A retrieval-augmented-generation pipeline to help users query system-provided documentation
summary
Describes a retrieval-augmented generation (RAG) pipeline that turns system-provided man pages into a searchable, natural-language query interface by tokenizing documentation, creating embeddings, and using dense retrieval to select relevant passages for a language generation model to produce concise answers. Focuses on enabling plain-language queries about command-line tool usage, flags, and parameters within Debian-style environments to improve tool discovery and onboarding.
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