Black Forest Labs Image Editing

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

Overview

Setup

API Key

# Set your Black Forest Labs API key
os.environ["BFL_API_KEY"] = "your-api-key-here"

Get your API key from Black Forest Labs.

Supported Models

Image Editing

Usage - LiteLLM Python SDK

# Set your API key
os.environ["BFL_API_KEY"] = "your-api-key-here"

# Edit an image with a prompt
response = litellm.image_edit(
    model="black_forest_labs/flux-kontext-pro",
    image=open("path/to/your/image.png", "rb"),
    prompt="Add a green leaf to the scene",
)

# BFL returns URLs
print(response.data[0].url)

# Set your API key
os.environ["BFL_API_KEY"] = "your-api-key-here"

async def edit_image():
    response = await litellm.aimage_edit(
        model="black_forest_labs/flux-kontext-pro",
        image=open("path/to/your/image.png", "rb"),
        prompt="Make this image look like a watercolor painting",
    )
    print(response.data[0].url)

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

# Set your API key
os.environ["BFL_API_KEY"] = "your-api-key-here"

# Use flux-pro-1.0-fill for inpainting
response = litellm.image_edit(
    model="black_forest_labs/flux-pro-1.0-fill",
    image=open("path/to/your/image.png", "rb"),
    mask=open("path/to/mask.png", "rb"),  # White areas will be edited
    prompt="Replace with a beautiful garden",
    steps=50,  # BFL-specific parameter
    guidance=30,  # BFL-specific parameter
)

print(response.data[0].url)

# Set your API key
os.environ["BFL_API_KEY"] = "your-api-key-here"

# Use flux-pro-1.0-expand to extend image borders
response = litellm.image_edit(
    model="black_forest_labs/flux-pro-1.0-expand",
    image=open("path/to/your/image.png", "rb"),
    prompt="Continue the scene with a mountain landscape",
    top=256,     # Expand 256 pixels at top
    bottom=256,  # Expand 256 pixels at bottom
    left=128,    # Expand 128 pixels at left
    right=128,   # Expand 128 pixels at right
)

print(response.data[0].url)

# Set your API key
os.environ["BFL_API_KEY"] = "your-api-key-here"

# Edit image with BFL-specific parameters
response = litellm.image_edit(
    model="black_forest_labs/flux-kontext-pro",
    image=open("path/to/your/image.png", "rb"),
    prompt="Transform into cyberpunk style with neon lights",
    seed=42,                    # For reproducible results
    output_format="png",        # png or jpeg
    safety_tolerance=2,         # 0-6, higher = more permissive
    aspect_ratio="16:9",        # Output aspect ratio
)

print(response.data[0].url)

Usage - LiteLLM Proxy Server

1. Configure your config.yaml

model_list:
  - model_name: bfl-kontext-pro
    litellm_params:
      model: black_forest_labs/flux-kontext-pro
      api_key: os.environ/BFL_API_KEY
    model_info:
      mode: image_edit

  - model_name: bfl-kontext-max
    litellm_params:
      model: black_forest_labs/flux-kontext-max
      api_key: os.environ/BFL_API_KEY
    model_info:
      mode: image_edit

  - model_name: bfl-fill
    litellm_params:
      model: black_forest_labs/flux-pro-1.0-fill
      api_key: os.environ/BFL_API_KEY
    model_info:
      mode: image_edit

  - model_name: bfl-expand
    litellm_params:
      model: black_forest_labs/flux-pro-1.0-expand
      api_key: os.environ/BFL_API_KEY
    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

from openai import OpenAI

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

# Edit image with FLUX Kontext Pro
response = client.images.edit(
    model="bfl-kontext-pro",
    image=open("path/to/your/image.png", "rb"),
    prompt="Add magical sparkles and fairy dust",
)

print(response.data[0].url)

curl --location 'http://localhost:4000/v1/images/edits' \\
--header 'Authorization: Bearer sk-1234' \\
--form 'model="bfl-kontext-pro"' \\
--form 'prompt="Add a sunset in the background"' \\
--form 'image=@"path/to/your/image.png"'

Supported Parameters

OpenAI-Compatible Parameters

Black Forest Labs Specific Parameters

How It Works

Black Forest Labs uses a polling-based API:

1. Submit Request: LiteLLM sends your image and prompt to BFL
2. Get Task ID: BFL returns a task ID and polling URL
3. Poll for Result: LiteLLM automatically polls until the image is ready
4. Return Result: The generated image URL is returned

This polling is handled automatically by LiteLLM - you just call image_edit() and get the result.

Getting Started

1. Create an account at Black Forest Labs
2. Get your API key from the dashboard
3. Set your BFL_API_KEY environment variable
4. Use litellm.image_edit() with any supported model

Additional Resources

• Black Forest Labs Documentation
• FLUX Model Information