- name
- opendataloader-pdf
- description
- Use when parsing PDFs for RAG pipelines, extracting structured data from PDFs, or converting PDFs to Markdown/JSON with bounding boxes for AI processing
- attribution
- Based on OpenDataLoader PDF (https://github.com/opendataloader-project/opendataloader-pdf), licensed under Apache 2.0
This skill is based on OpenDataLoader PDF, licensed under Apache License 2.0.
OpenDataLoader PDF
PDF parser for AI-ready data extraction. Open-source. #1 in benchmarks (0.90 overall accuracy).
Prerequisites
- Java 11+ required (run
java -version to verify) - Python 3.10+ or Node.js 18+
Installation
# Python
pip install -U opendataloader-pdf
# Python with hybrid AI mode (for complex documents)
pip install -U "opendataloader-pdf[hybrid]"
# Node.js
npm install @opendataloader/pdf
Quick Start
Python
import opendataloader_pdf
opendataloader_pdf.convert(
input_path=["file1.pdf", "file2.pdf", "folder/"],
output_dir="output/",
format="markdown,json" # Output formats: markdown, json, html
)
Node.js
import { convert } from '@opendataloader/pdf';
await convert(['file1.pdf', 'file2.pdf'], {
outputDir: 'output/',
format: 'markdown,json'
});
CLI
# Fast local mode (0.05s/page)
opendataloader-pdf file1.pdf file2.pdf -o output/
# With hybrid AI mode (higher accuracy for complex docs)
opendataloader-pdf --hybrid docling-fast file1.pdf
Mode Selection
| Document Type | Mode | Command |
|---|
| Standard digital PDF | Fast (default) | pip install opendataloader-pdf |
| Complex tables | Hybrid | pip install "opendataloader-pdf[hybrid]" + start server |
| Scanned PDFs | Hybrid + OCR | opendataloader-pdf-hybrid --force-ocr |
| Multi-language scanned | Hybrid + OCR | --ocr-lang "zh,en" |
| Mathematical formulas | Hybrid + formula | --enrich-formula |
| Charts needing description | Hybrid + picture | --enrich-picture-description |
Benchmark Comparison
| Engine | Overall | Table | Speed (s/page) |
|---|
| opendataloader [hybrid] | 0.90 | 0.93 | 0.43 |
| opendataloader (local) | 0.72 | 0.49 | 0.05 |
| docling | 0.86 | 0.89 | 0.73 |
| marker | 0.83 | 0.81 | 53.93 |
| pymupdf4llm | 0.57 | 0.40 | 0.09 |
Key Features
- Bounding boxes for every element (for source citations in RAG)
- XY-Cut++ reading order for multi-column layouts
- 100% local - no data sent to cloud
- AI safety filters - prompt injection protection
- Table extraction - borderless tables via hybrid mode
- OCR - 80+ languages via hybrid mode
- Formula extraction - LaTeX output
LangChain Integration
pip install langchain-opendataloader-pdf
from langchain_opendataloader_pdf import OpenDataLoaderPDF
loader = OpenDataLoaderPDF(file_path="document.pdf")
docs = loader.load()
Output Formats
- markdown: Structured text with heading hierarchy
- json: Element-level with bounding boxes, page numbers, types
- html: Rich formatted output
JSON output includes:
type: paragraph, heading, table, image, etc.content: text contentbbox: [left, bottom, right, top] in PDF pointspage: page numberheading_level: for headings
Common Issues
| Issue | Solution |
|---|
| "java not found" | Install JDK 11+ from adoptium.net |
| Slow repeated calls | Batch files in single call; each spawns JVM |
| Poor table accuracy | Use hybrid mode (--hybrid docling-fast) |
| Scanned PDF not extracted | Use hybrid mode with --force-ocr |
| Non-English OCR not work | Specify --ocr-lang "zh,en" |
Resources
