diff --git a/tests/agent_test.py b/tests/agent_test.py
index 048cc4807..6879a4519 100644
--- a/tests/agent_test.py
+++ b/tests/agent_test.py
@@ -1592,7 +1592,7 @@ def test_agent_execute_task_with_ollama():
     assert "AI" in result or "artificial intelligence" in result.lower()
 
 
-# @pytest.mark.vcr(filter_headers=["authorization"])
+@pytest.mark.vcr(filter_headers=["authorization"])
 def test_agent_with_knowledge_sources():
     # Create a knowledge source with some content
     content = "Brandon's favorite color is red and he likes Mexican food."
diff --git a/tests/cassettes/test_agent_with_knowledge_sources.yaml b/tests/cassettes/test_agent_with_knowledge_sources.yaml
index 066a6b4f5..bb9e6255f 100644
--- a/tests/cassettes/test_agent_with_knowledge_sources.yaml
+++ b/tests/cassettes/test_agent_with_knowledge_sources.yaml
@@ -37,14 +37,14 @@ interactions:
     uri: https://api.openai.com/v1/embeddings
   response:
     content: "{\n  \"object\": \"list\",\n  \"data\": [\n    {\n      \"object\":
-      \"embedding\",\n      \"index\": 0,\n      \"embedding\": \"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\"\n
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