embedding 文字向量模型

POST

https://api.mindcraft.com.cn/v1/embeddings

提示

headers 需要添加 "Bearer {{api_key}}" 用来认证
点击获取api_key

请求参数

Header 参数

Body 参数application/json

示例

{
    "model": "gemini-embedding-exp-03-07",
    "input": [
        {
            "text": "你好啊"
        },
        {
            "text": "你叫什么名字"
        }
    ],
    "dimensions": 1024
}

示例代码

Shell

JavaScript

Java

Swift

PHP

Python

HTTP

Objective-C

Ruby

OCaml

Dart

curl --location --request POST 'https://api.mindcraft.com.cn/v1/embeddings' \
--header 'Authorization: Bearer ' \
--header 'Content-Type: application/json' \
--data-raw '{
    "model": "gemini-embedding-exp-03-07",
    "input": [
        {
            "text": "你好啊"
        },
        {
            "text": "你叫什么名字"
        }
    ],
    "dimensions": 1024
}'

返回响应

🟢200成功

application/json

Body

示例

{
    "id": "f6bfc5224f2e45f3af2e39348d1f2781",
    "model": "GLM-Embedding-3",
    "usage": {
        "completion_tokens": 0,
        "prompt_tokens": 13,
        "total_tokens": 13
    },
    "data": [
        {
            "embedding": [
                -0.035929545760154724,
                -0.042329493910074234,
                -0.02364613115787506
            ],
            "index": 0,
            "type": "text"
        },
        {
            "embedding": [
                0.0515291653573513,
                0.007719388231635094,
                0.02654351107776165
            ],
            "index": 1,
            "type": "text"
        }
    ]
}

修改于 2025-03-11 11:57:19

embedding 多模态向量模型

rerank 文字向量模型