> ## Documentation Index
> Fetch the complete documentation index at: https://docs.definable.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Loop Workflow

> Iterative refinement with end conditions.

Run steps repeatedly until an end condition is met or max iterations reached.

```python theme={null}
from definable.agent import Agent
from definable.agent.workflow import Workflow, Loop, Step

generator = Agent(model="gpt-4o", instructions="Generate content based on feedback.")
evaluator = Agent(model="gpt-4o", instructions="Evaluate quality. Say APPROVED if it meets standards.")

workflow = Workflow(
    name="refinement",
    steps=[
        Loop(
            name="improve",
            steps=[
                Step(name="generate", agent=generator),
                Step(name="evaluate", agent=evaluator),
            ],
            end_condition=lambda outputs: any(
                "APPROVED" in (o.content or "") for o in outputs
            ),
            max_iterations=5,
        ),
    ],
)
```

## How It Works

1. `generate` and `evaluate` steps execute sequentially.
2. After each iteration, `end_condition` receives all step outputs from that iteration.
3. If it returns `True`, the loop stops.
4. If `max_iterations` is reached, the loop stops regardless.

## Parameters

<ParamField path="end_condition" type="Callable[[List[StepOutput]], bool]">
  Called after each iteration. Return `True` to stop. Supports sync and async.
</ParamField>

<ParamField path="max_iterations" type="int" default="3">
  Maximum iterations before stopping.
</ParamField>

## Tracking Iterations

Use the `LoopIterationEvent` to monitor progress:

```python theme={null}
from definable.agent.workflow import LoopIterationEvent

workflow.events.on(LoopIterationEvent, lambda e: print(f"Iteration {e.iteration}/{e.max_iterations}"))
```