Azure AI Image Generation (Black Forest Labs - Flux)

Azure AI provides powerful image generation capabilities using FLUX models from Black Forest Labs to create high-quality images from text descriptions.

Overview

Property	Details
Description	Azure AI Image Generation uses FLUX models to generate high-quality images from text descriptions.
Provider Route on LiteLLM	azure_ai/
Provider Doc	Azure AI FLUX Models ↗
Supported Operations	/images/generations, /images/edits

Setup

API Key & Base URL

# 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/

Get your API key and endpoint from Azure AI Studio.

Supported Models

Model Name	Description	Cost per Image
azure_ai/FLUX-1.1-pro	Latest FLUX 1.1 Pro model for high-quality image generation	$0.04
azure_ai/FLUX.1-Kontext-pro	FLUX 1 Kontext Pro model with enhanced context understanding	$0.04
azure_ai/flux.2-pro	FLUX 2 Pro model for next-generation image generation	$0.04

Image Generation

Usage - LiteLLM Python SDK

Basic Usage

Basic Image Generation

import litellm
import os

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

# Generate a single image
response = litellm.image_generation(
    model="azure_ai/FLUX.1-Kontext-pro",
    prompt="A cute baby sea otter swimming in crystal clear water",
    api_base=os.environ["AZURE_AI_API_BASE"],
    api_key=os.environ["AZURE_AI_API_KEY"]
)

print(response.data[0].url)

FLUX 1.1 Pro

FLUX 1.1 Pro Image Generation

import litellm
import os

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

# Generate image with FLUX 1.1 Pro
response = litellm.image_generation(
    model="azure_ai/FLUX-1.1-pro",
    prompt="A futuristic cityscape at night with neon lights and flying cars",
    api_base=os.environ["AZURE_AI_API_BASE"],
    api_key=os.environ["AZURE_AI_API_KEY"]
)

print(response.data[0].url)

FLUX 2 Pro

FLUX 2 Pro Image Generation

import litellm
import os

# Set your 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://litellm-ci-cd-prod.services.ai.azure.com

# Generate image with FLUX 2 Pro
response = litellm.image_generation(
    model="azure_ai/flux.2-pro",
    prompt="A photograph of a red fox in an autumn forest",
    api_base=os.environ["AZURE_AI_API_BASE"],
    api_key=os.environ["AZURE_AI_API_KEY"],
    api_version="preview",
    size="1024x1024",
    n=1
)

print(response.data[0].b64_json)  # FLUX 2 returns base64 encoded images

Async Usage

Async Image Generation

import litellm
import asyncio
import os

async def generate_image():
    # Set your API credentials
    os.environ["AZURE_AI_API_KEY"] = "your-api-key-here"
    os.environ["AZURE_AI_API_BASE"] = "your-azure-ai-endpoint"
    
    # Generate image asynchronously
    response = await litellm.aimage_generation(
        model="azure_ai/FLUX.1-Kontext-pro",
        prompt="A beautiful sunset over mountains with vibrant colors",
        api_base=os.environ["AZURE_AI_API_BASE"],
        api_key=os.environ["AZURE_AI_API_KEY"],
        n=1,
    )
    
    print(response.data[0].url)
    return response

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

Advanced Parameters

Advanced Image Generation with Parameters

import litellm
import os

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

# Generate image with additional parameters
response = litellm.image_generation(
    model="azure_ai/FLUX-1.1-pro",
    prompt="A majestic dragon soaring over a medieval castle at dawn",
    api_base=os.environ["AZURE_AI_API_BASE"],
    api_key=os.environ["AZURE_AI_API_KEY"],
    n=1,
    size="1024x1024",
    quality="standard"
)

for image in response.data:
    print(f"Generated image URL: {image.url}")

Usage - LiteLLM Proxy Server

1. Configure your config.yaml

Azure AI Image Generation Configuration

model_list:
  - model_name: azure-flux-kontext
    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
    model_info:
      mode: image_generation
  
  - model_name: azure-flux-11-pro
    litellm_params:
      model: azure_ai/FLUX-1.1-pro
      api_key: os.environ/AZURE_AI_API_KEY
      api_base: os.environ/AZURE_AI_API_BASE
    model_info:
      mode: image_generation

