diff --git a/README.md b/README.md
index b75593a9f..6a99d1b11 100644
--- a/README.md
+++ b/README.md
@@ -26,7 +26,7 @@
 
 ## 💡 What is RAGFlow?
 
-[RAGFlow](https://demo.ragflow.io) is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models) to provide truthful question-answering capabilities, backed by well-founded citations from various complex formatted data.
+[RAGFlow](https://ragflow.io/) is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models) to provide truthful question-answering capabilities, backed by well-founded citations from various complex formatted data.
 
 ## 📌 Latest Updates
 
@@ -274,6 +274,7 @@ $ systemctl start nginx
 
 ## 📚 Documentation
 
+- [Quickstart](./docs/quickstart.md)
 - [FAQ](./docs/faq.md)
 
 ## 📜 Roadmap
diff --git a/README_ja.md b/README_ja.md
index ef645f0e5..ddfc6ef44 100644
--- a/README_ja.md
+++ b/README_ja.md
@@ -26,7 +26,7 @@
 
 ## 💡 RAGFlow とは？
 
-[RAGFlow](https://demo.ragflow.io) は、深い文書理解に基づいたオープンソースの RAG (Retrieval-Augmented Generation) エンジンである。LLM（大規模言語モデル）を組み合わせることで、様々な複雑なフォーマットのデータから根拠のある引用に裏打ちされた、信頼できる質問応答機能を実現し、あらゆる規模のビジネスに適した RAG ワークフローを提供します。
+[RAGFlow](https://ragflow.io/) は、深い文書理解に基づいたオープンソースの RAG (Retrieval-Augmented Generation) エンジンである。LLM（大規模言語モデル）を組み合わせることで、様々な複雑なフォーマットのデータから根拠のある引用に裏打ちされた、信頼できる質問応答機能を実現し、あらゆる規模のビジネスに適した RAG ワークフローを提供します。
 
 ## 📌 最新情報
 
@@ -252,6 +252,7 @@ $ bash ./entrypoint.sh
 
 ## 📚 ドキュメンテーション
 
+- [Quickstart](./docs/quickstart.md)
 - [FAQ](./docs/faq.md)
 
 ## 📜 ロードマップ
diff --git a/README_zh.md b/README_zh.md
index 66ce13a39..8265c5950 100644
--- a/README_zh.md
+++ b/README_zh.md
@@ -26,7 +26,7 @@
 
 ## 💡 RAGFlow 是什么？
 
-[RAGFlow](https://demo.ragflow.io) 是一款基于深度文档理解构建的开源 RAG（Retrieval-Augmented Generation）引擎。RAGFlow 可以为各种规模的企业及个人提供一套精简的 RAG 工作流程，结合大语言模型（LLM）针对用户各类不同的复杂格式数据提供可靠的问答以及有理有据的引用。
+[RAGFlow](https://ragflow.io/) 是一款基于深度文档理解构建的开源 RAG（Retrieval-Augmented Generation）引擎。RAGFlow 可以为各种规模的企业及个人提供一套精简的 RAG 工作流程，结合大语言模型（LLM）针对用户各类不同的复杂格式数据提供可靠的问答以及有理有据的引用。
 
 ## 📌 近期更新
 
@@ -271,6 +271,7 @@ $ systemctl start nginx
 ```
 ## 📚 技术文档
 
+- [Quickstart](./docs/quickstart.md)
 - [FAQ](./docs/faq.md)
 
 ## 📜 路线图
diff --git a/docs/quickstart.md b/docs/quickstart.md
index 77d56b207..283cc7864 100644
--- a/docs/quickstart.md
+++ b/docs/quickstart.md
@@ -114,7 +114,7 @@ To add and configure an LLM:
 
    ![added available models](https://github.com/infiniflow/ragflow/assets/93570324/d08b80e4-f921-480a-b41d-11832489c916)
 
-3. Click **System Mode Settings** to globally set the following models: 
+3. Click **System Model Settings** to select the default models: 
 
    - Chat model, 
    - Embedding model, 
@@ -140,7 +140,7 @@ To create your first knowledge base:
 
 3. RAGFlow offers multiple chunk templates that cater to different document layouts and file formats. Select the embedding model and chunk method (template) for your knowledge base. 
 
-   > IMPORTANT: Once you have selected an embedding model and used it to parse a file, you are no longer allowed to change it. The obvious reason is that we must ensure that all files in a specific knowledge base are parsed using the *same* embedding model. 
+   > IMPORTANT: Once you have selected an embedding model and used it to parse a file, you are no longer allowed to change it. The obvious reason is that we must ensure that all files in a specific knowledge base are parsed using the *same* embedding model (ensure that they are being compared in the same embedding space). 
 
    _You are taken to the **Dataset** page of your knowledge base._
 
@@ -180,14 +180,15 @@ RAGFlow features visibility and explainability, allowing you to view the chunkin
 
 Conversations in RAGFlow are based on a particular knowledge base or multiple knowledge bases. Once you have created your knowledge base and finished file parsing, you can go ahead and start an AI conversation. 
 
-1. Click the **Chat** tab in the middle top of the mage **>** **Create an assistant** to show the **Chat Configuration** dialogue of your next dialogue.
+1. Click the **Chat** tab in the middle top of the mage **>** **Create an assistant** to show the **Chat Configuration** dialogue *of your next dialogue*.
+   > RAGFlow offer the flexibility of choosing a different chat model for each dialogue, while allowing you to set the default models in **System Model Settings**.
 
 2. Update **Assistant Setting**: 
 
    - Name your assistant and specify your knowledge bases.
    - **Empty response**:
      - If you wish to *confine* RAGFlow's answers to your knowledge bases, leave a response here. Then when it doesn't retrieve an answer, it *uniformly* responds with what you set here. 
-     - If you wish RAGFlow to *improvise* when it doesn't retrieve an answer from your knowledge bases, leave it blank, while may give rise to hallucinations. 
+     - If you wish RAGFlow to *improvise* when it doesn't retrieve an answer from your knowledge bases, leave it blank, which may give rise to hallucinations. 
 
 3. Update **Prompt Engine** or leave it as is for the beginning.