Parse documents using PaddleOCR's API.
Scanned 9/7/2026
Install to Claude Code
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---
name: paddleocr-doc-parsing
description: Parse documents using PaddleOCR's API.
homepage: https://www.paddleocr.com
metadata:
{
"openclaw":
{
"emoji": "📄",
"os": ["darwin", "linux"],
"requires":
{
"bins": ["curl", "base64", "jq"],
"env": ["PADDLEOCR_API_URL", "PADDLEOCR_ACCESS_TOKEN"],
},
},
}
---
# PaddleOCR Document Parsing
Parse images and PDF files using PaddleOCR's API. Supports multiple document parsing algorithms with structured output.
## Resource Links
| Resource | Link |
| --------------------- | ------------------------------------------------------------------------------ |
| **Official Website** | [https://www.paddleocr.com](https://www.paddleocr.com) |
| **API Documentation** | [https://ai.baidu.com/ai-doc/AISTUDIO/Cmkz2m0ma](https://ai.baidu.com/ai-doc/AISTUDIO/Cmkz2m0ma) |
| **GitHub** | [https://github.com/PaddlePaddle/PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR) |
## Key Features
- **Multi-format support**: PDF and image files (JPG, PNG, BMP, TIFF)
- **Layout analysis**: Automatic detection of text blocks, tables, formulas
- **Multi-language**: Support for 110+ languages
- **Structured output**: Markdown format with preserved document structure
## Setup
1. Obtain credentials from the [PaddleOCR official website](https://www.paddleocr.com). Click the “API” button, choose the desired algorithm (e.g., PP-StructureV3, PaddleOCR-VL-1.5), and copy the API URL and the access token.
2. Set environment variables:
```bash
export PADDLEOCR_API_URL="https://your-endpoint-here"
export PADDLEOCR_ACCESS_TOKEN="your_access_token"
```
## Usage Examples
### Run Script
```bash
# Parse local image
{baseDir}/paddleocr_parse.sh document.jpg
# Parse local PDF file
{baseDir}/paddleocr_parse.sh -t pdf document.pdf
# Parse document from URL
{baseDir}/paddleocr_parse.sh -t pdf https://example.com/document.pdf
# Output to stdout (default)
{baseDir}/paddleocr_parse.sh document.jpg
# Save output to file
{baseDir}/paddleocr_parse.sh -o result.json document.jpg
```
### Response Structure
```json
{
"logId": "unique_request_id",
"errorCode": 0,
"errorMsg": "Success",
"result": {
"layoutParsingResults": [
{
"prunedResult": [...],
"markdown": {
"text": "# Document Title\n\nParagraph content...",
"images": {}
},
"outputImages": [...],
"inputImage": "http://input-image"
}
],
"dataInfo": {...}
}
}
```
**Important Fields:**
- **`prunedResult`** - Contains detailed layout element information including positions, categories, etc.
- **`markdown`** - Stores the document content converted to Markdown format with preserved structure and formatting.
## Quota Information
See official documentation: https://ai.baidu.com/ai-doc/AISTUDIO/Xmjclapam
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