embedding 文字向量模型
POST
https://api.mindcraft.com.cn/v1/embeddings
提示
点击获取api_key
请求参数
Header 参数
Authorization
string
认证信息
示例值:
Bearer {{api_key}}
Body 参数application/json
model
enum<string>
调用的向量模型
枚举值:
qwen-text-embedding-v3GLM-Embedding-3BAAI-bge-m3text-embedding-004gemini-embedding-exp-03-07
示例值:
BAAI-bge-m3
input
array [object {1}]
会话和提问
text
string
字符串数据
示例值:
你好啊你叫什么名字
dimensions
integer
必需
默认值:
1024
示例值:
1024
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
Go
PHP
Python
HTTP
C
C#
Objective-C
Ruby
OCaml
Dart
R
请求示例请求示例
Shell
JavaScript
Java
Swift
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
id
string
必需
model
string
必需
usage
object
必需
completion_tokens
integer
必需
prompt_tokens
integer
必需
total_tokens
integer
必需
data
array [object {3}]
必需
embedding
array[number]
必需
index
integer
必需
type
string
必需
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