Adjusted page front matter for the 'Components' section.

content/docs/guides/_index.md

@@ -1,4 +1,5 @@
 +++
 title = "Guides"
-description = "How-to instructions on using Kubeflow."
+description = "Step-by-step instructions on how to use Kubeflow"
+weight = 3
 +++

content/docs/guides/components/_index.md

@@ -1,5 +1,5 @@
 +++
 title = "Components of Kubeflow"
-description = "Logical components that make up Kubeflow."
+description = "Logical components that make up Kubeflow"
 weight = 2
 +++

content/docs/guides/components/chainer.md

@@ -1,15 +1,12 @@
 +++
 title = "Chainer Training"
 description = "Instructions for using Chainer for training"
-weight = 10
+weight = 4
 toc = true
-bref= "This guide will walk you through using Chainer for training"
-[menu]
-[menu.docs]
-  parent = "components"
-  weight = 4
 +++
 
+This guide walks you through using Chainer for training your model.
+
 ## What is Chainer?
 
 [Chainer](https://chainer.org/) is a powerful, flexible and intuitive deep learning framework.

content/docs/guides/components/components.md

@@ -1,12 +1,8 @@
 +++
 title = "Components Overview"
 description = "Kubeflow components"
-weight = 10
-toc = true
+weight = 1
 aliases = ["/docs/guides/components/", "/docs/components/"]
-[menu.docs]
-  parent = "components"
-  weight = 1
 +++
 
 Kubeflow offers scripts and configuration files to activate a number of

content/docs/guides/components/hyperparameter.md

@@ -1,12 +1,7 @@
 +++
 title = "Hyperparameter Tuning (Katib)"
-description = "Hyperparameter Tuning (Katib)"
-weight = 10
-toc = true
-[menu]
-[menu.docs]
-  parent = "components"
-  weight = 5
+description = "Using Katib to tune your model's hyperparameters"
+weight = 5
 +++
 
 ## Using Katib

content/docs/guides/components/istio.md

@@ -1,12 +1,7 @@
 +++
 title = "Istio Integration (for TF Serving)"
-description = "Istio Integration (for TF Serving)"
-weight = 10
-toc = true
-[menu]
-[menu.docs]
-  parent = "components"
-  weight = 6
+description = "Using Istio for TF Serving"
+weight = 6
 +++
 
 [Istio](https://istio.io/) provides a lot of functionality that we want to have, such as metrics, auth and

content/docs/guides/components/jupyter.md

@@ -1,11 +1,7 @@
 +++
 title = "Jupyter Notebooks"
+description = "Using Jupyter notebooks in Kubeflow"
 weight = 10
-toc = true
-[menu]
-[menu.docs]
-  parent = "components"
-  weight = 10
 +++
 
 ## Bringing up a Jupyter Notebook

content/docs/guides/components/ksonnet.md

@@ -1,12 +1,7 @@
 +++
 title = "ksonnet"
-description = "ksonnet information related to Kubeflow"
-weight = 10
-toc = true
-[menu]
-[menu.docs]
-  parent = "components"
-  weight = 20
+description = "Information about ksonnet as used in Kubeflow"
+weight = 20
 +++
 
 Kubeflow makes use of [ksonnet] to help manage deployments.

content/docs/guides/components/mpi.md

@@ -1,15 +1,11 @@
 +++
 title = "MPI Training"
 description = "Instructions for using MPI for training"
-weight = 10
-toc = true
-bref= "This guide will walk you through using MPI for training"
-[menu]
-[menu.docs]
-  parent = "components"
-  weight = 25
+weight = 25
 +++
 
+This guide walks you through using MPI for training.
+
 ## Installing MPI Operator
 
 If you haven't already done so please follow the [Getting Started Guide](/docs/started/getting-started/) to deploy Kubeflow.

content/docs/guides/components/mxnet.md

@@ -1,15 +1,11 @@
 +++
 title = "MXNet Training"
 description = "Instructions for using MXNet"
-weight = 10
-toc = true
-bref= "This guide will walk you through using MXNet with Kubeflow"
-[menu]
-[menu.docs]
-  parent = "components"
-  weight = 25
+weight = 25
 +++
 
+This guide walks you through using MXNet with Kubeflow.
+
 ## Installing MXNet Operator
 
 If you haven't already done so please follow the [Getting Started Guide](https://www.kubeflow.org/docs/started/getting-started/) to deploy Kubeflow.

content/docs/guides/components/pipelines.md

@@ -1,12 +1,7 @@
 +++
 title = "Pipelines"
 description = "Introduction to Kubeflow Pipelines"
-weight = 10
-toc = true
-[menu]
-[menu.docs]
-  parent = "components"
-  weight = 35
+weight = 35
 +++
 
