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ci: add production topic channel spam audit mode #4866

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ci: add production topic channel spam audit mode #4866

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154 changes: 154 additions & 0 deletions .github/workflows/query-production-federation-export-event.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -76,6 +76,160 @@ jobs:

- name: Query federation export event rows
run: |
if [ "${{ inputs.article_id }}" = "0" ]; then
psql \
--host "$MATTERS_PG_HOST" \
--username "$MATTERS_PG_USER" \
--dbname "$MATTERS_PG_DATABASE" \
--no-password \
--set ON_ERROR_STOP=1 \
--command "
with spam_threshold as (
select coalesce(
(
select value::numeric
from feature_flag
where name = 'spam_detection'
and flag = 'on'
order by updated_at desc
limit 1
),
1
) as threshold
),
target_channels(name) as (
values ('生活'), ('書影音'), ('時事'), ('還有')
),
channel_rows as (
select
tc.name as channel_name,
tca.article_id,
tca.enabled as channel_row_enabled,
tca.pinned,
tca.is_labeled,
tca.created_at as channel_created_at,
tca.updated_at as channel_updated_at,
a.short_hash,
a.title,
a.author_id,
a.is_spam,
a.spam_score,
a.state,
a.channel_enabled,
a.created_at as article_created_at,
st.threshold
from topic_channel_article tca
join topic_channel tc on tc.id = tca.channel_id
join article a on a.id = tca.article_id
cross join spam_threshold st
join target_channels target on target.name = tc.name
where tca.enabled = true
and a.state = 'active'
and a.channel_enabled = true
),
metrics as (
select
channel_name,
count(*) as enabled_active_rows,
count(distinct article_id) as distinct_articles,
count(*) filter (
where is_spam is null
and spam_score >= threshold
) as null_high_score_rows,
count(*) filter (
where is_spam is null
and spam_score >= threshold
and pinned = false
) as null_high_score_unpinned_rows,
count(*) filter (
where is_spam is null
and spam_score >= threshold
and pinned = true
) as null_high_score_pinned_rows,
count(*) filter (where is_spam = true) as is_spam_true_rows,
count(*) filter (
where is_spam = false
and spam_score >= threshold
) as false_high_score_rows,
count(*) filter (
where article_created_at >= now() - interval '7 days'
and is_spam is null
and spam_score >= threshold
) as null_high_score_rows_7d,
count(*) filter (
where article_created_at >= now() - interval '30 days'
and is_spam is null
and spam_score >= threshold
) as null_high_score_rows_30d
from channel_rows
group by channel_name
),
sample_null_high_score as (
select
'null_high_score' as sample_type,
channel_name,
article_id,
short_hash,
left(title, 80) as title_preview,
author_id,
is_spam,
spam_score,
threshold,
pinned,
is_labeled,
article_created_at,
channel_created_at,
channel_updated_at
from channel_rows
where is_spam is null
and spam_score >= threshold
order by article_created_at desc
limit 20
),
sample_false_high_score as (
select
'false_high_score' as sample_type,
channel_name,
article_id,
short_hash,
left(title, 80) as title_preview,
author_id,
is_spam,
spam_score,
threshold,
pinned,
is_labeled,
article_created_at,
channel_created_at,
channel_updated_at
from channel_rows
where is_spam = false
and spam_score >= threshold
order by article_created_at desc
limit 20
),
samples as (
select * from sample_null_high_score
union all
select * from sample_false_high_score
)
select jsonb_pretty(
jsonb_build_object(
'threshold', (select threshold from spam_threshold),
'metrics', coalesce(
(select jsonb_agg(to_jsonb(metrics) order by channel_name) from metrics),
'[]'::jsonb
),
'samples', coalesce(
(select jsonb_agg(to_jsonb(samples) order by sample_type, article_created_at desc) from samples),
'[]'::jsonb
)
)
) as topic_channel_spam_audit;
"
exit 0
fi

if [ "${{ inputs.include_decision_report }}" = "true" ]; then
DECISION_REPORT_SQL='decision_report'
else
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