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Run the same agent step over a list, CSV, or text file — then aggregate results in one workflow. 
from praisonaiagents import Agent, AgentFlow, loop

processor = Agent(
    name="Processor",
    instructions="Process each item thoroughly.",
)

workflow = AgentFlow(
    steps=[
        loop(processor, over="topics"),
        Agent(name="Summariser", instructions="Summarise all processed results."),
    ],
    variables={"topics": ["AI Ethics", "Machine Learning", "Neural Networks"]},
)

result = workflow.start("Research and summarise these AI topics")
The user supplies a list of items; the workflow loops the agent over each entry then summarises results.

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Quick Start

1

Simple Usage

Loop an agent over a variable list:
from praisonaiagents import Agent, AgentFlow, loop

processor = Agent(name="Processor", instructions="Process each item thoroughly.")

workflow = AgentFlow(
    steps=[
        loop(processor, over="topics"),
        Agent(name="Summariser", instructions="Summarise all processed results."),
    ],
    variables={"topics": ["AI Ethics", "Machine Learning", "Neural Networks"]},
)

result = workflow.start("Research and summarise these AI topics")
print(result["output"][:500])
2

With Configuration

Process rows from a CSV file with a custom handler:
from praisonaiagents import Agent, AgentFlow, WorkflowContext, StepResult, loop

support_agent = Agent(
    name="Support Agent",
    instructions="Resolve customer issues efficiently.",
    llm="gpt-4o-mini",
)

def handle_customer(ctx: WorkflowContext) -> StepResult:
    row = ctx.variables.get("item", {})
    name = row.get("name", "unknown")
    issue = row.get("issue", "unknown")
    response = support_agent.chat(f"Help {name} with: {issue}")
    return StepResult(output=f"{name}: {response}")

workflow = AgentFlow(steps=[loop(handle_customer, from_csv="customers.csv")])
result = workflow.start("Process all customer issues")

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How It Works

Input sourceParameterBehaviour
Variable listover="topics"Iterates variables["topics"]
CSV filefrom_csv="data.csv"One sub-step per row
Text filefrom_file="urls.txt"One sub-step per line
Parallelparallel=TrueRuns iterations concurrently
Loop outputs are stored in result["variables"]["loop_outputs"] by default.

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Common Patterns

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CSV customer support

name,issue
John,Billing problem
Jane,Technical issue
Sarah,Password reset

workflow = AgentFlow(steps=[loop(handle_customer, from_csv="customers.csv")])

​
Line-by-line URL analysis

def analyse_url(ctx: WorkflowContext) -> StepResult:
    url = ctx.variables.get("item", "")
    result = url_agent.chat(f"Analyse this website: {url}")
    return StepResult(output=f"{url}: {result}")

workflow = AgentFlow(steps=[loop(analyse_url, from_file="urls.txt")])

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Parallel batch processing

workflow = AgentFlow(
    steps=[loop(process_item, from_csv="data.csv", parallel=True, max_workers=4)]
)

​
Best Practices

Check that CSV files exist and have headers. Empty files produce zero iterations silently.
When sub-steps do not depend on each other, set parallel=True and cap workers with max_workers.
Add a summariser agent after the loop step rather than embedding aggregation inside each iteration.
Pass row data via ctx.variables["item"] and return a StepResult — avoid side effects outside the workflow context.

Workflow Loop

Loop patterns inside multi-step workflows

Workflow Parallel Execution

Run independent workflow branches concurrently