1
Create a Python file
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touch run_workflows.py
2
Add the following code to your Python file
run_workflows.py
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import asyncio
from agno.client import AgentOSClient
async def run_workflow_non_streaming():
"""Execute a non-streaming workflow run."""
print("=" * 60)
print("Non-Streaming Workflow Run")
print("=" * 60)
client = AgentOSClient(base_url="http://localhost:7777")
# Get available workflows
config = await client.aget_config()
if not config.workflows:
print("No workflows available")
return
workflow_id = config.workflows[0].id
print(f"Running workflow: {workflow_id}")
try:
result = await client.run_workflow(
workflow_id=workflow_id,
message="What are the benefits of using Python for data science?",
)
print(f"\nRun ID: {result.run_id}")
print(f"Content: {result.content}")
except Exception as e:
print(f"Error: {e}")
async def run_workflow_streaming():
"""Execute a streaming workflow run."""
print("\n" + "=" * 60)
print("Streaming Workflow Run")
print("=" * 60)
client = AgentOSClient(base_url="http://localhost:7777")
# Get available workflows
config = await client.aget_config()
if not config.workflows:
print("No workflows available")
return
workflow_id = config.workflows[0].id
print(f"Streaming from workflow: {workflow_id}")
print("\nResponse: ", end="", flush=True)
try:
async for event in client.run_workflow_stream(
workflow_id=workflow_id,
message="Explain machine learning in simple terms.",
):
if event.event == "RunContent" and hasattr(event, "content"):
print(event.content, end="", flush=True)
elif event.event == "WorkflowAgentCompleted" and hasattr(event, "content") and event.content:
print(event.content, end="", flush=True)
print("\n")
except Exception as e:
print(f"\nError: {type(e).__name__}: {e}")
async def main():
await run_workflow_non_streaming()
await run_workflow_streaming()
if __name__ == "__main__":
asyncio.run(main())
3
Create a virtual environment
Open the
Terminal and create a python virtual environment.Copy
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python3 -m venv .venv
source .venv/bin/activate
4
Install libraries
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pip install -U agno openai
5
Export your OpenAI API key
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export OPENAI_API_KEY="your_openai_api_key_here"
6
Start an AgentOS Server
Make sure you have an AgentOS server running with workflows configured. See Creating Your First OS for setup instructions.
7
Run the Client
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python run_workflows.py