diff --git a/docs/extras/modules/chains/popular/openai_functions.ipynb b/docs/extras/modules/chains/popular/openai_functions.ipynb
index 44571cfb07..da4ed68ced 100644
--- a/docs/extras/modules/chains/popular/openai_functions.ipynb
+++ b/docs/extras/modules/chains/popular/openai_functions.ipynb
@@ -80,12 +80,13 @@
      "text": [
       "\n",
       "\n",
-      "\u001b[1m> Entering new  chain...\u001b[0m\n",
+      "\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
       "Prompt after formatting:\n",
       "\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for extracting information in structured formats.\n",
       "Human: Use the given format to extract information from the following input:\n",
       "Human: Sally is 13\n",
       "Human: Tips: Make sure to answer in the correct format\u001b[0m\n",
+      " {'function_call': {'name': '_OutputFormatter', 'arguments': '{\\n  \"output\": {\\n    \"name\": \"Sally\",\\n    \"age\": 13,\\n    \"fav_food\": \"Unknown\"\\n  }\\n}'}}\n",
       "\n",
       "\u001b[1m> Finished chain.\u001b[0m\n"
      ]
@@ -93,7 +94,7 @@
     {
      "data": {
       "text/plain": [
-       "{'name': 'Sally', 'age': 13}"
+       "Person(name='Sally', age=13, fav_food='Unknown')"
       ]
      },
      "execution_count": 3,
@@ -103,7 +104,7 @@
    ],
    "source": [
     "# If we pass in a model explicitly, we need to make sure it supports the OpenAI function-calling API.\n",
-    "llm = ChatOpenAI(model=\"gpt-3.5-turbo-0613\", temperature=0)\n",
+    "llm = ChatOpenAI(model=\"gpt-4\", temperature=0)\n",
     "\n",
     "prompt_msgs = [\n",
     "    SystemMessage(\n",
@@ -141,12 +142,13 @@
      "text": [
       "\n",
       "\n",
-      "\u001b[1m> Entering new  chain...\u001b[0m\n",
+      "\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
       "Prompt after formatting:\n",
       "\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for extracting information in structured formats.\n",
       "Human: Use the given format to extract information from the following input:\n",
       "Human: Sally is 13, Joey just turned 12 and loves spinach. Caroline is 10 years older than Sally, so she's 23.\n",
       "Human: Tips: Make sure to answer in the correct format\u001b[0m\n",
+      " {'function_call': {'name': '_OutputFormatter', 'arguments': '{\\n  \"output\": {\\n    \"people\": [\\n      {\\n        \"name\": \"Sally\",\\n        \"age\": 13,\\n        \"fav_food\": \"\"\\n      },\\n      {\\n        \"name\": \"Joey\",\\n        \"age\": 12,\\n        \"fav_food\": \"spinach\"\\n      },\\n      {\\n        \"name\": \"Caroline\",\\n        \"age\": 23,\\n        \"fav_food\": \"\"\\n      }\\n    ]\\n  }\\n}'}}\n",
       "\n",
       "\u001b[1m> Finished chain.\u001b[0m\n"
      ]
@@ -154,9 +156,7 @@
     {
      "data": {
       "text/plain": [
-       "{'people': [{'name': 'Sally', 'age': 13, 'fav_food': ''},\n",
-       "  {'name': 'Joey', 'age': 12, 'fav_food': 'spinach'},\n",
-       "  {'name': 'Caroline', 'age': 23, 'fav_food': ''}]}"
+       "People(people=[Person(name='Sally', age=13, fav_food=''), Person(name='Joey', age=12, fav_food='spinach'), Person(name='Caroline', age=23, fav_food='')])"
       ]
      },
      "execution_count": 4,
@@ -192,7 +192,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "id": "3484415e",
    "metadata": {},
    "outputs": [],
@@ -216,7 +216,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "id": "be9b76b3",
    "metadata": {},
    "outputs": [
@@ -226,12 +226,13 @@
      "text": [
       "\n",
       "\n",
-      "\u001b[1m> Entering new  chain...\u001b[0m\n",
+      "\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
       "Prompt after formatting:\n",
       "\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for extracting information in structured formats.\n",
       "Human: Use the given format to extract information from the following input:\n",
       "Human: Sally is 13\n",
       "Human: Tips: Make sure to answer in the correct format\u001b[0m\n",
+      " {'function_call': {'name': 'output_formatter', 'arguments': '{\\n  \"name\": \"Sally\",\\n  \"age\": 13\\n}'}}\n",
       "\n",
       "\u001b[1m> Finished chain.\u001b[0m\n"
      ]
@@ -242,7 +243,7 @@
        "{'name': 'Sally', 'age': 13}"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -278,7 +279,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "id": "17f52508",
