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POST
/
dedicated
/
v1
/
embeddings
Embeddings
curl --request POST \
  --url https://api.friendli.ai/dedicated/v1/embeddings \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
  "encoding_format": "float",
  "input": "The food was delicious and the waiter...",
  "model": "(endpoint-id)"
}'
{
  "id": "embd-26a1e10db1311bc2adb488d2d205288b",
  "model": "(endpoint-id)",
  "object": "list",
  "data": [
    {
      "index": 0,
      "object": "embedding",
      "embedding": [
        0.0023064255,
        -0.009327292,
        -0.0028842222
      ]
    }
  ],
  "usage": {
    "prompt_tokens": 26,
    "completion_tokens": 0,
    "total_tokens": 26
  },
  "created": 1735722153
}
Creates an embedding vector representing the input text. To request successfully, it is mandatory to enter a Friendli Token (e.g. flp_XXX) value in the Bearer Token field. Refer to the authentication section on our introduction page to learn how to acquire this variable and visit here to generate your token.

Authorizations

​
Authorization
string
header
required

When using Friendli Suite API for inference requests, you need to provide a Friendli Token for authentication and authorization purposes.

For more detailed information, please refer here.

Headers

​
X-Friendli-Team
string | null

ID of team to run requests as (optional parameter).

Body

application/json
​
model
string
required

ID of target endpoint. If you want to send request to specific adapter, use the format "YOUR_ENDPOINT_ID:YOUR_ADAPTER_ROUTE". Otherwise, you can just use "YOUR_ENDPOINT_ID" alone.

Examples:

"(endpoint-id)"

​
input
required

Input text to embed, encoded as a string or array of tokens. To embed multiple inputs in a single request, pass an array of strings or array of token arrays.

Examples:

"The food was delicious and the waiter..."

​
encoding_format
enum<string> | null
default:float

The format to return the embeddings in. Can be either float or base64.

Available options:
float,
base64

Response

Successfully generated embeddings.

​
id
string
required

A unique ID of the embeddings.

​
object
string
required

The object type, which is always set to list.

Allowed value: "list"
​
data
EmbeddingObject · object[]
required

A list of embedding objects.

​
usage
object
required
​
created
integer
required

The Unix timestamp (in seconds) for when the embeddings were created.

​
model
string | null

The model to generate the embeddings. For dedicated endpoints, it returns the endpoint id.