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POST
/
search
/
embeddings
Generate an embedding vector
curl --request POST \
  --url https://api.example.com/search/embeddings \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "text": "<string>",
  "model": "gemini-embedding-001"
}
'
{
  "embedding": [
    123
  ],
  "model": "<string>",
  "dimensions": 123
}

Documentation Index

Fetch the complete documentation index at: https://docs.emergence.ai/llms.txt

Use this file to discover all available pages before exploring further.

Authorizations

​
Authorization
string
header
required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Body

application/json

Request body for POST /utils/embeddings.

​
text
string
required

Text to embed

Minimum string length: 1
​
model
string | null

Model override. Uses the server-configured default if omitted.

Example:

"gemini-embedding-001"

Response

Successful Response

Response from POST /utils/embeddings.

​
embedding
number[]
required

Embedding vector

​
model
string
required

Model used to generate the embedding

​
dimensions
integer
required

Number of dimensions in the embedding vector