GLM-OCR Table Recognition Skill / GLM-OCR 表格识别技能

When to Use / 使用场景

• Extract tables from images or scanned documents / 从图片或扫描件中提取表格
• Convert table images to Markdown or Excel format / 将表格图片转为 Markdown 或可编辑格式
• Recognize complex tables with merged cells / 识别含合并单元格的复杂表格
• Parse financial statements, invoices, reports with tables / 解析财务报表、发票、带表格的报告
• User mentions "extract table", "recognize table", "表格识别", "提取表格", "表格OCR", "表格转文字"

Key Features / 核心特性

• Complex table support: Handles merged cells, nested tables, multi-row headers
• Markdown output: Tables are output in clean Markdown format, easy to edit and convert
• Multi-page PDF: Supports batch extraction from multi-page PDF documents
• 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）

ZHIPU_API_KEY

ZHIPU_API_KEY

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": {
         "ZHIPU_API_KEY": "你的密钥"
       }
     }
   }

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

   openclaw.json

   :
   json

   {
     "skills": {
       "entries": {
         "glmocr-table": {
           "env": {
             "ZHIPU_API_KEY": "你的密钥"
           }
         }
       }
     }
   }

3. Shell environment variable / Shell 环境变量： Add to

   ~/.zshrc

   :
   bash

   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。

Security & Transparency / 安全与透明度

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

  • ZHIPU_API_KEY

    (required / 必需)

  • GLM_OCR_TIMEOUT

    (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： this 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.

1. ONLY use GLM-OCR API — Execute the script

   python scripts/glm_ocr_cli.py

2. NEVER parse tables yourself — Do NOT try to extract tables using built-in vision or any other method
3. NEVER offer alternatives — Do NOT suggest "I can try to recognize it" or similar
4. IF API fails — Display the error message and STOP immediately
5. NO fallback methods — Do NOT attempt table extraction any other way

📋 Output Display Rules / 输出展示规则

• Show extracted table Markdown (

  text

  ) in full
• Summarization is allowed, but do not hide important extraction failures
• If

  layout_details

  contains table-related entries, you may highlight them
• 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

Extract from URL / 从 URL 提取

python scripts/glm_ocr_cli.py --file-url "https://example.com/table.png"

Extract from Local File / 从本地文件提取

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

Save Result to File / 保存结果到文件

python scripts/glm_ocr_cli.py --file table.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 table.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]

--file-url

--file

--output

-o

--pretty

--include-raw

result

Response Format / 响应格式

{
  "ok": true,
  "text": "| Column 1 | Column 2 |\n|----------|----------|\n| Data     | Data     |",
  "layout_details": [...],
  "result": null,
  "error": null,
  "source": "/path/to/file",
  "source_type": "file",
  "raw_result_included": false
}

• ok

  — whether extraction 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

ZHIPU_API_KEY not configured. Get your API key at: https://bigmodel.cn/usercenter/proj-mgmt/apikeys