POST /v1/embeddings — Text Embeddings

The /v1/embeddings endpoint converts text into numerical vector representations (embeddings). You can pass a single string or a batch of strings in one request. The resulting vectors can be stored in a vector database and used for semantic search, document clustering, classification, or as input to a retrieval-augmented generation (RAG) pipeline. This endpoint is compatible with the OpenAI embeddings format.

Request parameters

string

required

The embedding model to use. Use the list models endpoint to find available embedding model IDs.

string | string[]

required

The text to embed. Pass a single string or an array of strings to embed multiple inputs in one request. Token limits vary by model.

string

default:"float"

The format in which to return the embedding vectors. Use "float" for an array of floating-point numbers, or "base64" for a Base64-encoded string.

Response fields

string

Always "list".

array

An array of embedding objects, one for each input string. Objects are returned in the same order as the input.

Show properties

string

Always "embedding".

integer

Zero-based position of this embedding in the input array.

number[]

The embedding vector as an array of floats (or a Base64 string if encoding_format is "base64"). The dimensionality depends on the model.

string

The model used to generate the embeddings.

object

Token usage for the request.

Show properties

integer

Number of tokens in the input text(s).

integer

Total tokens consumed. Equal to prompt_tokens for embedding requests.

Example

Request

curl https://tokmodel.com/v1/embeddings \
  --request POST \
  --header "Authorization: Bearer YOUR_API_KEY" \
  --header "Content-Type: application/json" \
  --data '{
    "model": "openai/text-embedding-3-small",
    "input": ["TokModel is a unified LLM gateway.", "It supports 30+ AI providers."],
    "encoding_format": "float"
  }'

Response

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "index": 0,
      "embedding": [0.0023, -0.0091, 0.0412, -0.0188, "..."]
    },
    {
      "object": "embedding",
      "index": 1,
      "embedding": [0.0071, -0.0033, 0.0299, -0.0144, "..."]
    }
  ],
  "model": "openai/text-embedding-3-small",
  "usage": {
    "prompt_tokens": 16,
    "total_tokens": 16
  }
}

​Request parameters

​Response fields

​Example

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Request parameters

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Example

Request

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