List available embedding models

Returns a list of available embedding models with their limits. Use this endpoint to discover which models are available and their constraints (batch size, input length) before making embedding requests.

GET /api/v1/llm/embeddings/models

Python (SDK)

Python

from mka1 import SDK


with SDK(
    bearer_auth="<YOUR_BEARER_TOKEN_HERE>",
) as sdk:

    res = sdk.llm.embeddings.list_models()

    # Handle response
    print(res)

200

{
  "object": "list",
  "data": [
    {
      "id": "meetkai:embedding",
      "provider": "meetkai",
      "model": "embedding",
      "limits": {
        "max_batch_size": 1000,
        "max_input_tokens": 32768,
        "max_input_length": 65536
      }
    }
  ]
}

Authorizations

Authorization · string · header · required

Gateway auth: send Authorization: Bearer <mka1-api-key>. For multi-user server-side integrations, you can also send X-On-Behalf-Of: <external-user-id>.

Headers

X-On-Behalf-Of · string

Optional external end-user identifier forwarded by the API gateway.

Response

200 - application/json

OK

Response containing available embedding models and their limits

data · object[] · required

List of available embedding models with their limits

Show child attributes

object · any · default: list