RAGMill: Open-Source Python Library Builds Local RAG Pipelines Without Cloud Dependencies

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A developer has released RAGMill, a lightweight open-source Python library designed to build Retrieval-Augmented Generation (RAG) pipelines entirely offline without heavy framework dependencies. The tool ingests local text files in formats including Markdown, PDF, and DOCX, then splits them into semantically coherent chunks using recursive boundary analysis rather than arbitrary character-based splitting. RAGMill replaces bulky tokenizers like tiktoken with a custom deterministic regex routine to calculate text boundaries, keeping the core package dependency-free. The pipeline is structured in three decoupled stages: asynchronous directory ingestion, semantic chunking, and sliding-window context preservation for downstream embedding quality. RAGMill is available on PyPI via pip and its source code is publicly hosted on GitHub.

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