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Pass work from one agent to the next when each step depends on the previous output. 
from praisonaiagents import Agent, AgentFlow

researcher = Agent(name="Researcher", instructions="Research topics")
analyst = Agent(name="Analyst", instructions="Analyze research findings")
writer = Agent(name="Writer", instructions="Write based on analysis")
flow = AgentFlow(steps=[researcher, analyst, writer])
flow.start("AI trends in 2024")
The user chains agents in order; each step receives the prior output until the final result is ready.

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Sequential Workflow

Pass work from one agent to the next, like an assembly line.

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How Context Flows

Each agent receives the previous output automatically.

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When to Use

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Code

from praisonaiagents import Agent, AgentFlow

researcher = Agent(name="Researcher", instructions="Research topics")
analyst = Agent(name="Analyst", instructions="Analyze research findings")
writer = Agent(name="Writer", instructions="Write based on analysis")

# Sequential: researcher → analyst → writer
flow = AgentFlow(steps=[researcher, analyst, writer])
result = flow.start("AI trends in 2024")

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Example: Blog Post Pipeline

StepAgentReceivesOutputs
1ResearcherTopicFacts, data
2AnalystFactsKey insights
3WriterInsightsDraft article
4EditorDraftPolished post

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With Callbacks

from praisonaiagents import AgentFlow, WorkflowHooksConfig

flow = AgentFlow(
    steps=[researcher, analyst, writer],
    hooks=WorkflowHooksConfig(
        on_step_complete=lambda name, r: print(f"✅ {name} done")
    )
)

Parallel

All at once (faster)

Routing

Send to specialists