opendataloader-project/opendataloader-pdf

PDF Parser for AI-ready data. Automate PDF accessibility. Open-source.

What it solves

OpenDataLoader PDF is a high-accuracy PDF parser designed to convert PDFs into AI-ready structured data. It addresses the common problem of losing document structure (like reading order, tables, and heading hierarchies) during parsing, which is critical for RAG (Retrieval-Augmented Generation) and LLM pipelines. Additionally, it automates the creation of Tagged PDFs to reduce the high cost and manual effort of PDF accessibility remediation for screen readers.

How it works

The tool provides two primary processing modes:

  1. Deterministic Local Mode: Uses fast Java-based processing for standard digital PDFs.
  2. Hybrid AI Mode: Routes complex pages (containing borderless tables, scanned content, or mathematical formulas) to an AI backend for higher accuracy. This mode includes built-in OCR for 80+ languages and uses a lightweight vision model (SmolVLM) for describing charts and images.

It can extract data into formats like Markdown, JSON (with bounding boxes), and HTML. For accessibility, it performs layout analysis and auto-tagging to transform untagged PDFs into Tagged PDFs.

Who it’s for

  • AI Engineers: Those building RAG pipelines who need clean, structured Markdown or JSON for chunking and source citations.
  • Accessibility Specialists: Organizations needing to automate the creation of Tagged PDFs to comply with global accessibility regulations (e.g., ADA, EAA).
  • Developers: Anyone needing to programmatically extract tables, LaTeX formulas, and structured text from complex scientific or multi-column PDFs.

Highlights

  • Benchmark Leader: Ranks #1 in overall extraction accuracy (0.907) across reading order, tables, and headings.
  • AI-Enhanced Extraction: Supports LaTeX formula extraction, AI-generated image/chart descriptions, and OCR for scanned documents.
  • Accessibility Automation: The first open-source tool to generate Tagged PDFs end-to-end, following the Well-Tagged PDF specification.
  • RAG-Ready Output: Provides structured Markdown and JSON with bounding boxes for every element to enable precise source citations.
  • AI Safety: Includes built-in filters to protect against prompt injection attacks hidden in PDF layers.
  • Multi-Language SDKs: Available as Python, Node.js, and Java SDKs with LangChain integration.

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