From 370466691356ba060bd5ff16b339118e105586b5 Mon Sep 17 00:00:00 2001
From: Andy <andy.yj@antgroup.com>
Date: Tue, 25 Feb 2025 14:06:24 +0800
Subject: [PATCH] Update README.md

---
 README.md | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/README.md b/README.md
index e10079b..b9085f3 100644
--- a/README.md
+++ b/README.md
@@ -341,6 +341,11 @@ English/[简体中文](https://github.com/deepseek-ai/awesome-deepseek-integrati
         <td> <a href="https://github.com/zilliztech/deep-searcher"> DeepSearcher </a> </td>
         <td> DeepSearcher combines powerful LLMs (DeepSeek, OpenAI, etc.) and Vector Databases (Milvus, etc.) to perform search, evaluation, and reasoning based on private data, providing highly accurate answer and comprehensive report.  </td>
     </tr>
+    <tr>
+        <td width="80"> <img src="https://raw.githubusercontent.com/OpenSPG/openspg/089188f3e7b0392221f5a8e8f1a3629b6352a6f9/LOGO.png" alt="Icon" width="64" height="auto"/> </td>
+        <td> <a href="https://github.com/OpenSPG/KAG/blob/master/README.md"> KAG </a> </td>
+        <td> KAG is a logical reasoning and Q&A framework based on the <a href="https://github.com/OpenSPG/openspg">OpenSPG</a> engine and large language models, which is used to build logical reasoning and Q&A solutions for vertical domain knowledge bases. KAG can effectively overcome the ambiguity of traditional RAG vector similarity calculation and the noise problem of GraphRAG introduced by OpenIE. KAG supports logical reasoning and multi-hop fact Q&A, etc.</td>
+    </tr>
    
 </table>