feat: coverage V2 - historical evidence miner, KB evidence model + promotion audit + revalidation, Kodebar/OSCBR limits, KB/provider panel, seed import; 1.3.2 (Hub only)

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

central/app/enrichment/observability.py

@@ -39,6 +39,8 @@ def provider_sources(session, providers=None) -> list[dict]:
             "latency_ms": state.last_latency_ms if state else None,
             "cache_hit_rate": round(100 * usage.cache_hits / lookups) if usage and lookups else None,
             "errors": usage.errors if usage else 0, "rate_limited": usage.rate_limited if usage else 0,
+            "found_today": usage.found if usage else 0, "ncm_found_today": usage.ncm_found if usage else 0, "cache_hits": usage.cache_hits if usage else 0,
+            "next_reset": _aware(state.reset_at) if state and state.reset_at else None, "identity_only": not getattr(provider, "provides_ncm", False),
         })
     return rows
 
@@ -80,3 +82,24 @@ def coverage_metrics(session) -> dict:
             "NCM_AUTO_FILL_SAFE_RATE": rate(auto_ncm), "NAME_ONLY_RESOLUTION_RATE": rate(states.get("EXACT_KB_NAME_VERIFIED", 0)), "AMBIGUOUS_RATE": rate(states.get("AMBIGUOUS", 0)),
             "CONFLICT_RATE": rate(states.get("CONFLICT", 0)), "PROVIDER_QUOTA_BLOCK_RATE": round(100 * limited / requests, 1) if requests else None, "states": states, "by_status": by,
             "provider_cache_entries": session.scalar(select(func.count()).select_from(GtinLookupCache)) or 0, "provider_cache_hit_rate": round(100 * hits / (hits + misses), 1) if (hits + misses) else None}
+
+
+def kb_summary(session) -> dict:
+    """Compact Knowledge Base panel: known products, statuses of the NCM knowledge, hits today, and the latest conflicts with their evidence (no dashboard of its own)."""
+    from ..models import KbKnowledge, KbProduct
+    today = datetime.now(timezone.utc).strftime("%Y-%m-%d")
+    products = session.scalar(select(func.count()).select_from(KbProduct).where(KbProduct.gtin.is_not(None))) or 0
+    by = dict(session.execute(select(KbKnowledge.status, func.count(func.distinct(KbKnowledge.kb_product_id))).where(KbKnowledge.knowledge_key == "ncm").group_by(KbKnowledge.status)).all())
+    hits = session.scalar(select(func.coalesce(func.sum(ProviderUsageDaily.kb_hits), 0)).where(ProviderUsageDaily.day == today)) or 0
+    conflicts = []
+    rows = session.scalars(select(KbKnowledge).where(KbKnowledge.knowledge_key == "ncm", KbKnowledge.status == "CONFLICT").order_by(KbKnowledge.id.desc()).limit(60)).all()
+    grouped = {}
+    for r in rows:
+        grouped.setdefault(r.kb_product_id, []).append(r)
+    for pid, items in list(grouped.items())[:5]:
+        prod = session.get(KbProduct, pid)
+        conflicts.append({"gtin": (prod.gtin or "")[-13:], "description": (prod.normalized_description or "")[:60],
+                          "candidates": [{"ncm": i.value, "clients": sorted({c for c in (i.evidence or {}).get("clients", [])}), "documents": sum(int(l.get("docs", 0)) for l in ((i.evidence or {}).get("lineages") or {}).values()),
+                                          "providers": sorted(f for f in ((i.evidence or {}).get("families") or {}) if f.startswith("PROVIDER:"))} for i in items]})
+    return {"products": products, "verified": by.get("VERIFIED_KB", 0), "corroborated": by.get("CORROBORATED", 0) + by.get("EXTERNAL_CORROBORATED", 0), "observed": by.get("OBSERVED", 0),
+            "conflicts": by.get("CONFLICT", 0), "stale": by.get("STALE", 0), "hits_today": hits, "recent_conflicts": conflicts}