from_texts

This is a user-friendly interface that:

1. Embeds documents.
2. Adds the documents to a provided Pinecone index

This is intended to be a quick way to get started.

The pool_threads affects the speed of the upsert operations.

Setup: set the PINECONE_API_KEY environment variable to your Pinecone API key.

Example:

from langchain_pinecone import PineconeVectorStore, PineconeEmbeddings

embeddings = PineconeEmbeddings(model="multilingual-e5-large")

index_name = "my-index"
vectorstore = PineconeVectorStore.from_texts(
    texts,
    index_name=index_name,
    embedding=embedding,
    namespace=namespace,
)