generated from coulomb/repo-seed
Bernd Worsch
0f505feb2d
Closes the long-range feedback loop: outcome signals now enrich the full
traceability chain and feed back into routing, triage, and AI proposals.
Schema (T01):
- outcome_correlations (CHECK correlation_type)
- pattern_performance_records
- adaptive_threshold_configs
- institutional_knowledge_entries (GIN tsvector FTS)
- learning_insights (CHECK insight_type)
- ALTER TABLE decision_records + requirement_candidates: outcome_summary JSONB
- AFTER INSERT trigger trg_enrich_lineage on outcome_signals
- contracts/core/ updated (outcome-summary-columns-v1, append-only addendum)
Correlation engine (T02):
- Application/Helper/CorrelationEngine.hs: pure annotation→outcome SQL
- Web/Controller/OutcomeCorrelations.hs: ComputeCorrelationsAction + index
Pattern performance (T03):
- Web/Controller/PatternPerformance.hs: ComputePatternPerformanceAction
Adaptive thresholds (T04):
- Web/Controller/AdaptiveThresholds.hs: CalibrateThresholdsAction
- Application/Helper/FrictionScore.hs: applyAdaptiveWeights
Institutional knowledge (T05):
- DistilDecisionAction in DecisionRecords controller
- Web/Controller/InstitutionalKnowledge.hs: QueryKnowledgeBaseAction
Lineage enrichment (T06):
- Web/Controller/LineageEnrichment.hs: EnrichLineageAction (batch backfill)
- enrich_lineage_on_outcome_batch() PL/pgSQL helper in migration
Learning dashboard (T07):
- Web/Controller/LearningDashboard.hs: 5-panel autoRefresh view
- "Learning" nav link in FrontController
API v2 learning endpoints (T08):
- GET /api/v2/outcome-correlations, /pattern-performance, /knowledge-base/{id}
- OpenAPI schemas: OutcomeCorrelation, PatternPerformanceRecord, InstitutionalKnowledgeEntry
GAAF scorecard + docs (T09):
- Core 3.8→3.9, Functional 3.6→3.8, overall 3.61→3.68
- CLAUDE.md: IHF v0.2 complete, no active workplan
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
87 lines
3.6 KiB
Haskell
87 lines
3.6 KiB
Haskell
module Web.Controller.AdaptiveThresholds where
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-- IHF Phase 12 — Platform Memory (IHUB-WP-0013 T04)
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import Web.Controller.Prelude
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import Web.View.AdaptiveThresholds.Index
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import IHP.ModelSupport (sqlQuery)
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import Database.PostgreSQL.Simple (Only(..))
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instance Controller AdaptiveThresholdsController where
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beforeAction = ensureIsUser
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action AdaptiveThresholdsAction = do
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hubs <- query @Hub |> orderByAsc #name |> fetch
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configs <- query @AdaptiveThresholdConfig |> fetch
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insights <- query @LearningInsight
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|> filterWhere (#insightType, "threshold_calibration")
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|> orderByDesc #computedAt
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|> limit 10
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|> fetch
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render IndexView { hubs, configs, insights }
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action CalibrateThresholdsAction { hubIdForThreshold } = do
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let hubId = hubIdForThreshold
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-- Step 1: find weak-predictor categories (score < 0.3)
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weakCats <- sqlQuery
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"SELECT annotation_category FROM outcome_correlations \
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\ WHERE hub_id = ? AND correlation_score < 0.3"
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[hubId]
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:: IO [Only Text]
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-- Step 2: compute bottleneck threshold override = mean friction score
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-- for widgets with at least one negative outcome signal
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[Only mBottleneckOverride] <- sqlQuery
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"SELECT AVG(fs.score) \
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\ FROM friction_scores fs \
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\ JOIN widgets w ON w.id = fs.widget_id \
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\ WHERE w.hub_id = ? \
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\ AND EXISTS ( \
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\ SELECT 1 FROM outcome_signals os \
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\ JOIN deployment_records dep ON dep.id = os.deployment_id \
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\ JOIN decision_records dr ON dr.id = dep.decision_id \
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\ JOIN requirements r ON r.id = dr.requirement_id \
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\ JOIN requirement_candidates rc ON rc.id = r.candidate_id \
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\ WHERE rc.source_widget_id = w.id \
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\ AND os.signal_type NOT IN ('success','adoption','satisfaction') \
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\ )"
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[hubId]
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:: IO [Only (Maybe Double)]
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now <- getCurrentTime
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let weakNote = "Weak predictor categories (score < 0.3): "
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<> intercalate ", " (map fromOnly weakCats)
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-- Step 3: upsert AdaptiveThresholdConfig
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existing <- query @AdaptiveThresholdConfig
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|> filterWhere (#hubId, hubId)
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|> fetchOneOrNothing
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case existing of
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Just cfg ->
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cfg
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|> set #bottleneckThresholdOverride mBottleneckOverride
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|> set #calibrationDate now
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|> set #notes (Just weakNote)
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|> updateRecord
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Nothing ->
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newRecord @AdaptiveThresholdConfig
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|> set #hubId hubId
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|> set #weightOverrides (A.Object mempty)
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|> set #bottleneckThresholdOverride mBottleneckOverride
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|> set #calibrationDate now
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|> set #notes (Just weakNote)
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|> createRecord
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-- Step 4: write LearningInsight
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newRecord @LearningInsight
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|> set #hubId hubId
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|> set #insightType "threshold_calibration"
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|> set #title "Adaptive threshold calibration completed"
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|> set #body ("Calibrated friction thresholds. " <> weakNote
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<> maybe "" (\b -> " Bottleneck override: " <> show b) mBottleneckOverride)
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|> set #evidenceLinks (A.toJSON ([] :: [A.Value]))
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|> createRecord
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setSuccessMessage "Threshold calibration complete"
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redirectTo AdaptiveThresholdsAction
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