Azure AI 圖像生成（Black Forest Labs - Flux）
Azure AI 使用來自 Black Forest Labs 的 FLUX 模型，提供強大的圖像生成能力，可根據文字描述建立高品質圖片。
總覽
| 屬性 | 詳細資訊 |
|---|---|
| 說明 | Azure AI Image Generation 使用 FLUX 模型，從文字描述生成高品質圖片。 |
| LiteLLM 上的提供者路由 | azure_ai/ |
| 提供者文件 | Azure AI FLUX 模型 ↗ |
| 支援的操作 | /images/generations, /images/edits |
設定
API 金鑰與 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/
請從 Azure AI Studio 取得您的 API 金鑰與端點。
支援的模型
| 模型名稱 | 說明 | 每張圖片成本 |
|---|---|---|
azure_ai/FLUX-1.1-pro | 最新的 FLUX 1.1 Pro 模型，適用於高品質圖片生成 | $0.04 |
azure_ai/FLUX.1-Kontext-pro | 具有增強情境理解能力的 FLUX 1 Kontext Pro 模型 | $0.04 |
azure_ai/flux.2-pro | 下一代圖片生成用的 FLUX 2 Pro 模型 | $0.04 |
圖像生成
使用方式 - LiteLLM Python SDK
- 基本用法
- FLUX 1.1 Pro
- FLUX 2 Pro
- 非同步用法
- 進階參數
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 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 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 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 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}")
使用方式 - LiteLLM Proxy Server
1. 設定您的 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. 啟動 LiteLLM Proxy Server
Start LiteLLM Proxy Server
litellm --config /path/to/config.yaml
# RUNNING on http://0.0.0.0:4000
3. 使用 OpenAI Python SDK 發出請求
- OpenAI SDK
- LiteLLM SDK
- cURL
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)
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)
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"
}'
圖像編輯
FLUX 2 Pro 支援圖像編輯，方法是傳入輸入圖片，以及描述所需修改內容的提示詞。
使用方式 - LiteLLM Python SDK
- 基本圖像編輯
- 非同步圖像編輯
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 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())
使用方式 - LiteLLM Proxy Server
- cURL
- OpenAI SDK
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"'
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)
支援的參數
Azure AI Image Generation 支援以下與 OpenAI 相容的參數：
| 參數 | 類型 | 說明 | 預設值 | 範例 |
|---|---|---|---|---|
prompt | string | 要生成的圖片文字描述 | 必填 | "A sunset over the ocean" |
model | string | 要用於生成的 FLUX 模型 | 必填 | "azure_ai/FLUX.1-Kontext-pro" |
n | integer | 要生成的圖片數量（1-4） | 1 | 2 |
size | string | 圖片尺寸 | "1024x1024" | "512x512", "1024x1024" |
api_base | string | 您的 Azure AI 端點 URL | 必填 | "https://your-endpoint.eastus2.inference.ai.azure.com/" |
api_key | string | 您的 Azure AI API 金鑰 | 必填 | 環境變數或直接值 |
快速開始
- 在 Azure AI Studio 建立帳戶
- 在您的 Azure AI Studio 工作區部署 FLUX 模型
- 從部署詳細資料取得您的 API 金鑰與端點
- 設定您的
AZURE_AI_API_KEY與AZURE_AI_API_BASE環境變數 - 開始使用 LiteLLM 生成圖片