// Official skill for recognizing and extracting mathematical formulas from images and PDFs into LaTeX format using ZhiPu GLM-OCR API. Supports complex equations, inline formulas, and formula blocks. Use this skill when the user wants to extract formulas, convert formula images to LaTeX, or OCR mathematical expressions.
Official skill for recognizing handwritten text from images using ZhiPu GLM-OCR API. Supports various handwriting styles, languages, and mixed handwritten/printed content. Use this skill when the user wants to read handwritten notes, convert handwriting to text, or OCR handwritten documents.
Official skill for recognizing and extracting tables from images and PDFs into Markdown format using ZhiPu GLM-OCR API. Supports complex tables, merged cells, and multi-page documents. Use this skill when the user wants to extract tables, recognize spreadsheets, or convert table images to editable format.
Extract text from images using GLM-OCR API. Supports images and PDFs with high accuracy OCR, table recognition, formula extraction, and handwriting recognition. Use this skill whenever the user wants to extract text from images, perform OCR on pictures, scan documents, convert images to text, or process any image files to get their textual content.
Trigger when: (1) User wants to extract text, tables, formulas, or structured data from images/PDFs/scanned documents, (2) User mentions "OCR", "文字识别", "文档解析", (3) User has a document (screenshot, scanned page, invoice, paper, whiteboard photo) and needs its content in structured form, (4) User asks to parse, digitize, or extract content from a visual document. Invokes the GLM-OCR SDK (pip install glmocr) to parse documents via Zhipu's cloud API. No GPU required. Returns structured JSON (regions with labels + bounding boxes) and Markdown. Agent can operate entirely via CLI — no YAML files needed. NOT for: real-time camera feeds, audio transcription, or non-document images (photos, illustrations).
| name | glmocr-formula |
| description | Official skill for recognizing and extracting mathematical formulas from images and PDFs into LaTeX format using ZhiPu GLM-OCR API. Supports complex equations, inline formulas, and formula blocks. Use this skill when the user wants to extract formulas, convert formula images to LaTeX, or OCR mathematical expressions. |
| metadata | {"openclaw":{"requires":{"env":["ZHIPU_API_KEY","GLM_OCR_TIMEOUT"],"bins":["python"]},"primaryEnv":"ZHIPU_API_KEY","emoji":"📐","homepage":"https://github.com/zai-org/GLM-OCR/tree/main/skills/glmocr-formula"}} |
Recognize mathematical formulas from images and PDFs and convert them to LaTeX format using the ZhiPu GLM-OCR layout parsing API.
| Resource | Link |
|---|---|
| Get API Key | 智谱开放平台 API Keys |
| API Docs | Layout Parsing / 版面解析 |
脚本通过 ZHIPU_API_KEY 环境变量获取密钥，可与其他智谱技能复用同一个 key。
This script reads the key from the ZHIPU_API_KEY environment variable. Reusing the same key across Zhipu skills is optional.
Get Key / 获取 Key： Visit 智谱开放平台 API Keys to create or copy your key.
Setup options / 配置方式（任选一种）：
Global config (recommended) / 全局配置（推荐）： Set once in openclaw.json under env.vars, all Zhipu skills will share it:
{
"env": {
"vars": {
"ZHIPU_API_KEY": "你的密钥"
}
}
}
Skill-level config / Skill 级别配置： Set for this skill only in openclaw.json:
{
"skills": {
"entries": {
"glmocr-formula": {
"env": {
"ZHIPU_API_KEY": "你的密钥"
}
}
}
}
}
Shell environment variable / Shell 环境变量： Add to ~/.zshrc:
export ZHIPU_API_KEY="你的密钥"
💡 如果你已为其他智谱 skill（如
glmocr、glmv-caption、glm-image-generation）配置过 key，它们共享同一个ZHIPU_API_KEY，无需重复配置。
ZHIPU_API_KEY (required / 必需)GLM_OCR_TIMEOUT (optional timeout seconds / 可选超时秒数)https://open.bigmodel.cn/api/paas/v4/layout_parsing--include-raw only when needed for debugging.⛔ MANDATORY RESTRICTIONS / 强制限制 ⛔
python scripts/glm_ocr_cli.pyAfter running the script, present the OCR result clearly and safely.
text) in fulllayout_details contains formula-related entries, you may highlight them--include-raw)⚠️ LaTeX Rendering / LaTeX 渲染注意：
OCR API returns formulas in LaTeX format (e.g., $\frac{1}{2}$, $\theta^{x+1}$). Since most chat platforms do not render LaTeX, you should ask the user once (on first use):
"OCR 结果包含 LaTeX 公式，需要我将公式转为 Unicode 可读格式展示，还是保留原始 LaTeX？"
Remember the user's choice for the rest of the session. Do NOT ask again on subsequent calls unless the user explicitly changes their preference.
| LaTeX | Unicode / 纯文本 |
|---|---|
$\frac{a}{b}$ | a/b |
$x^{n}$ | x^n |
$x_{i}$ | xᵢ |
$\sqrt{x}$ | √x |
$\theta$ | θ |
$\phi$ | φ |
$\therefore$ | ∴ |
$\Rightarrow$ | ⇒ |
$\left\{ \begin{array}{l} ... \end{array} \right.$ | ⎧ line1 ⎨ line2 ⎩ |
$\textcircled{1}$ | ① |
$\in$ | ∈ |
$\infty$ | ∞ |
$\ln$ | ln |
$\leq$ / $\geq$ | ≤ / ≥ |
--output was used.python scripts/glm_ocr_cli.py --file-url "https://example.com/formula.png"
python scripts/glm_ocr_cli.py --file /path/to/equation.png
python scripts/glm_ocr_cli.py --file formula.png --output result.json --pretty
python scripts/glm_ocr_cli.py --file formula.png --output result.json --include-raw
python {baseDir}/scripts/glm_ocr_cli.py (--file-url URL | --file PATH) [--output FILE] [--pretty] [--include-raw]
| Parameter | Required | Description |
|---|---|---|
--file-url | One of | URL to image/PDF |
--file | One of | Local file path to image/PDF |
--output, -o | No | Save result JSON to file |
--pretty | No | Pretty-print JSON output |
--include-raw | No | Include raw upstream API response in result field (debug only) |
{
"ok": true,
"text": "Extracted formulas and text in Markdown/LaTeX...",
"layout_details": [...],
"result": null,
"error": null,
"source": "/path/to/file",
"source_type": "file",
"raw_result_included": false
}
Key fields:
ok — whether extraction succeededtext — extracted text in Markdown with LaTeX formulaslayout_details — layout analysis detailserror — error details on failureAPI key not configured:
ZHIPU_API_KEY not configured. Get your API key at: https://bigmodel.cn/usercenter/proj-mgmt/apikeys
→ Show exact error to user, guide them to configure
Authentication failed (401/403): API key invalid/expired → reconfigure
Rate limit (429): Quota exhausted → inform user to wait
File not found: Local file missing → check path