Change recall computation to be as ann-benchmarks'

Author: alonre24

engine/base_client/search.py

@@ -50,9 +50,17 @@ def _search_one(cls, query, top: Optional[int] = None):
 
         precision = 1.0
         if query.expected_result:
-            ids = set(x[0] for x in search_res)
-            precision = len(ids.intersection(query.expected_result[:top])) / top
-
+            # This was Qdrant original recall calculation
+            # ids = set(x[0] for x in search_res)
+            # precision = len(ids.intersection(query.expected_result[:top])) / top
+            # This is ann-benchmark recall calculation
+            epsilon = 1e-3
+            threshold = query.expected_scores[top - 1] + epsilon
+            actual = 0.0
+            for cand_res in search_res[:top]:
+                if cand_res[1] <= threshold:
+                    actual += 1
+            precision = actual/top
         return precision, end - start
 
     def search_all(