 Kubeflow Pipelines is a platform for building and deploying portable and

content/docs/guides/components/pytorch.md

@@ -1,15 +1,11 @@
 +++
 title = "PyTorch Training"
 description = "Instructions for using PyTorch"
-weight = 10
-toc = true
-bref= "This guide will walk you through using PyTorch with Kubeflow"
-[menu]
-[menu.docs]
-  parent = "components"
-  weight = 35
+weight = 35
 +++
 
+This guide walks you through using PyTorch with Kubeflow.
+
 ## Installing PyTorch Operator
 
 If you haven't already done so please follow the [Getting Started Guide](/docs/started/getting-started/) to deploy Kubeflow.

content/docs/guides/components/pytorchserving.md

@@ -1,15 +1,10 @@
 +++
 title = "PyTorch Serving"
 description = "Instructions for serving a PyTorch model with Seldon"
-weight = 10
-toc = true
-bref= "This guide will walk you through serving a PyTorch trained model in Kubeflow"
-[menu]
-[menu.docs]
-  parent = "components"
-  weight = 35
 +++
 
+This guide walks you through serving a PyTorch trained model in Kubeflow.
+
 ## Serving a model
 
 We use [seldon-core](https://github.com/SeldonIO/seldon-core) component deployed following [these](/docs/guides/components/seldon/) instructions to serve the model.

content/docs/guides/components/seldon.md

@@ -1,13 +1,7 @@
 +++
 title = "Seldon Serving"
-description = "Seldon Serving"
-weight = 10
-toc = true
-bref= "Model serving using Seldon"
-[menu]
-[menu.docs]
-  parent = "components"
-  weight = 40
+description = "Model serving using Seldon"
+weight = 40
 +++
 
 ## Serve a model using Seldon

content/docs/guides/components/tfbatchpredict.md

@@ -1,13 +1,7 @@
 +++
 title = "TensorFlow Batch Predict"
-description = ""
-weight = 10
-toc = true
-bref= "Batch Prediction for TensorFlow models"
-[menu]
-[menu.docs]
-  parent = "components"
-  weight = 60
+description = "Batch prediction for TensorFlow models"
+weight = 60
 +++
 
 ## Kubeflow Batch Predict

content/docs/guides/components/tfserving.md

@@ -1,13 +1,7 @@
 +++
 title = "TensorFlow Serving"
-description = ""
-weight = 10
-toc = true
-bref= "Training and serving using TFJob"
-[menu]
-[menu.docs]
-  parent = "components"
- weight = 50
+description = "Training and serving using TFJob"
+weight = 50
 +++
 
 ## Serving a model

content/docs/guides/components/tfserving_new.md

@@ -1,13 +1,7 @@
 +++
 title = "TensorFlow Serving (new)"
-description = ""
-weight = 10
-toc = true
-bref= "Serving Tensorflow models"
-[menu]
-[menu.docs]
-  parent = "components"
- weight = 51
+description = "Serving Tensorflow models"
+weight = 51
 +++
 
 This document is for the new Kubeflow TF Serving 

content/docs/guides/components/tftraining.md

@@ -2,15 +2,11 @@
 title = "TensorFlow Training (TFJob)"
 linkTitle = "TensorFlow Training (TFJob)"
 description = ""
-weight = 10
-toc = true
-bref= "This page describes TFJob for training a machine learning model with TensorFlow."
-[menu]
-[menu.docs]
-  parent = "components"
-  weight = 60
+weight = 60
 +++
 
+This page describes TFJob for training a machine learning model with TensorFlow.
+
 ## What is TFJob?
 
 TFJob is a Kubernetes 

content/docs/guides/components/trtinferenceserver.md

@@ -1,13 +1,7 @@
 +++
 title = "NVIDIA TensorRT Inference Server"
-description = ""
-weight = 10 
-toc = true
-bref= "Model serving using TRT Inference Server"
-[menu]
-[menu.docs]
-  parent = "components"
-  weight = 50
+description = "Model serving using TRT Inference Server"
+weight = 50
 +++
 
 NVIDIA TensorRT Inference Server is a REST and GRPC service for deep-learning

resources/_gen/assets/js/js/search.js_b4bb3e7b21b43e920b7c367ff787d383.content

@@ -27,7 +27,7 @@ limitations under the License.
                     }
 
                     var query = $(this).val();
-                    var searchPage = "/search/?q=" + query;
+                    var searchPage = "//localhost:1313/search/?q=" + query;
                     document.location = searchPage;
 
                     return false;