docs: add Pinecone tab to "How to create and query vector stores"

docs/docs/how_to/vectorstores.mdx

@@ -55,6 +55,41 @@ pip install langchain-chroma
 from langchain_chroma import Chroma
 
 db = Chroma.from_documents(documents, OpenAIEmbeddings())
+```
+
+  </TabItem>
+  <TabItem value="pinecone" label="Pinecone">
+
+This walkthrough uses the `Pinecone` vector database, which provides broad functionality to store and search over vectors. For a more detailed guide to using Pinecone with LangChain, check out the [Pinecone integration page](/docs/integrations/vectorstores/pinecone).
+
+```bash
+pip install langchain-pinecone
+```
+
+```python
+import time
+from langchain_pinecone import PineconeVectorStore
+from pinecone import Pinecone, ServerlessSpec
+
+pc = Pinecone(api_key=pinecone_api_key)
+
+os.environ['PINECONE_API_KEY'] = getpass.getpass('Pinecone API Key:')
+
+index_name = "langchain-index" #change if desired
+
+if index_name not in existing_indexes:
+    pc.create_index(
+        name=index_name,
+        dimension=1536,
+        metric="cosine",
+        spec=ServerlessSpec(cloud="aws", region="us-east-1"),
+    )
+    while not pc.describe_index(index_name).status["ready"]:
+        time.sleep(1)
+
+index = pc.Index(index_name)
+
+docsearch = PineconeVectorStore.from_documents(documents, OpenAIEmbeddings(), index_name=index_name)
 ```
 
   </TabItem>