Fix/discord link (#24)

* update discord link

* feat: add detail docs for local providers

* feat: add detail docs for local providers en

en/advanced/model-configuration/localai.md

@@ -6,6 +6,28 @@ Dify allows integration with LocalAI for local deployment of large language mode
 
 ## Deploying LocalAI
 
+### Before you start
+
+When using Docker to deploy a private model locally, you might need to access the service via the container's IP address instead of `127.0.0.1`. This is because `127.0.0.1` or `localhost` by default points to your host system and not the internal network of the Docker container. To retrieve the IP address of your Docker container, you can follow these steps:
+
+1. First, determine the name or ID of your Docker container. You can list all active containers using the following command:
+
+```bash
+docker ps
+```
+
+2. Then, use the command below to obtain detailed information about a specific container, including its IP address:
+
+```bash
+docker inspect -f '{{range .NetworkSettings.Networks}}{{.IPAddress}}{{end}}' container_name_or_ID
+```
+
+Please note that you usually do not need to manually find the IP address of the Docker container to access the service, because Docker offers a port mapping feature. This allows you to map the container ports to local machine ports, enabling access via your local address. For example, if you used the `-p 80:80` parameter when running the container, you can access the service inside the container by visiting `http://localhost:80` or `http://127.0.0.1:80`.
+
+If you do need to use the container's IP address directly, the steps above will assist you in obtaining this information.
+
+### Starting LocalAI
+
 You can refer to the official [Getting Started](https://localai.io/basics/getting_started/) guide for deployment, or quickly integrate following the steps below:
 
 (These steps are derived from [LocalAI Data query example](https://github.com/go-skynet/LocalAI/blob/master/examples/langchain-chroma/README.md))

en/advanced/model-configuration/openllm.md

@@ -5,6 +5,28 @@ And Dify supports connecting to OpenLLM deployed large language model's inferenc
 
 ## Deploy OpenLLM Model
 
+### Before you start
+
+When using Docker to deploy a private model locally, you might need to access the service via the container's IP address instead of `127.0.0.1`. This is because `127.0.0.1` or `localhost` by default points to your host system and not the internal network of the Docker container. To retrieve the IP address of your Docker container, you can follow these steps:
+
+1. First, determine the name or ID of your Docker container. You can list all active containers using the following command:
+
+```bash
+docker ps
+```
+
+2. Then, use the command below to obtain detailed information about a specific container, including its IP address:
+
+```bash
+docker inspect -f '{{range .NetworkSettings.Networks}}{{.IPAddress}}{{end}}' container_name_or_ID
+```
+
+Please note that you usually do not need to manually find the IP address of the Docker container to access the service, because Docker offers a port mapping feature. This allows you to map the container ports to local machine ports, enabling access via your local address. For example, if you used the `-p 80:80` parameter when running the container, you can access the service inside the container by visiting `http://localhost:80` or `http://127.0.0.1:80`.
+
+If you do need to use the container's IP address directly, the steps above will assist you in obtaining this information.
+
+### Starting OpenLLM
+
 Each OpenLLM Server can deploy one model, and you can deploy it in the following way:
 
 1. First, install OpenLLM through PyPI:

en/advanced/model-configuration/xinference.md

@@ -5,6 +5,28 @@ And Dify supports connecting to Xinference deployed large language model inferen
 
 ## Deploy Xinference
 
+### Before you start
+
+When using Docker to deploy a private model locally, you might need to access the service via the container's IP address instead of `127.0.0.1`. This is because `127.0.0.1` or `localhost` by default points to your host system and not the internal network of the Docker container. To retrieve the IP address of your Docker container, you can follow these steps:
+
+1. First, determine the name or ID of your Docker container. You can list all active containers using the following command:
+
+```bash
+docker ps
+```
+
+2. Then, use the command below to obtain detailed information about a specific container, including its IP address:
+
+```bash
+docker inspect -f '{{range .NetworkSettings.Networks}}{{.IPAddress}}{{end}}' container_name_or_ID
+```
+
+Please note that you usually do not need to manually find the IP address of the Docker container to access the service, because Docker offers a port mapping feature. This allows you to map the container ports to local machine ports, enabling access via your local address. For example, if you used the `-p 80:80` parameter when running the container, you can access the service inside the container by visiting `http://localhost:80` or `http://127.0.0.1:80`.
+
+If you do need to use the container's IP address directly, the steps above will assist you in obtaining this information.
+
+### Starting Xinference
+
 There are two ways to deploy Xinference, namely [local deployment](https://github.com/xorbitsai/inference/blob/main/README.md#local) and [distributed deployment](https://github.com/xorbitsai/inference/blob/main/README.md#distributed), here we take local deployment as an example.
 
 1. First, install Xinference via PyPI:

en/community/support.md

@@ -9,7 +9,7 @@ Please do not share your Dify account information or other sensitive information
 {% endhint %}
 
 * Submit an Issue on [GitHub](https://github.com/langgenius/dify)
-* Join the [Discord community](https://discord.gg/FngNHpbcY7)
+* Join the [Discord community](https://discord.gg/8Tpq4AcN9c)
 * Email [support@dify.ai](mailto:support@dify.ai)
 
