Search RAG Documents

mindee.search_rag_documents
ActionAI & modelsconnection required

Calls the Mindee API with the connection's credentials.

List the documents indexed against one extraction model for Retrieval-Augmented Generation.

Connection

Required
Yes — the node will not save without one
Auth type
API key
Providers
Mindee
Secret shape
the V2 API key, or {"api_key": "…"}
Config it needs
base_url, model_id
Resolved by
config.connection_id, else node.connection_id

Configuration

4 fields, none required. A dotted path is a nested object and name[] an array of objects — the editor renders the same tree.

FieldTypeRequiredDefaultConstraintsExample
model_id
UUID of the Mindee model to run. Defaults to the connection's model_id, which is how one credential can drive an invoice model from one node and a passport model from the next.
stringNo——a1b2c3d4-0000-4000-8000-000000000000
filename
Partial file name to match, case-insensitive.
stringNo———
page
1-based page index of results to return.
numberNo1≥ 1—
per_page
How many results to return per page; Mindee caps this at 100.
numberNo501–100—

Example configuration

Every value below is the contract’s own example or default — nothing invented.

{
  "model_id": "a1b2c3d4-0000-4000-8000-000000000000",
  "page": 1,
  "per_page": 50
}

Output

One shape.

result

FieldTypeExample
rag_documents
The indexed documents this page holds.
array—
count
How many documents this page contains.
number—
pagination
page, per_page, total_items and total_pages.
object—
{
  "count": 0,
  "pagination": {},
  "rag_documents": []
}

See Search RAG Documents run in a workflow.

In a technical demo we add the Mindee connection, drop the node on the canvas and let Workflow Health pre-flight it before the first real run.