跳转到内容

Aleph Alpha 嵌入

如果您在 Colab 上打开这个笔记本，您可能需要安装 LlamaIndex 🦙。

%pip install llama-index-embeddings-alephalpha

!pip install llama-index

# Initialise with your AA token
import os

os.environ["AA_TOKEN"] = "your_token_here"

使用 `luminous-base` 嵌入。

representation=“Document”：用于您想要存储在向量数据库中的文本（文档）
representation=“Query”：用于搜索查询，以在您的向量数据库中找到最相关的文档
representation=“Symmetric”: 适用于聚类、分类、异常检测或可视化任务。

from llama_index.embeddings.alephalpha import AlephAlphaEmbedding

# To customize your token, do this
# otherwise it will lookup AA_TOKEN from your env variable
# embed_model = AlephAlpha(token="<aa_token>")

# with representation='query'
embed_model = AlephAlphaEmbedding(
    model="luminous-base",
    representation="Query",
)

embeddings = embed_model.get_text_embedding("Hello Aleph Alpha!")

print(len(embeddings))
print(embeddings[:5])

representation_enum: SemanticRepresentation.Query


5120
[0.14257812, 2.59375, 0.33203125, -0.33789062, -0.94140625]

# with representation='Document'
embed_model = AlephAlphaEmbedding(
    model="luminous-base",
    representation="Document",
)

embeddings = embed_model.get_text_embedding("Hello Aleph Alpha!")

print(len(embeddings))
print(embeddings[:5])

representation_enum: SemanticRepresentation.Document


5120
[0.14257812, 2.59375, 0.33203125, -0.33789062, -0.94140625]