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Showing content from https://python.langchain.com/docs/integrations/text_embedding/aleph_alpha below:

Aleph Alpha | 🦜️🔗 LangChain

Aleph Alpha

There are two possible ways to use Aleph Alpha's semantic embeddings. If you have texts with a dissimilar structure (e.g. a Document and a Query) you would want to use asymmetric embeddings. Conversely, for texts with comparable structures, symmetric embeddings are the suggested approach.

Asymmetric
from langchain_community.embeddings import AlephAlphaAsymmetricSemanticEmbedding
document = "This is a content of the document"
query = "What is the content of the document?"
embeddings = AlephAlphaAsymmetricSemanticEmbedding(normalize=True, compress_to_size=128)
doc_result = embeddings.embed_documents([document])
query_result = embeddings.embed_query(query)
Symmetric
from langchain_community.embeddings import AlephAlphaSymmetricSemanticEmbedding
text = "This is a test text"
embeddings = AlephAlphaSymmetricSemanticEmbedding(normalize=True, compress_to_size=128)
doc_result = embeddings.embed_documents([text])
query_result = embeddings.embed_query(text)

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