> ## Documentation Index
> Fetch the complete documentation index at: https://docs.pdf4llm.com/llms.txt
> Use this file to discover all available pages before exploring further.
# PDF4LLM
> Extract clean, structured content from any document — ready for LLMs, RAG pipelines, and AI applications.
PyMuPDF4LLM is a single pip install and one function call away.
The same powerful extraction capabilities, the same consistent output — in a native .NET library.
## Document extraction that doesn't get in your way
Your LLM is only as good as the content you feed it. Most PDF libraries hand you a wall of unstructured text and leave you to figure out the rest. PDF4LLM gives you something you can actually use — clean Markdown, structured JSON, or plain text, with reading order preserved, tables intact, and images handled — in a single function call.
Built on [MuPDF](https://mupdf.com/), it is trusted by developers building production RAG pipelines, document intelligence systems, and LLM-powered applications worldwide.
***
## Everything your pipeline needs. Nothing it doesn't.
Multi-column layouts, sidebars, and complex designs are reconstructed in the correct sequence — so your LLM reads the document the way a human would.
Detected automatically and rendered as structured Markdown. No more table data scrambled across disconnected lines.
Scanned and image-based pages are detected and processed automatically. No configuration. No manual triggers.
Per-page chunk dictionaries carry everything downstream needs — text, metadata, TOC entries, table positions, and word-level coordinates.
PyMuPDF-Layout integration brings state-of-the-art AI region detection for the most complex and demanding documents.
Native loaders for LlamaIndex and LangChain. Drop into your existing pipeline with zero glue code.
***
## Three output formats. One consistent API.
Whether you're building a RAG pipeline, a custom document intelligence system, or a data extraction workflow, PDF4LLM produces the format you need.
| Format | Best for |
| -------------- | ----------------------------------------------------------------------------------- |
| **Markdown** | LLM ingestion, RAG pipelines, and human-readable output with structure preserved |
| **JSON** | Custom pipelines that need bounding boxes, font data, and per-block layout metadata |
| **Plain Text** | Search indexing, NLP preprocessing, and tools that don't need formatting |
***
## Works with the documents you already have
PDF, XPS, EPUB, MOBI, and more — supported out of the box, no extra setup required.
Unlock DOCX, PPTX, XLSX, and more with PyMuPDF Pro. The same clean API. The same consistent output.
***
## Trusted at every scale
PDF4LLM is built for production. It handles everything from single-page invoices to thousands of pages of legal, financial, or technical documentation — with predictable performance and output quality you can rely on.
Built on MuPDF, the fastest PDF engine available — benchmarked faster than every major alternative.
AI-powered layout analysis and best-in-class table detection means fewer pipeline errors and less manual correction.
Swap OCR engines, customise layout detection, apply page margins, or tune every extraction parameter to your needs.