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72 lines
3.9 KiB
Plaintext
72 lines
3.9 KiB
Plaintext
---
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title: Loop
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slug: /loop
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---
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import Icon from "@site/src/components/icon";
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import PartialParams from '@site/docs/_partial-hidden-params.mdx';
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The **Loop** component iterates over a list of input by passing individual items to other components attached at the **Item** output port until there are no items left to process.
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Then, the **Loop** component passes the aggregated result of all looping to the component connected to the **Done** port.
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## The looping process
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The **Loop** component is like a miniature flow within your flow.
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Here's a breakdown of the looping process:
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1. Accepts a list of [`JSON`](/data-types#json) or [`Table`](/data-types#table) objects, such as a CSV file, through the **Loop** component's **Inputs** port.
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2. Splits the input into individual items. For example, a CSV file is broken down by rows.
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Specifically, the **Loop** component repeatedly extracts items by `text` key in the `JSON` or `Table` objects until there are no more items to extract.
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Each `item` output is a `JSON` objects.
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3. Iterates over each `item` by passing them to the **Item** output port.
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This port connects to one or more components that perform actions on each item.
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The final component in the **Item** loop connects back to the **Loop** component's **Looping** port to process the next item.
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Only one component connects to the **Item** port, but you can pass the data through as many components as you need, as long as the last component in the chain connects back to the **Looping** port.
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The [**If-Else** component](/if-else) isn't compatible with the **Loop** component.
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For more information, see [Conditional looping](#conditional-looping).
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4. After processing all items, the results are aggregated into a single `JSON` object that is passed from the **Loop** component's **Done** port to the next component in the flow.
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The following simplified Python code summarizes how the **Loop** component works.
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This _isn't_ the actual component code; it is only meant to help you understand the general process.
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```python
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for i in input: # Receive input data as a list
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process_item(i) # Process each item through components connected at the Item port
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if has_more_items():
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continue # Loop back to Looping port to process the next item
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else:
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break # Exit the loop when no more items are left
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done = aggregate_results() # Compile all returned items
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print(done) # Send the aggregated results from the Done port to another component
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```
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## Loop example
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In the follow example, the **Loop** component iterates over a CSV file until there are no rows left to process.
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In this case, the **Item** port passes each row to a **Type Convert** component to convert the row into a `Message` object, passes the `Message` to a **Structured Output** component to be processed into structured data that is then passed back to the **Loop** component's **Looping** port.
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After processing all rows, the **Loop** component loads the aggregated list of structured data into a Chroma DB database through the **Chroma DB** component connected to the **Done** port.
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:::tip
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For more examples of the **Loop** component, try the **Research Translation Loop** template in Langflow, or see the video tutorial [Mastering the Loop Component & Agentic RAG in Langflow](https://www.youtube.com/watch?v=9Wx7WODSKTo).
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:::
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## Conditional looping
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The [**If-Else** component](/if-else) isn't compatible with the **Loop** component.
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If you need conditional loop events, redesign your flow to process conditions before the loop.
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For example, if you are looping over a `Table`, you could use multiple [**Table Operations** components](/dataframe-operations) to conditionally filter data, and then run separate loops on each set of filtered data.
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