docs: update notebook for new Pinecone API + serverless (#21923)

Thank you for contributing to LangChain!

- [x] **PR title**: "docs: update notebook for new Pinecone API +
serverless"


- [x] **PR message**: The published notebook is not runnable after
`pinecone-client` v2, which is deprecated. `langchain-pinecone` is not
compatible with the latest `pinecone-client` (v4), so I hardcoded it to
the last v3. Also updated for serverless indexes (only index type
available on Pinecone free plan).


- [x] **Add tests and docs**: N/A (tested in Colab)


- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/

Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.

If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.


---
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docs/docs/integrations/retrievers/self_query/pinecone.ipynb

@@ -42,7 +42,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install --upgrade --quiet  pinecone-client"
+    "%pip install --upgrade --quiet pinecone-notebooks pinecone-client==3.2.2"
    ]
   },
   {
@@ -61,13 +61,50 @@
     }
    ],
    "source": [
+    "# Connect to Pinecone and get an API key.\n",
+    "from pinecone_notebooks.colab import Authenticate\n",
+    "\n",
+    "Authenticate()\n",
+    "\n",
     "import os\n",
     "\n",
-    "import pinecone\n",
+    "api_key = os.environ[\"PINECONE_API_KEY\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bdaebe0d",
+   "metadata": {},
+   "source": [
+    "We want to use `OpenAIEmbeddings` so we have to get the OpenAI API Key."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "04b33384",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import getpass\n",
     "\n",
-    "pinecone.init(\n",
+    "os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"OpenAI API Key:\")"
-    "    api_key=os.environ[\"PINECONE_API_KEY\"], environment=os.environ[\"PINECONE_ENV\"]\n",
+   ]
-    ")"
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c9ab3a96",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pinecone import Pinecone, ServerlessSpec\n",
+    "\n",
+    "api_key = os.getenv(\"PINECONE_API_KEY\") or \"PINECONE_API_KEY\"\n",
+    "\n",
+    "index_name = \"langchain-self-retriever-demo\"\n",
+    "\n",
+    "pc = Pinecone(api_key=api_key)"
    ]
   },
   {
@@ -82,8 +119,15 @@
     "from langchain_pinecone import PineconeVectorStore\n",
     "\n",
     "embeddings = OpenAIEmbeddings()\n",
+    "\n",
     "# create new index\n",
-    "pinecone.create_index(\"langchain-self-retriever-demo\", dimension=1536)"
+    "if index_name not in pc.list_indexes().names():\n",
+    "    pc.create_index(\n",
+    "        name=index_name,\n",
+    "        dimension=1536,\n",
+    "        metric=\"cosine\",\n",
+    "        spec=ServerlessSpec(cloud=\"aws\", region=\"us-east-1\"),\n",
+    "    )"
    ]
   },
   {