Skip to main content

The official Python library for the Black Forest Labs API

Project description

BFL Client - Black Forest Labs API Client

A Python client for interacting with the Black Forest Labs API.

Installation

You can install the package using either name:

pip install blackforest

Quick Start

# You can import using either name
from blackforest import BFLClient
# or
from blackforestlabs import BFLClient

import os

# For synchronous API call (great for testing, but please use "production" for async calls, for faster throughput)
os.environ["BFL_ENV"] = "dev"  

# Initialize the client
client = BFLClient(api_key="your-api-key")

# Use the client to make API calls
inputs = {
        "prompt": "a beautiful sunset over mountains, digital art style",
        "width": 1024,
        "height": 768,
        "output_format": "jpeg"
    }
response = client.generate("flux-pro-1.1", inputs)

# For Flux Kontext Pro with reference images
kontext_inputs = {
        "prompt": "A beautiful landscape in the style of the reference image",
        "input_image": "path/to/reference/image.jpg",  # File path (auto-encoded) or base64
        "input_image_2": "path/to/another/image.png",  # Optional multiref (experimental)
        "aspect_ratio": "16:9",  # Between 1:4 and 4:1
        "output_format": "png",
        "seed": 42,  # Optional for reproducibility
        "safety_tolerance": 2,  # 0-6, higher = less strict
        "prompt_upsampling": True  # Enhanced prompt processing
    }
response = client.generate("flux-kontext-pro", kontext_inputs)

Features

  • Official Python interface for Black Forest Labs API
  • Automatic request handling and response parsing
  • Type hints for better IDE support
  • Support for all Flux models including Flux Kontext Pro with multi-reference capabilities

Supported Models

  • flux-dev - Development model
  • flux-pro - Professional model
  • flux-pro-1.1 - Enhanced professional model
  • flux-pro-1.1-ultra - Ultra high-quality model
  • flux-kontext-pro - Context-aware model with reference image support and experimental multi-reference capabilities
  • flux-pro-1.0-fill - Image inpainting model
  • flux-pro-1.0-expand - Image expansion model
  • flux-pro-1.0-canny - Canny edge-guided model
  • flux-pro-1.0-depth - Depth-guided model

Requirements

  • Python 3.7+
  • requests>=2.31.0
  • pydantic>=2.0.0,
  • pillow==10.4.0,

License

This project is licensed under the Apache 2.0 License - see the LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

blackforest-0.1.3.tar.gz (18.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

blackforest-0.1.3-py3-none-any.whl (22.9 kB view details)

Uploaded Python 3

File details

Details for the file blackforest-0.1.3.tar.gz.

File metadata

  • Download URL: blackforest-0.1.3.tar.gz
  • Upload date:
  • Size: 18.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for blackforest-0.1.3.tar.gz
Algorithm Hash digest
SHA256 8e5b069690a036fda90c1f3b8b44189a873522d54852cbea5642f2bcf4df3158
MD5 7a67e651b0efe6c8e94616ddb12a7399
BLAKE2b-256 b4e5e580c9ae37bcf2d70365c452d3e6a34e5f9cf0ced4fcb63430d46530a908

See more details on using hashes here.

File details

Details for the file blackforest-0.1.3-py3-none-any.whl.

File metadata

  • Download URL: blackforest-0.1.3-py3-none-any.whl
  • Upload date:
  • Size: 22.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for blackforest-0.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 8f0fed51e305ed93711e756971bf7b85569f03714504d55e154bbb0c2cf6cfb1
MD5 fa01b4d4db742ca21929b30fca553445
BLAKE2b-256 8bca02cbaab5a7979fa39547269bbb9bf434013c68115ae633d948697514ef4d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page