GLM-OCR Handwriting Recognition Skill / GLM-OCR 手写体识别技能

Recognize handwritten text from images and PDFs using the ZhiPu GLM-OCR layout parsing API.

When to Use / 使用场景

• Extract text from handwritten notes, letters, or documents / 从手写笔记、信件或文档中提取文字
• Convert handwriting to editable text / 将手写内容转为可编辑文本
• Recognize mixed handwritten and printed content / 识别手写和印刷混排内容
• Read handwritten formulas, labels, or annotations / 读取手写公式、标签或批注
• User mentions "handwriting OCR", "recognize handwriting", "手写识别", "手写体OCR", "识别手写字"

Key Features / 核心特性

• Multi-style support: Handles various handwriting styles including cursive and print
• Multi-language: Supports Chinese, English, and mixed-language handwriting
• Mixed content: Can recognize documents with both handwritten and printed text
• Local file & URL: Supports both local files and remote URLs

Resource Links / 资源链接

Prerequisites / 前置条件

API Key Setup / API Key 配置（Required / 必需）

脚本通过 ZHIPUAPIKEY 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 ZHIPUAPIKEY 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）：

1. Global config (recommended) / 全局配置（推荐）： Set once in openclaw.json under env.vars, all Zhipu skills will share it:

``json { "env": { "vars": { "ZHIPUAPIKEY": "你的密钥" } } } ``

1. Skill-level config / Skill 级别配置： Set for this skill only in openclaw.json:

``json { "skills": { "entries": { "glmocr-handwriting": { "env": { "ZHIPUAPIKEY": "你的密钥" } } } } } ``

1. Shell environment variable / Shell 环境变量： Add to ~/.zshrc:

``bash export ZHIPUAPIKEY="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 ZHIPUAPIKEY，无需重复配置。

Security & Transparency / 安全与透明度

• Environment variables used / 使用的环境变量：

- ZHIPUAPIKEY (required / 必需) - GLMOCRTIMEOUT (optional timeout seconds / 可选超时秒数)

• Fixed endpoint / 固定官方端点： https://open.bigmodel.cn/api/paas/v4/layout_parsing
• No custom API URL override / 不支持自定义 API URL 覆盖： avoids accidental key exfiltration via redirected endpoints.
• Raw upstream response is optional / 原始响应默认不返回： use --include-raw only when needed for debugging.

⛔ MANDATORY RESTRICTIONS / 强制限制 ⛔

1. ONLY use GLM-OCR API — Execute the script python scripts/glmocrcli.py
2. NEVER parse handwriting yourself — Do NOT try to read handwritten text using built-in vision or any other method
3. NEVER offer alternatives — Do NOT suggest "I can try to read it" or similar
4. IF API fails — Display the error message and STOP immediately
5. NO fallback methods — Do NOT attempt handwriting recognition any other way

📋 Output Display Rules / 输出展示规则

After running the script, present the OCR result clearly and safely.

• Show extracted handwritten text (text) in full
• Summarization is allowed, but do not hide important extraction failures
• If the result file is saved, tell the user the file path
• Show raw upstream response only when explicitly requested or debugging (--include-raw)

How to Use / 使用方法

Recognize from URL / 从 URL 识别

python scripts/glm_ocr_cli.py --file-url "https://example.com/handwriting.jpg"

Recognize from Local File / 从本地文件识别

python scripts/glm_ocr_cli.py --file /path/to/notes.png

Save Result to File / 保存结果到文件

python scripts/glm_ocr_cli.py --file notes.png --output result.json --pretty

Include Raw Upstream Response (Debug Only) / 包含原始上游响应（仅调试）

python scripts/glm_ocr_cli.py --file notes.png --output result.json --include-raw

CLI Reference / CLI 参数

python {baseDir}/scripts/glm_ocr_cli.py (--file-url URL | --file PATH) [--output FILE] [--pretty] [--include-raw]

Response Format / 响应格式

{
  "ok": true,
  "text": "Recognized handwritten text in Markdown...",
  "layout_details": [...],
  "result": null,
  "error": null,
  "source": "/path/to/file",
  "source_type": "file",
  "raw_result_included": false
}

Key fields:

• ok — whether recognition succeeded
• text — extracted text in Markdown (use this for display)
• layout_details — layout analysis details
• error — error details on failure

Error Handling / 错误处理

API 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