 ### Contact Us

zh_CN/advanced/model-configuration/localai.md

@@ -5,6 +5,28 @@ Dify 支持以本地部署的方式接入 LocalAI 部署的大型语言模型推
 
 ## 部署 LocalAI
 
+### 使用前注意事项
+
+当您使用 Docker 在本地部署一个私有模型时，您可能需要通过容器的 IP 地址而不是 `127.0.0.1` 来访问该服务。这是因为 `127.0.0.1` 或 `localhost` 默认指向您的主机系统，而不是 Docker 容器的内部网络。为了获取 Docker 容器的 IP 地址，您可以按照以下步骤操作：
+
+1. 首先，确定您的 Docker 容器的名称或 ID。您可以使用以下命令列出所有运行中的容器：
+
+```bash
+docker ps
+```
+
+2. 然后，使用以下命令获取指定容器的详细信息，包括其 IP 地址：
+
+```bash
+docker inspect -f '{{range .NetworkSettings.Networks}}{{.IPAddress}}{{end}}' 容器名称或ID
+```
+
+请注意，您通常不需要手动寻找 Docker 容器的 IP 地址来访问服务，因为 Docker 提供了端口映射功能，允许您将容器端口映射到本机端口，从而通过本机地址进行访问。例如，如果您在运行容器时使用了 `-p 80:80` 参数，那么您可以通过访问 `http://localhost:80` 或 `http://127.0.0.1:80` 来访问容器中的服务。
+
+如果确实需要直接使用容器的 IP 地址，以上步骤将帮助您获取到这一信息。
+
+### 开始部署
+
 可参考官方 [Getting Started](https://localai.io/basics/getting_started/) 进行部署，也可参考下方步骤进行快速接入：
 
 （以下步骤来自 [LocalAI Data query example](https://github.com/go-skynet/LocalAI/blob/master/examples/langchain-chroma/README.md)）

zh_CN/advanced/model-configuration/openllm.md

@@ -5,6 +5,28 @@ Dify 支持以本地部署的方式接入 OpenLLM 部署的大型语言模型的
 
 ## 部署 OpenLLM 模型
 
+### 使用前注意事项
+
+当您使用 Docker 在本地部署一个私有模型时，您可能需要通过容器的 IP 地址而不是 `127.0.0.1` 来访问该服务。这是因为 `127.0.0.1` 或 `localhost` 默认指向您的主机系统，而不是 Docker 容器的内部网络。为了获取 Docker 容器的 IP 地址，您可以按照以下步骤操作：
+
+1. 首先，确定您的 Docker 容器的名称或 ID。您可以使用以下命令列出所有运行中的容器：
+
+```bash
+docker ps
+```
+
+2. 然后，使用以下命令获取指定容器的详细信息，包括其 IP 地址：
+
+```bash
+docker inspect -f '{{range .NetworkSettings.Networks}}{{.IPAddress}}{{end}}' 容器名称或ID
+```
+
+请注意，您通常不需要手动寻找 Docker 容器的 IP 地址来访问服务，因为 Docker 提供了端口映射功能，允许您将容器端口映射到本机端口，从而通过本机地址进行访问。例如，如果您在运行容器时使用了 `-p 80:80` 参数，那么您可以通过访问 `http://localhost:80` 或 `http://127.0.0.1:80` 来访问容器中的服务。
+
+如果确实需要直接使用容器的 IP 地址，以上步骤将帮助您获取到这一信息。
+
+### 开始部署
+
 每个 OpenLLM Server 可以部署一个模型，您可以通过以下方式部署：
 
 1. 首先通过 PyPI 安装 OpenLLM：

zh_CN/advanced/model-configuration/xinference.md

@@ -5,6 +5,28 @@ Dify 支持以本地部署的方式接入 Xinference 部署的大型语言模型
 
 ## 部署 Xinference
 
+### 使用前注意事项
+
+当您使用 Docker 在本地部署一个私有模型时，您可能需要通过容器的 IP 地址而不是 `127.0.0.1` 来访问该服务。这是因为 `127.0.0.1` 或 `localhost` 默认指向您的主机系统，而不是 Docker 容器的内部网络。为了获取 Docker 容器的 IP 地址，您可以按照以下步骤操作：
+
+1. 首先，确定您的 Docker 容器的名称或 ID。您可以使用以下命令列出所有运行中的容器：
+
+```bash
+docker ps
+```
+
+2. 然后，使用以下命令获取指定容器的详细信息，包括其 IP 地址：
+
+```bash
+docker inspect -f '{{range .NetworkSettings.Networks}}{{.IPAddress}}{{end}}' 容器名称或ID
+```
+
+请注意，您通常不需要手动寻找 Docker 容器的 IP 地址来访问服务，因为 Docker 提供了端口映射功能，允许您将容器端口映射到本机端口，从而通过本机地址进行访问。例如，如果您在运行容器时使用了 `-p 80:80` 参数，那么您可以通过访问 `http://localhost:80` 或 `http://127.0.0.1:80` 来访问容器中的服务。
+
+如果确实需要直接使用容器的 IP 地址，以上步骤将帮助您获取到这一信息。
+
+### 开始部署
+
 部署 Xinference 有两种方式，分别为[本地部署](https://github.com/xorbitsai/inference/blob/main/README_zh_CN.md#%E6%9C%AC%E5%9C%B0%E9%83%A8%E7%BD%B2)和[分布式部署](https://github.com/xorbitsai/inference/blob/main/README_zh_CN.md#%E5%88%86%E5%B8%83%E5%BC%8F%E9%83%A8%E7%BD%B2)，以下以本地部署为例。
 
 1. 首先通过 PyPI 安装 Xinference：

zh_CN/community/support.md

@@ -9,7 +9,7 @@
 {% endhint %}
 
 * 在 [Github](https://github.com/langgenius/dify) 上提交 Issue
-* 加入 [Discord ](https://discord.gg/FngNHpbcY7)社群
+* 加入 [Discord ](https://discord.gg/8Tpq4AcN9c)社群
 * 发邮件至 [support@dify.ai](mailto:support@dify.ai)
 
 ### 联系我们