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Milestone 0.7.0: LLM MEAT extractor (Qwen/Qwen2.5-3B-Instruct + T4)β
Replaces the rule-based MEAT matcher (which couldn't follow implicit references like "Continue metformin" β TREAT-for-DM) with a small instruction-tuned LLM producing structured JSON. Component I's byte-exact substring guarantee still enforces faithfulness downstream. New - app/pipeline/components/f_meat_llm.py::LLMMEATExtractor * Lazy transformers import; CPU-only installs unaffected. * Chat-formatted prompt asking for {"M","E","A","T"} with verbatim quotes or null. * Balanced-JSON parser over the model output. * try_extract() returns None when unavailable / empty list when the LLM saw no MEAT β Composite uses the distinction. Changed - f_meat.py adds CompositeMEATExtractor and a HCC_MEAT_EXTRACTOR_BACKEND env selector. CompositeMEATExtractor only falls back to rule-based when the primary (LLM) is genuinely unavailable; empty LLM output is trusted ("LLM saw no MEAT") to avoid rule-based false positives. - app/api/server.py lifespan spawns a background thread foβ¦5eed8db -
0.6.5: Fault-tolerant startup + route guards + /api/status errorsβ
If reference CSVs are missing, the pipeline fails to import, or gallery prewarm raises, the prior lifespan would crash uvicorn and HF would return a 502 with no diagnostic path. Now each of the three startup steps (pipeline build, gallery prime, metrics snapshot) is wrapped independently β failures are logged with full tracebacks and recorded to app.state.startup_errors. /api/status surfaces the error dict so the UI banner can show exactly which facet failed. Route guards: POST /api/code and POST /api/benchmark return 503 with a pointer to /api/status when the pipeline is None, instead of crashing on AttributeError. UI: ServerStatus interface gains optional startup_errors: Record<string, string>. Tests: test_api.py adds a positive assertion that /api/status reports "ok" with the local reference data. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>14a3550 -
0.6.4: /api/status diagnostic + StatusBanner + remove unused NotePanel propβ
Runtime diagnostic - GET /api/status returns pipeline_ready, reference_counts (hcc_labels + hcc_crosswalk_icd10), gallery_size, metrics_available. Status is "ok" if everything loaded, else "degraded" with the failing facets exposed. - ui/src/components/StatusBanner.tsx renders ONLY on degraded state β rose-colored, calls out which facet is missing, points at the HF build logs. Normal OK status stays silent to avoid banner competition with the amber research-demo disclaimer. - App.tsx fetches /api/status on load alongside gallery + metrics. Cleanup - NotePanel.Props no longer declares a `result: CodingResult | null` prop it never read. App stops passing it. Strict TS stays clean. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>d0ec498 -
Initial scaffold: HCC-MEAT Coder v0.1.0β
End-to-end runnable pipeline with rule-based baselines in place of ML components, a FastAPI backend serving a React three-panel UI, and a 10-case regression suite guarding the invariants from AGENT_BRIEF.md Β§3 (faithfulness, negation/family-history filtering, hierarchy trumping, transparent risk). Deterministic components (real, tested): - E β HCC crosswalk + trumping over CMS-HCC v28 seed tables - H β over-coding (RADV) risk heuristic with named components + reasons - I β faithfulness verifier (substring guarantee + NLI hook) Baseline / swappable components: - A segmenter, B dictionary NER, C negation, D exact/alias linker, F rule-based MEAT extractor, G identity calibrator Infra: uv-driven pyproject, ruff + pytest + pre-commit, GH Actions CI for Python and UI, multi-stage Dockerfile for the HF Docker Space, typer CLIs for pipeline (`hcc-meat`) and evaluation (`hcc-meat-eval`). Reference data in data/reference/ uses PLACEHOLDER RAF weights; hydrate via scripts/fetch_cms_hcc_v28.β¦c6cfe5f