    "metadata": {},
    "outputs": [],
@@ -301,7 +302,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "id": "a4658ad8",
    "metadata": {},
    "outputs": [
@@ -311,12 +312,13 @@
      "text": [
       "\n",
       "\n",
-      "\u001b[1m> Entering new  chain...\u001b[0m\n",
+      "\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
       "Prompt after formatting:\n",
       "\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for recording entities\n",
       "Human: Make calls to the relevant function to record the entities in the following input:\n",
       "Human: Harry was a chubby brown beagle who loved chicken\n",
       "Human: Tips: Make sure to answer in the correct format\u001b[0m\n",
+      " {'function_call': {'name': 'RecordDog', 'arguments': '{\\n  \"name\": \"Harry\",\\n  \"color\": \"brown\",\\n  \"fav_food\": \"chicken\"\\n}'}}\n",
       "\n",
       "\u001b[1m> Finished chain.\u001b[0m\n"
      ]
@@ -327,7 +329,7 @@
        "RecordDog(name='Harry', color='brown', fav_food='chicken')"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -360,7 +362,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "id": "95ac5825",
    "metadata": {},
    "outputs": [
@@ -370,12 +372,13 @@
      "text": [
       "\n",
       "\n",
-      "\u001b[1m> Entering new  chain...\u001b[0m\n",
+      "\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
       "Prompt after formatting:\n",
       "\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for recording entities\n",
       "Human: Make calls to the relevant function to record the entities in the following input:\n",
       "Human: The most important thing to remember about Tommy, my 12 year old, is that he'll do anything for apple pie.\n",
       "Human: Tips: Make sure to answer in the correct format\u001b[0m\n",
+      " {'function_call': {'name': 'record_person', 'arguments': '{\\n  \"name\": \"Tommy\",\\n  \"age\": 12,\\n  \"fav_food\": {\\n    \"food\": \"apple pie\"\\n  }\\n}'}}\n",
       "\n",
       "\u001b[1m> Finished chain.\u001b[0m\n"
      ]
@@ -386,7 +389,7 @@
        "{'name': 'Tommy', 'age': 12, 'fav_food': {'food': 'apple pie'}}"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -431,7 +434,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "id": "8b0d11de",
    "metadata": {},
    "outputs": [
@@ -441,12 +444,13 @@
      "text": [
       "\n",
       "\n",
-      "\u001b[1m> Entering new  chain...\u001b[0m\n",
+      "\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
       "Prompt after formatting:\n",
       "\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for recording entities\n",
       "Human: Make calls to the relevant function to record the entities in the following input:\n",
       "Human: I can't find my dog Henry anywhere, he's a small brown beagle. Could you send a message about him?\n",
       "Human: Tips: Make sure to answer in the correct format\u001b[0m\n",
+      " {'function_call': {'name': 'record_dog', 'arguments': '{\\n  \"name\": \"Henry\",\\n  \"color\": \"brown\",\\n  \"fav_food\": {\\n    \"food\": null\\n  }\\n}'}}\n",
       "\n",
       "\u001b[1m> Finished chain.\u001b[0m\n"
      ]
@@ -458,7 +462,7 @@
        " 'arguments': {'name': 'Henry', 'color': 'brown', 'fav_food': {'food': None}}}"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -494,14 +498,6 @@
     "- [OpenAPI](/docs/modules/chains/additional/openapi_openai): take an OpenAPI spec and create + execute valid requests against the API, using OpenAI functions under the hood.\n",
     "- [QA with citations](/docs/modules/chains/additional/qa_citations): use OpenAI functions ability to extract citations from text."
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "93425c66",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
diff --git a/langchain/chat_models/openai.py b/langchain/chat_models/openai.py
index 0a8d7b84fd..fbc888111e 100644
--- a/langchain/chat_models/openai.py
+++ b/langchain/chat_models/openai.py
@@ -102,7 +102,7 @@ def _convert_dict_to_message(_dict: Mapping[str, Any]) -> BaseMessage:
     elif role == "assistant":
         # Fix for azure
         # Also OpenAI returns None for tool invocations
-        content = _dict.get("content", "")
+        content = _dict.get("content", "") or ""
         if _dict.get("function_call"):
             additional_kwargs = {"function_call": dict(_dict["function_call"])}
         else: