From a84524ada8612e5e93f27facfa93c5dc2b820f32 Mon Sep 17 00:00:00 2001
From: hshen14 <haihao.shen@intel.com>
Date: Thu, 21 Mar 2024 13:49:20 +0800
Subject: [PATCH 1/5] Update ChatQnA

---
 README.md | 56 +++++++++++++++++++++++++++++++++++++++++++++++--------
 1 file changed, 48 insertions(+), 8 deletions(-)

diff --git a/README.md b/README.md
index aa5c52ca23..f9954ea6a5 100644
--- a/README.md
+++ b/README.md
@@ -1,15 +1,55 @@
-# GenerativeAIExamples
-Generative AI (GenAI) Examples is a collection of GenAI examples such as ChatQnA, Copilot, which heavily reused ecosystem-based components plus Intel optimizations.
+# Intel Generative AI Examples
 
-# ChatQnA
-[ChatQnA](./ChatQnA/README.md) is a chatbot for question and answering through retrieval argumented generation (RAG). The example is developed with Langchain API and Redis as vector store, and deployed on Gaudi with Xeon through Hugging Face text generation inference (TGI) serving.
+## Introduction
 
-# CodeGen
+This project provides a collective list of Generative AI (GenAI) examples such as chatbot with question and answering (ChatQnA), code generation, document summary, etc. The examples are developed by leveraging the ecosystem components with Intel optimizations, therefore delivering the high perforamnce on Intel platforms. 
+
+## GenAI Examples
+
+### ChatQnA
+
+[ChatQnA](./ChatQnA/README.md) is an example of chatbot with question and answering through retrieval argumented generation (RAG).
+
+
+<table>
+	<tbody>
+		<tr>
+			<td colspan="2">Framework</td>
+			<td colspan="2">LLM</td>
+			<td colspan="2">Embedding</td>
+			<td colspan="2">Vector Database</td>
+			<td colspan="2">Serving</td>
+			<td colspan="2">HW</td>
+			<td colspan="2">Description</td>
+		</tr>
+		<tr>
+			<td>[angChain](https://www.langchain.com/)</td>
+			<td>[NeuralChat-v3](https://huggingface.co/Intel/neural-chat-7b-v3-1)</td>
+			<td>[BGE-Base](https://huggingface.co/BAAI/bge-base-en)</td>
+			<td>[Redis](https://redis.io/)</td>
+			<td>[TGI-Habana](https://github.com/huggingface/tgi-gaudi)</td>
+			<td>Gaudi2</td>
+			<td>Chatbot</td>
+		</tr>
+		<tr>
+			<td>[angChain](https://www.langchain.com/)</td>
+			<td>[NeuralChat-v3](https://huggingface.co/Intel/neural-chat-7b-v3-1)</td>
+			<td>[BGE-Base](https://huggingface.co/BAAI/bge-base-en)</td>
+			<td>[Chroma](https://www.trychroma.com/)</td>
+			<td>[TGI-Habana](https://github.com/huggingface/tgi-gaudi)</td>
+			<td>Gaudi2</td>
+			<td>Chatbot</td>
+		</tr>
+	</tbody>
+</table>
+
+
+### CodeGen
 [CodeGen](./CodeGen/README.md) is a copilot application designed for code generation use case. We offer a VS Code plugin for easy usage. In this example, we demonstrate how code generation can be efficiently executed on the Intel Gaudi2 platform.
 
 
-# DocSum
+### DocSum
 [DocSum](./DocSum/README.md) is a chatbot for summarizing the content of your documents or reports. The example is developed with Langchain API and deployed on Gaudi through Hugging Face text generation inference (TGI) serving.
 
-# VisualQnA
-[VisualQnA](./VisualQnA/README.md) is a chatbot for visual question and answering task. This example guides you through how to deploy a [LLaVA](https://llava-vl.github.io/) (Large Language and Vision Assistant) model on Intel Gaudi2.
\ No newline at end of file
+### VisualQnA
+[VisualQnA](./VisualQnA/README.md) is a chatbot for visual question and answering task. This example guides you through how to deploy a [LLaVA](https://llava-vl.github.io/) (Large Language and Vision Assistant) model on Intel Gaudi2.

