Embedding service
文本向量化(Embedding)基础服务。将自然语言转换为高维稠密向量,为语义搜索、聚类分析、推荐系统等下游任务提供核心数据支持。From its SKILL.md
npx -y skills add Lin-A1/skills-agent --skill embedding_serviceAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
- 7 stars7 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
0.9 KB, 231 tokens by cl100k_base, as published. Nobody here has run it
功能
将输入文本转换为高维向量表示,用于语义相似度计算、聚类分析等下游任务。
调用方式
from services.embedding_service.client import EmbeddingServiceClient
client = EmbeddingServiceClient()
# 单个文本向量化
vector = client.embed_query("人工智能") # -> list[float]
# 多个文本向量化
texts = ["机器学习", "深度学习", "自然语言处理"]
vectors = client.embed_documents(texts) # -> list[list[float]]
返回格式
{
"object": "list",
"data": [
{
"object": "embedding",
"index": 0,
"embedding": [-0.031, -0.016, -0.007, ...]
}
],
"model": "Qwen/Qwen3-Embedding-0.6B"
}
What ships with it: 3 files
3.5 KB alongside SKILL.md, 2 of them executable
- client.pyruns2.6 KB
- Dockerfile575 B
- entrypoint.shruns298 B