diff --git a/docs/docs/tutorials/chatbot.ipynb b/docs/docs/tutorials/chatbot.ipynb
index 05f73ef9525a5..996892c9bc16c 100644
--- a/docs/docs/tutorials/chatbot.ipynb
+++ b/docs/docs/tutorials/chatbot.ipynb
@@ -105,7 +105,7 @@
     "\n",
     "## Quickstart\n",
     "\n",
-    "First up, let's learn how to use a language model by itself. LangChain supports many different language models that you can use interchangably - select the one you want to use below!\n",
+    "First up, let's learn how to use a language model by itself. LangChain supports many different language models that you can use interchangeably - select the one you want to use below!\n",
     "\n",
     "```{=mdx}\n",
     "import ChatModelTabs from \"@theme/ChatModelTabs\";\n",
@@ -254,7 +254,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# ! pip install langchain_community"
+    "%pip install langchain_community"
    ]
   },
   {
@@ -952,7 +952,7 @@
    "source": [
     "## Streaming\n",
     "\n",
-    "Now we've got a function chatbot. However, one *really* important UX consideration for chatbot application is streaming. LLMs can sometimes take a while to respond, and so in order to improve the user experience one thing that most application do is stream back each token as it is generated. This allows the user to see progress.\n",
+    "Now we've got a functioning chatbot. However, one *really* important UX consideration for chatbot applications is streaming. LLMs can sometimes take a while to respond, and so in order to improve the user experience one thing that most applications do is stream back each token as it is generated. This allows the user to see progress.\n",
     "\n",
     "It's actually super easy to do this!\n",
     "\n",