From 16874c236bf490a67979ca907753875cf57b5eec Mon Sep 17 00:00:00 2001
From: hshen14 <haihao.shen@intel.com>
Date: Thu, 21 Mar 2024 13:59:13 +0800
Subject: [PATCH 2/5] Format table

---
 README.md | 34 +++++++++++++++++-----------------
 1 file changed, 17 insertions(+), 17 deletions(-)

diff --git a/README.md b/README.md
index f9954ea6a5..c17d46ebc9 100644
--- a/README.md
+++ b/README.md
@@ -14,29 +14,29 @@ This project provides a collective list of Generative AI (GenAI) examples such a
 <table>
 	<tbody>
 		<tr>
-			<td colspan="2">Framework</td>
-			<td colspan="2">LLM</td>
-			<td colspan="2">Embedding</td>
-			<td colspan="2">Vector Database</td>
-			<td colspan="2">Serving</td>
-			<td colspan="2">HW</td>
-			<td colspan="2">Description</td>
+			<td>Framework</td>
+			<td>LLM</td>
+			<td>Embedding</td>
+			<td>Vector Database</td>
+			<td>Serving</td>
+			<td>HW</td>
+			<td>Description</td>
 		</tr>
 		<tr>
-			<td>[angChain](https://www.langchain.com/)</td>
-			<td>[NeuralChat-v3](https://huggingface.co/Intel/neural-chat-7b-v3-1)</td>
-			<td>[BGE-Base](https://huggingface.co/BAAI/bge-base-en)</td>
-			<td>[Redis](https://redis.io/)</td>
-			<td>[TGI-Habana](https://github.com/huggingface/tgi-gaudi)</td>
+			<td><a href="https://www.langchain.com">LangChain</a></td>
+			<td><a href="https://huggingface.co/Intel/neural-chat-7b-v3-1">NeuralChat-v3</a></td>
+			<td><a href="https://huggingface.co/BAAI/bge-base-en">BGE-Base</a></td>
+			<td><a href="https://redis.io/">Redis</a></td>
+			<td><a href="https://github.com/huggingface/tgi-gaudi">TGI-Habana</a></td>
 			<td>Gaudi2</td>
 			<td>Chatbot</td>
 		</tr>
 		<tr>
-			<td>[angChain](https://www.langchain.com/)</td>
-			<td>[NeuralChat-v3](https://huggingface.co/Intel/neural-chat-7b-v3-1)</td>
-			<td>[BGE-Base](https://huggingface.co/BAAI/bge-base-en)</td>
-			<td>[Chroma](https://www.trychroma.com/)</td>
-			<td>[TGI-Habana](https://github.com/huggingface/tgi-gaudi)</td>
+			<td><a href="https://www.langchain.com">LangChain</a></td>
+			<td><a href="https://huggingface.co/Intel/neural-chat-7b-v3-1">NeuralChat-v3</a></td>
+			<td><a href="https://huggingface.co/BAAI/bge-base-en">BGE-Base</a></td>
+			<td><a href="https://www.trychroma.com/">Chroma</a></td>
+			<td><a href="https://github.com/huggingface/tgi-gaudi">TGI-Habana</a></td>
 			<td>Gaudi2</td>
 			<td>Chatbot</td>
 		</tr>

From b904b3974e6da235a831d82aab05d581d4e02898 Mon Sep 17 00:00:00 2001
From: hshen14 <haihao.shen@intel.com>
Date: Thu, 21 Mar 2024 14:16:48 +0800
Subject: [PATCH 3/5] Format table

---
 README.md | 77 +++++++++++++++++++++++++++++++++++++++++++++++++++++--
 1 file changed, 75 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index c17d46ebc9..f049a21146 100644
--- a/README.md
+++ b/README.md
@@ -24,7 +24,7 @@ This project provides a collective list of Generative AI (GenAI) examples such a
 		</tr>
 		<tr>
 			<td><a href="https://www.langchain.com">LangChain</a></td>
-			<td><a href="https://huggingface.co/Intel/neural-chat-7b-v3-1">NeuralChat-v3</a></td>
+			<td><a href="https://huggingface.co/Intel/neural-chat-7b-v3-3">NeuralChat-7B</a></td>
 			<td><a href="https://huggingface.co/BAAI/bge-base-en">BGE-Base</a></td>
 			<td><a href="https://redis.io/">Redis</a></td>
 			<td><a href="https://github.com/huggingface/tgi-gaudi">TGI-Habana</a></td>
@@ -33,13 +33,22 @@ This project provides a collective list of Generative AI (GenAI) examples such a
 		</tr>
 		<tr>
 			<td><a href="https://www.langchain.com">LangChain</a></td>
-			<td><a href="https://huggingface.co/Intel/neural-chat-7b-v3-1">NeuralChat-v3</a></td>
+			<td><a href="https://huggingface.co/Intel/neural-chat-7b-v3-3">NeuralChat-7B</a></td>
 			<td><a href="https://huggingface.co/BAAI/bge-base-en">BGE-Base</a></td>
 			<td><a href="https://www.trychroma.com/">Chroma</a></td>
 			<td><a href="https://github.com/huggingface/tgi-gaudi">TGI-Habana</a></td>
 			<td>Gaudi2</td>
 			<td>Chatbot</td>
 		</tr>
+		<tr>
+			<td><a href="https://www.langchain.com">LangChain</a></td>
+			<td><a href="https://huggingface.co/mistralai/Mistral-7B-v0.1">Mistral-7B</a></td>
+			<td><a href="https://huggingface.co/BAAI/bge-base-en">BGE-Base</a></td>
+			<td><a href="https://redis.io/">Redis</a></td>
+			<td><a href="https://github.com/huggingface/tgi-gaudi">TGI-Habana</a></td>
+			<td>Gaudi2</td>
+			<td>Chatbot</td>
+		</tr>
 	</tbody>
 </table>
 
