Sep 2026· Zenodo (CERN European Organization for Nuclear Research)
Abstract
A privacy-first, self-hosted gateway for local large language models (Ollama). Pukara runs a Dockerized Ollama server behind an application-layer encrypted proxy, and ships a desktop client that pseudonymises sensitive entities on-device (BERT + regex) before anything leaves the machine. The name Pukara (Quechua for "fortress") plays on Ollama's alpaca: a small, resilient stronghold around your model. Pukara addresses the gap between self-hosted LLMs and privacy. It encrypts the whole client–server channel with protocol v2 (pre-shared key, AES-256-GCM with HKDF-SHA256, direction-separated keys, server-clock freshness and anti-replay), and pseudonymises personal data on the client before transmission: detected entities are replaced by reversible placeholders and the placeholder→text map never leaves the client. The sender's data remain personal to the client; whether the transmitted text is anonymous for the recipient depends on residual re-identification risk (see the threat model and docs/metrics.md). It is designed for Spanish clinical text and is model-agnostic (swap BERT_MODEL for another language).
Supporting data, adapters, predictions and code for the article *Low-Cost LoRA Fine-Tuning of Small Language Models for Multi-Step Arithmetic Reasoning* by Jake O'Grady, Asena Isik Gürhan, Chee Fong Ting and Effirul Ramlan (University of Galway). We generated 20,000 GSM8K-derived arithmetic problems with step-by-step s...
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