#Document-parser
Showing 13 of 13 repositories tagged #document-parser, ranked by stars
Get your documents ready for gen AI
Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding.
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AutoRAG: An Open-Source Framework for Retrieval-Augmented Generation (RAG) Evaluation & Optimization with AutoML-Style Automation
A Repo For Document AI
Extract and convert data from any document, images, pdfs, word doc, ppt or URL into multiple formats (Markdown, JSON, CSV, HTML) with intelligent structured data extraction and advanced OCR.
모두 파싱해버리겠다 — HWP3·HWP·HWPX·HWPML·PDF·XLS·XLSX·DOCX → Markdown. 신구대조·양식 자동 채우기·MCP 통합 (CLI + MCP Server) | Parse Korean documents (HWP3-5, HWPX, HWPML, PDF, Office) to Markdown — CLI + MCP Server with form-filler & diff
LAYRA—an enterprise-ready, out-of-the-box solution—unlocks next-generation intelligent systems powered by visual RAG and limitless visual multi-step agent workflow orchestration.
Complex data extraction and orchestration framework designed for processing unstructured documents. It integrates AI-powered document pipelines (GenAI, LLM, VLLM) into your applications, supporting various tasks such as document cleanup, optical character recognition (OCR), classification, splitting, named entity recognition, and form processing
AI-Native document parser: PDF, Office & images → clean Markdown with LaTeX, tables & OCR. Zero-dependency CLI & skill for Claude Code, Cursor & AI agents.
Parse any file in opencode. Supports PDF, DOCX, XLSX, PPTX, images, EPUB, HTML, Markdown, Jupyter, archives, and plain text.
Graphlit Platform
An open source framework for Retrieval-Augmented System (RAG) uses semantic search helps to retrieve the expected results and generate human readable conversational response with the help of LLM (Large Language Model).