Three-path classification: ML (transformers pipeline, lazy singleton) →
pattern_tags (YAML pattern severity dict) → regex (detect_severity).
- Path A: HF text-classification pipeline loaded lazily on first classify()
call via module-level singleton; shim promotes ERROR+keyword hits to CRITICAL
and demotes low-confidence INFO to DEBUG.
- Path B: maps cluster.pattern_tags through the loaded pattern severity dict;
picks the highest severity across matching tags.
- Path C: falls back to detect_severity() regex scan on representative_text;
defaults to INFO when no keyword matches.
- Pattern file resolved from constructor arg or TURNSTONE_PATTERNS env var
(mirrors app/rest.py convention).
- No crash when transformers is not installed; ImportError on per-cluster ML
inference triggers clean per-cluster fallback to pattern_tags/regex.
- ClassifiedTimeline.classifier_used reflects the primary session path.
Tests (10 new, 328 total, all passing):
- ML ERROR, CRITICAL promotion, DEBUG demotion, WARNING→WARN
- pattern_tags resolution from YAML fixture
- regex ERROR detection and INFO default
- ImportError clean fallback
- empty timeline no-crash
- ClassifiedTimeline FrozenInstanceError on mutation
Closes: #29
pyr0ball
5c95bc0e96