connor
c89a723603
Ground-up replacement for news_triage, whose signal quality failed because it had no representation of what its user likes -- three keywords fed to BM25 plus a two-term substring blocklist. profile/ holds the taste model as prose and TOML: 11 interest blocks, 3 veto blocks, 5 importance blocks, each a set of probe sentences to be embedded. The [scoring] constants are fitted, not guessed. CALIBRATION.md records the measurements against all 3,885 items in the v0.2 database and 40 real feedback labels, including two findings that changed the design: - compare blocks by z-score within block, never raw cosine; raw cosine let geopolitics win 78% of items and buried known-liked items at median rank 1246 of 3885 (293 after normalizing) - veto needs a margin over the interest signal, not a threshold; a plain 0.55 cutoff falsely killed "Belgian mayor blocks club from hosting Israeli opponent in Europa League", which the old substring blocklist also killed
2.3 KiB
news
A personal news aggregator: many sources in, two to five well-chosen push notifications and one readable daily digest out.
This is a ground-up rewrite of news_triage, which is still
running. The rewrite exists because the old system had no representation of what
its user actually likes — its whole preference model was three keywords fed to
BM25 plus a two-term substring blocklist, and everything else was ranking
machinery with nothing meaningful to rank.
The core idea
Taste is a set of vectors, not a bag of keywords.
Every interest, veto and importance category in profile/profile.toml
is written as prose and embedded with a small CPU model (bge-small-en-v1.5,
~130 MB, ONNX, no torch, no GPU — so it never contends with the llama-swap stack).
An item's score is the max cosine similarity across a block's probes, never the
mean: averaging "Middle East geopolitics" with "grid-scale energy storage" gives
a vector near neither.
This is what lets a topic be expressed as a region rather than a string. The
old system could not represent "sports" as a concept, only as the literal
characters s-p-o-r-t-s, which is why 18 of its 32 feedback clicks were its user
hand-rejecting baseball recaps that blocklist = ["sports"] never matched.
A generative LLM is used only for prose — the daily digest write-up and cluster headlines — at roughly 1–30 calls/day through LiteLLM, never for per-item scoring.
Two routing lanes
Notifications are decided on two independent axes, because "something I might like" and "something I need to know about" are different questions:
- interest — high similarity to the profile's interest vectors.
- importance — burst velocity, independent-source-bucket count, editorial prominence, and aggregator-native scores. Deliberately not raw corroboration count, which just measures how many wire-reprinting outlets you subscribed to.
Vetoes are absolute on both lanes. In the old system the bypass lane ignored relevance entirely, so a blocklisted item could still fire at priority 5.
Layout
profile/ the user's taste, as prose and as TOML. Start here.
news/ the pipeline: sources, store, embed, cluster, score, route, deliver
tests/
deploy/
Status
Early. profile/ is written; the pipeline is not yet built.