Commit graph

7 commits

Author SHA1 Message Date
2375e073ba feat(pipeline): add TURNSTONE_CLASSIFIER_MODEL env var for Stage 2 ML config
Makes the HuggingFace classifier model for Stage 2 configurable via
TURNSTONE_CLASSIFIER_MODEL. When unset (default), Stage 2 falls back
to pattern_tags then regex — no download required on first run.

Also documents TURNSTONE_MULTI_AGENT_DIAGNOSE, TURNSTONE_CLASSIFIER_MODEL,
TURNSTONE_EMBED_BACKEND/MODEL/DEVICE in .env.example.
2026-05-25 19:11:32 -07:00
85e7a70536 refactor: pipeline cleanup — 6 follow-up fixes (#33-#38)
- #33: Wrap ClassifiedTimeline.cluster_severities in MappingProxyType for
  true immutability (frozen=True only blocks field reassignment, not dict
  mutation).

- #34: Remove dead suppression branch in synthesizer._build_hypothesis_block.
  active[] is already filtered to not rh.suppress, so the 'Yes — suppressed'
  branch was unreachable. Now shows novelty score only.

- #35: Extract shared _llm_client.py with call_llm() + extract_content() +
  strip_json_fences(). Both RootCauseHypothesizer and SummarySynthesizer
  now import from one source. Also strips JSON fences from LLM output before
  parsing in hypothesizer._parse_response.

- #36: Add per-stage try/except in pipeline.run_pipeline(). Unhandled
  stage exceptions now emit {type: 'error'} + {type: 'done'} SSE events
  instead of silently closing the stream.

- #37: Move format_context_block() call inside the legacy LLM branch in
  diagnose/__init__.py — it was being computed unconditionally but only
  used in the non-pipeline path.

- #38: Coerce supporting_cluster_ids items to str() in hypothesizer
  _parse_response to guard against LLMs returning integers instead of
  string cluster IDs.
2026-05-25 19:05:56 -07:00
1b949337da fix: tighten suppression_reason display guard, document unused since/until params 2026-05-25 15:02:48 -07:00
1865ba1f02 feat: Stage 5 synthesizer + pipeline orchestrator + feature flag wiring (issue #29)
- Add app/services/diagnose/synthesizer.py: SummarySynthesizer (Stage 5)
  - Builds structured LLM prompt from ranked hypotheses, timeline, RAG context
  - Excludes suppressed hypotheses from the narrative prompt
  - Deterministic fallback when no LLM configured or LLM call fails
  - Same cf-orch task endpoint + direct OpenAI-compat fallback pattern as other stages

- Replace pipeline.py stub with full run_pipeline() async generator
  - Orchestrates all 5 stages via asyncio.to_thread for each synchronous stage
  - Yields typed SSE event dicts: status, pipeline_stage (1-4), hypotheses, reasoning, done
  - Suppressor counts (active vs suppressed) reported in stage 4 event message

- Wire MULTI_AGENT_ENABLED feature flag into diagnose_stream()
  - TURNSTONE_MULTI_AGENT_DIAGNOSE=true routes through run_pipeline()
  - pipeline emits its own done event; legacy path unchanged when flag is false
  - Import of run_pipeline added to __init__.py

- Add 21 new tests (350 -> 371 passing):
  - tests/test_diagnose_synthesizer.py: 8 tests (with/without LLM, suppressed,
    empty ranked, LLM failure fallback)
  - tests/test_diagnose_pipeline.py: 13 tests (flag off, flag on event sequence,
    empty entries, no LLM, stage 1 cluster count message)

Closes: #29
2026-05-25 14:56:25 -07:00
f7429ee963 feat: Stage 1 — TimelineReconstructor for multi-agent diagnose pipeline (issue #29)
- Add app/services/diagnose/timeline.py: pure-Python TimelineReconstructor
  - Sorts entries by timestamp_iso (None entries appended at end)
  - Sliding-window clustering anchored to first entry in each cluster
  - Computes cluster_id (sha1[:12]), severity (highest wins), burst flag,
    gap_before_seconds, representative_text (highest rank, longest text tiebreak)
  - Builds TimelineResult with dominant_sources sorted by entry count descending
- Update pipeline.py stub to import TimelineReconstructor (Task 6 wiring prep)
- Add tests/test_diagnose_timeline.py: 15 tests covering all 13 required cases
  plus null-timestamp edge case variant; all 318 tests passing

Closes: #29
2026-05-25 12:54:15 -07:00
afab3ca869 fix: frozen dataclasses, clean __all__, improve exception logging in diagnose package 2026-05-25 12:31:07 -07:00
da28757a20 refactor: convert diagnose module to package for multi-agent pipeline (issue #29)
- Move app/services/diagnose.py verbatim to app/services/diagnose/legacy.py
- Create app/services/diagnose/__init__.py with full implementation so that
  patch('app.services.diagnose._HAS_DATEPARSER') targets the correct namespace
  and all 303 existing tests continue to pass without modification
- Add app/services/diagnose/models.py with 5 pipeline dataclasses:
  EventCluster, TimelineResult, ClassifiedTimeline, Hypothesis, RankedHypothesis
- Add app/services/diagnose/pipeline.py with run_pipeline() stub (Task 6)
- Add MULTI_AGENT_ENABLED feature flag (off by default via env var)
- Zero behavior change; ruff clean

Closes: #29
2026-05-25 11:12:39 -07:00