docs[patch]: Update PineconeStore creation to include namespace parameter

docs/core_docs/docs/how_to/qa_per_user.ipynb

@@ -121,9 +121,19 @@
         "\n",
         "const pineconeIndex = pinecone.Index(Deno.env.get(\"PINECONE_INDEX\"));\n",
         "\n",
+        "/**\n",
+        " * Pinecone allows you to partition the records in an index into namespaces. \n",
+        " * Queries and other operations are then limited to one namespace, \n",
+        " * so different requests can search different subsets of your index.\n",
+        " * Read more about namespaces here: https://docs.pinecone.io/guides/indexes/use-namespaces\n",
+        " * \n",
+        " * NOTE: If you have namespace enabled in your Pinecone index, you must provide the namespace when creating the PineconeStore.\n",
+        " */\n",
+        "const namespace = \"pinecone\";\n",
+        "\n",
         "const vectorStore = await PineconeStore.fromExistingIndex(\n",
         "  new OpenAIEmbeddings(),\n",
-        "  { pineconeIndex },\n",
+        "  { pineconeIndex, namespace },\n",
         ");\n",
         "\n",
         "await vectorStore.addDocuments(\n",

examples/src/indexes/vector_stores/pinecone/mmr.ts

@@ -11,9 +11,19 @@ const pinecone = new Pinecone();
 
 const pineconeIndex = pinecone.Index(process.env.PINECONE_INDEX!);
 
+/**
+ * Pinecone allows you to partition the records in an index into namespaces.
+ * Queries and other operations are then limited to one namespace,
+ * so different requests can search different subsets of your index.
+ * Read more about namespaces here: https://docs.pinecone.io/guides/indexes/use-namespaces
+ *
+ * NOTE: If you have namespace enabled in your Pinecone index, you must provide the namespace when creating the PineconeStore.
+ */
+const namespace = "pinecone";
+
 const vectorStore = await PineconeStore.fromExistingIndex(
   new OpenAIEmbeddings(),
-  { pineconeIndex }
+  { pineconeIndex, namespace }
 );
 
 /* Search the vector DB independently with meta filters */

examples/src/indexes/vector_stores/pinecone/query_docs.ts

@@ -11,9 +11,19 @@ const pinecone = new Pinecone();
 
 const pineconeIndex = pinecone.Index(process.env.PINECONE_INDEX!);
 
+/**
+ * Pinecone allows you to partition the records in an index into namespaces.
+ * Queries and other operations are then limited to one namespace,
+ * so different requests can search different subsets of your index.
+ * Read more about namespaces here: https://docs.pinecone.io/guides/indexes/use-namespaces
+ *
+ * NOTE: If you have namespace enabled in your Pinecone index, you must provide the namespace when creating the PineconeStore.
+ */
+const namespace = "pinecone";
+
 const vectorStore = await PineconeStore.fromExistingIndex(
   new OpenAIEmbeddings(),
-  { pineconeIndex }
+  { pineconeIndex, namespace }
 );
 
 /* Search the vector DB independently with metadata filters */

examples/src/prompts/semantic_similarity_example_selector_custom_retriever.ts

@@ -11,9 +11,19 @@ const pinecone = new Pinecone();
 
 const pineconeIndex = pinecone.Index(process.env.PINECONE_INDEX!);
 
+/**
+ * Pinecone allows you to partition the records in an index into namespaces.
+ * Queries and other operations are then limited to one namespace,
+ * so different requests can search different subsets of your index.
+ * Read more about namespaces here: https://docs.pinecone.io/guides/indexes/use-namespaces
+ *
+ * NOTE: If you have namespace enabled in your Pinecone index, you must provide the namespace when creating the PineconeStore.
+ */
+const namespace = "pinecone";
+
 const pineconeVectorstore = await PineconeStore.fromExistingIndex(
   new OpenAIEmbeddings(),
-  { pineconeIndex }
+  { pineconeIndex, namespace }
 );
 
 const pineconeMmrRetriever = pineconeVectorstore.asRetriever({