#Document-processing
Showing 40 of 40 repositories tagged #document-processing, ranked by stars
A fast, helpful, and open-source document parser
Modular SenseNova skills for building AI-powered office assistants and productivity workflows
A system for agentic LLM-powered data processing and ETL
在保留版面、公式与结构的前提下进行 PDF 翻译，适用于科研与技术文档
ExtractThinker is a Document Intelligence library for LLMs, offering ORM-style interaction for flexible and powerful document workflows.
The fastest PDF library for Python and Rust. Text extraction, image extraction, markdown conversion, PDF creation & editing. 0.8ms mean, 5× faster than industry leaders, 100% pass rate on 3,830 PDFs. MIT/Apache-2.0.
Local-first, open-source AI assistant for your data. Unify tasks, notes, docs, photos, and bookmarks. Private, self-hosted, and extensible via APIs.
📄 The PDF intelligence layer for AI agents — Agent Document Twin, evidence-first extraction, visual crops, OCR provenance, trust reports, and benchmark-gated releases. MCP server for Claude, Cursor, VS Code, and any MCP client.
Java PDF table extraction & OCR library. Extract structured tables from text-based and scanned PDFs using stream, lattice (OpenCV-style grid detection), and hybrid parsing.
Generic framework for historical document processing
:zap: Cloud-native, AI-powered, document processing pipelines on AWS.
Turn PDFs into clean, structured Markdown
Pure Rust PDF library for AI/RAG: structure-aware chunking, no ML, no C deps.
Python, LlamaIndex, LangChain, Docker Compose: 15 Property Graph, 4 RDF , 10 Vector, OpenSearch, Elasticsearch, Alfresco DBs. 13 data sources (9 auto-sync), KG auto-building, Ontologies, LLMs, Docling or LlamaParse doc processing, GraphRAG, RAG only, Hybrid Search, AI Chat. TypeScript React, Vue, Angular frontends, FastAPI REST backend, MCP Server.
Open-source document chat platform with semantic search, RAG (Retrieval Augmented Generation), and multi-provider AI support (OpenRouter, OpenAI, ImageRouter).
Open-source toolkit for reliable RAG pipelines: convert PDFs to Markdown, clean documents, inspect chunks, compare chunking strategies, and enrich metadata for LLM applications.
Plug-and-play document AI with zero-shot models.
InferrLM - On-device AI for iOS & Android
A Python framework for multi-modal document understanding with Amazon Bedrock
ComPDF Skills are AI-agent-ready PDF processing skills for Claude Code, Cursor, Copilot, OpenCode, and 39+ coding agents to convert, edit, split, insert, compare, compress PDFs, and more.
Retrieval of fully structured data made easy. Use LLMs or custom models. Specialized on PDFs and HTML files. Extensive support of tabular data extraction and multimodal queries.
AI-Native document parser: PDF, Office & images → clean Markdown with LaTeX, tables & OCR. Zero-dependency CLI & skill for Claude Code, Cursor & AI agents.
An MCP server that lets Claude Code and other AI agents work through large PDFs without overflowing their context — search by meaning or keyword, read only the pages that matter, and cleanly pull out tables, images, and scanned text, even from multi-column and Japanese layouts.
AI-powered platform for OSINT intelligence analysis. Features archive discovery with hypothesis-driven investigation, GLiNER entity extraction, Mapbox geospatial visualization, network analysis, and document processing. Built with FastAPI, Next.js, Weaviate, and DSPy.
AI Document Assistant for PSPDFKit Demo showcases how to interact with PDFs using natural language commands powered by AI, integrated with PSPDFKit for Web.
AI 驱动的桌面助手，支持多模型服务商。如北极星般为你的工作指引方向 - 文档处理、代码编写、智能问答。AI-driven desktop assistant with multi-model support. Like Polaris guiding your work - document processing, code writing, and intelligent Q&A.
The fastest Office document library for Python, Rust, Go, JS/TS, C# and WASM. DOCX, XLSX, PPTX, DOC, XLS, PPT. Up to 100× faster than python-docx/openpyxl/python-pptx. 100% pass rate on valid Office files. MIT/Apache-2.0.
Rust CLI implementing the Recursive Language Model (RLM) pattern for Claude Code. Process documents 100x larger than context windows through intelligent chunking, SQLite persistence, and recursive sub-LLM orchestration.
3DCF / doc2dataset: token-efficient document layer with NumGuard numeric integrity and multi-framework exports for RAG & fine-tuning.
ResumeTex is an AI-powered tool that converts standard PDF resumes into professionally formatted LaTeX documents. This service helps you create elegant, structured resumes without needing to learn LaTeX syntax.
Agent skills for LandingAI's Agentic Document Extraction (ADE) — production-ready document AI for agentic coding assistants
DPG Campus Tool. Shrink massive PDFs to fit AI upload limits. Sanitize before uploading to reduce risk of exposing sensitive data.
Local-first CLI + MCP server: Any file → AI-ready Markdown + JSON
Enterprise-ready vector database toolkit for building searchable knowledge bases from multiple data sources. Supports multi-project management, automatic ingestion from Confluence/JIRA/Git, intelligent file conversion (PDF/Office/images), and semantic search. Includes MCP server for seamless AI assistant integration.
This repository contains examples for customers to get started using Amazon Bedrock Data Automation. The samples focus mainly on document processing use cases
Anthropic's Contextual Retrieval implementation with visual chunk comparison. Preview context enrichment before/after embedding.
Open-source PDF-to-Markdown post-processor with footnotes, LaTeX normalization, figure links, and YAML metadata. Supports Marker, MinerU, PyMuPDF, and Docling. Includes a self-hosted web UI.
Multi-Modal RAG for .NET — query databases, documents, images and audio in natural language. Production-ready with multi-AI support, vector storage, and multi-database coordination.
Cutting-edge tool that unlocks the full potential of semantic chunking
High-quality scientific PDF translation using Claude Code Max - Transform scanned academic documents from English to French with precision