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Author SHA1 Message Date
ElebobaandClaude Opus 5.5 6a77831603 feat(llm): RAG knowledge base over clinical guidelines with cited extractive answers
CI / ruff · pytest (pull_request) Successful in 1m30s
Details 
- docs/source/rag: PDF sources (KR PTSD 2023, KR depression 2024, meds module spec),
  pdf->txt converter (tables as markdown, page markers, hand-transcribed figures),
  word-level check against pdftotext; fixes HAM-D/MADRS fake headers and split rows
- config/rag: corpus txt + sources.yaml (documents, audiences, retrieval params, synonyms)
- app/llm/rag: Snowball stemmer, section-aware chunker with page citations,
  BM25 + synonym expansion + densest-passage reranking, extractive answer()
  with coverage gate, patient dose/prescribing filter, optional LLM rephrasing
  rejected when it adds content; CLI python -m app.llm.rag
- tests: gold retrieval set (hit@3 >= 15/18), off-topic, safety, faithfulness
- ADR-011

Refs #60

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
 2026-10-04 04:11:06 +03:00
ElebobaandClaude Opus 5.5 51cc259002 feat(bot): med_qa answers about the drug only from ГРЛС excerpts
CI / ruff · pytest (pull_request) Successful in 21s
Details 
Topic from engine or keyword classifier, section via integrations.drug_info,
sentence retrieval by keyword overlap (dosing sentences dropped), LLM only
rephrases the excerpt through gateway.phrase("med_answer") with forbidden-output
and added-content guards; dose questions and missing answers -> None + fallback text.

Refs #15

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
 2026-10-03 15:32:48 +03:00
ElebobaandClaude Opus 5.5 924a51c483 feat(bot): LLM gateway with GigaChat and offline mock providers
CI / ruff · pytest (pull_request) Successful in 23s
Details 
Single entry point app/llm/gateway.py: extract_item, extract_checkin,
risk_classify, phrase, summarize_for_doctor. Two-level design:
LLMProvider (transport, GigaChat) and LLMTasks (PromptedTasks over a
provider, or rule-based MockTasks). Shared policy in the gateway:
assert_scrubbed backstop, confidence threshold 0.5, risk failure -> NONE,
forbidden-output filter with config/texts/phrases.yaml fallbacks.

Refs #7

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
 2026-10-03 15:00:41 +03:00