From a96a6e0f2cc93b85272107c840375f362cb269cd Mon Sep 17 00:00:00 2001
From: Prashanth Rao <35005448+prrao87@users.noreply.github.com>
Date: Mon, 11 Mar 2024 10:42:46 -0400
Subject: [PATCH] =?UTF-8?q?docs:=20Fix=20typo=20and=20add=20K=C3=B9zuDB=20?=
 =?UTF-8?q?to=20graphs=20docs=20(#18915)?=
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- **Description:** Adding Kùzu (an embedded graph DB that uses Cypher)
to the graph docs, and fixing a typo
 - **Issue:** docs update
---
 docs/docs/use_cases/graph/index.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/docs/use_cases/graph/index.ipynb b/docs/docs/use_cases/graph/index.ipynb
index 345560bc68..06bffdbf7a 100644
--- a/docs/docs/use_cases/graph/index.ipynb
+++ b/docs/docs/use_cases/graph/index.ipynb
@@ -15,7 +15,7 @@
    "source": [
     "# Graphs\n",
     "\n",
-    "One of the common types of databases that we can build Q&A systems for are graph databases. LangChain comes with a number of built-in chains and agents that are compatible with graph query language dialects like Cypher, SparQL, and others (e.g., Neo4j, MemGraph, Amazon Neptune, OntoText, Tigegraph). They enable use cases such as:\n",
+    "One of the common types of databases that we can build Q&A systems for are graph databases. LangChain comes with a number of built-in chains and agents that are compatible with graph query language dialects like Cypher, SparQL, and others (e.g., Neo4j, MemGraph, Amazon Neptune, Kùzu, OntoText, Tigergraph). They enable use cases such as:\n",
     "\n",
     "* Generating queries that will be run based on natural language questions,\n",
     "* Creating chatbots that can answer questions based on database data,\n",