opendataloader-project/langchain-opendataloader-pdf

python package to parse pdfs with different parsers

Collection of PDF parsing libraries like AI based docling, claude, openai, gemini, meta's llama-vision, unstructured-io, and pdfminer, pymupdf, pdfplumber etc for efficient snapshot, text, table, and metadata extraction.

Visual document analysis studio powered by Docling — configure the extraction pipeline, inspect text, tables and bounding boxes in the browser, then chunk, embed and index into OpenSearch and Neo4j.

Improved file parsing for LLM’s

EdgeParse converts any digital PDF into Markdown, JSON (with bounding boxes), HTML, or plain text — deterministically, without a JVM, without a GPU, and with best-in-class accuracy on the 200-document benchmark suite included in this repository.

PDF extraction that audits its own output — and certifies any other extractor's, catching pages they silently dropped. Verify signed manifests offline: free, MIT, no account. 0.903 on opendataloader-bench, #2 of 8 engines. 7-tool MCP server.

A Docker-powered service for PDF document layout analysis. This service provides a powerful and flexible PDF analysis service. The service allows for the segmentation and classification of different parts of PDF pages, identifying the elements such as texts, titles, pictures, tables and so on.

📄🔍 Parse, extract, and analyze documents with ease 📄🔍

Retrieval of fully structured data made easy. Use LLMs or custom models. Specialized on PDFs and HTML files. Extensive support of tabular data extraction and multimodal queries.