> For the complete documentation index, see [llms.txt](https://docs.pletor.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.pletor.ai/build-agents/studio/loop-mode.md).
# Loop mode
Loop Mode lets you process multiple inputs through the same node chain automatically — one at a time. Instead of generating a single output per run, the node iterates over each input and produces a separate output for each one.
It's the fastest way to scale your workflows without duplicating nodes or running your agent manually for every asset.
***
### How it works
When Loop Mode is **off**, a node takes all its connected inputs and produces one output per run.
When Loop Mode is **on**, the node processes each input individually through the downstream chain. If you connect 10 images, the node runs 10 times — once per image — and produces 10 separate outputs.
You'll find the **Loop Mode** toggle in the top-right corner of the Inputs section in any node's configuration panel.
***
### Where Loop Mode appears
Loop Mode is available on most nodes that accept inputs, including:
* **AI Image nodes** (Generate Image, Edit Image, etc.)
* **AI Video nodes** (Generate Video, etc.)
* **Import from Google Drive**
* **Text Assistants**
When connected inputs have Loop Mode enabled, they show a **Loop** badge next to the input pill in the configuration panel.
***
### Per-input loop control
When a node has multiple inputs, you can enable Loop Mode independently on each one. This gives you fine-grained control over which inputs iterate and which stay fixed.
**Example:** In a Generate Image node with Loop Mode on:
* **Text prompt** → connected to a fixed prompt instruction (Loop off) — the same prompt is used for every iteration.
* **Reference image(s)** → connected to Import from Google Drive (Loop on) — each imported image is processed one at a time.
This means: one prompt × N images = N outputs, each using a different reference image but the same instructions.
***
### Common Loop Mode patterns
#### Batch product shots from Google Drive
Import product photos from a Drive folder, generate a styled variation of each one, and export back to Drive.
**Flow:** Text Prompt (folder URL) → Import from Google Drive → Text Prompt (fixed instructions) → **Generate Image** (Loop Mode on for reference images) → Export to Google Drive
Each product photo gets its own generation. The fixed prompt applies the same styling to every image.
[→ Try this template](https://app.pletor.ai/flow/346c73f3-08ff-46eb-bc7e-3dc523977f33) (fashion)
[→ Try this template](https://app.pletor.ai/flow/c5bef676-5137-4145-b397-52004cc45f51) (furniture)
#### Multiple headline variations
Use a Text Assistant to generate several headline options, split them, and generate an image for each one.
**Flow:** Text Prompt (brief) → Text Assistant (generate 5 headlines) → Split Text → **Generate Image** (Loop Mode on for text prompt)
Each headline becomes a separate image generation.
#### Multi-format adaptation
Take one source image and generate it in multiple aspect ratios for different platforms.
**Flow:** Upload Image → **Change Aspect Ratio** (Loop Mode on) with multiple target ratios
One input, multiple format outputs — ready for Instagram, Stories, and landscape.
***
### Cost and performance
Each loop iteration counts as a separate run and consumes credits independently. The **run cost** shown in the configuration panel reflects the cost per iteration — multiply by the number of inputs to estimate total cost.
Loop Mode processes inputs sequentially (one at a time), not in parallel. Larger batches take proportionally longer.
***
### Tips
* **Start with a small batch.** Test your Loop Mode workflow with 2-3 inputs first to make sure the outputs look right before running it on a full folder of assets.
* **Combine with Google Drive for end-to-end automation.** Import → Loop → Export is the core pattern for batch processing at scale.
* **Use fixed prompts alongside looped inputs.** The power of Loop Mode is applying the same instructions to many different assets — keep your prompt constant and let the inputs vary.
* **Check the run cost before launching large batches.** A 15-credit node × 50 looped inputs = 750 credits per run.
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