Editorial updates (#168)

README.md

@@ -20,16 +20,17 @@
     <img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?style=flat-square&labelColor=d4eaf7&color=7d09f1" alt="license">
   </a>
 </p>
-[RagFlow](https://demo.ragflow.io) is a knowledge management platform built on custom-build document understanding engine and LLM, with reasoned and well-founded answers to your question. Clone this repository, you can deploy your own knowledge management platform to empower your business with AI.
-    
+## 💡 What is RagFlow?
+
+[RagFlow](http://demo.ragflow.io) is a knowledge management platform built on custom-build document understanding engine and LLM, with reasoned and well-founded answers to your question. Clone this repository, you can deploy your own knowledge management platform to empower your business with AI.
 
 <div align="center" style="margin-top:20px;margin-bottom:20px;">
 <img src="https://github.com/infiniflow/ragflow/assets/12318111/b24a7a5f-4d1d-4a30-90b1-7b0ec558b79d" width="1000"/>
 </div>
 
-## 🌟Key Features
+## 🌟 Key Features
 - 🍭**Custom-build document understanding engine.** Our deep learning engine is made according to the needs of analyzing and searching various type of documents in different domain.
-  - For documents from different domain for different purpose, the engine applys different analyzing and search strategy.
+  - For documents from different domain for different purpose, the engine applies different analyzing and search strategy.
   - Easily intervene and manipulate the data proccessing procedure when things goes beyond expectation.
   - Multi-media document understanding is supported using OCR and multi-modal LLM. 
 - 🍭**State-of-the-art table structure and layout recognition.** Precisely extract and understand the document including table content. See [README.](./deepdoc/README.md)
@@ -46,34 +47,52 @@
 
 ## 🤺RagFlow vs. other RAG applications
 
+## 🔎 System Architecture
 
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/infiniflow/ragflow/assets/12318111/d6ac5664-c237-4200-a7c2-a4a00691b485" width="1000"/>
+</div>
 
 ## 🎬 Get Started
 
-### 📝Prerequisites
+### 📝 Prerequisites
+
 - CPU >= 2 cores
 - RAM >= 8 GB
+- Docker
+- `vm.max_map_count` > 65535
 
-Then, you need to check the following command:
-```bash
-$ sysctl vm.max_map_count
-vm.max_map_count = 262144
-```
-If **vm.max_map_count** is not greater  than 65535:
-```bash
-$ sudo sysctl -w vm.max_map_count=262144
-```
-Note that this change is reset after a system reboot. To render your change permanent, add or update the following line in **/etc/sysctl.conf**:
+> To check the value of `vm.max_map_count`:
+>
+> ```bash 
+> $ sysctl vm.max_map_count
+> ```
+>
+> Reset `vm.max_map_count` to a value greater than 65535 if it is not. In this case, we set it to 262144:
+>
+> ```bash
+> $ sudo sysctl -w vm.max_map_count=262144
+> ```
+>
+> This change will be reset after a system reboot. To ensure your change remains permanent, add or update the following line in **/etc/sysctl.conf** accordingly:
+>
+> ```bash
+> vm.max_map_count=262144
+> ```
 
-```bash
-vm.max_map_count=262144
-```
 
-### Install docker
 
-If you have not installed *Docker* on your local machine, see [Install Docker Engine](https://docs.docker.com/engine/install/)
+### Start up the RagFlow server
 
-### Quick Start
+1. Clone the repo
+
+   ```bash
+   $ git clone https://github.com/infiniflow/ragflow.git
+   ```
+
+   
+
+2. 
 
 > - In [service_conf.yaml](./docker/service_conf.yaml), configuration of *LLM* in **user_default_llm** is strongly recommended. 
 > In **user_default_llm** of [service_conf.yaml](./docker/service_conf.yaml), you need to specify LLM factory and your own _API_KEY_.
@@ -83,7 +102,7 @@ Settings the next time you log in to the system.
 > [OpenAI](https://platform.openai.com/login?launch), [Tongyi-Qianwen](https://dashscope.console.aliyun.com/model), 
 > [ZHIPU-AI](https://open.bigmodel.cn/), [Moonshot](https://platform.moonshot.cn/docs/docs)
 ```bash
-$ git clone https://github.com/infiniflow/ragflow.git
+
 $ cd ragflow/docker
 $ docker compose up -d
 ```
@@ -98,11 +117,11 @@ $ docker compose up -d
 ```
 > The core image is about 15 GB in size and may take a while to load.
 
-Check the server status after pulling all images and running up:
+Check the server status after pulling all images and having Docker up and running:
 ```bash
 $ docker logs -f  ragflow-server
 ```
-*Hallelujah! The following outputs indicates that you have successfully launched the system:*
+*The following output confirms the successful launch of the system:*
 
 ```bash
     ____                 ______ __               
@@ -118,20 +137,17 @@ $ docker logs -f  ragflow-server
 INFO:werkzeug:Press CTRL+C to quit
 
 ```
-Open your browser, enter the IP address of your server, _**Hallelujah**_ again!
-> The default serving port is 80, if you want to change that, refer to the [docker-compose.yml](./docker-compose.yaml) and change the left part of *'80:80'*'.
+In your browser, enter the IP address of your server.
 
-## 🔎System Architecture
 
-<div align="center" style="margin-top:20px;margin-bottom:20px;">
-<img src="https://github.com/infiniflow/ragflow/assets/12318111/d6ac5664-c237-4200-a7c2-a4a00691b485" width="1000"/>
-</div>
 
 ## 🔧 Configurations
 
+> The default serving port is 80, if you want to change that, refer to the [docker-compose.yml](./docker-compose.yaml) and change the left part of `80:80`, say `66:80`.
+
 If you need to change the default setting of the system when you deploy it. There several ways to configure it. 
 Please refer to this [README](./docker/README.md) to manually update the configuration. 
-After changing something, please run *docker-compose up -d* again. 
+Updates to system configurations require a system reboot to take effect *docker-compose up -d* again. 
 
 > If you want to change the basic setups, like port, password .etc., please refer to [.env](./docker/.env) before starting up the system.
 
@@ -141,15 +157,12 @@ After changing something, please run *docker-compose up -d* again.
 
 See the [RagFlow Roadmap 2024](https://github.com/infiniflow/ragflow/issues/162)
 
-## 🏄Community
+## 🏄 Community
 
 - [Discord](https://discord.gg/uqQ4YMDf)
-- X
-- [GitHub Discussions]()
-- YouTube
-- WeChat
-
+- [Twitter](https://twitter.com/infiniflowai)
+- GitHub Discussions
 
 ## 🙌 Contributing
 
-For those who'd like to contribute code, see our [Contribution Guide](https://github.com/infiniflow/ragflow/blob/main/CONTRIBUTING.md). 
+RagFlow flourishes via open-source collaboration. In this spirit, we embrace diverse contributions from the community. If you would like to be a part, review our [Contribution Guidelines](https://github.com/infiniflow/ragflow/blob/main/CONTRIBUTING.md) first.