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Unstructured

Open-source document ingestion library — partition PDFs, HTML, DOCX, and 25+ formats into clean elements for RAG pipelines.

Instalaciones72k
⟳ upstream 0.27.5 · updated 14d ago
Repositorio fuente
! Grade B · 75/100 · ReviewSecurity assessment
No compromise signals28capabilities surfaced1known CVE5of 20 OWASP controls clear
Suspicious code patternsBroad capability surfaceSuspicious code patternsInternal host / private infrastructure reference
scanned 13d agoosv · gitleaks · opengrep · picklescan + heuristicsfull breakdown in the Security tab ↓

Unstructured

Unstructured is the leading open-source library for ingesting and preprocessing unstructured documents for use in LLM applications. It partitions documents into typed elements (Title, NarrativeText, Table, Image, etc.), extracts metadata, and cleans text — making raw files ready for chunking and embedding.

Key Features

  • 25+ file formats — PDF, HTML, DOCX, PPTX, XLSX, EML, MSG, MD, RST, TXT, images, and more
  • Partition strategiesfast (rule-based), hi_res (layout detection with detectron2), ocr_only
  • Element types — Title, NarrativeText, Table, ListItem, Image, Header, Footer, FigureCaption
  • Table extraction — HTML table extraction from PDFs with hi_res strategy
  • LangChain / LlamaIndex connectorsUnstructuredLoader is a first-class integration in both
  • Connectors — S3, GCS, Azure Blob, Confluence, Google Drive, SharePoint, Slack, and more

Quick Start

pip install unstructured[pdf]
from unstructured.partition.pdf import partition_pdf

elements = partition_pdf("research_paper.pdf", strategy="hi_res")
for el in elements[:5]:
    print(el.category, ":", str(el)[:80])

Install via ai-supply

npx ai-supply add unstructured-document-ingestion

Curated mirror of the open-source Unstructured project (Apache-2.0). Install upstream from the repository.

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