llama-index readers pdfmux integration
Project description
LlamaIndex Readers Integration: pdfmux
pdfmux extracts PDFs into section-aware, LLM-ready chunks. It scores each page's extraction confidence and routes low-confidence or scanned pages to an OCR fallback automatically, so mixed digital/scanned documents come back as clean text without manual pre-processing. Each chunk is returned as a LlamaIndex Document with title, page range, token estimate, and confidence metadata.
Installation
pip install llama-index-readers-pdfmux
Usage
from llama_index.readers.pdfmux import PDFMuxReader
reader = PDFMuxReader(quality="standard") # "fast" | "standard" | "high"
documents = reader.load_data("report.pdf")
for doc in documents:
print(doc.metadata["title"], "—", doc.metadata["tokens"], "tokens")
Each returned Document carries metadata: source, title, page_start, page_end, tokens, confidence. Pass extra_info={...} to load_data to merge additional metadata into every document.
This loader is designed for RAG/LLM pipelines that ingest a mix of scanned and digital PDFs and need per-page confidence to decide what to trust.
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