# Runtime configuration and tuning knobs.
#
# Three-file split, so a new user knows what to touch:
#   config.toml   this file -- machinery. Sane defaults; rarely edited.
#   profile.toml  who you are: interests, vetoes, importance, delivery.
#   sources.toml  what to read.
#
# Nothing here is specific to any person. Everything personal lives in the
# other two files.

[http]
# Sent on every outbound request. Feed operators use it to identify traffic and
# some will block a generic or absent agent, so put a real contact here.
# CHANGE THIS if you are not Connor -- it is the contact address feed operators
# see, and pointing them at someone else's domain is rude and unhelpful.
user_agent = "news/0.1 (+https://news.rcjohnstone.com; personal feed reader; one user)"
timeout_secs = 30
connect_timeout_secs = 10
concurrency = 8
max_body_bytes = 10485760

[embedding]
# Any model fastembed can serve. `dim` must match the model.
#
# The default is English-only. For native-language sources use a multilingual
# model -- "intfloat/multilingual-e5-small" (384 dim) is the usual choice.
# Be aware that changing the model INVALIDATES the calibrated constants below
# and in [scoring]: they are cosine thresholds, and a different model puts
# similarity on a different scale. Re-run the calibration before trusting them.
model = "BAAI/bge-small-en-v1.5"
dim = 384

[clustering]
# Calibrated by inspection on a 3,885-item corpus; see CALIBRATION.md.
# 0.70 merged "Solheim Cup capsules" with "FIBA Women's World Cup Glance";
# 0.86 under-merged. Over-merging is the worse failure because it inflates the
# corroboration signal that feeds importance.
#
# Re-tune if your sources differ substantially in style or language.
threshold = 0.82
window_hours = 48

# Above this cosine, two items from DIFFERENT newsrooms are treated as the same
# syndicated copy rather than independent corroboration. Deliberately high:
# eight outlets each writing their own Renoir-heist headline stayed separate,
# while a local station reprinting a wire dispatch collapsed correctly.
syndication_threshold = 0.97

[scoring]
# Compare blocks by z-score WITHIN each block, never by raw cosine: cosine
# magnitude is not comparable across blocks, and a plain max let one block win
# 78% of all items. See CALIBRATION.md.
# "zscore-per-block" or "top-anchored". Both normalise per GROUP (see `group`
# in profile.toml), not per block: taking the max across blocks gives a subject
# one draw per block, so a topic split into five blocks beats one covered by a
# single block purely by having more chances.
#
# NOTE the thresholds in [routing] are in z-score units. "top-anchored" puts
# scores on a different scale (1.0 = that group's 99th percentile), so switching
# normalizer REQUIRES re-tuning them -- verified: leaving them at 2.0 silences
# the interest lane completely.
normalize = "zscore-per-block"

# Veto is not a plain similarity threshold. A story can be genuinely adjacent to
# a vetoed topic and still be wanted, so an item is vetoed on unambiguous
# similarity OR when the veto signal beats the best interest signal by a margin.
veto_absolute = 0.60
veto_margin_over_interest = 0.3

# Corroboration = origins + pickup_weight*log1p(pickups) + depth_weight*log1p(depth).
# "Several outlets carried this" covers four different situations; see
# news/cluster.py:Corroboration. Origins (independent newsrooms doing their own
# reporting) dominate; the other two break ties among the many two- and
# three-origin clusters. Measured on a real corpus: 163 origins, 90 depth,
# 11 pickups -- depth matters far more here because these sources mostly write
# their own copy. Raise pickup_weight if you add local papers running wire.
corroboration_pickup_weight = 0.3
corroboration_depth_weight = 0.2

[routing]
# Daily budgets. Deliberately small: the point of the system is a handful of
# well-chosen interruptions, not a feed.
interest_per_day = 3
# Max alerts per quota group per day (see `group` in profile.toml). Stops one
# subject taking every slot.
max_alerts_per_group_per_day = 1
important_per_day = 2
# Hard cap on waking the reader during quiet hours, inside important_per_day.
important_per_night = 1

# Minimum spacing between sends on a lane. Budgets alone are not a rate: without
# these the whole day's allowance fires in one cycle, and six notifications
# arrived in the same minute.
interest_min_gap_minutes = 75
important_min_gap_minutes = 30

# Thresholds are in z-score units -- "how many standard deviations above normal
# for this block", not raw cosine. Calibrate with `news simulate`, which reports
# the notifications-per-day these values would actually have produced.
interest_threshold = 2.0
important_threshold = 2.0
digest_floor = 0.5
# A floor alone yielded 198 items a day. The digest is capped by count and fed
# strongest-first, so the cap is always spent on the best candidates.
digest_max_items = 25
# Max items per topic group in the digest, so no single subject crowds it out.
# Measured before this existed: conflict and diplomacy took 18 of 28 slots while
# software-systems took 0, despite being 141 of the eligible clusters.
digest_max_per_group = 4
# Slots reserved for the day's most important stories regardless of topic, so a
# major event stays in the record even when your own interests are busy. The
# remaining slots are ranked by interest.
digest_importance_slots = 6
# Serendipity slots are filled from items BELOW this interest score, so they are
# genuinely outside the profile rather than near-misses.
serendipity_max_interest = 0.5

# Aggregator maturation: an HN post at 3 points is noise, at 300 it is news.
# 100, not 150: the HN front page has a median of ~117 points, so a higher bar
# would reject most of what the crowd has actually promoted.
hn_min_score = 100

# Nothing older than this may generate a notification. Feeds return large
# archives on first fetch -- one run pulled 88 items going back five months --
# and those belong in the scoring corpus but not in your pocket.
max_age_hours = 48

[scoring.importance_weights]
# Importance is NOT corroboration count -- that was the old system's error.
# Velocity is weighted as heavily as corroboration: 0 to 6 independent origins
# in ninety minutes is what breaking news looks like, and a story sitting at 6
# origins for three days is not.
block = 1.0
corroboration = 0.4
velocity = 0.5
prominence = 0.3
aggregator = 0.3

[llm]
# The ENTIRE generative-model surface of this system: one call per day to write
# the digest prose. Clustering, relevance, importance and vetoes are all
# embeddings and arithmetic -- no model in the scoring path.
#
# Cost on this alias is pinned to 0.0 in the LiteLLM config, so a NONZERO spend
# row is the deliberate quota-overflow alarm, not a billing surprise.
enabled = true
base_url = "http://litellm:4000"
model = "news/glm-5.3-flash"
api_key_env = "NEWS_LITELLM_KEY"
# 180, not 60: the real digest payload (28 stories) took 70.3s to generate, so a
# 60s timeout failed every morning and silently fell back to the templated list.
timeout_secs = 180