A powerful text-to-image skill for AI agents using ModelScope API to generate professional visuals with LoRA fine-tuning.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install modelscope-img
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 modelscope-img 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 ModelScope AI Image Generation?
ModelScope AI Image Generation is a specialized skill designed for AI agents to create high-quality visual content. It leverages the ModelScope platform to provide access to leading image generation models like Tongyi Z-Image and Qwen-Image. This Openclaw Skills integration allows developers and users to generate images directly through natural language triggers or command-line scripts.
The skill is built for flexibility, offering deep customization for artistic output. By supporting LoRA (Low-Rank Adaptation) fine-tuning, it enables precise control over style and aesthetics, making it an essential tool for creators using Openclaw Skills in their automated workflows.
ModelScope AI Image Generation Use Cases
- Automated graphic generation for marketing materials and social media posts.
- Creative prototyping and concept art generation during the design phase.
- Integrating AI-driven image creation into chat-based workflows and developer productivity tools.
- Generating stylized images using custom LoRA models for consistent brand aesthetics.
How ModelScope AI Image Generation Works
- The AI agent receives a prompt or trigger related to image generation.
- The system checks for the required ModelScope API key in environment variables or configuration files.
- The skill processes the prompt, selecting the specified model (e.g., Qwen-Image or Tongyi Z-Image) and any provided LoRA weights.
- A request is sent to the ModelScope API to generate the image based on the text description.
- The generated image is saved to the local file system at the designated output path.
ModelScope AI Image Generation Setup
Install the necessary Python dependencies and configure your API key to start using these Openclaw Skills:
pip install requests pillow
Set your API key using one of the following methods:
# Method 1: Environment Variable
set MODELSCOPE_API_KEY=your_actual_key
# Method 2: Save to configuration via script
python scripts/generate_tongyi.py --save-key your_actual_key
ModelScope AI Image Generation Data Schema & Taxonomy
The skill uses a structured command-line interface to manage inputs and outputs. You can specify parameters as follows:
| Argument | Description | Default |
|---|---|---|
| -p, --prompt | Text description for image generation | Required |
| -m, --model | Model identifier (e.g., Tongyi-MAI/Z-Image) | Tongyi-MAI/Z-Image |
| -o, --output | Destination path for the result file | result_image.jpg |
| -l, --lora | Repository ID for a single LoRA model | None |
| --lora-weight | Weight for the single LoRA model | 1.0 |
| --lora-json | Configuration for multiple LoRA models in JSON format | None |
ModelScope AI Image Generation Advanced Features
- Support for multiple concurrent LoRA models with custom weight distribution via JSON configuration.
- Automatic API key resolution prioritizing CLI arguments, then environment variables, then local configuration files.
- Seamless switching between high-performance models including Qwen-Image-2512 and Z-Image for different aesthetic needs.
- Built-in support for multiple languages in prompts, including Chinese and English, for global Openclaw Skills applications.
SKILL.md
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