Curation v2 step 1: three-way feedback, rating events, reader profile
- Migration 0002: rating_events, article_embeddings, interest_embeddings, article_assessments, candidate_runs, runs.config_json/provider_costs_json, issue_articles.why; copies ratings into rating_events and drops ratings and feed_priors (scores stays until step 4). - Vote is Loved | Good | NotForMe; legacy `up` links still verify as Loved. - Footer offers Loved it / Good / Not for me; the confirmation page offers the other two so a mis-tap can be corrected. handle_rating appends one event. - db::current_ratings implements the latest-explicit-event rule with summaries and facets; `ratings list|set|clear` CLI appends source='cli' events. - data/profile.md replaces the hard-coded reader prose; the system prompt is rebuilt every run in the §8.4 order with a recent-verdicts block. - Weekly rebuild reads summaries, facets and notes; feed priors removed. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01A1rCLQeKBgnBo3oTgHuTMe
This commit is contained in:
Claude Fable 5.1
+5
-79
@@ -12,15 +12,14 @@
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//! | came via Scour | +8 | §3.5 (already matched a stated interest) |
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//! | came via HN frontpage | +8 | §3.5 |
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//! | carried by several feeds | 0 … +8 | §3.2 (multi-source *is* social proof) |
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//! | feed prior | −12 … +12 | §3.9 beta-smoothed upvote rate, neutral at 0.5 |
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//! | excerpt only | −20 | §3.5 (penalized, never banned — §7) |
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//! | roundup/release-notes title | −15 | §3.5 |
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//! | blocked domain | excluded | §3.5 |
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use std::collections::{HashMap, HashSet};
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use std::collections::HashSet;
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use crate::config::{Config, CurationConfig};
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use crate::types::{Article, ArticleId, FeedId, FeedPrior, ScoredArticle, SourceKind};
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use crate::types::{Article, ArticleId, FeedId, ScoredArticle, SourceKind};
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/// Title patterns that mark low-effort posts: link roundups, release notes,
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/// sponsor posts (§3.5).
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@@ -64,7 +63,6 @@ pub const MAX_SOCIAL_POINTS: f64 = 25.0;
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pub const SCOUR_BONUS: f64 = 8.0;
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pub const HN_FRONTPAGE_BONUS: f64 = 8.0;
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pub const MAX_MULTI_SOURCE_POINTS: f64 = 8.0;
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pub const MAX_FEED_PRIOR_POINTS: f64 = 12.0;
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pub const EXCERPT_ONLY_PENALTY: f64 = 20.0;
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pub const ROUNDUP_TITLE_PENALTY: f64 = 15.0;
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@@ -75,8 +73,6 @@ const SOCIAL_SATURATION: f64 = 6.0;
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/// Everything the pre-filter needs beyond the articles themselves (§3.5, §3.9).
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#[derive(Debug, Clone, Default)]
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pub struct PrefilterContext {
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/// Per-feed Bayesian upvote rate from ratings history (§3.9).
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pub feed_priors: HashMap<FeedId, FeedPrior>,
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/// Article ids already published in a previous issue (§3.5).
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pub already_published: Vec<ArticleId>,
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/// Article ids the LLM scored < [`STALE_LOW_SCORE`] recently (§3.5).
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@@ -94,43 +90,18 @@ impl PrefilterContext {
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let since = today
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.checked_sub(jiff::Span::new().days(STALE_LOOKBACK_DAYS))
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.unwrap_or(today);
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let feed_priors = db
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.feed_priors()
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.await?
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.into_iter()
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.map(|p| (p.feed_id, p))
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.collect();
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let already_published = db.previously_published_ids().await?;
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let recently_rejected = db.recently_low_scored_ids(STALE_LOW_SCORE, since).await?;
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tracing::debug!(
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priors = ?feed_priors_len(&feed_priors),
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published = already_published.len(),
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rejected = recently_rejected.len(),
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"loaded prefilter context"
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);
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Ok(Self {
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feed_priors,
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already_published,
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recently_rejected,
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})
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}
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fn prior_for(&self, article: &Article) -> f64 {
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// The cluster's feeds are all candidates; take the most favourable one,
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// since a story carried by a well-rated feed is a better bet.
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let mut best = self.feed_priors.get(&article.feed_id).map(FeedPrior::rate);
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for source in &article.sources {
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if let Some(p) = self.feed_priors.get(&source.feed_id) {
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let rate = p.rate();
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best = Some(best.map_or(rate, |b: f64| b.max(rate)));
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}
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}
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best.unwrap_or(0.5)
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}
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}
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fn feed_priors_len(m: &HashMap<FeedId, FeedPrior>) -> usize {
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m.len()
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}
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/// True when the article's feed is in `curation.always_include_feeds` (§3.5).
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@@ -226,9 +197,9 @@ pub fn social_points(social_score: f64) -> f64 {
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MAX_SOCIAL_POINTS * (social_score / SOCIAL_SATURATION).min(1.0).sqrt()
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}
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/// Score one article 0–100 from word count, social proof, source signals, feed
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/// prior, and the excerpt/roundup/blocklist penalties (§3.5).
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pub fn score_article(article: &Article, ctx: &PrefilterContext, cfg: &Config) -> f64 {
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/// Score one article 0–100 from word count, social proof, source signals,
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/// and the excerpt/roundup/blocklist penalties (§3.5).
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pub fn score_article(article: &Article, _ctx: &PrefilterContext, cfg: &Config) -> f64 {
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if is_blocked(article, &cfg.curation) {
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return 0.0;
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}
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@@ -245,9 +216,6 @@ pub fn score_article(article: &Article, ctx: &PrefilterContext, cfg: &Config) ->
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let extra_feeds = article.sources.len().saturating_sub(1) as f64;
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score += (extra_feeds * 4.0).min(MAX_MULTI_SOURCE_POINTS);
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// Beta-smoothed upvote rate, neutral (0.5) contributing nothing (§3.9).
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score += (ctx.prior_for(article) - 0.5) * 2.0 * MAX_FEED_PRIOR_POINTS;
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if article.excerpt_only {
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score -= EXCERPT_ONLY_PENALTY;
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}
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@@ -288,12 +256,10 @@ pub fn run(articles: Vec<Article>, ctx: &PrefilterContext, cfg: &Config) -> Vec<
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let prefilter_score = score_article(&article, ctx, cfg);
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let social_score = article.social_score();
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let feed_prior = ctx.prior_for(&article);
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scored.push(ScoredArticle {
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article,
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prefilter_score,
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social_score,
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feed_prior,
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llm: None,
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auto_include,
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});
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@@ -488,35 +454,6 @@ pub(crate) mod tests {
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);
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}
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#[test]
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fn feed_prior_moves_the_score_both_ways() {
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let cfg = cfg();
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let mut liked = PrefilterContext::default();
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liked.feed_priors.insert(
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7,
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FeedPrior {
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feed_id: 7,
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upvotes: 18,
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downvotes: 0,
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included: 18,
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},
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);
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let mut disliked = PrefilterContext::default();
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disliked.feed_priors.insert(
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7,
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FeedPrior {
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feed_id: 7,
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upvotes: 0,
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downvotes: 18,
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included: 18,
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},
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);
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let a = article(1, "Deep dive", 1200);
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let neutral = score_article(&a, &PrefilterContext::default(), &cfg);
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assert!(score_article(&a, &liked, &cfg) > neutral);
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assert!(score_article(&a, &disliked, &cfg) < neutral);
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}
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#[test]
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fn blocked_domains_and_auto_includes_match_urls_and_ids() {
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let mut cfg = cfg();
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@@ -563,7 +500,6 @@ pub(crate) mod tests {
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let ctx = PrefilterContext {
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already_published: vec![4],
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recently_rejected: vec![6],
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..PrefilterContext::default()
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};
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let kept = run(articles, &ctx, &cfg);
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@@ -598,7 +534,6 @@ pub(crate) mod tests {
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let ctx = PrefilterContext {
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recently_rejected: vec![1],
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already_published: vec![2],
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..PrefilterContext::default()
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};
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let kept = run(vec![a, b], &ctx, &cfg);
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let ids: Vec<ArticleId> = kept.iter().map(|s| s.article.id).collect();
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@@ -613,14 +548,6 @@ pub(crate) mod tests {
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.expect("db");
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let date: jiff::civil::Date = "2026-08-15".parse().expect("date");
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db.upsert_feed_prior(&FeedPrior {
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feed_id: 7,
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upvotes: 4,
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downvotes: 1,
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included: 5,
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})
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.await
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.expect("prior");
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sqlx::query(
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"INSERT INTO articles (id, canonical_url, title, first_seen) VALUES
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(42, 'https://example.com/42', 'Printed', '2026-08-14T00:00:00Z'),
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@@ -660,6 +587,5 @@ pub(crate) mod tests {
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let ctx = PrefilterContext::load(&db, date).await.expect("context");
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assert_eq!(ctx.already_published, vec![42]);
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assert_eq!(ctx.recently_rejected, vec![43], "old rejects age out");
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assert!((ctx.feed_priors[&7].rate() - 5.0 / 7.0).abs() < 1e-12);
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}
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}
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+435
-567
File diff suppressed because it is too large
Load Diff
@@ -425,7 +425,6 @@ mod tests {
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article: article(id, title, words),
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prefilter_score: 50.0,
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social_score: 0.0,
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feed_prior: 0.5,
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llm: None,
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auto_include: false,
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}
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@@ -144,9 +144,8 @@ fn render_candidate(candidate: &ScoredArticle) -> String {
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}
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let _ = writeln!(
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block,
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"signals: social {:.2}; feed prior {:.2}; via {}{}",
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"signals: social {:.2}; via {}{}",
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candidate.social_score,
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candidate.feed_prior,
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source_kinds(candidate),
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if candidate.auto_include {
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"; ALWAYS-INCLUDE"
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@@ -716,7 +715,6 @@ mod tests {
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article: article(id, title, words),
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prefilter_score: 40.0 + score,
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social_score: 1.0,
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feed_prior: 0.5,
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llm: Some(LlmScore {
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score,
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category: "Tech & Engineering".into(),
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