Create Embeddings - AITRE API Documents(English)

Obtain a vector representation of the given input, which machine learning models and algorithms can easily use.
Related guidelines: [Insert]（ https://platform.openai.com/docs/guides/embeddings )
Create an embedding vector representing the input text.

Request

Header Params

Authorization

string

required

Provide your bearer token in the Authorization header when making requests to protected resources.
Example:
Authorization: Bearer ********************

Example:

Bearer {{YOUR_API_KEY}}

Body Params application/json

model

string

required

The ID of the model to be used. You can use [List models]（ https://platform.openai.com/docs/api-reference/models/list ）API to view all available models, or view our [Model Overview]（ https://platform.openai.com/docs/models/overview ）To understand their descriptions.

input

string

required

Enter text to obtain embeddings, encoded as strings or tag arrays. To obtain embeddings for multiple inputs in a single request, pass a string array or token array array. The length of each input must not exceed 8192 tags.

Example

{
  "model": "text-embedding-3-large",
  "input": "The food was delicious and the waiter..."
}

Request samples

Shell

JavaScript

Java

Swift

PHP

Python

HTTP

Objective-C

Ruby

OCaml

Dart

Responses

🟢200Create embeddings

application/json

Body

object

string

required

data

array [object {3}]

required

object

string

optional

embedding

array[number]

optional

index

integer

optional

model

string

required

usage

object

required

prompt_tokens

integer

required

total_tokens

integer

required

Example

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "embedding": [
        0.0023064255,
        -0.009327292,
        .... (1536 floats total for ada-002)
        -0.0028842222
      ],
      "index": 0
    }
  ],
  "model": "text-embedding-ada-002",
  "usage": {
    "prompt_tokens": 8,
    "total_tokens": 8
  }
}