connor
b852840729
Following Connor's point that corpus prevalence reflects how much an outlet publishes rather than what deserves a notification: allocation should track stated weights, not corpus composition in EITHER direction. Penalising a topic for being prevalent is a bug; rewarding it would just amplify whoever publishes most. This rules out the "reserve slots proportional to corpus share" model that the previous commit's findings were pointing toward. Two fixes: 1. Normalisation moves from per-block to per-GROUP. Taking the max across blocks gives a subject one draw per block, so foreign affairs -- six of 23 blocks -- beat everything else by having more chances. It held 70% of the digest while software-systems, a quarter of the corpus, held none. Collapsing to the group before normalising prices that in. Digest conflict share 13 -> 9, space 2 -> 4, and us-national appears at all. 2. The per-group quota now keys on the INTEREST group for both lanes. Importance blocks describe a kind of importance, not a subject, so two stories on one subject could each take a slot via different importance blocks -- which is what happened: both importance alerts were Middle East, one via war-escalation and one via economic-break. Interest alerts went from five-of-five Middle East to Ohio redistricting, political theory and tech policy. Also demoted prerelease/nightly build entries. The first alert software-systems ever won was "Nvim development (prerelease) build", which matches the block correctly and is worthless as a notification. Documented that switching normalizer requires re-tuning [routing] thresholds: they are in z-score units, and leaving them at 2.0 under "top-anchored" silences the interest lane entirely.
122 lines
5.4 KiB
TOML
122 lines
5.4 KiB
TOML
# Runtime configuration and tuning knobs.
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#
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# Three-file split, so a new user knows what to touch:
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# config.toml this file -- machinery. Sane defaults; rarely edited.
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# profile.toml who you are: interests, vetoes, importance, delivery.
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# sources.toml what to read.
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#
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# Nothing here is specific to any person. Everything personal lives in the
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# other two files.
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[http]
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# Sent on every outbound request. Feed operators use it to identify traffic and
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# some will block a generic or absent agent, so put a real contact here.
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# CHANGE THIS if you are not Connor -- it is the contact address feed operators
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# see, and pointing them at someone else's domain is rude and unhelpful.
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user_agent = "news/0.1 (+https://news.rcjohnstone.com; personal feed reader; one user)"
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timeout_secs = 30
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connect_timeout_secs = 10
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concurrency = 8
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max_body_bytes = 10485760
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[embedding]
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# Any model fastembed can serve. `dim` must match the model.
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#
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# The default is English-only. For native-language sources use a multilingual
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# model -- "intfloat/multilingual-e5-small" (384 dim) is the usual choice.
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# Be aware that changing the model INVALIDATES the calibrated constants below
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# and in [scoring]: they are cosine thresholds, and a different model puts
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# similarity on a different scale. Re-run the calibration before trusting them.
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model = "BAAI/bge-small-en-v1.5"
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dim = 384
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[clustering]
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# Calibrated by inspection on a 3,885-item corpus; see CALIBRATION.md.
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# 0.70 merged "Solheim Cup capsules" with "FIBA Women's World Cup Glance";
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# 0.86 under-merged. Over-merging is the worse failure because it inflates the
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# corroboration signal that feeds importance.
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#
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# Re-tune if your sources differ substantially in style or language.
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threshold = 0.82
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window_hours = 48
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# Above this cosine, two items from DIFFERENT newsrooms are treated as the same
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# syndicated copy rather than independent corroboration. Deliberately high:
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# eight outlets each writing their own Renoir-heist headline stayed separate,
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# while a local station reprinting a wire dispatch collapsed correctly.
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syndication_threshold = 0.97
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[scoring]
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# Compare blocks by z-score WITHIN each block, never by raw cosine: cosine
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# magnitude is not comparable across blocks, and a plain max let one block win
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# 78% of all items. See CALIBRATION.md.
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# "zscore-per-block" or "top-anchored". Both normalise per GROUP (see `group`
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# in profile.toml), not per block: taking the max across blocks gives a subject
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# one draw per block, so a topic split into five blocks beats one covered by a
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# single block purely by having more chances.
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#
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# NOTE the thresholds in [routing] are in z-score units. "top-anchored" puts
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# scores on a different scale (1.0 = that group's 99th percentile), so switching
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# normalizer REQUIRES re-tuning them -- verified: leaving them at 2.0 silences
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# the interest lane completely.
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normalize = "zscore-per-block"
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# Veto is not a plain similarity threshold. A story can be genuinely adjacent to
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# a vetoed topic and still be wanted, so an item is vetoed on unambiguous
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# similarity OR when the veto signal beats the best interest signal by a margin.
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veto_absolute = 0.60
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veto_margin_over_interest = 0.3
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# Corroboration = origins + pickup_weight*log1p(pickups) + depth_weight*log1p(depth).
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# "Several outlets carried this" covers four different situations; see
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# news/cluster.py:Corroboration. Origins (independent newsrooms doing their own
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# reporting) dominate; the other two break ties among the many two- and
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# three-origin clusters. Measured on a real corpus: 163 origins, 90 depth,
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# 11 pickups -- depth matters far more here because these sources mostly write
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# their own copy. Raise pickup_weight if you add local papers running wire.
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corroboration_pickup_weight = 0.3
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corroboration_depth_weight = 0.2
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[routing]
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# Daily budgets. Deliberately small: the point of the system is a handful of
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# well-chosen interruptions, not a feed.
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interest_per_day = 3
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# Max alerts per quota group per day (see `group` in profile.toml). Stops one
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# subject taking every slot.
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max_alerts_per_group_per_day = 1
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important_per_day = 2
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# Hard cap on waking the reader during quiet hours, inside important_per_day.
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important_per_night = 1
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# Thresholds are in z-score units -- "how many standard deviations above normal
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# for this block", not raw cosine. Calibrate with `news simulate`, which reports
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# the notifications-per-day these values would actually have produced.
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interest_threshold = 2.0
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important_threshold = 2.0
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digest_floor = 0.5
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# A floor alone yielded 198 items a day. The digest is capped by count and fed
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# strongest-first, so the cap is always spent on the best candidates.
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digest_max_items = 25
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# Serendipity slots are filled from items BELOW this interest score, so they are
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# genuinely outside the profile rather than near-misses.
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serendipity_max_interest = 0.5
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# Aggregator maturation: an HN post at 3 points is noise, at 300 it is news.
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hn_min_score = 150
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# Nothing older than this may generate a notification. Feeds return large
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# archives on first fetch -- one run pulled 88 items going back five months --
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# and those belong in the scoring corpus but not in your pocket.
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max_age_hours = 48
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[scoring.importance_weights]
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# Importance is NOT corroboration count -- that was the old system's error.
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# Velocity is weighted as heavily as corroboration: 0 to 6 independent origins
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# in ninety minutes is what breaking news looks like, and a story sitting at 6
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# origins for three days is not.
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block = 1.0
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corroboration = 0.4
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velocity = 0.5
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prominence = 0.3
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aggregator = 0.3
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