add like neo4j filter

Author: wustzdy

examples/basic_modules/neo4j_search.py

@@ -1091,11 +1091,16 @@ def test_get_by_metadata(graph, filters: list[dict], user_name: str, filter_exam
 
     # Example filter for testing - common filter used by multiple tests
     filter_example = {
+        # "and": [
+        #     {"id": "cfe42bd6-ee78-4f6f-b997-8baa0ea957e1"},
+        #     {"A": "中国广西"},
+        #     {"created_at": {"gt": "2025-09-19"}},
+        #     {"created_at": {"lt": "2025-11-26"}},
+        #     {"tags": {"contains": "mode:fast"}},
+        #     {"user_name": {"like": "1744"}},
+        # ]
         "and": [
-            {"id": "cfe42bd6-ee78-4f6f-b997-8baa0ea957e1"},
-            {"A": "中国广西"},
-            {"created_at": {"gt": "2025-09-19"}},
-            {"created_at": {"lt": "2025-11-26"}}
+            {"created_at": {"gt": "2025-11-26"}}
         ]
     }
     knowledgebase_ids = ["adimin1", "adimin2"]
@@ -1111,5 +1116,5 @@ def test_get_by_metadata(graph, filters: list[dict], user_name: str, filter_exam
     user_name = "memosfeebbc2bd1744d7bb5b5ec57f38e828d"
     scope = "LongTermMemory"
     # test_search_by_embedding(graph, vector, user_name, filter_example,knowledgebase_ids)
-    # test_get_all_memory_items(graph, scope, user_name, filter_example, knowledgebase_ids)
-    test_get_by_metadata(graph, filters_example, user_name, filter_example, knowledgebase_ids)
+    test_get_all_memory_items(graph, scope, user_name, filter_example, knowledgebase_ids)
+    # test_get_by_metadata(graph, filters_example, user_name, filter_example, knowledgebase_ids)

examples/basic_modules/polardb_search.py

@@ -1272,17 +1272,28 @@ def test_get_by_metadata(graph, filters: list[dict], user_name: str, filter: Opt
     ]
     # Example filter for testing - common filter used by multiple tests
     filter_example = {
+        # "and": [
+        #     {"id": "45a4f936-2182-44c6-8c4f-4a9476941e51"},
+        #     {
+        #         "A": "中国广西"
+        #     },
+        #     {
+        #         "B": "狗肉"
+        #     },
+        #     {"created_at":{"gt":"2025-09-19"}},
+        #     {"created_at": {"lt": "2025-11-26"}},
+        #     {"tags": {"contains": "test:zdy"}},
+        #     {"user_name": {"like": "828"}},
+        #     {"memory_type": {"like": "WorkingMemory"}},
+        # ]
         "and": [
             {"id": "45a4f936-2182-44c6-8c4f-4a9476941e51"},
-            {
-                "A": "中国广西"
-            },
-            {
-                "B": "狗肉"
-            },
-            {"created_at":{"gt":"2025-09-19"}},
+            {"A": "中国广西"},
+            {"created_at": {"gt": "2025-09-19"}},
             {"created_at": {"lt": "2025-11-26"}},
-            # {"tags": {"=": "mode:fast"}}
+            {"tags": {"contains": "test:zdy"}},
+            {"user_name": {"like": "828"}},
+            {"memory_type": {"like": "WorkingMemory"}},
         ]
     }
 
@@ -1298,8 +1309,9 @@ def test_get_by_metadata(graph, filters: list[dict], user_name: str, filter: Opt
     knowledgebase_ids = ["memosfeebbc2bd1744d7bb5b5ec57f38e828d","adimin2"]
 
     # Run all tests - uncomment the test you want to run
-    test_search_by_embedding(graph, vector, user_name, filter_example,knowledgebase_ids)
+    # test_search_by_embedding(graph, vector, user_name, filter_example,knowledgebase_ids)
     # test_get_all_memory_items(graph, "WorkingMemory", False, user_name, filter_example,knowledgebase_ids)
+    test_get_by_metadata(graph, filters_example, user_name, filter_example,knowledgebase_ids)
     # test_get_by_metadata(graph, filters_example, user_name, filter_example,knowledgebase_ids)
 
     # Or run all tests

src/memos/graph_dbs/neo4j.py

@@ -1415,6 +1415,25 @@ def build_filter_condition(condition_dict: dict, param_counter: list) -> tuple[s
                                 condition_parts.append(f"{node_alias}.{key} {cypher_op} datetime(${param_name})")
                             else:
                                 condition_parts.append(f"{node_alias}.{key} {cypher_op} ${param_name}")
+                        elif op == "contains":
+                            # Handle contains operator (for array fields like tags, sources)
+                            param_name = f"filter_{key}_{op}_{param_counter[0]}"
+                            param_counter[0] += 1
+                            params[param_name] = op_value
+                            
+                            # For array fields, check if element is in array
+                            if key in ("tags", "sources"):
+                                condition_parts.append(f"${param_name} IN {node_alias}.{key}")
+                            else:
+                                # For non-array fields, contains might not be applicable, but we'll treat it as IN for consistency
+                                condition_parts.append(f"${param_name} IN {node_alias}.{key}")
+                        elif op == "like":
+                            # Handle like operator (for fuzzy matching, similar to SQL LIKE '%value%')
+                            # Neo4j uses CONTAINS for string matching
+                            param_name = f"filter_{key}_{op}_{param_counter[0]}"
+                            param_counter[0] += 1
+                            params[param_name] = op_value
+                            condition_parts.append(f"{node_alias}.{key} CONTAINS ${param_name}")
                 else:
                     # All fields are stored as flat properties in Neo4j (simple equality)
                     param_name = f"filter_{key}_{param_counter[0]}"