  - model_name: azure-flux-2-pro
    litellm_params:
      model: azure_ai/flux.2-pro
      api_key: os.environ/AZURE_AI_API_KEY
      api_base: os.environ/AZURE_AI_API_BASE
      api_version: preview
    model_info:
      mode: image_generation

general_settings:
  master_key: sk-1234

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 requests with OpenAI Python SDK

OpenAI SDK

Azure AI Image Generation 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-1234"                  # Your proxy API key
)

# Generate image with FLUX Kontext Pro
response = client.images.generate(
    model="azure-flux-kontext",
    prompt="A serene Japanese garden with cherry blossoms and a peaceful pond",
    n=1,
    size="1024x1024"
)

print(response.data[0].url)

LiteLLM SDK

Azure AI Image Generation via Proxy - LiteLLM SDK

import litellm

# Configure LiteLLM to use your proxy
response = litellm.image_generation(
    model="litellm_proxy/azure-flux-11-pro",
    prompt="A cyberpunk warrior in a neon-lit alleyway",
    api_base="http://localhost:4000",
    api_key="sk-1234"
)

print(response.data[0].url)

cURL

Azure AI Image Generation via Proxy - cURL

curl --location 'http://localhost:4000/v1/images/generations' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer sk-1234' \
--data '{
    "model": "azure-flux-kontext",
    "prompt": "A cozy coffee shop interior with warm lighting and rustic wooden furniture",
    "n": 1,
    "size": "1024x1024"
}'

Image Editing

FLUX 2 Pro supports image editing by passing an input image along with a prompt describing the desired modifications.

Usage - LiteLLM Python SDK

Basic Image Edit

Basic Image Editing with FLUX 2 Pro

import litellm
import os

# Set your 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://litellm-ci-cd-prod.services.ai.azure.com

# Edit an existing image
response = litellm.image_edit(
    model="azure_ai/flux.2-pro",
    prompt="Add a red hat to the subject",
    image=open("input_image.png", "rb"),
    api_base=os.environ["AZURE_AI_API_BASE"],
    api_key=os.environ["AZURE_AI_API_KEY"],
    api_version="preview",
)

print(response.data[0].b64_json)  # FLUX 2 returns base64 encoded images

Async Image Edit

Async Image Editing

import litellm
import asyncio
import os

async def edit_image():
    os.environ["AZURE_AI_API_KEY"] = "your-api-key-here"
    os.environ["AZURE_AI_API_BASE"] = "your-azure-ai-endpoint"
    
    response = await litellm.aimage_edit(
        model="azure_ai/flux.2-pro",
        prompt="Change the background to a sunset beach",
        image=open("input_image.png", "rb"),
        api_base=os.environ["AZURE_AI_API_BASE"],
        api_key=os.environ["AZURE_AI_API_KEY"],
        api_version="preview",
    )
    
    return response

asyncio.run(edit_image())

Usage - LiteLLM Proxy Server

cURL

Image Edit via Proxy - cURL

curl --location 'http://localhost:4000/v1/images/edits' \
--header 'Authorization: Bearer sk-1234' \
--form 'model="azure-flux-2-pro"' \
--form 'prompt="Add sunglasses to the person"' \
--form 'image=@"input_image.png"'

OpenAI SDK

Image Edit via Proxy - OpenAI SDK

from openai import OpenAI

client = OpenAI(
    base_url="http://localhost:4000",
    api_key="sk-1234"
)

response = client.images.edit(
    model="azure-flux-2-pro",
    prompt="Make the sky more dramatic with storm clouds",
    image=open("input_image.png", "rb"),
)

print(response.data[0].b64_json)

Supported Parameters

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

Parameter	Type	Description	Default	Example
prompt	string	Text description of the image to generate	Required	"A sunset over the ocean"
model	string	The FLUX model to use for generation	Required	"azure_ai/FLUX.1-Kontext-pro"
n	integer	Number of images to generate (1-4)	1	2
size	string	Image dimensions	"1024x1024"	"512x512", "1024x1024"
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

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 and AZURE_AI_API_BASE environment variables
5. Start generating images using LiteLLM

Additional Resources

• Azure AI Studio Documentation
• FLUX Models Announcement