ragSaveEmbeddings( )

function ragSaveEmbeddings(params): Promise<RagSaveEmbeddingsResult[]>;

Part of the segregated flow: ragChunk() → embed() → ragSaveEmbeddings(). Implicitly opens (or creates) the workspace.

Parameters

Name	Type	Required?	Default	Description
params.documents	`RagEmbeddedDoc[]`	✓	—	Pre-embedded documents
params.modelId	`string`	✗	—	Embedding model ID (required if no cached RAG instance exists)
params.workspace	`string`	✗	`"default"`	Workspace for isolated storage
params.onProgress	`(stage, current, total) => void`	✗	—	Progress callback
params.progressInterval	`number`	✗	—	Minimum interval between progress updates in ms

`RagEmbeddedDoc`

Field	Type	Required?	Description
id	`string`	✓	Document identifier
content	`string`	✓	Document text content
embedding	`number[]`	✓	Pre-computed embedding vector
embeddingModelId	`string`	✓	Model used to generate the embedding
metadata	`Record<string, unknown>`	✗	Optional metadata

Returns

Promise<RagSaveEmbeddingsResult[]> — Array of { status: "fulfilled" | "rejected", id?, error? }.

Throws

Error	When
`RAG_SAVE_FAILED`	The save operation fails
`STREAM_ENDED_WITHOUT_RESPONSE`	Streaming ends unexpectedly (when using `onProgress`)

Example

const chunks = await ragChunk({ documents: ["text1", "text2"] });
const embeddings = await embed({ modelId, text: chunks.map(c => c.content) });
const embeddedDocs = chunks.map((chunk, i) => ({
  ...chunk,
  embedding: embeddings[i],
  embeddingModelId: modelId,
}));
const result = await ragSaveEmbeddings({
  documents: embeddedDocs,
  workspace: "my-workspace",
});