AI & RAG
Index New Dropbox Contracts into a Clause Vector Store
When a new or updated agreement lands in a Dropbox folder, it extracts the text, splits it into clause-level chunks, embeds them with OpenAI.
How it runs
The automated pipeline, trigger to output.
- TriggerFile added or updated in Dropbox folderDropbox
- ActionDownload and extract document textDropbox
- LogicChunk into clauses and tag metadata
- ActionEmbed chunks with OpenAIOpenAI
- OutputUpsert vectors into Postgres storePostgres
What it does
This is the ingestion pipeline that powers every contract-question bot. Drop a signed PDF or DOCX into your Dropbox agreements folder and it becomes searchable clause-by-clause within minutes, with metadata for document name, type, and effective date.
When to use it
Run this as the always-on backbone behind any MSA retrieval workflow. Use it whenever legal or ops adds, renews, or amends an agreement and you need the knowledge base to reflect it without a manual re-index.
How it works
- 1A file-added or file-modified event in the watched Dropbox folder triggers the flow.
- 2An action downloads the document and extracts its full text.
- 3A logic step splits the text into clause-sized chunks and tags each with source metadata (filename, contract type, party names).
- 4OpenAI generates an embedding for every chunk.
- 5The final step upserts the chunks and vectors into the Postgres store, replacing prior versions of the same document so stale clauses never resurface.
Set it up
What you configure once, before turning it on.
- 1Connect DropboxFiles and folders.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect PostgresAny Postgres URL — query, write, migrate.
- 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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