Enables TURNSTONE_MULTI_AGENT_DIAGNOSE and other env vars set in
.env to reach the running process without manual export. Variables
already set in the caller's environment take precedence.
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.
- #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.
