Hugo website first draft

.gitignore

@@ -408,3 +408,10 @@ tools/
 
 # duplicated/copied proto file for python code generation
 source/Mlos.Proto/mlos/Grpc/OptimizerService.proto
+
+# generated website
+website/public
+website/content/documentation/
+website/content/notebooks/
+website/sphinx/_build
+website/sphinx/api

README.md

@@ -66,18 +66,54 @@ To achieve this MLOS provides:
 
     Once hooks are created in the target system, iteration on the external agent can be more rapidly developed and deployed.
 
-## Build
+
+## Python only installation
+
+Some of the examples require only the installation of the mlos Python library. These examples do not use the shared memory infrastructure.
+To use this simplified installation, it's recommended to use the Anaconda python distribution and create a new conda environment:
+
+```
+$ conda create -n mlos_environment
+$ conda activate mlos_environment
+```
+
+You can download the mlos code using git:
+
+```
+$ git clone git@github.com:microsoft/MLOS.git
+```
+
+To install the Python library, change to the Python directory and install with ``pip``:
+
+```
+$ cd MLOS/source/Mlos.Python
+$ pip install -e .
+```
+
+You can also install the package directly without checking out the code:
+
+```
+$ pip install "git+https://github.com/microsoft/MLOS.git#egg=mlos&subdirectory=source/Mlos.Python"
+```
+
+However, this does not include the examples.
+
+After this installation, you can run any of the Python-only example notebooks.
+A good place to start is the [Introduction to Bayesian Optimization](./notebooks/BayesianOptimization/) notebook.
+
+## Full Build (C# and C++ components)
 
 MLOS supports Windows and Linux build environments.
 
 For detailed instructions, please refer to:
 
-  1. [documentation/01-Prerequisites.md](./documentation/01-Prerequisites.md)
-  2. [documentation/02-Build.md](./documentation/02-Build.md)
+  1. [Prerequisites](./documentation/01-Prerequisites.md)
+  2. [Build](./documentation/02-Build.md)
 
 ## Examples
 
-Code and documentation for examples of using MLOS to optimize a system are described in [documentation/03-ExampleUsage.md](./documentation/04-ExampleUsage.md) and in the [source/Examples](./source/Examples/) tree.
+Code and documentation for examples of using MLOS to optimize a system are described in the [Notebooks](./notebooks/) section. Additional code is in the  [source/Examples](https://github.com/microsoft/MLOS/tree/main/source/Examples) source directory.
+You can find the source of the notebooks [on github as well](https://github.com/microsoft/MLOS/tree/main/source/Mlos.Notebooks).
 
 ## Documentation
 
@@ -87,9 +123,9 @@ Code and documentation for examples of using MLOS to optimize a system are descr
 
 ## Contributing
 
-We welcome contributions!  Please see [CONTRIBUTING.md](./CONTRIBUTING.md) and [CODE_OF_CONDUCT.md](./CODE_OF_CONDUCT.md) for details.
+We welcome contributions!  Please see [Contributing](./CONTRIBUTING.md) and [Code of Conduct](./CODE_OF_CONDUCT.md) for details.
 
-Also, please see the [Roadmap](TODOFIXME) of planned features.
+Also, please see the [Roadmap](#) of planned features.
 
 ## Contact
 

website/archetypes/default.md

@@ -0,0 +1,6 @@
+---
+title: "{{ replace .Name "-" " " | title }}"
+date: {{ .Date }}
+draft: true
+---
+

website/build_site.sh

@@ -0,0 +1,23 @@
+#!/bin/sh
+
+cp -r ../documentation content/
+jupyter nbconvert ../source/Mlos.Notebooks/*.ipynb --to markdown --output-dir content/notebooks
+
+# nbconvert and hugo disagree about paths
+sed -i 's/BayesianOptimization_files/\.\.\/BayesianOptimization_files/g' content/notebooks/BayesianOptimization.md
+
+cp ../*.md content/
+cp ../LICENSE content/
+cp ../README.md content/_index.md
+mv content/documentation/README.md content/documentation/_index.md
+
+# replace markdown links
+# this allows the original files to link on github directly
+# while also rendering properly in hugo (which requires no .md in the links)
+sed -i 's/\.md/\//g' content/*.md
+sed -i 's/\.md/\//g' content/documentation/*.md
+
+
+if [ ! -d "themes/book" ]; then
+    git clone --depth 1 --branch v8 https://github.com/alex-shpak/hugo-book.git themes/book/
+fi

website/config.toml

@@ -0,0 +1,9 @@
+title = 'MLOS'
+
+theme = "book"
+baseURL = "https://microsoft.github.io/MLOS/"
+DisablePathToLower = "True"
+
+[params]
+  BookRepo = 'https://github.com/microsoft/MLOS'
+  BookMenuBundle = '/menu'

website/content/menu/index.md

@@ -0,0 +1,25 @@
++++
+headless = true
++++
+
+- [Documentation]({{< relref "/documentation" >}})
+  - [Prerequisits]({{< relref "/documentation/01-Prerequisites" >}})
+  - [Build]({{< relref "/documentation/02-Build" >}})
+  - [Test]({{< relref "/documentation/05-Test" >}})
+  - [Coding Standard]({{< relref "/documentation/CodingStandard" >}})
+  - [Architecture]({{< relref "/documentation/MlosArchitecture" >}})
+  - [Repo Organization]({{< relref "/documentation/RepoOrganization" >}})
+
+- Notebooks
+  - [Start Here]({{< relref "/notebooks/StartHere" >}})
+  - [Smart Cache]({{< relref "/notebooks/SmartCache" >}})
+  - [Smart Cache Active Learning]({{< relref "/notebooks/SmartCacheActiveLearning" >}})
+  - [Optimizer Monitor]({{< relref "/notebooks/OptimizerMonitor" >}})
+  - [Bayesian Optimization]({{< relref "/notebooks/BayesianOptimization" >}})
+
+
+- API Documentation
+  - [Python](/MLOS/python_api/)
+
+- [Code of Conduct]({{< relref "/CODE_OF_CONDUCT" >}})
+- [Contributing]({{< relref "/CONTRIBUTING" >}})