afrom_embeddings(
cls: Type[AzureSearch],
text_embeddings: Iterable[Tuple[str| Name | Type | Description |
|---|---|---|
text_embeddings* | Iterable[Tuple[str, List[float]]] | Iterable of (text, embedding) tuples. |
embedding* | Embeddings | Embeddings instance to use for future queries. |
metadatas | Optional[List[dict]] | Default: None |
azure_search_endpoint | str | Default: '' |
azure_search_key | str | Default: '' |
index_name | str | Default: 'langchain-index' |
fields | Optional[List[SearchField]] | Default: None |
**kwargs | Any | Default: {} |
Asynchronously create Azure Search vector store from text embeddings.
Optional list of metadata dicts for each text.
Azure Search service endpoint.
Azure Search service API key.
Name of the search index. Defaults to "langchain-index".
List of search fields to use for the index.
Additional keyword arguments.