Document Parser by Contextual AI
Multimodal document parser designed for RAG systems. Parse a file into a structured Markdown and/or JSON. Files must be less than 300MB and 2000 pages. We use LibreOffice to convert DOC(X) and PPT(X) files to PDF, which may affect page count. See our blog post and code examples. Email parse-feedback@contextual.ai with any feedback or questions. A document parser designed for RAG use cases, which achieves superior accuracy and reliability by excelling in the following areas: 1.
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This repo provides the server side code for llmsherpa API to connect. It includes parsers for various file formats.
Stop using static chunk sizes. A lightweight, production-ready RAG ingestion toolkit. Uses Docling for layout-aware parsing and applies smart heuristics for optimal chunking (PDF vs Code vs MD). Extracted from a production RAG platform
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