addressed comments

microsoft · Nov 14, 2024 · 0596755 · 0596755
1 parent 62c0161
commit 0596755
Show file tree

Hide file tree

Showing 3 changed files with 22 additions and 21 deletions.
diff --git a/python/samples/concepts/memory/new_memory.py b/python/samples/concepts/memory/new_memory.py
@@ -54,11 +54,12 @@ class DataModelArray:
                 deserialize_function=np.array,
             ),
         ] = None
-        other: str | None = None
         id: Annotated[str, VectorStoreRecordKeyField()] = field(default_factory=lambda: str(uuid4()))
         content: Annotated[
             str, VectorStoreRecordDataField(has_embedding=True, embedding_property_name="vector", property_type="str")
         ] = "content1"
+        title: Annotated[str, VectorStoreRecordDataField(property_type="str", is_full_text_searchable=True)] = "title"
+        tag: Annotated[str, VectorStoreRecordDataField(property_type="str", is_filterable=True)] = "tag"
 
     return DataModelArray
 
@@ -77,11 +78,12 @@ class DataModelList:
                 property_type="float",
             ),
         ] = None
-        other: str | None = None
         id: Annotated[str, VectorStoreRecordKeyField()] = field(default_factory=lambda: str(uuid4()))
         content: Annotated[
             str, VectorStoreRecordDataField(has_embedding=True, embedding_property_name="vector", property_type="str")
         ] = "content1"
+        title: Annotated[str, VectorStoreRecordDataField(property_type="str", is_full_text_searchable=True)] = "title"
+        tag: Annotated[str, VectorStoreRecordDataField(property_type="str", is_filterable=True)] = "tag"
 
     return DataModelList
 

diff --git a/python/semantic_kernel/connectors/memory/azure_ai_search/utils.py b/python/semantic_kernel/connectors/memory/azure_ai_search/utils.py
@@ -148,18 +148,21 @@ def data_model_definition_to_azure_ai_search_index(
             try:
                 algo_class, algo_params = INDEX_ALGORITHM_MAP[field.index_kind or "default"]
             except KeyError as e:
-                raise ServiceInitializationError(f"Error: {e} not found in INDEX_ALGORITHM_MAP.") from e
+                raise ServiceInitializationError(f"Error: {field.index_kind} not found in INDEX_ALGORITHM_MAP.") from e
             try:
-                search_algos.append(
-                    algo_class(
-                        name=algo_name,
-                        parameters=algo_params(
-                            metric=DISTANCE_FUNCTION_MAP[field.distance_function or "default"],
-                        ),
-                    )
-                )
+                distance_metric = DISTANCE_FUNCTION_MAP[field.distance_function or "default"]
             except KeyError as e:
-                raise ServiceInitializationError(f"Error: {e} not found in DISTANCE_FUNCTION_MAP.") from e
+                raise ServiceInitializationError(
+                    f"Error: {field.distance_function} not found in DISTANCE_FUNCTION_MAP."
+                ) from e
+            search_algos.append(
+                algo_class(
+                    name=algo_name,
+                    parameters=algo_params(
+                        metric=distance_metric,
+                    ),
+                )
+            )
     return SearchIndex(
         name=collection_name,
         fields=fields,

diff --git a/python/semantic_kernel/connectors/memory/redis/redis_collection.py b/python/semantic_kernel/connectors/memory/redis/redis_collection.py
@@ -467,18 +467,14 @@ def _serialize_dicts_to_store_models(
     def _deserialize_store_models_to_dicts(
         self,
         records: Sequence[dict[str, Any]],
-        keys: Sequence[str] | None = None,
         **kwargs: Any,
     ) -> Sequence[dict[str, Any]]:
-        key_field_name = self.data_model_definition.key_field_name
-        if keys is None:
-            if key_field_name in records[0]:
-                return records
-            raise MemoryConnectorException("Key field not found in records, and not supplied.")
         results = []
-        for key, record in zip(keys, records):
-            record[self.data_model_definition.key_field_name] = self._unget_redis_key(key)
-            results.append(record)
+        key_field_name = self.data_model_definition.key_field_name
+        for record in records:
+            rec = record.copy()
+            rec[key_field_name] = self._unget_redis_key(record[key_field_name])
+            results.append(rec)
         return results
 
     def _add_return_fields(self, query: TQuery, include_vectors: bool) -> TQuery: