Create savant_wrapper.py

savant_wrapper.py

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+import numpy as np
+from geometry_audit import GeometryAuditLog
+from rrf_safe_similarity import stabilize_vector
+
+
+class SavantWrapper:
+    def __init__(
+        self,
+        embedder,
+        r_min: float = 1e-4,
+        r_max: float = 1e4,
+        enable_audit: bool = True,
+    ):
+        """
+        embedder: callable(text) -> np.ndarray
+        """
+        self.embedder = embedder
+        self.r_min = r_min
+        self.r_max = r_max
+        self.audit_log = GeometryAuditLog() if enable_audit else None
+
+        print("✅ SavantWrapper Initialized (Logarithmic Regularization Active).")
+
+    def encode(self, text: str) -> np.ndarray:
+        vec = self.embedder(text).astype(np.float64)
+
+        stabilized_vec, audit_event = stabilize_vector(
+            vec,
+            r_min=self.r_min,
+            r_max=self.r_max,
+        )
+
+        if audit_event and self.audit_log is not None:
+            self.audit_log.record(audit_event)
+
+        return stabilized_vec
+
+    def batch_encode(self, texts):
+        return np.vstack([self.encode(t) for t in texts])
+
+    def get_audit_log(self):
+        if self.audit_log is None:
+            return []
+        return self.audit_log.events