Generate high-dimensional vector representations for semantic search, RAG retrieval, and clustering.

Endpoint: POST /v1/embeddings
Surface: Gateway Data Plane (:8080)

Request Parameters #

Parameter	Type	Required	Description
`model`	`string`	Yes	Embedding model (e.g. `text-embedding-3-small`, `text-embedding-3-large`).
`input`	`string` / `array`	Yes	Input text or array of strings to embed.
`dimensions`	`integer`	No	Desired vector dimensions (supported models only).

Example cURL Request #

bash

curl -X POST "http://localhost:8080/v1/embeddings" \
  -H "Authorization: Bearer nsk_live_YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "text-embedding-3-small",
    "input": "Naagmani AI Operating System"
  }'

Response Example #

json

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "index": 0,
      "embedding": [-0.00692, -0.00533, 0.01254, "... 1536 floats"]
    }
  ],
  "model": "text-embedding-3-small",
  "usage": {
    "prompt_tokens": 5,
    "total_tokens": 5
  }
}

Embeddings API

Request Parameters #

Example cURL Request #

Response Example #