An AI-driven skill for fashion model replacement and background scene swapping that preserves original garments.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install aimodel-openapi-skill
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install aimodel-openapi-skill 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 WeShop AI Model - Fashion & Apparel Generator?
This skill integrates the WeShop OpenAPI into your agent workflow, allowing for sophisticated image manipulation specialized for the fashion industry. By leveraging Openclaw Skills, developers can programmatically swap human models, change background locations, and adjust scene styles while maintaining the integrity of the original apparel. It provides a robust solution for e-commerce platforms looking to automate high-quality product photography without the need for expensive physical reshoots.
The skill handles complex tasks like apparel segmentation and scene composition, ensuring that the focus remains on the garment while the surrounding elements are realistically transformed. It is designed to work seamlessly within an AI agent ecosystem, providing a high degree of control over the creative output through specific parameters and preset IDs.
WeShop AI Model - Fashion & Apparel Generator Use Cases
- Replacing existing fashion models with different ethnicities or styles to tailor content for global markets.
- Swapping basic studio backgrounds for outdoor, lifestyle, or high-end interior scenes to enhance product appeal.
- Automating batch generation of apparel photos with various poses and locations for catalog updates.
- Generating high-fidelity fashion imagery from simple product shots for social media and digital marketing materials.
How WeShop AI Model - Fashion & Apparel Generator Works
- The user provides a source image URL and configures generation parameters such as mask type, target model, and scene style.
- The skill initiates a run request via the WeShop OpenAPI agent endpoints using the configured API key.
- The system performs automatic segmentation on the apparel (upper, lower, or full-body) to protect the garment during the generation process.
- The agent polls the execution status via the polling endpoint until the process reaches a success or terminal state.
- The final generated images are retrieved from the response payload and presented to the user or application.
WeShop AI Model - Fashion & Apparel Generator Setup
To use this skill, you must first obtain an API key from the official WeShop developer portal. Follow these steps to configure your environment:
- Visit https://open.weshop.ai/authorization/apikey to generate your key.
- Set the environment variable for your Openclaw Skills environment:
export WESHOP_API_KEY="your_api_key_here"
- Ensure your network environment has HTTPS access to the
openapi.weshop.aidomain. Note that the API key should never be sent to any other domain.
WeShop AI Model - Fashion & Apparel Generator Data Schema & Taxonomy
The skill utilizes a structured JSON schema for inputs and tracking. Data is organized as follows:
| Data Type | Description |
|---|---|
| Input Schema | Contains originalImage (URL), generatedContent mode, and maskType. |
| Run Parameters | Includes locationId, fashionModelId, textDescription, and pose controls. |
| Status Metadata | Tracks execution through states: Pending, Segmenting, Running, Success, Failed. |
| Result Payload | An array of generated image objects containing high-resolution URLs. |
All metadata and preset IDs can be retrieved by calling the agent information endpoint to list available models and locations.
WeShop AI Model - Fashion & Apparel Generator Advanced Features
- Automatic apparel segmentation (autoApparelSegment) for precise garment preservation without manual masking.
- Granular pose control allowing users to maintain the original pose, adopt a reference pose, or let the AI decide.
- Support for custom PNG mask URLs for professional-grade control over protected image regions.
- High-volume batch generation supporting up to 16 unique variations in a single API execution.
- Seamless integration with Openclaw Skills for multi-agent creative workflows and automation.
SKILL.md
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