---
title: "Creates an embedding vector representing the input text."
method: POST
path: "/embeddings"
tags: ["Embeddings"]
---

# Creates an embedding vector representing the input text.

`POST /embeddings`

## Request body

- CreateEmbeddingRequest
  - `input` union, 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. The input must not exceed the max input tokens for the model (8192 tokens for `text-embedding-ada-002`), cannot be an empty string, and any array must be 2048 dimensions or less. [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens.
    - string — The string that will be turned into an embedding.
    - string[] — The array of strings that will be turned into an embedding.
    - integer[] — The array of integers that will be turned into an embedding.
    - array[] — The array of arrays containing integers that will be turned into an embedding.
      - integer[]
  - `model` union, required — ID of the model to use. You can use the [List models](https://platform.openai.com/docs/api-reference/models/list) API to see all of your available models, or see our [Model overview](https://platform.openai.com/docs/models) for descriptions of them.
    - string
    - 'text-embedding-ada-002' | 'text-embedding-3-small' | 'text-embedding-3-large'
  - `encoding_format` 'float' | 'base64' — The format to return the embeddings in. Can be either `float` or [`base64`](https://pypi.org/project/pybase64/).
  - `dimensions` integer — The number of dimensions the resulting output embeddings should have. Only supported in `text-embedding-3` and later models.
  - `user` string — A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](https://platform.openai.com/docs/guides/safety-best-practices#end-user-ids).

## Response `200`

OK

- CreateEmbeddingResponse
  - `data` Embedding[], required — The list of embeddings generated by the model.
    - `index` integer, required — The index of the embedding in the list of embeddings.
    - `embedding` number[], required — The embedding vector, which is a list of floats. The length of vector depends on the model as listed in the [embedding guide](https://platform.openai.com/docs/guides/embeddings).
    - `object` 'embedding', required — The object type, which is always "embedding".
  - `model` string, required — The name of the model used to generate the embedding.
  - `object` 'list', required — The object type, which is always "list".
  - `usage` object, required — The usage information for the request.
    - `prompt_tokens` integer, required — The number of tokens used by the prompt.
    - `total_tokens` integer, required — The total number of tokens used by the request.

---

[API](https://skmtc.net/openai/apis/openai-api-2.md) · [All operations](https://skmtc.net/openai/apis/openai-api-2/llms.txt) · [OpenAPI document](https://skmtc-service-staging.skmtc.workers.dev/v1/apis/openai/openai-api-2/revisions/2f8ca92b9b18/schema)