OwlerLite: Scope- and Freshness-Aware Web Retrieval for LLM Assistants

TL;DR

OwlerLite is a browser extension that enhances web retrieval for language models by allowing user-defined scopes and freshness monitoring, leading to more controlled and trustworthy information retrieval.

Contribution

It introduces a scope- and freshness-aware retrieval system that enables user control and dynamic updating of web content for language model assistants.

Findings

Supports user-defined web source scopes.

Uses semantic change detection for live page updates.

Integrates relevance, scope, and recency into retrieval.

Abstract

Browser-based language models often use retrieval-augmented generation (RAG) but typically rely on fixed, outdated indices that give users no control over which sources are consulted. This can lead to answers that mix trusted and untrusted content or draw on stale information. We present OwlerLite, a browser-based RAG system that makes user-defined scopes and data freshness central to retrieval. Users define reusable scopes-sets of web pages or sources-and select them when querying. A freshness-aware crawler monitors live pages, uses a semantic change detector to identify meaningful updates, and selectively re-indexes changed content. OwlerLite integrates text relevance, scope choice, and recency into a unified retrieval model. Implemented as a browser extension, it represents a step toward more controllable and trustworthy web assistants.