[doc] Updated document on max map count

README.md

@@ -113,7 +113,7 @@ Try our demo at [https://demo.ragflow.io](https://demo.ragflow.io).
 
 ### 🚀 Start up the server
 
-1. Ensure `vm.max_map_count` >= 262144 ([more](./docs/guides/max_map_count.md)):
+1. Ensure `vm.max_map_count` >= 262144:
 
    > To check the value of `vm.max_map_count`:
    >

README_ja.md

@@ -95,7 +95,7 @@
 
 ### 🚀 サーバーを起動
 
-1. `vm.max_map_count` >= 262144 であることを確認する【[もっと](./docs/guides/max_map_count.md)】:
+1. `vm.max_map_count` >= 262144 であることを確認する:
 
    > `vm.max_map_count` の値をチェックするには:
    >

README_zh.md

@@ -94,7 +94,7 @@
 
 ### 🚀 启动服务器
 
-1. 确保 `vm.max_map_count` 不小于 262144 【[更多](./docs/guides/max_map_count.md)】：
+1. 确保 `vm.max_map_count` 不小于 262144：
 
    > 如需确认 `vm.max_map_count` 的大小：
    >

docs/quickstart.md → docs/quickstart.mdx

@@ -4,6 +4,8 @@ slug: /
 ---
 
 # Quick start
+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
 
 RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. When integrated with LLMs, it is capable of providing truthful question-answering capabilities, backed by well-founded citations from various complex formatted data.
 
@@ -25,29 +27,102 @@ This quick start guide describes a general process from:
 
 ## Start up the server
 
-This section provides instructions on setting up the RAGFlow server on Linux. If you are on a different operating system, no worries. Most steps are alike. 
-
-1. Ensure `vm.max_map_count` >= 262144:
-
-   > To check the value of `vm.max_map_count`:
-   >
-   > ```bash
-   > $ sysctl vm.max_map_count
-   > ```
-   >
-   > Reset `vm.max_map_count` to a value at least 262144 if it is not.
-   >
-   > ```bash
-   > # In this case, we set it to 262144:
-   > $ 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 `vm.max_map_count` value in **/etc/sysctl.conf** accordingly:
-   >
-   > ```bash
-   > vm.max_map_count=262144
-   > ```
-   > See [this guide](./guides/max_map_count.md) for instructions on permanently setting `vm.max_map_count` on an operating system other than Linux. 
+This section provides instructions on setting up the RAGFlow server on Linux. If you are on a different operating system, no worries. Most steps are alike.
+
+<details>
+  <summary>1. Ensure <code>vm.max_map_count</code> >= 262144:</summary>
+
+   `vm.max_map_count`. This value sets the the maximum number of memory map areas a process may have. Its default value is 65530. While most applications require fewer than a thousand maps, reducing this value can result in abmornal behaviors, and the system will throw out-of-memory errors when a process reaches the limitation. 
+
+   RAGFlow v0.7.0 uses Elasticsearch for multiple recall. Setting the value of `vm.max_map_count` correctly is crucial to the proper functioning the Elasticsearch component.
+
+<Tabs
+  defaultValue="linux"
+  values={[
+    {label: 'Linux', value: 'linux'},
+    {label: 'macOS', value: 'macos'},
+    {label: 'Windows', value: 'windows'},
+  ]}>
+  <TabItem value="linux">
+   1.1. Check the value of `vm.max_map_count`:
+
+   ```bash
+   $ sysctl vm.max_map_count
+   ```
+
+   1.2. Reset `vm.max_map_count` to a value at least 262144 if it is not.
+
+   ```bash
+   $ sudo sysctl -w vm.max_map_count=262144
+   ```
+
+   :::caution WARNING
+   This change will be reset after a system reboot. If you forget to update the value the next time you start up the server, you may get a `Can't connect to ES cluster` exception.
+   :::
+
+   1.3. To ensure your change remains permanent, add or update the `vm.max_map_count` value in **/etc/sysctl.conf** accordingly:
+
+   ```bash
+   vm.max_map_count=262144
+   ```
+  </TabItem>
+  <TabItem value="macos">
+   If you are on macOS with Docker Desktop, then you *must* use docker-machine to update `vm.max_map_count`:
+
+   ```bash
+   $ docker-machine ssh
+   $ sudo sysctl -w vm.max_map_count=262144
+   ```
+
+   :::caution WARNING
+   This change will be reset after a system reboot. If you forget to update the value the next time you start up the server, you may get a `Can't connect to ES cluster` exception.
+   :::
+  </TabItem>
+  <TabItem value="windows">
+
+   #### If you are on Windows with Docker Desktop, then you *must* use docker-machine to set `vm.max_map_count`:
+
+   ```bash
+   $ docker-machine ssh
+   $ sudo sysctl -w vm.max_map_count=262144
+   ```
+   #### If you are on Windows with Docker Desktop WSL 2 backend, then use docker-desktop to set `vm.max_map_count`:
+
+   1.1. Run the following in WSL: 
+   ```bash
+   $ wsl -d docker-desktop -u root
+   $ sysctl -w vm.max_map_count=262144
+   ```
+
+   :::caution WARNING
+   This change will be reset after you restart Docker. If you forget to update the value the next time you start up the server, you may get a `Can't connect to ES cluster` exception.
+   :::
+
+   1.2. If you do not wish to have to run those commands each time you restart Docker, you can update your `%USERPROFILE%.wslconfig` as follows to keep your change permanent and globally for all WSL distributions:
+
+   ```bash
+   [wsl2]
+   kernelCommandLine = "sysctl.vm.max_map_count=262144"
+   ```
+   *This causes all WSL2 virtual machines to have that setting assigned when they start.*
+
+   :::note
+   If you are on Windows 11 or Windows 10 version 22H2, and have installed the Microsoft Store version of WSL, you can also update the **/etc/sysctl.conf** within the docker-desktop WSL distribution to keep your change permanent:
+
+   ```bash
+   $ wsl -d docker-desktop -u root
+   $ vi /etc/sysctl.conf
+   ```
+
+   ```bash
+   # Append a line, which reads: 
+   vm.max_map_count = 262144
+   ```
+   :::
+  </TabItem>
+</Tabs>
+
+</details>
 