@@ -47,9 +56,73 @@ This project provides a collective list of Generative AI (GenAI) examples such a
 ### CodeGen
 [CodeGen](./CodeGen/README.md) is a copilot application designed for code generation use case. We offer a VS Code plugin for easy usage. In this example, we demonstrate how code generation can be efficiently executed on the Intel Gaudi2 platform.
 
+<table>
+	<tbody>
+		<tr>
+			<td>Framework</td>
+			<td>LLM</td>
+			<td>Serving</td>
+			<td>HW</td>
+			<td>Description</td>
+		</tr>
+		<tr>
+			<td><a href="https://www.langchain.com">LangChain</a></td>
+			<td><a href="https://huggingface.co/deepseek-ai/deepseek-coder-33b-instruct">Deepseek-Coder-33B</a></td>
+			<td><a href="https://github.com/huggingface/tgi-gaudi">TGI-Habana</a></td>
+			<td>Gaudi2</td>
+			<td>Chatbot</td>
+		</tr>
+	</tbody>
+</table>
+
 
 ### DocSum
 [DocSum](./DocSum/README.md) is a chatbot for summarizing the content of your documents or reports. The example is developed with Langchain API and deployed on Gaudi through Hugging Face text generation inference (TGI) serving.
 
+<table>
+	<tbody>
+		<tr>
+			<td>Framework</td>
+			<td>LLM</td>
+			<td>Serving</td>
+			<td>HW</td>
+			<td>Description</td>
+		</tr>
+		<tr>
+			<td><a href="https://www.langchain.com">LangChain</a></td>
+			<td><a href="https://huggingface.co/Intel/neural-chat-7b-v3-3">NeuralChat-7B</a></td>
+			<td><a href="https://github.com/huggingface/tgi-gaudi">TGI-Habana</a></td>
+			<td>Gaudi2</td>
+			<td>Chatbot</td>
+		</tr>
+		<tr>
+			<td><a href="https://www.langchain.com">LangChain</a></td>
+			<td><a href="https://huggingface.co/mistralai/Mistral-7B-v0.1">Mistral-7B</a></td>
+			<td><a href="https://github.com/huggingface/tgi-gaudi">TGI-Habana</a></td>
+			<td>Gaudi2</td>
+			<td>Chatbot</td>
+		</tr>
+	</tbody>
+</table>
+
 ### VisualQnA
 [VisualQnA](./VisualQnA/README.md) is a chatbot for visual question and answering task. This example guides you through how to deploy a [LLaVA](https://llava-vl.github.io/) (Large Language and Vision Assistant) model on Intel Gaudi2.
+
+<table>
+	<tbody>
+		<tr>
+			<td>Framework</td>
+			<td>LLM</td>
+			<td>Serving</td>
+			<td>HW</td>
+			<td>Description</td>
+		</tr>
+		<tr>
+			<td><a href="https://www.langchain.com">LangChain</a></td>
+			<td><a href="https://huggingface.co/llava-hf/llava-1.5-7b-hf">LLaVA-1.5-7B</a></td>
+			<td><a href="https://github.com/huggingface/tgi-gaudi">TGI-Habana</a></td>
+			<td>Gaudi2</td>
+			<td>Chatbot</td>
+		</tr>
+	</tbody>
+</table>

From 2b9a3a3d465bbe323a3bd93481494df0095a2d3b Mon Sep 17 00:00:00 2001
From: hshen14 <haihao.shen@intel.com>
Date: Thu, 21 Mar 2024 14:50:31 +0800
Subject: [PATCH 4/5] Refine the readme

---
 README.md | 19 ++++++++++++-------
 1 file changed, 12 insertions(+), 7 deletions(-)

diff --git a/README.md b/README.md
index f049a21146..5745a9936e 100644
--- a/README.md
+++ b/README.md
@@ -2,13 +2,19 @@
 
 ## Introduction
 
-This project provides a collective list of Generative AI (GenAI) examples such as chatbot with question and answering (ChatQnA), code generation, document summary, etc. The examples are developed by leveraging the ecosystem components with Intel optimizations, therefore delivering the high perforamnce on Intel platforms. 
+This project provides a collective list of Generative AI (GenAI) examples such as chatbot with question and answering (ChatQnA), code generation, document summary, etc. The examples are developed by leveraging the ecosystem components such as LangChain with Intel optimizations, therefore delivering the high performance for your deployment on Intel platforms.
 
