Upsert Vectors

Insert new documents or update existing documents in a vector store.

Upsert Behavior: If a document ID already exists, it will be completely replaced with the new content and metadata. The previous document’s text, embedding, and all metadata fields are discarded. If the ID does not exist, a new document is created.

Document Content: Each document supports several modes:

• content only: text is automatically embedded using the store’s configured model.
• embedding only: pre-computed embedding vector is used directly. Dimension must match the store’s configuration.
• Both content and embedding: the pre-computed embedding is stored and text is kept for retrieval/search.
• Neither (metadata-only): only metadata is updated on an existing document without re-embedding. If the document does not exist, it will appear as a failure in the batch response.

A store created without an embedding model (dimensions-only) only accepts documents with pre-computed embedding.

Batch Operations: This endpoint supports batch operations with partial success handling and mixed document types (some with raw embeddings, some with content) in the same call.

Metadata: Supports nested metadata with string, number, boolean, object, and array types. Null values are not permitted—omit the field or use an empty string instead.

POST /v5/vector-stores/{vector_store_name}/upsert

Upsert Vectors

cURL

curl --request POST \
  --url https://api.egp.scale.com/v5/vector-stores/{vector_store_name}/upsert \
  --header 'Content-Type: application/json' \
  --header 'x-api-key: <api-key>' \
  --data '
{
  "vectors": [
    {
      "id": "<string>",
      "embedding": [
        123
      ],
      "metadata": {}
    }
  ]
}
'

200

{
  "success_count": 123,
  "failure_count": 123,
  "succeeded": [
    "<string>"
  ],
  "failed": [
    {
      "id": "<string>",
      "error": "<string>"
    }
  ]
}

Authorizations

x-api-key · string · header · required

Headers

x-selected-account-id · string | null

Path Parameters

vector_store_name · string · required

The name of the vector store

Body

application/json

Request to upsert documents.

vectors · VectorDocumentRequest · object[] · required

Array of documents to upsert

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Response

200

application/json

Successful Response

Response for batch insert/upsert operations.

success_count · integer · required

Number of successfully processed documents

failure_count · integer · required

Number of failed documents

succeeded · string[]

IDs of successfully processed documents

failed · FailedDocumentResponse · object[]

Failed documents with their error messages

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