 2. Clone the repo:
 

docs/references/faq.md

@@ -194,11 +194,7 @@ Ignore this warning and continue. All system warnings can be ignored.
 
 ![](https://github.com/infiniflow/ragflow/assets/93570324/ef5a6194-084a-4fe3-bdd5-1c025b40865c)
 
-#### 4.3 Why does it take so long to parse a 2MB document?
-
-Parsing requests have to wait in queue due to limited server resources. We are currently enhancing our algorithms and increasing computing power.
-
-#### 4.4 Why does my document parsing stall at under one percent?
+#### 4.3 Why does my document parsing stall at under one percent?
 
 ![stall](https://github.com/infiniflow/ragflow/assets/93570324/3589cc25-c733-47d5-bbfc-fedb74a3da50)
 
@@ -211,7 +207,7 @@ docker logs -f ragflow-server
 2. Check if the **task_executor.py** process exists.
 3. Check if your RAGFlow server can access hf-mirror.com or huggingface.com.
 
-#### 4.5 Why does my pdf parsing stall near completion, while the log does not show any error?
+#### 4.4 Why does my pdf parsing stall near completion, while the log does not show any error?
 
 If your RAGFlow is deployed *locally*, the parsing process is likely killed due to insufficient RAM. Try increasing your memory allocation by increasing the `MEM_LIMIT` value in **docker/.env**.
 
@@ -225,17 +221,17 @@ If your RAGFlow is deployed *locally*, the parsing process is likely killed due
 
 ![nearcompletion](https://github.com/infiniflow/ragflow/assets/93570324/563974c3-f8bb-4ec8-b241-adcda8929cbb)
 
-#### 4.6 `Index failure`
+#### 4.5 `Index failure`
 
 An index failure usually indicates an unavailable Elasticsearch service.
 
