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Overview

The RAG API lets a workspace ingest documents, chunk and embed them, and query them with natural-language questions that return a generated answer plus the source passages it was grounded in.
1

Upload documents

POST files to /api/v1/rag/upload. Each file is text-extracted, chunked, embedded, and indexed per-workspace.
2

Query

POST a natural-language question to /api/v1/rag/query. The engine retrieves the most relevant chunks and returns a generated answer with cited sources.

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Base URL

https://suite.sundaypyjamas.com/api/v1/rag
Unlike the rest of the platform API, the RAG endpoints currently authenticate via a Supabase session (the same auth used by the AI Suite web app) rather than a workspace API key. If you’re integrating from a backend service rather than the AI Suite frontend, reach out about API-key support for these endpoints before building against them in production.

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Quotas

Each workspace has a monthly query quota (rag_workspaces.monthly_quota, defaults to 1,000). Queries increment usage by 1; uploads are not quota-limited but are capped at 100 MB per file.

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Resources

Upload

Ingest documents (PDF, DOCX, TXT, MD, CSV, JSON) into the workspace’s RAG index.

Query

Ask questions and get grounded answers with source citations.