嵌入向量(Embedding)

将文本转换为高维向量,用于语义搜索、相似度匹配、RAG 等场景。

POSThttps://allmodel.top/v1/embeddings

Python 示例

Python
from openai import OpenAI

client = OpenAI(
    api_key="am-your-api-key",
    base_url="https://allmodel.top/v1"
)

# 单条文本
response = client.embeddings.create(
    model="text-embedding-3-small",
    input="The food was delicious and the waiter was friendly."
)
vector = response.data[0].embedding
print(f"向量维度: {len(vector)}")
print(f"前5个值: {vector[:5]}")

# 批量(节省 API 调用)
responses = client.embeddings.create(
    model="text-embedding-3-small",
    input=["第一段文本", "第二段文本", "第三段文本"]
)
for r in responses.data:
    print(f"index={r.index}, embedding长度={len(r.embedding)}")

支持的模型

模型维度价格
text-embedding-3-small1536$0.02/M tokens
text-embedding-3-large3072$0.13/M tokens