feat: add autonomous fiscal completion v1

central/app/evidence_aggregation.py

@@ -0,0 +1,47 @@
+"""Conservative aggregation of supplier/document observations."""
+
+from dataclasses import dataclass
+from collections import defaultdict
+from typing import Any, Iterable
+
+
+@dataclass(frozen=True)
+class Observation:
+    product_id: str
+    attribute: str
+    value: str
+    supplier_id: str
+    document_id: str
+    observed_at: str
+    provenance: str = "SUPPLIER_OBSERVATION"
+
+
+def aggregate_observations(observations: Iterable[Observation]) -> dict[tuple[str, str], dict[str, Any]]:
+    grouped: dict[tuple[str, str], list[Observation]] = defaultdict(list)
+    seen: set[tuple[str, str, str, str]] = set()
+    for observation in observations:
+        key = (observation.product_id, observation.attribute)
+        dedupe = (observation.product_id, observation.attribute, observation.supplier_id, observation.document_id)
+        if dedupe not in seen and observation.value not in (None, ""):
+            grouped[key].append(observation)
+            seen.add(dedupe)
+
+    output = {}
+    for key, rows in grouped.items():
+        values = {row.value for row in rows}
+        counts = {value: sum(row.value == value for row in rows) for value in values}
+        supplier_count = len({row.supplier_id for row in rows})
+        agreement_rate = max(counts.values()) / len(rows) if rows else 0.0
+        conflict_count = max(0, len(values) - 1)
+        strong = len(rows) >= 2 and supplier_count >= 2 and len(values) == 1
+        output[key] = {
+            "value": next(iter(values)) if strong else None,
+            "observation_count": len(rows),
+            "supplier_count": supplier_count,
+            "agreement_rate": agreement_rate,
+            "latest_observation": max(row.observed_at for row in rows),
+            "conflict_count": conflict_count,
+            "strong_evidence": strong,
+            "provenance": sorted({row.provenance for row in rows}),
+        }
+    return output