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feat(trials): replace hardcoded entity regex with LLM extraction
KevinIsInCoding +1: Claude Sonnet 4.6- Remove _KNOWN_TARGETS regex list — cannot handle novel compounds like AMX0114 - Add extract_target_entities_llm(): batches 10 trials per Claude Haiku call, extracts biological target (gene/protein) not drug name, canonicalizes via extraction/normalizer. AMX0114 now correctly maps to TARDBP. - Add data/tools/extract_trial_targets.json tool schema - Add TRIAL_EXTRACTION_TOOLS export to tools.py - Widen default status filter from RECRUITING-only to also include NOT_YET_RECRUITING and ACTIVE_NOT_RECRUITING - ingest_trials.py: --status now accepts multiple values; creates Anthropic client and passes it to fetch_als_trials() Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>0569d05
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feat: initial project scaffold and Stage 2 ingestion pipeline
KevinIsInCoding +1: Claude Sonnet 4.6- Project foundation: config, models, tools, llm, logging, prompts - Tool schemas: extract_entities.json, search_landscape.json - Stage 2 ingestion: - ingestion/pubmed.py: PubMed Entrez client (batch fetch, rate-limit aware) - ingestion/pmc.py: PMC XML full-text fetcher (JATS section parser) - ingestion/semantic_scholar.py: citation count enrichment via S2 batch API - ingestion/clinicaltrials.py: ClinicalTrials.gov v2 ALS trials client - scripts/ingest_papers.py: orchestrates PubMed + PMC + citations - scripts/ingest_trials.py: fetches recruiting ALS trials - Stub modules for Stage 3-5 (rag/, graph/, agents/, app.py, main.py) - MIT License, .gitignore (excludes data/, .env, logs/) - CLAUDE.md architecture guide Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>0ccfe4a