Example Use-Cases: Content type routing, topic-specific processing, quality-based decisions Conditional workflows provide predictable branching logic while maintaining deterministic execution paths. Workflows condition steps diagram

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Example

conditional_workflow.py
from agno.workflow import Condition, Step, Workflow

def is_tech_topic(step_input) -> bool:
    topic = step_input.input.lower()
    return any(keyword in topic for keyword in ["ai", "tech", "software"])

workflow = Workflow(
    name="Conditional Research",
    steps=[
        Condition(
            name="Tech Topic Check",
            evaluator=is_tech_topic,
            steps=[Step(name="Tech Research", agent=tech_researcher)]
        ),
        Step(name="General Analysis", agent=general_analyst),
    ]
)

workflow.print_response("Comprehensive analysis of AI and machine learning trends", markdown=True)

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Developer Resources

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Reference

For complete API documentation, see Condition Steps Reference.