Iteration
Repeat a section of the flow over each item of a list.
The Iteration node processes lists item by item, applying the same logic to each.
Unlike other nodes, it creates a sub-flow: on the canvas it shows up as a larger block, with nodes drawn inside it.
The cycle
- Input: receives a list variable, such as
{{ extrator_arquivos.contents }}. - Processing: runs the inner nodes once per item.
- Output: gathers the individual results into a new list.
The input has to be a list. Pointing it at a single value makes the node fail at run time.
Inside the loop
The Iteration start node appears automatically inside the block and provides item and index to the inner nodes.
A typical chain connects the Iteration start to an LLM node whose prompt uses {{ inicio_da_iteracao.item }}.
Output variables
This is where you declare what leaves the loop, with two fields:
- Output name: the name of the new list, for example
summaries. - Source variable: which piece of the sub-flow's data feeds each position, usually the inner LLM node's answer.
Without declaring output variables, the loop runs and nothing reaches the following nodes.
Each node inside the loop runs once per item. An LLM node over a list of 200 elements means 200 model calls. Estimate the cost before releasing the flow to the team.
Next steps
- Understand the inner node in Iteration start.
- See a complete batch flow in Extract data from documents in bulk.