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docs: fix part of the link failure (#3271)

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Nowinkey
2023-06-04 21:23:18 +08:00
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docs/4.0/docs/examples/ai-applications/athenaserving.md
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@@ -96,7 +96,7 @@ $ sealos run registry.cn-qingdao.aliyuncs.com/labring/athenaserving:v2.0.0rc1
3. HTTP call AI demo capability MMOCR capability
MMOCR is an open source toolbox based on PyTorch and mmdetection, focusing on text detection, text recognition and
corresponding downstream tasks such as key information extraction. It is part of the OpenMMLab project. [Project address](https://github.com/open-mmlab/mmocr/blob/main/README_zh-CN.md) In [wrapper.py](https://github.com/iflytek/aiges/blob/master/demo/mmocr/wrapper/wrapper_v2.py), we use python to easily convert [text + detection and recognition ability](https://mmocr.readthedocs.io/zh_CN/latest/demo.html#id4) encapsulates the ability to deploy into `ASF` as an HTTP API. After deploying `ASF` using Sealos, you can use the following script to modify the `url` value to complete the call to
corresponding downstream tasks such as key information extraction. It is part of the OpenMMLab project. [Project address](https://github.com/open-mmlab/mmocr/blob/main/README_zh-CN.md) In [wrapper.py](https://github.com/iflytek/aiges_demo/blob/f5061b3b9a4d05f491cfdc21c525e22f8239b760/mmocr/wrapper/wrapper_v2.py), we use python to easily convert [text + detection and recognition ability](https://mmocr.readthedocs.io/zh_CN/latest/demo.html#id4) encapsulates the ability to deploy into `ASF` as an HTTP API. After deploying `ASF` using Sealos, you can use the following script to modify the `url` value to complete the call to
the `MMOCR (text + detection)` AI capability.
```python
@@ -211,7 +211,7 @@ MMocr Result: box located at [223, 214, 240, 214, 240, 226, 223, 226], box score
To implement new AI capabilities, you should develop and build your AI Capability image according to the loader Spec Sheet. And then deploy it to the cluster.
How to build your custom AI capability image, please refer
to:[Fastly create wrapper.py](https://iflytek.github.io/athena_website/docs/%E5%8A%A0%E8%BD%BD%E5%99%A8/Python%E6%8F%92%E4%BB%B6)
to:[Fastly create wrapper.py](https://iflytek.github.io/athena_website/docs/current/%E5%8A%A0%E8%BD%BD%E5%99%A8/Python%E6%8F%92%E4%BB%B6)
## More
docs/4.0/docs/lifecycle-management/operations/build-image/build-image-with-kubeadm-run-cluster.md
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@@ -94,4 +94,4 @@ spec:
**⚠️ 注意：**
+ 您可以参考[官方文档](https://kubernetes.io/docs/reference/config-api/kubeadm-config.v1beta2/)或使用`kubeadm config print init-defaults`命令打印kubeadm配置。
+ 您可以参考[官方文档](https://kubernetes.io/docs/reference/setup-tools/kubeadm/kubeadm-config/)或使用`kubeadm config print init-defaults`命令打印kubeadm配置。
docs/4.0/docs/lifecycle-management/operations/run-cluster/gen-apply-cluster.md
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@@ -123,4 +123,4 @@ spec:
**注意：**
- 可以参考[官方文档](https://kubernetes.io/docs/reference/config-api/kubeadm-config.v1beta2/)或运行 `kubeadm config print init-defaults` 命令来打印 kubeadm 配置。
- 可以参考[官方文档](https://kubernetes.io/docs/reference/setup-tools/kubeadm/kubeadm-config/)或运行 `kubeadm config print init-defaults` 命令来打印 kubeadm 配置。
docs/4.0/i18n/zh-Hans/examples/ai-applications/athenaserving.md
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@@ -94,7 +94,7 @@ $ sealos run registry.cn-qingdao.aliyuncs.com/labring/athenaserving:v2.0.0rc1
3. HTTP 调用 AI 演示 MMOCR 功能
MMOCR 是基于 PyTorch 和 mmdetection 的开源工具箱，专注于文本检测，文本识别以及相应的关键信息提取等下游任务。 它是 OpenMMLab 项目的一部分。[项目地址](https://github.com/open-mmlab/mmocr/blob/main/README_zh-CN.md) 在 [wrapper.py](https://github.com/iflytek/aiges/blob/master/demo/mmocr/wrapper/wrapper_v2.py) 中，我们使用 python 轻而易举的将 [文本+检测识别 ](https://mmocr.readthedocs.io/zh_CN/latest/demo.html#id4)功能封装部署到 `ASF ` 作为 HTTP API。使用 sealos 部署完 `ASF` 后，可以使用如下脚本修改 `url` 的值，即可完成调用 `MMOCR(文本+检测)` AI 功能调用。
MMOCR 是基于 PyTorch 和 mmdetection 的开源工具箱，专注于文本检测，文本识别以及相应的关键信息提取等下游任务。 它是 OpenMMLab 项目的一部分。[项目地址](https://github.com/open-mmlab/mmocr/blob/main/README_zh-CN.md) 在 [https://github.com/iflytek/aiges_demo/blob/f5061b3b9a4d05f491cfdc21c525e22f8239b760/mmocr/wrapper/wrapper_v2.py) 中，我们使用 python 轻而易举的将 [文本+检测识别 ](https://mmocr.readthedocs.io/zh_CN/latest/demo.html#id4)功能封装部署到 `ASF ` 作为 HTTP API。使用 sealos 部署完 `ASF` 后，可以使用如下脚本修改 `url` 的值，即可完成调用 `MMOCR(文本+检测)` AI 功能调用。
```python
import requests
@@ -207,7 +207,7 @@ MMocr Result: box located at [223, 214, 240, 214, 240, 226, 223, 226], box score
要实现新的 AI 功能，您应该根据 loader Spec Sheet 开发和构建您的 AI 功能图像。然后部署到集群中。
如何构建自定义 AI 功能镜像，请参考: [快速构建 wrapper.py](https://iflytek.github.io/athena_website/docs/%E5%8A%A0%E8%BD%BD%E5%99%A8/Python%E6%8F%92%E4%BB%B6)
如何构建自定义 AI 功能镜像，请参考: [快速构建 wrapper.py](https://iflytek.github.io/athena_website/docs/current/%E5%8A%A0%E8%BD%BD%E5%99%A8/Python%E6%8F%92%E4%BB%B6)
## 更多