OpenDataLoader PDF

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name: opendataloader-pdf description: OpenDataLoader PDF — AI-ready PDF parser. Parse PDFs into Markdown/JSON/HTML for RAG pipelines, extract tables with bounding boxes, OCR scanned PDFs, and enrich charts/formulas with AI descriptions. Use when: (1) parsing PDFs for knowledge bases or RAG systems; (2) extracting structured data from medical reports, academic papers, invoices; (3) building AI knowledge bases from PDF documents; (4) converting PDF documents to Markdown/JSON for further processing; (5) any PDF-to-LLM data extraction task.

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OpenDataLoader PDF Skill

Quick Install

# Basic (CPU, ~20 pages/sec)
pip install -U opendataloader-pdf
Hybrid mode (AI-enhanced, for complex docs, ~2 pages/sec)
pip install -U "opendataloader-pdf[hybrid]"
LangChain integration
pip install langchain-opendataloader-pdf

Requirements: Java 11+ (for hybrid mode), Python 3.10+

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Core Usage Patterns

1. Parse PDF → Markdown (best for RAG chunking)

from opendataloader_pdf import convert
convert(
    input_path=["file1.pdf", "folder/"],
    output_dir="output/",
    format="markdown"  # clean text, LLM-ready
)

2. Parse PDF → JSON (with bounding boxes for citations)

convert(
    input_path=["report.pdf"],
    output_dir="output/",
    format="json",           # structured data + coordinates
    image_output="embedded"  # "off" | "embedded" | "external"
)

3. LangChain + RAG Pipeline

from langchain_opendataloader_pdf import OpenDataLoaderPDFLoader
from langchain.text_splitter import RecursiveCharacterTextSplitter
loader = OpenDataLoaderPDFLoader(file_path="document.pdf", format="text")
docs = loader.load()
splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)
chunks = splitter.split_documents(docs)
→ embed → vector store → RAG

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CLI Commands

# Basic: single file or folder
opendataloader-pdf file1.pdf file2.pdf folder/
Complex tables / nested structure (hybrid mode)
opendataloader-pdf --hybrid docling-fast file1.pdf
Start hybrid backend first, then:
opendataloader-pdf-hybrid --port 5002
(in another terminal)
opendataloader-pdf --hybrid docling-fast file1.pdf
OCR for scanned PDFs
opendataloader-pdf-hybrid --port 5002 --force-ocr file1.pdf
Math formula extraction (LaTeX)
opendataloader-pdf-hybrid --enrich-formula
opendataloader-pdf --hybrid docling-fast --hybrid-mode full file1.pdf
Chart/image AI description
opendataloader-pdf-hybrid --enrich-picture-description
opendataloader-pdf --hybrid docling-fast --hybrid-mode full file1.pdf
Security: sanitize prompt injection
opendataloader-pdf file1.pdf --sanitize

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Output Format Selection Guide

| Document Type | Recommended Format | Mode | |--------------|-------------------|------| | Standard digital PDF | markdown | Basic | | Complex/nested tables | json | Hybrid | | Scanned PDFs | any + --force-ocr | Hybrid | | Math formulas | markdown + --enrich-formula | Hybrid | | Charts needing description | markdown + --enrich-picture-description | Hybrid | | Medical reports (cite-able) | json | Hybrid | | RAG knowledge base | markdown | Basic or Hybrid |

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Key Reference Files

API Reference — Full Python API, all parameters

CLI Reference — All CLI flags and hybrid mode

Examples — RAG pipeline, table extraction, batch processing

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Benchmark Results (v2.0)

| Metric | Score | |--------|-------| | Overall Accuracy | 0.90 | | Reading Order | 0.94 | | Table Accuracy | 0.93 | | Heading Accuracy | 0.83 |

License: Apache 2.0 | GitHub: opendataloader-project/opendataloader-pdf