 ## GenAI Examples
+All the examples are well-validated on Intel platforms withe below features:
 
-### ChatQnA
+* <b>Easy to use</b>. Use ecosystem-compliant APIs to build the end-to-end GenAI examples.
+
+* <b>Easy to customize</b>. Customize the example using different framework, LLM, embedding, serving.
 
-[ChatQnA](./ChatQnA/README.md) is an example of chatbot with question and answering through retrieval argumented generation (RAG).
+* <b>Easy to deploy</b>. Deploy the GenAI examples with performance on Intel platforms.
+
+### ChatQnA
+[ChatQnA](./ChatQnA/README.md) is an example of chatbot for question and answering through retrieval argumented generation (RAG).
 
 
 <table>
@@ -52,9 +58,8 @@ This project provides a collective list of Generative AI (GenAI) examples such a
 	</tbody>
 </table>
 
-
 ### CodeGen
-[CodeGen](./CodeGen/README.md) is a copilot application designed for code generation use case. We offer a VS Code plugin for easy usage. In this example, we demonstrate how code generation can be efficiently executed on the Intel Gaudi2 platform.
+[CodeGen](./CodeGen/README.md) is an example of copilot designed for code generation in Visual Studio Code.
 
 <table>
 	<tbody>
@@ -77,7 +82,7 @@ This project provides a collective list of Generative AI (GenAI) examples such a
 
 
 ### DocSum
-[DocSum](./DocSum/README.md) is a chatbot for summarizing the content of your documents or reports. The example is developed with Langchain API and deployed on Gaudi through Hugging Face text generation inference (TGI) serving.
+[DocSum](./DocSum/README.md) is an example of chatbot for summarizing the content of your documents or reports.
 
 <table>
 	<tbody>
@@ -106,7 +111,7 @@ This project provides a collective list of Generative AI (GenAI) examples such a
 </table>
 
 ### VisualQnA
-[VisualQnA](./VisualQnA/README.md) is a chatbot for visual question and answering task. This example guides you through how to deploy a [LLaVA](https://llava-vl.github.io/) (Large Language and Vision Assistant) model on Intel Gaudi2.
+[VisualQnA](./VisualQnA/README.md) is an example of chatbot for question and answering based on images.
 
 <table>
 	<tbody>

From a90f86e6e20005f59234d24e06e57a0fe4b6ed96 Mon Sep 17 00:00:00 2001
From: hshen14 <haihao.shen@intel.com>
Date: Thu, 21 Mar 2024 14:53:21 +0800
Subject: [PATCH 5/5] Refine the readme

---
 README.md | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/README.md b/README.md
index 5745a9936e..1a5b87eed7 100644
--- a/README.md
+++ b/README.md
@@ -7,11 +7,11 @@ This project provides a collective list of Generative AI (GenAI) examples such a
 ## GenAI Examples
 All the examples are well-validated on Intel platforms withe below features:
 
-* <b>Easy to use</b>. Use ecosystem-compliant APIs to build the end-to-end GenAI examples.
+* <b>Easy to use</b>. Use ecosystem-compliant APIs to build the end-to-end GenAI examples
 
-* <b>Easy to customize</b>. Customize the example using different framework, LLM, embedding, serving.
+* <b>Easy to customize</b>. Customize the example using different framework, LLM, embedding, serving
 
-* <b>Easy to deploy</b>. Deploy the GenAI examples with performance on Intel platforms.
+* <b>Easy to deploy</b>. Deploy the GenAI examples with performance on Intel platforms
 
 ### ChatQnA
 [ChatQnA](./ChatQnA/README.md) is an example of chatbot for question and answering through retrieval argumented generation (RAG).
@@ -75,14 +75,14 @@ All the examples are well-validated on Intel platforms withe below features:
 			<td><a href="https://huggingface.co/deepseek-ai/deepseek-coder-33b-instruct">Deepseek-Coder-33B</a></td>
 			<td><a href="https://github.com/huggingface/tgi-gaudi">TGI-Habana</a></td>
 			<td>Gaudi2</td>
-			<td>Chatbot</td>
+			<td>Copilot</td>
 		</tr>
 	</tbody>
 </table>
 
 
 ### DocSum
-[DocSum](./DocSum/README.md) is an example of chatbot for summarizing the content of your documents or reports.
+[DocSum](./DocSum/README.md) is an example of chatbot for summarizing the content of documents or reports.
 
 <table>
 	<tbody>
@@ -111,7 +111,7 @@ All the examples are well-validated on Intel platforms withe below features:
 </table>
 
 ### VisualQnA
-[VisualQnA](./VisualQnA/README.md) is an example of chatbot for question and answering based on images.
+[VisualQnA](./VisualQnA/README.md) is an example of chatbot for question and answering based on the images.
 
 <table>
 	<tbody>
