from typing import List
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.workflow import Loop
from agno.workflow.step import Step
from agno.workflow.types import StepOutput
from agno.workflow.workflow import Workflow
def is_detailed_enough(outputs: List[StepOutput]) -> bool:
"""End the loop when the output is sufficiently detailed (> 200 chars)."""
if not outputs:
return False
last = outputs[-1]
return last.content is not None and len(str(last.content)) > 200
# Inner workflow: iterative research
researcher = Agent(
name="Iterative Researcher",
model=OpenAIChat(id="gpt-4o-mini"),
instructions=(
"You are a researcher. Each iteration, expand on the previous research "
"with more detail and specifics. Build on what was already written."
),
)
inner_workflow = Workflow(
name="Iterative Research",
description="Researches a topic in iterative passes until sufficiently detailed",
steps=[
Loop(
name="research_loop",
steps=[Step(name="research_pass", agent=researcher)],
end_condition=is_detailed_enough,
max_iterations=3,
),
],
)
# Outer workflow
writer = Agent(
name="Writer",
model=OpenAIChat(id="gpt-4o-mini"),
instructions="Write a polished summary from the detailed research provided.",
)
outer_workflow = Workflow(
name="Iterative Research and Write",
description="Iteratively researches until detailed, then writes a summary",
steps=[
Step(name="research_phase", workflow=inner_workflow),
Step(name="writing_phase", agent=writer),
],
)
if __name__ == "__main__":
outer_workflow.print_response(
input="Explain how neural networks learn",
stream=True,
)
