文本向量化

POST

/v1/embeddings

获取给定输入文本的向量表示，这些向量可以被机器学习模型和算法轻松使用。
需要使用支持embedding的模型，支持批量向量化操作：text-embedding-3-small，text-embedding-3-large

请求参数

Header 参数

Body 参数application/json

示例

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

请求示例代码

Shell

JavaScript

Java

Swift

PHP

Python

HTTP

Objective-C

Ruby

OCaml

Dart

curl --location '/v1/embeddings' \
--header 'Authorization: Bearer {YOUR_API_KEY}' \
--header 'Content-Type: application/json' \
--data '{
    "input": "The food was delicious and the waiter...",
    "model": "text-embedding-3-small",
    "encoding_format": "float"
  }'

返回响应

🟢200成功

application/json

Bodyapplication/json

示例

{
    "object": "list",
    "data": [
        {
            "object": "embedding",
            "embedding": [
                0.0023064255,
                -0.009327292,
                // ... (1536 个浮点数,用于 ada-002)
                -0.0028842222
            ],
            "index": 0
        }
    ],
    "model": "text-embedding-ada-002",
    "usage": {
        "prompt_tokens": 8,
        "total_tokens": 8
    }
}

修改于 2025-12-05 08:45:15

语音回复(chat)

聊天