview"  # Example API version

Get your API key and endpoint from Azure AI Studio.

Supported Models

Model Name	Description	Cost per Image
azure_ai/FLUX.1-Kontext-pro	FLUX 1 Kontext Pro model with enhanced context understanding for editing	$0.04
azure_ai/flux.2-pro	FLUX 2 Pro, up to 8 reference images per edit	$0.04
azure_ai/FLUX.2-flex	FLUX 2 Flex, up to 10 reference images per edit, adjustable guidance and steps	$0.05 per megapixel ($0.052 at 1024x1024)

FLUX 2 edits go to the same model-specific Black Forest Labs route as FLUX 2 generation (/providers/blackforestlabs/v1/flux-2-pro or /providers/blackforestlabs/v1/flux-2-flex), with the reference images sent as base64 in the JSON body instead of multipart form data. Pass a list of files as image to edit against several references at once. The model name is matched case-insensitively, so azure_ai/flux.2-flex works too

Image Editing

Usage - LiteLLM Python SDK

Basic Usage

Basic Image Editing

import os
import base64
from pathlib import Path

import litellm

# Set your API credentials
os.environ["AZURE_AI_API_KEY"] = "your-api-key-here"
os.environ["AZURE_AI_API_BASE"] = "your-azure-ai-endpoint"
os.environ["AZURE_AI_API_VERSION"] = "2025-04-01-preview"

# Edit an image with a prompt
response = litellm.image_edit(
    model="azure_ai/FLUX.1-Kontext-pro",
    image=open("path/to/your/image.png", "rb"),
    prompt="Add a winter theme with snow and cold colors",
    api_base=os.environ["AZURE_AI_API_BASE"],
    api_key=os.environ["AZURE_AI_API_KEY"],
    api_version=os.environ["AZURE_AI_API_VERSION"]
)

img_base64 = response.data[0].get("b64_json")
img_bytes = base64.b64decode(img_base64)
path = Path("edited_image.png")
path.write_bytes(img_bytes)

Async Usage

Async Image Editing

import os
import base64
from pathlib import Path

import litellm
import asyncio

# Set your API credentials
os.environ["AZURE_AI_API_KEY"] = "your-api-key-here"
os.environ["AZURE_AI_API_BASE"] = "your-azure-ai-endpoint"
os.environ["AZURE_AI_API_VERSION"] = "2025-04-01-preview"

async def edit_image():
    # Edit image asynchronously
    response = await litellm.aimage_edit(
        model="azure_ai/FLUX.1-Kontext-pro",
        image=open("path/to/your/image.png", "rb"),
        prompt="Make this image look like a watercolor painting",
        api_base=os.environ["AZURE_AI_API_BASE"],
        api_key=os.environ["AZURE_AI_API_KEY"],
        api_version=os.environ["AZURE_AI_API_VERSION"]
    )
    img_base64 = response.data[0].get("b64_json")
    img_bytes = base64.b64decode(img_base64)
    path = Path("async_edited_image.png")
    path.write_bytes(img_bytes)

# Run the async function
asyncio.run(edit_image())

Advanced Parameters

Advanced Image Editing with Parameters

import os
import base64
from pathlib import Path

import litellm

# Set your API credentials
os.environ["AZURE_AI_API_KEY"] = "your-api-key-here"
os.environ["AZURE_AI_API_BASE"] = "your-azure-ai-endpoint"
os.environ["AZURE_AI_API_VERSION"] = "2025-04-01-preview"

# Edit image with additional parameters
response = litellm.image_edit(
    model="azure_ai/FLUX.1-Kontext-pro",
    image=open("path/to/your/image.png", "rb"),
    prompt="Add magical elements like floating crystals and mystical lighting",
    api_base=os.environ["AZURE_AI_API_BASE"],
    api_key=os.environ["AZURE_AI_API_KEY"],
    api_version=os.environ["AZURE_AI_API_VERSION"],
    n=1
)
img_base64 = response.data[0].get("b64_json")
img_bytes = base64.b64decode(img_base64)
path = Path("advanced_edited_image.png")
path.write_bytes(img_bytes)

FLUX 2 Multi-Reference

FLUX 2 Flex Edit with Several Reference Images

import os
import base64
from pathlib import Path

import litellm

os.environ["AZURE_AI_API_KEY"] = "your-api-key-here"
os.environ["AZURE_AI_API_BASE"] = "your-azure-ai-endpoint"  # e.g., https://your-resource.services.ai.azure.com

# FLUX 2 Flex accepts up to 10 reference images, FLUX 2 Pro up to 8
response = litellm.image_edit(
    model="azure_ai/FLUX.2-flex",
    image=[open("subject.png", "rb"), open("style.png", "rb")],
    prompt="Render the subject from the first image in the style of the second",
    api_base=os.environ["AZURE_AI_API_BASE"],
    api_key=os.environ["AZURE_AI_API_KEY"],
    api_version="preview",
    size="1024x1024",
    guidance=4.5,
    steps=32,
)
img_bytes = base64.b64decode(response.data[0].get("b64_json"))
Path("flux2_edited_image.png").write_bytes(img_bytes)

Usage - LiteLLM Proxy Server

1. Configure your config.yaml

Azure AI Image Editing Configuration

model_list:
  - model_name: azure-flux-kontext-edit
    litellm_params:
      model: azure_ai/FLUX.1-Kontext-pro
      api_key: os.environ/AZURE_AI_API_KEY
      api_base: os.environ/AZURE_AI_API_BASE
      api_version: os.environ/AZURE_AI_API_VERSION
    model_info:
      mode: image_edit

  - model_name: azure-flux-2-flex-edit
    litellm_params:
      model: azure_ai/FLUX.2-flex
      api_key: os.environ/AZURE_AI_API_KEY
      api_base: os.environ/AZURE_AI_API_BASE
      api_version: preview
    model_info:
      mode: image_edit

general_settings:
  master_key: os.environ/LITELLM_MASTER_KEY

2. Start LiteLLM Proxy Server

Start LiteLLM Proxy Server

litellm --config /path/to/config.yaml

# RUNNING on http://0.0.0.0:4000

3. Make image editing requests with OpenAI Python SDK

OpenAI SDK

Azure AI Image Editing via Proxy - OpenAI SDK

from openai import OpenAI

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

# Edit image with FLUX Kontext Pro
response = client.images.edit(
    model="azure-flux-kontext-edit",
    image=open("path/to/your/image.png", "rb"),
    prompt="Transform this image into a beautiful oil painting style",
)

img_base64 = response.data[0].b64_json
img_bytes = base64.b64decode(img_base64)
path = Path("proxy_edited_image.png")
path.write_bytes(img_bytes)

LiteLLM SDK

Azure AI Image Editing via Proxy - LiteLLM SDK

import litellm

# Edit image through proxy
response = litellm.image_edit(
    model="litellm_proxy/azure-flux-kontext-edit",
    image=open("path/to/your/image.png", "rb"),
    prompt="Add a mystical forest background with magical creatures",
    api_base="http://localhost:4000",
    api_key="sk-<your-litellm-api-key>"
)

img_base64 = response.data[0].b64_json
img_bytes = base64.b64decode(img_base64)
path = Path("proxy_edited_image.png")
path.write_bytes(img_bytes)

cURL

Azure AI Image Editing via Proxy - cURL

curl --location 'http://localhost:4000/v1/images/edits' \
--header "Authorization: Bearer $LITELLM_API_KEY" \
--form 'model="azure-flux-kontext-edit"' \
--form 'prompt="Convert this image to a vintage sepia tone with old-fashioned effects"' \
--form 'image=@"path/to/your/image.png"'

Supported Parameters

Azure AI Image Editing supports the following OpenAI-compatible parameters:

Parameter	Type	Description	Default	Example
image	file	The image file to edit	Required	File object or binary data
prompt	string	Text description of the desired changes	Required	"Add snow and winter elements"
model	string	The FLUX model to use for editing	Required	"azure_ai/FLUX.1-Kontext-pro"
n	integer	Number of edited images to generate (You can specify only 1)	1	1
api_base	string	Your Azure AI endpoint URL	Required	"https://your-endpoint.eastus2.inference.ai.azure.com/"
api_key	string	Your Azure AI API key	Required	Environment variable or direct value
api_version	string	API version for Azure AI	Required	"2025-04-01-preview"

FLUX 2 Pro and FLUX 2 Flex edits take the same parameters as FLUX 2 generation: size (or width and height), output_format, seed, safety_tolerance, aspect_ratio, and for Flex guidance and steps. The OpenAI-only fields user, quality, background, moderation, and output_compression are accepted and dropped, so an OpenAI SDK client that sets them keeps working

Getting Started

1. Create an account at Azure AI Studio
2. Deploy a FLUX model in your Azure AI Studio workspace
3. Get your API key and endpoint from the deployment details
4. Set your AZURE_AI_API_KEY, AZURE_AI_API_BASE and AZURE_AI_API_VERSION environment variables
5. Prepare your source image
6. Use litellm.image_edit() to modify your images with text instructions

Additional Resources

• Azure AI Studio Documentation
• FLUX Models Announcement