feat: add logo-with-text.png (#184)

* feat: alter "RagFlow" to "RAGFlow"

* feat: move logo style to style tag

* feat: add logo-with-text.png

* feat: hide TranslationIcon

README.md

@@ -1,10 +1,9 @@
 <div align="center">
 <a href="https://demo.ragflow.io/">
-<img src="https://github.com/infiniflow/ragflow/assets/12318111/f034fb27-b3bf-401b-b213-e1dfa7448d2a" width="320" alt="ragflow logo">
+<img src="web/src/assets/logo-with-text.png" width="350" alt="ragflow logo">
 </a>
 </div>
 
-
 <p align="center">
   <a href="./README.md">English</a> |
   <a href="./README_zh.md">简体中文</a> 
@@ -28,21 +27,26 @@
 ## 🌟 Key Features
 
 ### 🍭 **"Quality in, quality out"**
+
 - Deep document understanding-based knowledge extraction from unstructured data with complicated formats.
 - Finds "needle in a data haystack" of literally unlimited tokens.
 
 ### 🍱 **Template-based chunking**
+
 - Intelligent and explainable.
 - Plenty of template options to choose from.
 
 ### 🌱 **Grounded citations with reduced hallucinations**
+
 - Visualization of text chunking to allow human intervention.
 - Quick view of the key references and traceable citations to support grounded answers.
 
 ### 🍔 **Compatibility with heterogeneous data sources**
+
 - Supports Word, slides, excel, txt, images, scanned copies, structured data, web pages, and more.
 
 ### 🛀 **Automated and effortless RAG workflow**
+
 - Streamlined RAG orchestration catered to both personal and large businesses.
 - Configurable LLMs as well as embedding models.
 - Multiple recall paired with fused re-ranking.
@@ -102,10 +106,12 @@
    > The core image is about 15 GB in size and may take a while to load.
 
 4. Check the server status after having the server up and running:
+
    ```bash
    $ docker logs -f ragflow-server
    ```
-   *The following output confirms a successful launch of the system:*
+
+   _The following output confirms a successful launch of the system:_
 
    ```bash
        ____                 ______ __
@@ -123,10 +129,10 @@
 
 5. In your web browser, enter the IP address of your server as prompted and log in to RAGFlow.
 6. In [service_conf.yaml](./docker/service_conf.yaml), select the desired LLM factory in `user_default_llm` and update the `API_KEY` field with the corresponding API key.
+
    > See [./docs/llm_api_key_setup.md](./docs/llm_api_key_setup.md) for more information.
 
-   *The show is now on!*
+   _The show is now on!_
-
 
 ## 🔧 Configurations
 

README_zh.md

@@ -1,10 +1,9 @@
 <div align="center">
 <a href="https://demo.ragflow.io/">
-<img src="https://github.com/infiniflow/ragflow/assets/12318111/f034fb27-b3bf-401b-b213-e1dfa7448d2a" width="320" alt="ragflow logo">
+<img src="web/src/assets/logo-with-text.png" width="350" alt="ragflow logo">
 </a>
 </div>
 
-
 <p align="center">
   <a href="./README.md">English</a> |
   <a href="./README_zh.md">简体中文</a> 
@@ -28,21 +27,26 @@
 ## 🌟 主要功能
 
 ### 🍭 **"Quality in, quality out"**
+
 - 基于深度文档理解，能够从各类复杂格式的非结构化数据中提取真知灼见。
 - 真正在无限上下文（token）的场景下快速完成大海捞针测试。
 
 ### 🍱 **基于模板的文本切片**
+
 - 不仅仅是智能，更重要的是可控可解释。
 - 多种文本模板可供选择
 
 ### 🌱 **有理有据、最大程度降低幻觉（hallucination）**
+
 - 文本切片过程可视化，支持手动调整。
 - 有理有据：答案提供关键引用的快照并支持追根溯源。
 
 ### 🍔 **兼容各类异构数据源**
+
 - 支持丰富的文件类型，包括 Word 文档、PPT、excel 表格、txt 文件、图片、PDF、影印件、复印件、结构化数据, 网页等。
 
 ### 🛀 **全程无忧、自动化的 RAG 工作流**
+
 - 全面优化的 RAG 工作流可以支持从个人应用乃至超大型企业的各类生态系统。
 - 大语言模型 LLM 以及向量模型均支持配置。
 - 基于多路召回、融合重排序。
@@ -102,10 +106,12 @@
    > 核心镜像文件大约 15 GB，可能需要一定时间拉取。请耐心等待。
 
 4. 服务器启动成功后再次确认服务器状态：
+
    ```bash
    $ docker logs -f ragflow-server
    ```
-   *出现以下界面提示说明服务器启动成功：*
+
+   _出现以下界面提示说明服务器启动成功：_
 
