DOCUMENT OPS
Scanned receipt batch to BigQuery expense ledger
Watches a Dropbox folder for new scanned receipts, extracts vendor, date, total, and tax with a vision model, and appends each parsed receipt as a structured row in BigQuery.
How it runs
The automated pipeline, trigger to output.
- TriggerNew file added to Dropbox receipts folderDropbox
- ActionDownload receipt file from DropboxDropbox
- ActionExtract fields with Hugging Face vision modelHugging Face
- LogicValidate total parsed; skip and flag if unreadable
- OutputInsert structured row into BigQuery expenses tableBigQuery
What it does
Turns a drop folder of phone-scanned and emailed receipts into clean, queryable expense rows. Each new image or PDF in Dropbox is read by a Hugging Face vision-language model that pulls vendor name, transaction date, line-item subtotal, tax, and grand total, then writes one normalized record to a BigQuery expenses table.
When to use it
Use it when your team dumps receipts into a shared Dropbox folder and finance needs them as analyzable data, not a pile of JPEGs. Ideal for monthly close, reimbursement prep, or feeding a spend dashboard without manual data entry.
How it works
- 1A new file landing in the watched Dropbox receipts folder triggers the run.
- 2The file is downloaded and its bytes passed to a Hugging Face OCR/vision model that returns vendor, date, currency, subtotal, tax, and total as JSON.
- 3A logic step validates the extraction: if the total is missing or unparseable, the receipt is skipped and flagged.
- 4The cleaned record, with the original file path retained, is inserted into the BigQuery expenses table for reporting.
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 BigQueryDatasets, queries, schemas.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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