bfl-api

black-forest-labs/skills · updated May 22, 2026

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$npx skills add https://github.com/black-forest-labs/skills --skill bfl-api
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summary

Use this skill when integrating BFL FLUX APIs into applications for image generation, editing, and processing.

skill.md

BFL API Integration Guide

Use this skill when integrating BFL FLUX APIs into applications for image generation, editing, and processing.

First: Check API Key

Before generating images, verify your API key is set:

echo $BFL_API_KEY

If empty or you see "Not authenticated" errors, see API Key Setup below.

Important: Image URLs Expire in 10 Minutes

Result URLs from the API are temporary. Download images immediately after generation completes - do not store or cache the URLs themselves.

When to Use

  • Setting up BFL API client
  • Implementing async polling patterns
  • Handling rate limits and errors
  • Configuring webhooks for production
  • Selecting regional endpoints
  • Building production-ready integrations

Quick Reference

Base Endpoints

Region Endpoint Use Case
Global https://api.bfl.ai Default, automatic failover
EU https://api.eu.bfl.ai GDPR compliance
US https://api.us.bfl.ai US data residency

Model Endpoints & Pricing

Credit pricing: 1 credit = $0.01 USD. FLUX.2 uses megapixel-based pricing (cost scales with resolution).

FLUX.2 Models

Model Path 1st MP +MP 1MP T2I 1MP I2I Best For
FLUX.2 [klein] 4B /v1/flux-2-klein-4b 1.4c 0.1c $0.014 $0.015 Real-time, high volume
FLUX.2 [klein] 9B /v1/flux-2-klein-9b 1.5c 0.2c $0.015 $0.017 Balanced quality/speed
FLUX.2 [pro] /v1/flux-2-pro 3c 1.5c $0.03 $0.045 Production, fast turnaround
FLUX.2 [max] /v1/flux-2-max 7c 3c $0.07 $0.10 Maximum quality
FLUX.2 [flex] /v1/flux-2-flex 5c 5c $0.05 $0.10 Typography, adjustable controls
FLUX.2 [dev] - - - Free Free Local development (non-commercial)

Pricing formula: (firstMP + (outputMP-1) * mpPrice) + (inputMP * mpPrice) in cents

FLUX.1 Models

Model Path Price/Image Best For
FLUX.1 Kontext [pro] /v1/flux-kontext $0.04 Image editing with context
FLUX.1 Kontext [max] /v1/flux-kontext-max $0.08 Max quality editing
FLUX1.1 [pro] /v1/flux-pro-1.1 $0.04 Standard T2I, fast & reliable
FLUX1.1 [pro] Ultra /v1/flux-pro-1.1-ultra $0.06 Ultra high-resolution
FLUX1.1 [pro] Raw /v1/flux-pro-1.1-raw $0.06 Candid photography feel
FLUX.1 Fill [pro] /v1/flux-pro-1.0-fill $0.05 Inpainting

Tip: All FLUX.2 models support image editing via the input_image parameter - no separate editing endpoint needed. Use bfl.ai/pricing calculator for exact costs at different resolutions.

Image Input for Editing

Preferred: Use URLs directly - simpler and more convenient than base64.

Single image editing:

curl -X POST "https://api.bfl.ai/v1/flux-2-pro" \
  -H "x-key: $BFL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Change the background to a sunset",
    "input_image": "https://example.com/photo.jpg"
  }'

Multi-reference editing:

curl -X POST "https://api.bfl.ai/v1/flux-2-pro" \
  -H "x-key: $BFL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "The person from image 1 in the environment from image 2",
    "input_image": "https://example.com/person.jpg",
    "input_image_2": "https://example.com/background.jpg"
  }'

The API fetches URLs automatically. Both URL and base64 work, but URLs are recommended when available.

