2 commits

Author	SHA1	Message	Date
pyr0ball	e8c66972fa	fix: defensive coercion for LLM confidence and cluster fields in hypothesizer ... - Add _coerce_float() module-level helper: catches TypeError/ValueError from non-numeric LLM output (e.g. 'high', 'N/A') and returns a caller-supplied default instead of raising. - Replace float(item.get('confidence', 0.5)) with _coerce_float(item.get('confidence'), 0.5) in _parse_response. - Guard supporting_cluster_ids: tuple(item.get(...) or []) so a JSON null from the LLM does not cause TypeError('NoneType is not iterable'). - runbook_refs is hardcoded as () and not sourced from LLM output; no change needed there. - Add test_non_numeric_confidence_uses_default (Test 10) to cover the 'high' string case: asserts no exception and confidence == 0.5. - 341 tests passing (+1). Closes: #29	2026-05-25 14:00:30 -07:00
pyr0ball	eefd65f903	feat: Stage 3 — RootCauseHypothesizer for multi-agent diagnose pipeline (issue #29) ... - Add app/services/diagnose/hypothesizer.py with RootCauseHypothesizer class - Stage 3 of the multi-agent diagnose pipeline: accepts ClassifiedTimeline + RetrievedContext, builds a structured JSON prompt, calls the LLM via the same cf-orch task → OpenAI-compat fallback pattern used by llm.py - Parses JSON array response into list[Hypothesis] dataclasses with UUID ids, severity validation (WARNING→WARN, unknown→ERROR), confidence coercion - Gracefully returns [] when llm_url/llm_model absent or clusters empty - Add tests/test_diagnose_hypothesizer.py: 12 tests, all mocked, no LLM I/O covering: valid response, UUID generation, malformed JSON, non-list JSON, empty clusters, missing URL/model, max_hypotheses cap, severity mapping, confidence string coercion - 340 tests passing (328 prior + 12 new) Closes: #29	2026-05-25 13:49:18 -07:00