Embeddings

Create embeddings

Authorization

bearerAuth

AuthorizationBearer <token>

API key in format: eur_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

In: header

Request Body

application/json

TypeScript Definitions

Use the request body type in TypeScript.

model*string

Model identifier (e.g., "openai/text-embedding-3-small")

Length1 <= length

input*|array<>|array<number>|array<array<number>>

Input text or token arrays to embed. Can be a single string, array of strings, token array, or array of token arrays.

encoding_format*string

The format to return the embeddings in. Default: float

Default"float"

Value in"float" | "base64"

dimensions?integer

The number of dimensions for the output embeddings. Only supported by some models.

Range1 <= value <= 9007199254740991

user?string

End-user identifier for abuse detection

provider?

Provider routing preferences

trace?

Trace context for Broadcast observability

session_id?string

Session identifier for grouping related requests

Lengthlength <= 128

[key: string]?unknown

Response Body

`application/json`

curl -X POST "https://api.eurouter.ai/api/v1/embeddings" \  -H "Content-Type: application/json" \  -d '{    "model": "bge-m3",    "input": "European AI infrastructure"  }'

{
  "id": "string",
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "embedding": [
        0
      ],
      "index": -9007199254740991
    }
  ],
  "model": "string",
  "usage": {
    "prompt_tokens": -9007199254740991,
    "total_tokens": -9007199254740991,
    "cost": 0,
    "cost_currency": "USD",
    "cost_eur": 0,
    "is_byok": true,
    "cost_details": {
      "upstream_inference_cost": 0,
      "upstream_inference_prompt_cost": 0,
      "upstream_inference_completions_cost": 0
    }
  },
  "provider": "string"
}