run-llama--liteparse/ocr/paddleocr/README.md

PaddleOCR Service

This is a simple Flask server that wraps PaddleOCR to conform to the LiteParse OCR API specification (see ../../OCR_API_SPEC.md).

PaddleOCR is especially fast and accurate for Chinese, Japanese, and Korean languages.

Build and Run

# install and run (in one command)
uv run server.py

Usage

The service exposes a single endpoint:

• POST /ocr - Perform OCR on an uploaded image

Parameters

• file - Image file (multipart/form-data)
• language - Language code (e.g., 'en', 'zh', 'ja', 'ko')

Example

curl -X POST -F "file=@image.png" -F "language=zh" http://localhost:8829/ocr

Response Format

{
  "results": [
    {
      "text": "recognized text",
      "bbox": [x1, y1, x2, y2],
      "confidence": 0.95
    }
  ]
}

This conforms to the LiteParse OCR API specification.

Supported Languages

PaddleOCR supports 80+ languages with excellent support for CJK:

• en - English
• zh / zh-cn - Chinese (Simplified)
• zh-tw / zh-hant - Chinese (Traditional)
• ja - Japanese
• ko - Korean
• fr - French
• de - German
• es - Spanish
• pt - Portuguese
• ru - Russian
• ar - Arabic
• hi - Hindi/Devanagari

Full list: https://github.com/PaddlePaddle/PaddleOCR

Performance

PaddleOCR is optimized for speed and accuracy:

• Fast: 2-3x faster than EasyOCR
• Accurate: Especially for Asian languages (Chinese, Japanese, Korean)
• Lightweight: Smaller model sizes

Use with LiteParse

Once the server is running, use it with LiteParse:

# Parse with PaddleOCR
lit parse document.pdf --ocr-server-url http://localhost:8829/ocr

# With specific language
lit parse document.pdf --ocr-server-url http://localhost:8829/ocr --ocr-language zh

Or in code:

import { LiteParse } from 'liteparse';

const parser = new LiteParse({
  ocrServerUrl: 'http://localhost:8829/ocr',
  ocrLanguage: 'zh',
});

const result = await parser.parse('document.pdf');

Testing

If you make changes to the server, make sure to adapt and run tests:

uv run pytest test_server.py

GPU Support

For GPU acceleration, set use_gpu=True in server.py.

Notes

• First request may be slow as PaddleOCR downloads models
• Models are cached after first use
• Default port is 8829 (different from EasyOCR's 8828)