    ```bash
        ____                 ______ __
@@ -123,11 +129,15 @@
 
 5. 根据刚才的界面提示在你的浏览器中输入你的服务器对应的 IP 地址并登录 RAGFlow。
    > 上面这个例子中，您只需输入 http://172.22.0.5 即可：端口 9380 已通过 Docker 端口映射被设置成 80（默认的 HTTP 服务端口）。
-7. 在 [service_conf.yaml](./docker/service_conf.yaml) 文件的 `user_default_llm` 栏配置 LLM factory，并在 `API_KEY` 栏填写和你选择的大模型相对应的 API key。
+6. 在 [service_conf.yaml](./docker/service_conf.yaml) 文件的 `user_default_llm` 栏配置 LLM factory，并在 `API_KEY` 栏填写和你选择的大模型相对应的 API key。
+
    > 详见 [./docs/llm_api_key_setup.md](./docs/llm_api_key_setup.md)。
 
-   *好戏开始，接着奏乐接着舞！*
+   _好戏开始，接着奏乐接着舞！_
 
+   > 详见 [./docs/llm_api_key_setup.md](./docs/llm_api_key_setup.md)。
+
+   _好戏开始，接着奏乐接着舞！_
 
 ## 🔧 系统配置
 

web/src/layouts/components/header/index.tsx

@@ -55,7 +55,7 @@ const RagHeader = () => {
     >
       <Space size={12} onClick={handleLogoClick} className={styles.logoWrapper}>
         <Logo className={styles.appIcon}></Logo>
-        <span className={styles.appName}>RagFlow</span>
+        <span className={styles.appName}>RAGFlow</span>
       </Space>
       <Space size={[0, 8]} wrap>
         <Radio.Group

web/src/layouts/components/right-toolbar/index.tsx

@@ -1,6 +1,4 @@
-import { ReactComponent as MoonIcon } from '@/assets/svg/moon.svg';
+import { GithubOutlined } from '@ant-design/icons';
-import { ReactComponent as TranslationIcon } from '@/assets/svg/translation.svg';
-import { BellOutlined, GithubOutlined } from '@ant-design/icons';
 import { Space } from 'antd';
 import React from 'react';
 import User from '../user';
@@ -21,15 +19,12 @@ const RightToolBar = () => {
         <Circle>
           <GithubOutlined onClick={handleGithubCLick} />
         </Circle>
-        <Circle>
+        {/* <Circle>
           <TranslationIcon />
         </Circle>
-        <Circle>
-          <BellOutlined />
-        </Circle>
         <Circle>
           <MoonIcon />
-        </Circle>
+        </Circle> */}
         <User></User>
       </Space>
     </div>

web/src/pages/add-knowledge/components/knowledge-setting/configuration.tsx

@@ -62,7 +62,7 @@ const ConfigurationForm = ({ form }: { form: FormInstance }) => {
       <Form.Item
         label="Language"
         name="language"
-        initialValue={'Chinese'}
+        initialValue={'English'}
         rules={[{ required: true, message: 'Please input your language!' }]}
       >
         <Select placeholder="select your language">

web/src/pages/add-knowledge/components/knowledge-setting/utils.ts

@@ -81,7 +81,7 @@ export const TextMap = {
     The résumé comes in a variety of formats, just like a person’s personality, but we often have to organize them into structured data that makes it easy to search.
     </p><p>
     Instead of chunking the résumé, we parse the résumé into structured data. As a HR, you can dump all the résumé you have, 
-    the you can list all the candidates that match the qualifications just by talk with <i>'RagFlow'</i>.
+    the you can list all the candidates that match the qualifications just by talk with <i>'RAGFlow'</i>.
     </p>
     `,
   },

web/src/pages/user-setting/setting-profile/index.tsx

@@ -8,7 +8,7 @@ import {
   getUploadFileListFromBase64,
   normFile,
 } from '@/utils/fileUtil';
-import { PlusOutlined, QuestionCircleOutlined } from '@ant-design/icons';
+import { PlusOutlined } from '@ant-design/icons';
 import {
   Button,
   Divider,
@@ -17,7 +17,6 @@ import {
   Select,
   Space,
   Spin,
-  Tooltip,
   Upload,
   UploadFile,
 } from 'antd';
@@ -108,9 +107,7 @@ const UserSettingProfile = () => {
           <Form.Item<FieldType>
             label={
               <div>
-                <Space>
+                <Space>Your photo</Space>
-                  Your photo
-                </Space>
                 <div>This will be displayed on your profile.</div>
               </div>
             }
@@ -177,8 +174,7 @@ const UserSettingProfile = () => {
               <Input disabled />
             </Form.Item>
             <p className={parentStyles.itemDescription}>
-              Once registered, an account cannot be changed and can only be
+              Once registered, E-mail cannot be changed.
-              cancelled.
             </p>
           </Form.Item>
           <Form.Item