feat: initial commit - oncology literature search platform

OncoLit: a multi-tenant oncology literature search, feed, and
collaboration platform. Built with FastAPI + Vue 3 + PostgreSQL.
Includes PubMed pipeline, drug approvals, AI summaries, and
systematic review tools.

tmp_refresh_all_v2.py

@@ -0,0 +1,55 @@
+"""Run FULL citation refresh with incremental progress logging"""
+import asyncio, sys, os
+from datetime import datetime
+from sqlalchemy.ext.asyncio import create_async_engine, AsyncSession
+from sqlalchemy.orm import sessionmaker
+from sqlalchemy import select
+from app.models.literature import GlobalLiterature
+from app.services.pubmed_api import fetch_citedby_counts, update_citation_counts
+
+DATABASE_URL = 'postgresql+asyncpg://scilit:scilit_prod_2026@postgres:5432/scilit'
+
+async def main():
+    engine = create_async_engine(DATABASE_URL, pool_size=4)
+    async_session = sessionmaker(engine, class_=AsyncSession)
+
+    print(f"[{datetime.now().isoformat()}] Starting full citation refresh...", flush=True)
+
+    async with async_session() as db:
+        # Get all PMIDs
+        result = await db.execute(select(GlobalLiterature.pmid).order_by(GlobalLiterature.created_at.desc()))
+        all_pmids = [r for (r,) in result]
+        total = len(all_pmids)
+        print(f"[{datetime.now().isoformat()}] Found {total} PMIDs to process", flush=True)
+
+        # Process in chunks of 5000 (matching the admin API limit=5000 behavior)
+        BATCH = 5000
+        total_updated = 0
+        total_errors = 0
+
+        for i in range(0, len(all_pmids), BATCH):
+            batch = all_pmids[i:i+BATCH]
+            counts = await fetch_citedby_counts(batch)
+
+            async with async_session()() as s:
+                updated = 0
+                for pmid, cited in counts.items():
+                    from sqlalchemy import update as sql_update
+                    await s.execute(
+                        sql_update(GlobalLiterature)
+                        .where(GlobalLiterature.pmid == pmid)
+                        .values(cited_by_count=cited, updated_at=datetime.now())
+                    )
+                    updated += 1
+                await s.commit()
+
+            total_updated += updated
+            errors_in_batch = len(batch) - len(counts)
+            total_errors += errors_in_batch
+            pct = min(100, (i + BATCH) / total * 100)
+            print(f"[{datetime.now().isoformat()}] batch {i//BATCH+1}/{(total+BATCH-1)//BATCH}: +{updated} updated ({pct:.0f}%)", flush=True)
+
+    print(f"[{datetime.now().isoformat()}] Done. Updated: {total_updated}, Errors: {total_errors}", flush=True)
+    await engine.dispose()
+
+asyncio.run(main())