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Running models on private hardware for data privacy.
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This project is a privacy-first backend service designed to facilitate retrieval-augmented generation by processing local documents into searchable vector representations. It provides a modular architecture that allows users to ingest diverse file formats, manage document metadata, and perform semantic searches to prov
Hosts large language models on private hardware to ensure complete data privacy and infrastructure control.