create_index#

langchain_community.retrievers.pinecone_hybrid_search.create_index( contexts: List[str], index: Any, embeddings: Embeddings, sparse_encoder: Any, ids: List[str] | None = None, metadatas: List[dict] | None = None, namespace: str | None = None, text_key: str = 'context', ) → None[source]#

Create an index from a list of contexts.

It modifies the index argument in-place!

Parameters:

contexts (List[str]) – List of contexts to embed.
index (Any) – Index to use.
embeddings (Embeddings) – Embeddings model to use.
sparse_encoder (Any) – Sparse encoder to use.
ids (List[str] | None) – List of ids to use for the documents.
metadatas (List[dict] | None) – List of metadata to use for the documents.
namespace (str | None) – Namespace value for index partition.
text_key (str)

Return type:

None