Features
Converts input text into high-dimensional vector representations for downstream tasks such as semantic similarity calculation and clustering analysis.
Invocation Method
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]]
Return Format
{
"object": "list",
"data": [
{
"object": "embedding",
"index": 0,
"embedding": [-0.031, -0.016, -0.007, ...]
}
],
"model": "Qwen/Qwen3-Embedding-0.6B"
}