pinecone[patch], docs: PineconeVectorStore, release 0.0.3 (#17896)

libs/community/langchain_community/vectorstores/pinecone.py

@@ -402,7 +402,9 @@ class Pinecone(VectorStore):
         embeddings_chunk_size: int = 1000,
         **kwargs: Any,
     ) -> Pinecone:
-        """Construct Pinecone wrapper from raw documents.
+        """
+        DEPRECATED: use langchain_pinecone.PineconeVectorStore.from_texts instead:
+        Construct Pinecone wrapper from raw documents.
 
         This is a user friendly interface that:
             1. Embeds documents.
@@ -411,21 +413,20 @@ class Pinecone(VectorStore):
         This is intended to be a quick way to get started.
 
         The `pool_threads` affects the speed of the upsert operations.
+
         Example:
             .. code-block:: python
 
-                from langchain_community.vectorstores import Pinecone
-                from langchain_community.embeddings import OpenAIEmbeddings
-                import pinecone
+                from langchain_pinecone import PineconeVectorStore
+                from langchain_openai import OpenAIEmbeddings
 
-                # The environment should be the one specified next to the API key
-                # in your Pinecone console
-                pinecone.init(api_key="***", environment="...")
                 embeddings = OpenAIEmbeddings()
-                pinecone = Pinecone.from_texts(
-                    texts,
-                    embeddings,
-                    index_name="langchain-demo"
+                index_name = "my-index"
+                namespace = "my-namespace"
+                vectorstore = Pinecone(
+                    index_name=index_name,
+                    embedding=embedding,
+                    namespace=namespace,
                 )
         """
         pinecone_index = cls.get_pinecone_index(index_name, pool_threads)