Documentation Index
Fetch the complete documentation index at: /llms.txt
Use this file to discover all available pages before exploring further.
curl -X POST 'https://app.memorylake.cn/openapi/memorylake/router/openai/v1/embeddings' \
-H 'Authorization: Bearer sk_xxxxxx' \
-H 'Content-Type: application/json' \
-d '{
"input": "Lisbon is my favourite city.",
"model": "text-embedding-3-small"
}'
{
"data": [
{
"embedding": [
0.0123,
-0.0456,
0.0789
],
"index": 0,
"object": "embedding"
}
],
"model": "text-embedding-3-small",
"object": "list",
"usage": {
"prompt_tokens": 7,
"total_tokens": 7
}
}
用 OpenAI 兼容的向量模型把文本转成向量
curl -X POST 'https://app.memorylake.cn/openapi/memorylake/router/openai/v1/embeddings' \
-H 'Authorization: Bearer sk_xxxxxx' \
-H 'Content-Type: application/json' \
-d '{
"input": "Lisbon is my favourite city.",
"model": "text-embedding-3-small"
}'
{
"data": [
{
"embedding": [
0.0123,
-0.0456,
0.0789
],
"index": 0,
"object": "embedding"
}
],
"model": "text-embedding-3-small",
"object": "list",
"usage": {
"prompt_tokens": 7,
"total_tokens": 7
}
}
POST /openapi/memorylake/router/openai/v1/embeddings
X-Trace-ID 中返回同一个 trace id。float、base64。curl -X POST 'https://app.memorylake.cn/openapi/memorylake/router/openai/v1/embeddings' \
-H 'Authorization: Bearer sk_xxxxxx' \
-H 'Content-Type: application/json' \
-d '{
"input": "Lisbon is my favourite city.",
"model": "text-embedding-3-small"
}'
list{
"data": [
{
"embedding": [
0.0123,
-0.0456,
0.0789
],
"index": 0,
"object": "embedding"
}
],
"model": "text-embedding-3-small",
"object": "list",
"usage": {
"prompt_tokens": 7,
"total_tokens": 7
}
}