diff --git a/examples/multi_agent/test_sequentialworkflow_streaming.py b/examples/multi_agent/test_sequentialworkflow_streaming.py
deleted file mode 100644
index 95fcf55d..00000000
--- a/examples/multi_agent/test_sequentialworkflow_streaming.py
+++ /dev/null
@@ -1,59 +0,0 @@
-from swarms.structs.agent import Agent
-from swarms.structs.sequential_workflow import SequentialWorkflow
-
-def streaming_callback(token):
-    buffer.append(token)
-    if len(buffer) >= 20 or token.endswith("\n"):
-        print("".join(buffer), end="", flush=True)
-        buffer.clear()
-
-def run_workflow_with_streaming_callback(task, streaming_callback):
-
-    agent1 = Agent(
-        name="Research Agent",
-        description="A research agent that can answer questions",
-        model_name="gpt-4o",
-        system_prompt=(
-            "You are a ResearchAgent. Your task is to research and gather "
-            "information about the given topic. Provide comprehensive research "
-            "findings and key insights."
-        ),
-        max_loops=1,
-        interactive=True,
-        verbose=True,
-    )
-
-    agent2 = Agent(
-        name="Analysis Agent",
-        description="An analysis agent that draws conclusions from research",
-        model_name="gpt-4o-mini",
-        system_prompt=(
-            "You are an AnalysisAgent. Your task is to analyze the research "
-            "provided by the previous agent and draw meaningful conclusions. "
-            "Provide detailed analysis and actionable insights."
-        ),
-        max_loops=1,
-        interactive=True,
-        verbose=True,
-    )
-
-    workflow = SequentialWorkflow(
-        id="research_analysis_workflow",
-        name="Research Analysis Workflow",
-        description="A sequential workflow that researches and analyzes topics",
-        agents=[agent1, agent2],
-        max_loops=1,
-        output_type="str",
-        streaming_callback=streaming_callback,
-        multi_agent_collab_prompt=True,
-    )
-    return workflow.run(task)
-
-if __name__ == "__main__":
-
-    buffer = []
-
-    run_workflow_with_streaming_callback(
-        task="What are the latest advancements in AI?",
-        streaming_callback=streaming_callback,
-    )
\ No newline at end of file