CONTENT CREATION
Caption new Dropbox images and write a sidecar text file
When a new image lands in a watched Dropbox folder, generates a caption with Hugging Face and saves it as a matching .txt sidecar file next to the original.
How it runs
The automated pipeline, trigger to output.
- TriggerDropbox image added to watched folderDropbox
- LogicContinue only for image file types
- ActionDownload image from DropboxDropbox
- ActionGenerate caption via Hugging FaceHugging Face
- OutputWrite .txt sidecar caption to DropboxDropbox
What it does
Watches a Dropbox folder for newly uploaded images and, for each one, produces a descriptive caption from a Hugging Face vision model. The caption is saved as a sidecar text file (same name, `.txt` extension) right beside the image, so downstream tools and editors pick it up automatically.
When to use it
Your team drops raw photos and screenshots into a shared Dropbox folder and wants captions ready before assets move into production. Sidecar `.txt` files are the convention many DAM importers and static-site pipelines expect.
How it works
- 1A Dropbox file-added event triggers on the watched folder.
- 2Branch on file extension: only continue for image types, ignore everything else.
- 3Download the image bytes from Dropbox.
- 4Send the image to the Hugging Face image-to-text model and receive a caption.
- 5Compose the caption into a small text payload.
- 6Upload it back to Dropbox as `<filename>.txt` alongside the original image.
Set it up
What you configure once, before turning it on.
- 1Connect DropboxFiles and folders.
- 2Connect Hugging FaceModels, datasets, spaces — the open-source hub.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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