-#### 4.7 How to check the log of RAGFlow?
+#### 4.6 How to check the log of RAGFlow?
 
 ```bash
 tail -f path_to_ragflow/docker/ragflow-logs/rag/*.log
 ```
 
-#### 4.8 How to check the status of each component in RAGFlow?
+#### 4.7 How to check the status of each component in RAGFlow?
 
 ```bash
 $ docker ps
@@ -249,7 +245,7 @@ d8c86f06c56b   mysql:5.7.18        "docker-entrypoint.s…"   7 days ago     Up
 cd29bcb254bc   quay.io/minio/minio:RELEASE.2023-12-20T01-00-02Z       "/usr/bin/docker-ent…"   2 weeks ago    Up 11 hours      0.0.0.0:9001->9001/tcp, :::9001->9001/tcp, 0.0.0.0:9000->9000/tcp, :::9000->9000/tcp     ragflow-minio
 ```
 
-#### 4.9 `Exception: Can't connect to ES cluster`
+#### 4.8 `Exception: Can't connect to ES cluster`
 
 1. Check the status of your Elasticsearch component:
 
@@ -276,26 +272,26 @@ $ docker ps
     curl http://<IP_OF_ES>:<PORT_OF_ES>
     ```
 
-#### 4.10 Can't start ES container and get `Elasticsearch did not exit normally`
+#### 4.9 Can't start ES container and get `Elasticsearch did not exit normally`
 
 This is because you forgot to update the `vm.max_map_count` value in **/etc/sysctl.conf** and your change to this value was reset after a system reboot. 
 
-#### 4.11 `{"data":null,"retcode":100,"retmsg":"<NotFound '404: Not Found'>"}`
+#### 4.10 `{"data":null,"retcode":100,"retmsg":"<NotFound '404: Not Found'>"}`
 
 Your IP address or port number may be incorrect. If you are using the default configurations, enter `http://<IP_OF_YOUR_MACHINE>` (**NOT 9380, AND NO PORT NUMBER REQUIRED!**) in your browser. This should work.
 
-#### 4.12 `Ollama - Mistral instance running at 127.0.0.1:11434 but cannot add Ollama as model in RagFlow`
+#### 4.11 `Ollama - Mistral instance running at 127.0.0.1:11434 but cannot add Ollama as model in RagFlow`
 
 A correct Ollama IP address and port is crucial to adding models to Ollama:
 
 - If you are on demo.ragflow.io, ensure that the server hosting Ollama has a publicly accessible IP address.Note that 127.0.0.1 is not a publicly accessible IP address.
 - If you deploy RAGFlow locally, ensure that Ollama and RAGFlow are in the same LAN and can comunicate with each other.
 
-#### 4.13 Do you offer examples of using deepdoc to parse PDF or other files?
+#### 4.12 Do you offer examples of using deepdoc to parse PDF or other files?
 
 Yes, we do. See the Python files under the **rag/app** folder. 
 
-#### 4.14 Why did I fail to upload a 10MB+ file to my locally deployed RAGFlow?
+#### 4.13 Why did I fail to upload a 10MB+ file to my locally deployed RAGFlow?
 
 You probably forgot to update the **MAX_CONTENT_LENGTH** environment variable:
 
@@ -314,7 +310,7 @@ docker compose up ragflow -d
 ```
    *Now you should be able to upload files of sizes less than 100MB.*
 
-#### 4.15 `Table 'rag_flow.document' doesn't exist`
+#### 4.14 `Table 'rag_flow.document' doesn't exist`
 
 This exception occurs when starting up the RAGFlow server. Try the following: 
 
@@ -337,15 +333,15 @@ This exception occurs when starting up the RAGFlow server. Try the following:
   docker compose up
   ```
 
-#### 4.16 `hint : 102  Fail to access model  Connection error`
+#### 4.15 `hint : 102  Fail to access model  Connection error`
 
 ![hint102](https://github.com/infiniflow/ragflow/assets/93570324/6633d892-b4f8-49b5-9a0a-37a0a8fba3d2)
 
 1. Ensure that the RAGFlow server can access the base URL.
 2. Do not forget to append **/v1/** to **http://IP:port**: 
    **http://IP:port/v1/**
 
-#### 4.17 `FileNotFoundError: [Errno 2] No such file or directory`
+#### 4.16 `FileNotFoundError: [Errno 2] No such file or directory`
 
 1. Check if the status of your minio container is healthy:
    ```bash