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AI Document Intelligence

A Python SDK for document intelligence and ingestion pipelines for LLM and RAG applications.

The SDK provides a unified pipeline for:

  • 📄 Document parsing
  • 📑 Page-wise text and Markdown extraction
  • 📋 Document metadata
  • 🧩 Semantic Markdown-aware chunking
  • 🧠 Embedding generation
  • 🔗 Standardized document, chunk, and embedding models
  • ⚡ Support for multiple document input sources
  • 🐍 Strongly typed Pydantic models

The SDK is designed to be domain-agnostic and can be used for financial documents, resumes, reports, contracts, and other business documents.


Features

📄 Document Parsing

Parse documents using pluggable parser implementations.

Currently supported:

  • LiteParse — local/free parsing
  • Llama Cloud — premium cloud-based parsing

The parser layer exposes a unified interface so the rest of the pipeline does not depend on a specific parsing provider.

📑 Page-wise Extraction

Parsed documents provide page-level information including:

  • Text
  • Markdown
  • Page number
  • Document elements where supported

📋 Document Metadata

Standardized document metadata is exposed through Pydantic models.

document.metadata.page_count

Metadata

Release files for ai-document-intelligence 0.3.0

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Source distribution for ai-document-intelligence 0.3.0
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Table of built distributions (wheels) for ai-document-intelligence 0.3.0
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ai_document_intelligence-0.3.0-py3-none-any.whl Python 3 none any Details

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Release files / ai_document_intelligence-0.3.0.tar.gz

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Release files / ai_document_intelligence-0.3.0-py3-none-any.whl

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0.3.0 This release

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0.1.0

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