Bria Visual Asset Generator for Openclaw

A sophisticated AI skill for generating, editing, and processing commercially-safe visual assets through high-performance API workflows.

galbria
v0.0.1
Feb 6, 2026
0
0
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install bria-ai-api

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install bria-ai-api using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is Bria Visual Asset Generator?

The Bria Visual Asset Generator is a comprehensive toolset designed for developers who need to integrate high-quality, commercially-safe AI imaging into their applications. Unlike many generative models, Bria is built on datasets that ensure legal safety for enterprise use, making it an essential addition to the Openclaw Skills ecosystem for professional projects.

This skill provides deep integration with Bria's advanced models, including FIBO for text-to-image generation and RMBG-2.0 for industry-leading background removal. It supports a wide array of transformations such as outpainting, upscaling, and object replacement, all accessible via structured API patterns that allow for seamless automation of visual content creation.

Bria Visual Asset Generator Use Cases

  • Creating high-resolution hero images and banners for web development and landing pages.
  • Automating e-commerce product photography pipelines, including background removal and lifestyle scene placement.
  • Generating professional-grade presentation visuals, icons, and corporate graphics.
  • Batch producing social media assets across various aspect ratios for marketing campaigns.
  • Executing precise image edits such as color modification, object insertion, or seasonal restyling.

How Bria Visual Asset Generator Works

  1. The skill sends a POST request to the Bria API containing specific instructions, such as a prompt or an image URL for editing.
  2. Bria processes the request asynchronously and immediately returns a request ID and a status tracking URL.
  3. The client application polls the status URL periodically to monitor the progress of the image generation or transformation.
  4. Once the process is marked as COMPLETED, the final high-resolution image URL is provided in the JSON result.
  5. For complex tasks, the skill can chain these steps into a pipeline, such as generating an object, removing its background, and then placing it into a new lifestyle scene.

Bria Visual Asset Generator Setup

To get started with this skill, you must obtain an API token from Bria.ai. Configure your environment by setting the API key as an environment variable:

export BRIA_API_KEY='your_api_token_here'

You can then use the skill through standard HTTP requests or by integrating the provided Python and TypeScript patterns into your Openclaw Skills workflow.

Bria Visual Asset Generator Data Schema & Taxonomy

The skill manages data through structured JSON payloads for both requests and responses.

Attribute Description
prompt The textual description of the desired image or edit.
aspect_ratio Defined dimensions such as 1:1, 16:9, 4:3, 9:16, or 3:4.
image A source URL or base64 encoded string for editing operations.
status_url The endpoint used to track the asynchronous lifecycle of the asset.
result The final object containing the image_url and metadata.

Bria Visual Asset Generator Advanced Features

  • Batch & Parallel Processing: Utilize asyncio or concurrent Promise patterns to generate dozens of images simultaneously with managed rate limiting.
  • Automated Pipelines: Chain multiple Bria endpoints to perform complex workflows like generate -> remove background -> relight in a single automated pass.
  • Deterministic Controls: Integration with VGL allows for precise, JSON-based control over visual attributes, bypassing the unpredictability of natural language.
  • Async Polling Logic: Robust handling of asynchronous responses to ensure high reliability in production environments.

SKILL.md


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