diff --git a/tests/structs/test_majority_voting.py b/tests/structs/test_majority_voting.py
index 709946f9..1ee8fea3 100644
--- a/tests/structs/test_majority_voting.py
+++ b/tests/structs/test_majority_voting.py
@@ -151,51 +151,60 @@ async def test_majority_voting_run_asynchronous(mocker):
     # Assert majority vote is correct
     assert majority_vote is not None
 
-def test_streaming_majority_voting(agent_name: str, chunk: str, is_final: bool):
-    # Chunk buffer static per call (reset each session)
-    if not hasattr(streaming_callback, "_buffer"):
-        streaming_callback._buffer = ""
-        streaming_callback._buffer_size = 0
-
-    min_chunk_size = 512  # or any large chunk size you want
-
-    if chunk:
-        streaming_callback._buffer += chunk
-        streaming_callback._buffer_size += len(chunk)
-    if streaming_callback._buffer_size >= min_chunk_size or is_final:
-        if streaming_callback._buffer:
-            print(streaming_callback._buffer, end="", flush=True)
+def test_streaming_majority_voting():
+    """
+    Test the streaming_majority_voting with logging/try-except and assertion.
+    """
+    logs = []
+    def streaming_callback(agent_name: str, chunk: str, is_final: bool):
+        # Chunk buffer static per call (reset each session)
+        if not hasattr(streaming_callback, "_buffer"):
             streaming_callback._buffer = ""
             streaming_callback._buffer_size = 0
-    if is_final:
-        print()
-
-    load_dotenv()
-    
-    
-    # Initialize the agent
-    agent = Agent(
-        agent_name="Financial-Analysis-Agent",
-        agent_description="Personal finance advisor agent",
-        system_prompt=FINANCIAL_AGENT_SYS_PROMPT,
-        max_loops=1,
-        model_name="gpt-4.1",
-        dynamic_temperature_enabled=True,
-        user_name="swarms_corp",
-        retry_attempts=3,
-        context_length=8192,
-        return_step_meta=False,
-        output_type="str",  # "json", "dict", "csv" OR "string" "yaml" and
-        auto_generate_prompt=False,  # Auto generate prompt for the agent based on name, description, and system prompt, task
-        max_tokens=4000,  # max output tokens
-        saved_state_path="agent_00.json",
-        interactive=False,
-        streaming_on=True,  #if concurrent agents want to be streamed
-    )
-    
-    swarm = MajorityVoting(agents=[agent, agent, agent])
-    
-    return swarm.run(
-        "Create a table of super high growth opportunities for AI. I have $40k to invest in ETFs, index funds, and more. Please create a table in markdown.",
-        streaming_callback=streaming_callback,
-    )
+
+        min_chunk_size = 512  # or any large chunk size you want
+
+        if chunk:
+            streaming_callback._buffer += chunk
+            streaming_callback._buffer_size += len(chunk)
+        if streaming_callback._buffer_size >= min_chunk_size or is_final:
+            if streaming_callback._buffer:
+                print(streaming_callback._buffer, end="", flush=True)
+                logs.append(streaming_callback._buffer)
+                streaming_callback._buffer = ""
+                streaming_callback._buffer_size = 0
+        if is_final:
+            print()
+     
+    try:
+        # Initialize the agent
+        agent = Agent(
+            agent_name="Financial-Analysis-Agent",
+            agent_description="Personal finance advisor agent",
+            system_prompt="You are a financial analysis agent.",  # replaced missing const
+            max_loops=1,
+            model_name="gpt-4.1",
+            dynamic_temperature_enabled=True,
+            user_name="swarms_corp",
+            retry_attempts=3,
+            context_length=8192,
+            return_step_meta=False,
+            output_type="str",  # "json", "dict", "csv" OR "string" "yaml" and
+            auto_generate_prompt=False,  # Auto generate prompt for the agent based on name, description, and system prompt, task
+            max_tokens=4000,  # max output tokens
+            saved_state_path="agent_00.json",
+            interactive=False,
+            streaming_on=True,  #if concurrent agents want to be streamed
+        )
+        
+        swarm = MajorityVoting(agents=[agent, agent, agent])
+        
+        result = swarm.run(
+            "Create a table of super high growth opportunities for AI. I have $40k to invest in ETFs, index funds, and more. Please create a table in markdown.",
+            streaming_callback=streaming_callback,
+        )
+        assert result is not None
+    except Exception as e:
+        print("Error in test_streaming_majority_voting:", e)
+        print("Logs so far:", logs)
+        raise