A zero-dependency Python skill for analyzing images and answering visual questions using iFlytek's Spark Vision model.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ifly-image-understanding
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 ifly-image-understanding 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 iFlytek Image Understanding?
iFlytek Image Understanding is a high-performance tool designed to integrate computer vision into your automation workflows. By leveraging the Spark Vision model, this skill allows users to describe images, identify objects, and perform sophisticated OCR tasks through a simple CLI interface. As part of the Openclaw Skills library, it stands out by using the Python standard library for WebSocket communication, meaning it requires no external pip dependencies and maintains a minimal footprint.
This skill supports both the advanced imagev3 domain for high-accuracy analysis and a general domain for cost-effective, fixed-token processing. Whether you are building an AI agent that needs to 'see' or a researcher automating document analysis, this skill provides a robust bridge to iFlytek's powerful vision infrastructure.
iFlytek Image Understanding Use Cases
- Automated OCR for receipts and invoices to extract financial data.
- Object and scene identification for media tagging and organization.
- Visual question answering to interpret data trends within charts and graphs.
- Content moderation and sensitive information screening for uploaded imagery.
- Enhancing accessibility by providing detailed text descriptions for visual content.
How iFlytek Image Understanding Works
- The user triggers the script by providing a local image file path and an optional natural language question.
- The skill authenticates with iFlytek services using an HMAC-SHA256 signed WebSocket URL constructed from your API credentials.
- The image data is transmitted over a secure WebSocket connection using Python's built-in socket and ssl modules.
- The Spark Vision model processes the image and the text prompt to generate a contextual response.
- The result is streamed back to the terminal or provided as raw JSON for downstream processing within Openclaw Skills pipelines.
iFlytek Image Understanding Setup
To get started, first create an application at the iFlytek console and enable the Image Understanding service. Then, configure your environment by setting the following variables:
export IFLY_APP_ID="your_app_id"
export IFLY_API_KEY="your_api_key"
export IFLY_API_SECRET="your_api_secret"
You can then run the skill using the provided Python script:
python3 scripts/image_understanding.py your_image.jpg -q "What is in this image?"
iFlytek Image Understanding Data Schema & Taxonomy
The skill manages data through direct API interaction and local file handling. Below are the primary specifications for data processing:
| Feature | Specification |
|---|---|
| Supported Formats | .jpg, .jpeg, .png |
| File Size Limit | Maximum 4MB per image |
| Context Window | Up to 8192 combined tokens (input + output) |
| Model Domains | imagev3 (Dynamic) or general (Fixed 273 tokens) |
| Output Type | Plain text description or raw WebSocket JSON frames |
iFlytek Image Understanding Advanced Features
- Zero-dependency architecture utilizing only Python standard library for maximum portability across Openclaw Skills environments.
- Support for multiple model domains allowing developers to balance between high-precision vision and token-cost efficiency.
- Raw mode capability to output full WebSocket JSON frames for deep debugging and custom data parsing.
- Configurable sampling temperature and max-token parameters to fine-tune the creativity and length of the model's responses.
SKILL.md
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