PALModelEmbeddings

class hana_ai.vectorstore.embedding_service.PALModelEmbeddings(connection_context, model_version=None, batch_size=None, thread_number=None, is_query=None, **kwargs)

PAL embedding model.

Parameters:
connection_contextConnectionContext

Connection context.

model_versionstr, optional

Model version. Default to None.

batch_sizeint, optional

Batch size. Default to None.

thread_numberint, optional

Thread number. Default to None.

is_querybool, optional

Use different embedding model for query purpose. Default to None.

embed_documents(texts: List[str]) List[List[float]]

Embed multiple documents.

Parameters:
textsList[str]

List of texts.

Returns:
List[List[float]]

List of embeddings.

embed_query(text: str) List[float]

Embed a single query.

Parameters:
textstr

Text.

Returns:
List[float]

Embedding.

get_text_embedding_batch(texts: List[str], show_progress=False, **kwargs)

Get text embedding batch.

Parameters:
textsList[str]

List of texts.

Returns:
List[List[float]]

List of embeddings.