Show HN: Raggy – A lightweight CLI tool for RAG over local documents

Raggy is a command-line tool for performing RAG (retrieval-augmented generation) operations on local documents, per a Show HN post from developer paulknysh. The project is open source and available on GitHub, designed as a lightweight alternative to more complex RAG frameworks.

RAG systems combine document retrieval with language model generation, allowing users to query private or local knowledge bases without sending data to external APIs. Raggy targets developers and users who want to run RAG workflows locally on their machines, avoiding cloud dependencies and keeping documents private. The tool operates as a CLI interface, making it accessible for command-line workflows and scripting.

The project launched on Hacker News and has attracted early attention from the developer community. No specific funding, company structure, or commercial plans are mentioned in the available information—this is a community-driven open source release by an individual developer.

RAG tools have proliferated as developers seek ways to ground large language models with custom data. Raggy positions itself in the lightweight and local-first segment of this market, contrasting with heavier cloud-based RAG platforms. The creator's emphasis on simplicity and low overhead suggests the tool is aimed at developers building smaller-scale projects or those with privacy and cost constraints.