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FLUX-fill Standalone

This workflow is designed to automate image editing. Users can upload images and draw masks through a web editor. After entering text prompts, the system will call AI services for intelligent filling and restoration. The entire process automatically detects task status and quickly returns high-quality processed images, greatly simplifying the complexity of traditional image editing and improving efficiency. It is suitable for various scenarios such as e-commerce, graphic design, and content creation.

Workflow Diagram
FLUX-fill Standalone Workflow diagram

Workflow Name

FLUX-fill Standalone

Key Features and Highlights

This workflow automates image editing based on the FLUX AI fill service. Users can upload or select images via a web editor, use brush tools to draw masks, and input text prompts to trigger FLUX AI’s intelligent filling and repair of specified areas. The process automatically monitors task completion status and promptly returns the generated edited images, achieving seamless integration from editing and AI processing to result delivery. It incorporates front-end interactive components such as the Konva.js canvas and image comparison sliders to enhance user experience.

Core Problems Addressed

Traditional image editing for intelligent filling and repair of specific regions often requires professional software and complex operations. This workflow simplifies the editing process by automating calls to a remote AI fill API, saving users time and lowering technical barriers, enabling fast, high-quality local image repair and creative filling.

Application Scenarios

  • Partial retouching of e-commerce product images, such as defect removal and background replacement
  • Rapid replacement or filling of image areas in graphic design
  • Intelligent editing and enhancement of materials by content creators
  • Any scenario requiring AI-assisted local intelligent image filling

Main Process Steps

  1. The user triggers the workflow via a webhook, entering the image editing web page (Editor page).
  2. The page offers multiple default sample images and local upload options; the user selects or uploads an image.
  3. The user draws mask areas on the Konva.js canvas and inputs text prompts along with parameters (e.g., steps, guidance strength).
  4. The workflow calls the FLUX Fill API, submitting the original image, mask, and parameters to initiate the AI fill task.
  5. The workflow polls the API to monitor task status until completion.
  6. Upon completion, the generated filled image URL is retrieved.
  7. The generated image is returned to the user in binary form; the page displays the edited result with save support.
  8. The user can compare results and reuse them as needed.

Involved Systems or Services

  • n8n automation platform (webhook, conditional logic, wait nodes, etc.)
  • FLUX AI Fill Service API (https://api.bfl.ml)
  • Front-end technologies: Konva.js canvas drawing, img-comparison-slider for image comparison
  • HTTP request and response nodes for data interaction and file transfer

Target Users and Value

  • Designers and content creators seeking to improve image editing efficiency and quickly achieve complex local replacements and repairs
  • E-commerce operators aiming to streamline product image optimization workflows
  • Automation workflow developers integrating intelligent image processing modules into larger systems
  • Any users needing fast, AI-powered local image filling and editing, reducing the need for specialized skills and boosting productivity

By combining flexible front-end interactions with powerful AI image filling capabilities, this workflow perfectly integrates automation and intelligent processing, significantly enhancing the image editing experience and efficiency. Users can achieve high-quality AI-powered intelligent repair results with minimal effort, suitable for a wide range of creative and commercial applications.