diff --git a/tests/agent_test.py b/tests/agent_test.py
index 796e651db..83e530427 100644
--- a/tests/agent_test.py
+++ b/tests/agent_test.py
@@ -1618,57 +1618,71 @@ def test_agent_with_knowledge_sources():
 def test_agent_with_knowledge_sources_with_query_limit_and_score_threshold():
     content = "Brandon's favorite color is red and he likes Mexican food."
     string_source = StringKnowledgeSource(content=content)
-    knowledge_config = KnowledgeConfig(limit=10, score_threshold=0.5)
-    with patch.object(Knowledge, "query") as mock_knowledge_query:
-        agent = Agent(
-            role="Information Agent",
-            goal="Provide information based on knowledge sources",
-            backstory="You have access to specific knowledge sources.",
-            llm=LLM(model="gpt-4o-mini"),
-            knowledge_sources=[string_source],
-            knowledge_config=knowledge_config,
-        )
-        task = Task(
-            description="What is Brandon's favorite color?",
-            expected_output="Brandon's favorite color.",
-            agent=agent,
-        )
-        crew = Crew(agents=[agent], tasks=[task])
-        crew.kickoff()
+    knowledge_config = KnowledgeConfig(results_limit=10, score_threshold=0.5)
+    with patch(
+        "crewai.knowledge.storage.knowledge_storage.KnowledgeStorage"
+    ) as MockKnowledge:
+        mock_knowledge_instance = MockKnowledge.return_value
+        mock_knowledge_instance.sources = [string_source]
+        mock_knowledge_instance.query.return_value = [{"content": content}]
+        with patch.object(Knowledge, "query") as mock_knowledge_query:
+            agent = Agent(
+                role="Information Agent",
+                goal="Provide information based on knowledge sources",
+                backstory="You have access to specific knowledge sources.",
+                llm=LLM(model="gpt-4o-mini"),
+                knowledge_sources=[string_source],
+                knowledge_config=knowledge_config,
+            )
+            task = Task(
+                description="What is Brandon's favorite color?",
+                expected_output="Brandon's favorite color.",
+                agent=agent,
+            )
+            crew = Crew(agents=[agent], tasks=[task])
+            crew.kickoff()
 
-        assert agent.knowledge is not None
-        mock_knowledge_query.assert_called_once_with(
-            [task.prompt()],
-            **knowledge_config.model_dump(),
-        )
+            assert agent.knowledge is not None
+            mock_knowledge_query.assert_called_once_with(
+                [task.prompt()],
+                **knowledge_config.model_dump(),
+            )
 
 
 def test_agent_with_knowledge_sources_with_query_limit_and_score_threshold_default():
     content = "Brandon's favorite color is red and he likes Mexican food."
     string_source = StringKnowledgeSource(content=content)
     knowledge_config = KnowledgeConfig()
-    with patch.object(Knowledge, "query") as mock_knowledge_query:
-        agent = Agent(
-            role="Information Agent",
-            goal="Provide information based on knowledge sources",
-            backstory="You have access to specific knowledge sources.",
-            llm=LLM(model="gpt-4o-mini"),
-            knowledge_sources=[string_source],
-            knowledge_config=knowledge_config,
-        )
-        task = Task(
-            description="What is Brandon's favorite color?",
-            expected_output="Brandon's favorite color.",
-            agent=agent,
-        )
-        crew = Crew(agents=[agent], tasks=[task])
-        crew.kickoff()
+    with patch(
+        "crewai.knowledge.storage.knowledge_storage.KnowledgeStorage"
+    ) as MockKnowledge:
+        mock_knowledge_instance = MockKnowledge.return_value
+        mock_knowledge_instance.sources = [string_source]
+        mock_knowledge_instance.query.return_value = [{"content": content}]
+        with patch.object(Knowledge, "query") as mock_knowledge_query:
+            string_source = StringKnowledgeSource(content=content)
+            knowledge_config = KnowledgeConfig()
+            agent = Agent(
+                role="Information Agent",
+                goal="Provide information based on knowledge sources",
+                backstory="You have access to specific knowledge sources.",
+                llm=LLM(model="gpt-4o-mini"),
+                knowledge_sources=[string_source],
+                knowledge_config=knowledge_config,
+            )
+            task = Task(
+                description="What is Brandon's favorite color?",
+                expected_output="Brandon's favorite color.",
+                agent=agent,
+            )
+            crew = Crew(agents=[agent], tasks=[task])
+            crew.kickoff()
 
-        assert agent.knowledge is not None
-        mock_knowledge_query.assert_called_once_with(
-            [task.prompt()],
-            **knowledge_config.model_dump(),
-        )
+            assert agent.knowledge is not None
+            mock_knowledge_query.assert_called_once_with(
+                [task.prompt()],
+                **knowledge_config.model_dump(),
+            )
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])