CONTENT CREATION
Media librarian agent: caption, dedupe, and organize Dropbox assets into Airtable
An agent that reviews a Dropbox media backlog, captions and zero-shot tags each image with Hugging Face, detects likely duplicates, and curates a clean.
How it runs
The automated pipeline, trigger to output.
- TriggerScheduled or manual agent run
- ActionList and read new images from DropboxDropbox
- ActionCaption and zero-shot tag via Hugging FaceHugging Face
- LogicReason over duplicates and target collection
- ActionUpsert curated records into AirtableAirtable
- OutputPost run summary report to SlackSlack
What it does
This runs an agent that acts like a media librarian over a Dropbox backlog. For each image it generates a caption and zero-shot category tags via Hugging Face, reasons about near-duplicates and naming, decides the right Airtable collection, and files a curated record. At the end it writes a summary of what it captioned, tagged, flagged as duplicate, and what needs human attention.
When to use it
A messy shared Dropbox of mixed assets needs to become an organized, captioned, deduped Airtable catalog — and the cleanup involves judgment (is this a dup, which collection, is the caption good enough) rather than a fixed rule set.
How it works
- 1A schedule or manual run starts the agent on the Dropbox folder.
- 2The agent lists and reads new images from Dropbox.
- 3For each image it calls Hugging Face for a caption and zero-shot tags.
- 4It reasons over captions and tags to detect probable duplicates and pick a target collection.
- 5It upserts curated records into Airtable, flagging duplicates and weak captions.
- 6It posts a run summary report to Slack for the content owner.
Set it up
What you configure once, before turning it on.
- 1Connect DropboxFiles and folders.
- 2Connect Hugging FaceModels, datasets, spaces — the open-source hub.
- 3Connect AirtableBases, tables, views, automations.
- 4Connect SlackChannels, DMs, threads, mentions.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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