llama-index-readers-oxidize-pdf 0.1.0

LlamaIndex reader for oxidize-pdf — fast, Rust-powered PDF parsing with RAG-ready chunking

llama-index-readers-oxidize-pdf

LlamaIndex reader backed by oxidize-pdf, a fast Rust-powered PDF engine with first-class RAG chunking.

Install

pip install llama-index-readers-oxidize-pdf

Usage

RAG chunks (default)

from llama_index.readers.oxidize_pdf import OxidizePdfReader

reader = OxidizePdfReader()  # mode="rag" by default
documents = reader.load_data("paper.pdf")

for doc in documents:
    print(doc.metadata["chunk_index"], doc.metadata["heading_context"])
    print(doc.text[:200])

Each Document carries:

Field	Description
chunk_index	0-based index within the document
page_numbers	list of 1-indexed pages covered by the chunk
element_types	list of semantic types detected (e.g. title, paragraph)
heading_context	nearest surrounding heading, or None
token_estimate	rough token count for budget planning
file_path / file_name / total_pages / pdf_version	source metadata

One document per page

reader = OxidizePdfReader(mode="pages")
docs = reader.load_data("paper.pdf")
for doc in docs:
    print(doc.metadata["page_number"], len(doc.text))

Whole PDF as markdown

reader = OxidizePdfReader(mode="markdown")
[doc] = reader.load_data("paper.pdf")
print(doc.text)

Why oxidize-pdf

• Rust parser: fast on large PDFs, low memory footprint.
• Native RAG primitives: semantic chunking, element partitioning, heading-aware context — no post-processing needed.
• CJK friendly: compact output for multibyte documents (see oxidize-pdf 2.5.4 subsetter fixes).
• Pure Python install: ships as a wheel for Linux/macOS/Windows via the oxidize-pdf package; no system dependencies.

Source

Part of oxidize-pdf-integrations, the ecosystem of integrations around oxidize-pdf. The Rust core and Python bridge live in oxidize-python.

License

MIT