Loop to repeat steps until they produce what you need. An end condition checks
each iteration’s output, and max_iterations caps how many times the loop can run.
When to use: Iterative refinement, research gathering, or another process whose
end condition depends on the generated content.
Install dependencies:
uv pip install agno openai ddgs
loop_steps_workflow.py
from typing import List
from agno.agent import Agent
from agno.tools.hackernews import HackerNewsTools
from agno.tools.websearch import WebSearchTools
from agno.workflow import Loop, Step, Workflow
from agno.workflow.types import StepOutput
# Create agents for research
research_agent = Agent(
name="Research Agent",
role="Research specialist",
tools=[HackerNewsTools(), WebSearchTools()],
instructions="You are a research specialist. Research the given topic thoroughly.",
markdown=True,
)
content_agent = Agent(
name="Content Agent",
role="Content creator",
instructions="You are a content creator. Create engaging content based on research.",
markdown=True,
)
# Create research steps
research_hackernews_step = Step(
name="Research HackerNews",
agent=research_agent,
description="Research trending topics on HackerNews",
)
research_web_step = Step(
name="Research Web",
agent=research_agent,
description="Research additional information from web sources",
)
content_step = Step(
name="Create Content",
agent=content_agent,
description="Create content based on research findings",
)
# End condition function
def research_evaluator(outputs: List[StepOutput]) -> bool:
"""
Evaluate if research results are sufficient
Returns True to break the loop, False to continue
"""
# Check if any outputs are present
if not outputs:
return False
# Check if any output contains substantial content
for output in outputs:
if output.content and len(output.content) > 200:
print(
f"Research evaluation passed - found substantial content ({len(output.content)} chars)"
)
return True
print("Research evaluation failed - need more substantial research")
return False
# Create workflow with loop
workflow = Workflow(
name="Research and Content Workflow",
description="Research topics in a loop until conditions are met, then create content",
steps=[
Loop(
name="Research Loop",
steps=[research_hackernews_step, research_web_step],
end_condition=research_evaluator,
max_iterations=3, # Maximum 3 iterations
),
content_step,
],
)
if __name__ == "__main__":
# Test the workflow
workflow.print_response(
input="Research the latest trends in AI and machine learning, then create a summary",
)