Question 1

Does this require a new permission?

Accepted Answer

No. We re-use the same `drive.file` OAuth scope as the Google Sheets connector. It's a non-sensitive scope — Google does not put it through verification, and we only get access to files you explicitly hand to us via the Picker. If you've already connected Google Sheets, no extra consent is needed.

Question 2

What does iDBQuery actually store?

Accepted Answer

We export the Doc as `.docx`, save it on the folder source's storage, then run our standard text extraction → chunking → embedding pipeline. The `.docx` blob, text chunks, and 1536-dimension embedding vectors are stored per-source in an isolated SQLite index. Nothing is sent to third-party SaaS beyond the embedding API call (OpenAI text-embedding-3-small).

Question 3

Will edits in the Doc reflect automatically?

Accepted Answer

Not automatically — Docs aren't on a TTL like Sheets. Click 'resync' on the file row (or re-import) and we'll re-export, re-chunk, and re-embed. Auto-sync via Drive change webhooks is on the roadmap.

Question 4

What about images, tables, or comments inside the Doc?

Accepted Answer

Tables in the Doc are flattened into the extracted text (rows separated, cells concatenated). Inline images aren't OCR'd in this pipeline (the OCR fallback is PDF-only for now). Comments and suggestions aren't part of the export.

Question 5

Can the AI write back to my Doc?

Accepted Answer

No. Docs import is strictly read-only. The OAuth scope (`drive.file`) technically permits writes, but the Docs path in iDBQuery never invokes write methods — and we'd add an explicit per-source toggle if write-back ever ships.

Question 6

How big a Doc can I import?

Accepted Answer

Each `.docx` export is capped at 50 MB; the folder source caps at 5 GB total. A 200-page Doc typically exports to ~2 MB and indexes in well under a minute.

Google Docs

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Create or open a folder source

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