AI & RAG
Coda Workspace Embedding Index Builder
Crawls every doc, page, and canvas table in a Coda workspace, chunks the content into blocks, embeds each chunk with a Hugging Face model.
How it runs
The automated pipeline, trigger to output.
- TriggerOperator starts index build for a workspace
- ActionList docs and fetch page + table content from CodaCoda
- LogicChunk content into blocks with anchor coordinates
- ActionEmbed each chunk with Hugging FaceHugging Face
- OutputUpsert vectors + source metadata to Supabase indexSupabase
What it does
Builds the searchable vector index that every other workflow in this collection queries. It walks a Coda workspace, breaks each page into block-level chunks, generates embeddings, and writes them to a Supabase table along with the exact doc ID, page ID, and block anchor so answers can cite their source later.
When to use it
Run this once to bootstrap a new corpus, or on a schedule to keep large workspaces fresh when you don't have edit webhooks wired up. It's the prerequisite for the webhook QA endpoint and the citation-checking flows.
How it works
- 1A manual run starts the indexing job for a chosen workspace.
- 2Coda lists all docs, then pulls each page's content and canvas tables.
- 3A logic step splits page content into block-sized chunks and attaches each block's anchor coordinates.
- 4Hugging Face embeds every chunk into a vector.
- 5Supabase upserts the vectors with doc/page/block metadata into the corpus index table, replacing any stale rows for that doc.
Set it up
What you configure once, before turning it on.
- 1Connect CodaDocs, packs, automations.
- 2Connect Hugging FaceModels, datasets, spaces — the open-source hub.
- 3Connect SupabaseTables, auth, storage, edge functions.
- 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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Run this workflow in your colony.
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