From 486d5412af683c509674f4c3086cb2102c87aa5e Mon Sep 17 00:00:00 2001
From: Talha Munir <103119362+devs-talha@users.noreply.github.com>
Date: Sun, 24 Nov 2024 00:37:55 +0500
Subject: [PATCH] docs: Fix grammatical mistake in introduction.ipynb (#2521)

---
 docs/docs/tutorials/introduction.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/docs/tutorials/introduction.ipynb b/docs/docs/tutorials/introduction.ipynb
index 712fbc28f..119fbf861 100644
--- a/docs/docs/tutorials/introduction.ipynb
+++ b/docs/docs/tutorials/introduction.ipynb
@@ -2043,7 +2043,7 @@
     "\n",
     "So far, we've relied on a simple state (it's just a list of messages!). You can go far with this simple state, but if you want to define complex behavior without relying on the message list, you can add additional fields to the state. In this section, we will extend our chat bot with a new node to illustrate this.\n",
     "\n",
-    "In the examples above, we involved a human deterministically: the graph __always__ interrupted whenever an tool was invoked. Suppose we wanted our chat bot to have the choice of relying on a human.\n",
+    "In the examples above, we involved a human deterministically: the graph __always__ interrupted whenever a tool was invoked. Suppose we wanted our chat bot to have the choice of relying on a human.\n",
     "\n",
     "One way to do this is to create a passthrough \"human\" node, before which the graph will always stop. We will only execute this node if the LLM invokes a \"human\" tool. For our convenience, we will include an \"ask_human\" flag in our graph state that we will flip if the LLM calls this tool.\n",
     "\n",