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

Setup

API Key & Base URL & API Version

# Set your Azure AI API credentials

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

Image Editing

Usage - LiteLLM Python SDK

from pathlib import Path

# 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)

from pathlib import Path

# 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())

from pathlib import Path

# 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)

Usage - LiteLLM Proxy Server

1. Configure your config.yaml

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

general_settings:
  master_key: sk-1234

2. 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

from openai import OpenAI

# Initialize client with your proxy URL
client = OpenAI(
    base_url="http://localhost:4000",  # Your proxy URL
    api_key="sk-1234"                  # 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)

# 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-1234"
)

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 --location 'http://localhost:4000/v1/images/edits' \\
--header 'Authorization: Bearer sk-1234' \\
--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:

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