Was hardcoded to llama3.1, which isn't actually on this machine.
Switched to gemma4-e4b (5.0 GB, already pulled) as a speed/quality
balance for a call made once per shortlisted article on every
pipeline run.
Rust workspace with core (topic-affinity learning engine + relevance
scoring), db (sqlite/sqlx schema + repo), feeds (RSS/Atom fetch), llm
(rig + local Ollama embeddings/completion), and web (axum + Dioxus
fullstack UI, no separate JS stack). Two-stage relevance filtering
(embedding shortlist -> LLM judgment) and an engagement/surprise-based
topic affinity engine with daily decay. All crates compile and core's
affinity engine has passing unit tests; server and wasm client targets
of feedsignal-web both check clean.
