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POST
/
api
/
{workspaceID}
/
v1
/
embeddings
Create embeddings
curl --request POST \
  --url https://ai.liara.ir/api/{workspaceID}/v1/embeddings \
  --header 'Authorization: <api-key>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "input": "<string>",
  "model": "openai/text-embedding-3-small",
  "dimensions": 123,
  "encoding_format": "<string>",
  "user": "<string>"
}
'
{
  "data": [
    {
      "embedding": [
        123
      ],
      "index": 123
    }
  ],
  "model": "<string>",
  "usage": {
    "prompt_tokens": 123,
    "total_tokens": 123,
    "total_cost_toman": 123,
    "total_cost": 123
  }
}

Authorizations

Authorization
string
header
required

Enter the API key with the Bearer: prefix, e.g. "Bearer "

Path Parameters

workspaceID
string
required

The workspace ID

Pattern: ^[a-f0-9]{24}$

Body

application/json
input
required

Text or array of texts to embed

model
string
required

Embedding model ID. Supported models:

  • google/gemini-embedding-2
  • intfloat/multilingual-e5-large
  • google/gemini-embedding-001
  • openai/text-embedding-3-small
  • openai/text-embedding-3-large
  • openai/text-embedding-ada-002
Example:

"openai/text-embedding-3-small"

dimensions
number

Output dimensions (model-dependent)

encoding_format
string

Encoding format for embeddings

user
string

End-user identifier

Response

Successful response

object
enum<string>
Available options:
list
data
object[]
model
string

Model ID used

usage
object