git clone https://github.com/fanfpy/m3e.local.git
cd m3e.local
# 这一步会下载镜像 使用的魔搭的模型源,文件大概1G,需要一分钟左右
# 可以使用docker-compose up 观察输出
docker-compose up -d
# running on http://0.0.0.0:6006
curl --location 'http://127.0.0.1:6006/v1/embeddings' \
--header 'Authorization: Bearer sk-aaabbbcccdddeeefffggghhhiiijjjkkk' \
--header 'Content-Type: application/json' \
--data '{
"input": ["hello m3e"],
"model": "text-embedding-ada-002",
"encoding_format": "float"
}'
{
"data": [
{
"embedding": [
0.04027857258915901,
0.005487577989697456,
-0.025278501212596893,
-0.004541480913758278 ...
],
"index": 0,
"object": "embedding"
}
],
"model": "text-embedding-ada-002",
"object": "list",
"usage": {
"prompt_tokens": 2,
"total_tokens": 4
}
}
4 commits
Python
88.3%
Dockerfile
11.7%
git clone https://github.com/fanfpy/m3e.local.git
cd m3e.local
# 这一步会下载镜像 使用的魔搭的模型源,文件大概1G,需要一分钟左右
# 可以使用docker-compose up 观察输出
docker-compose up -d
# running on http://0.0.0.0:6006
curl --location 'http://127.0.0.1:6006/v1/embeddings' \
--header 'Authorization: Bearer sk-aaabbbcccdddeeefffggghhhiiijjjkkk' \
--header 'Content-Type: application/json' \
--data '{
"input": ["hello m3e"],
"model": "text-embedding-ada-002",
"encoding_format": "float"
}'
{
"data": [
{
"embedding": [
0.04027857258915901,
0.005487577989697456,
-0.025278501212596893,
-0.004541480913758278 ...
],
"index": 0,
"object": "embedding"
}
],
"model": "text-embedding-ada-002",
"object": "list",
"usage": {
"prompt_tokens": 2,
"total_tokens": 4
}
}
4 commits
Python
88.3%
Dockerfile
11.7%