Multi-Reference I2I

FLUX.2 models support multiple input images for combining elements, style transfer, and character consistency:

Model Max References
FLUX.2 [klein] 4 images
FLUX.2 [pro/max/flex] 8 images

Parameters: input_image, input_image_2, input_image_3, ... input_image_8

Prompt pattern: Reference images by number in your prompt:

  • "The subject from image 1 in the environment from image 2"
  • "Apply the style of image 2 to the scene in image 1"
  • "The person from image 1 wearing the outfit from image 2, in the pose from image 3"

For detailed multi-reference patterns (character consistency, style transfer, pose guidance), see flux-best-practices/rules/multi-reference-editing.md

Rate Limits

Tier Concurrent Requests
Standard (most endpoints) 24

Polling vs Webhooks

Approach Use When
Polling Scripts, CLI tools, local development, single requests, simple integrations
Webhooks Production apps, high volume, server-to-server, when you need immediate notification

Start with polling - it's simpler and works everywhere. Switch to webhooks when you need to scale or want event-driven architecture.

Key Behaviors

  • Polling: Response includes polling_url for async results
  • URL Expiration: Result URLs expire after 10 minutes
  • Webhook Support: Configure webhook_url for production workloads

API Key Setup

Required: The BFL_API_KEY environment variable must be set before using the API.

Quick Check

echo $BFL_API_KEY

If Not Set

  1. Get a key: Go to https://dashboard.bfl.ai/get-started → Click "Create Key" → Select organization
  2. Save to .env (recommended for persistence):
    echo 'BFL_API_KEY=bfl_your_key_here' >> .env
    echo '.env' >> .gitignore  # Don't commit secrets
    

See references/api-key-setup.md for detailed setup instructions.

Authentication

x-key: YOUR_API_KEY

Basic Request Flow

1. POST request to model endpoint
   └─> Response: { "polling_url": "..." }

2. GET polling_url (repeat until complete)
   └─> Response: { "status": "Pending" | "Ready" | "Error", ... }

3. When Ready, download result URL
   └─> URL expires in 10 minutes - download immediately

Related

  • Prompting best practices (T2I, I2I, typography, colors): see the flux-best-practices skill
  • Multi-reference patterns (character consistency, style transfer, pose guidance): see flux-best-practices/rules/multi-reference-editing.md

References

Code Examples

Note: cURL examples are preferred by default as they work universally without requiring Python or Node.js. Use language-specific clients when building production applications.

Quick Start Example

1. Submit Generation Request

curl -s -X POST "https://api.bfl.ai/v1/flux-2-pro" \
  -H "x-key: $BFL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt": "A serene mountain landscape at sunset", "width": 1024, "height": 1024}'

Response:

{ "id": "abc123", "polling_url": "https://api.bfl.ai/v1/get_result?id=abc123" }

2. Poll for Result

curl -s "POLLING_URL" -H "x-key: $BFL_API_KEY"

Response when ready:

{ "status": "Ready", "result": { "sample": "https://...", "seed": 1234 } }

3. Download Image

curl -s -o output.png "IMAGE_URL"

Tip: Result URLs expire in 10 minutes. Download immediately after status becomes Ready.

4. Multi-Reference Example

Combine elements from multiple images:

curl -s -X POST "https://api.bfl.ai/v1/flux-2-pro" \
  -H "x-key: $BFL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "The cat from image 1 sitting in the cozy room from image 2",
    "input_image": "https://example.com/cat.jpg",
    "input_image_2": "https://example.com/room.jpg",
    "width": 1024,
    "height": 1024
  }'

Reference images by number in your prompt. See Multi-Reference I2I for limits and patterns.

how to use bfl-api

How to use bfl-api on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add bfl-api
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/black-forest-labs/skills --skill bfl-api

The skills CLI fetches bfl-api from GitHub repository black-forest-labs/skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/bfl-api

Reload or restart Cursor to activate bfl-api. Access the skill through slash commands (e.g., /bfl-api) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.630 reviews
  • Benjamin Jackson· Dec 28, 2024

    We added bfl-api from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Evelyn Sanchez· Dec 16, 2024

    bfl-api has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Shikha Mishra· Dec 12, 2024

    bfl-api is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Meera Desai· Nov 7, 2024

    Solid pick for teams standardizing on skills: bfl-api is focused, and the summary matches what you get after install.

  • Rahul Santra· Nov 3, 2024

    bfl-api fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Yuki Tandon· Oct 26, 2024

    bfl-api is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Pratham Ware· Oct 22, 2024

    bfl-api has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Mateo Johnson· Sep 25, 2024

    We added bfl-api from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Luis Nasser· Sep 17, 2024

    Keeps context tight: bfl-api is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Sofia Ramirez· Sep 1, 2024

    I recommend bfl-api for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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