From 11d0e1a222477f2857661f442f878c5cebafde25 Mon Sep 17 00:00:00 2001
From: Viktor Palmkvist <vipa@kth.se>
Date: Wed, 10 Jun 2026 14:53:04 +0200
Subject: [PATCH] Fix broken link

---
 docs/r-interface.md  | 15 +++++++--------
 docusaurus.config.js | 21 +++++++++++++--------
 2 files changed, 20 insertions(+), 16 deletions(-)

diff --git a/docs/r-interface.md b/docs/r-interface.md
index d65dd3e..6b6434a 100644
--- a/docs/r-interface.md
+++ b/docs/r-interface.md
@@ -9,24 +9,24 @@ sidebar_position: 5
 `treepplr` is an interface for using the TreePPL program. All functions start
 with `tp_` to easily distinguish them from functions from other packages.
 
-The three necessary parts for doing analysis with TreePPL are: model, data and 
-inference machinery. 
+The three necessary parts for doing analysis with TreePPL are: model, data and
+inference machinery.
 
 ## Model
 
-You can choose a model in TreePPL language from our 
+You can choose a model in TreePPL language from our
 [library](https://treeppl.org/docs/model-library) or you can write your own model.
 
 To list all available models in our library, use `tp_model_library()` to retrieve
-the models within the [TreePPL github repository](https://github.com/treeppl/treeppl/tree/main/models). 
+the models within the [TreePPL github repository](https://github.com/treeppl/treeppl/tree/main/lib/models).
 
 ```r
 model_lib <- tp_model_library()
 ````
 To use one of these models you just need its name in `model_lib$model_name`.
 
-If you want to use your own custom model, you will need to write it in TreePPL 
-language and pass it to an R object that contains either the full path to the 
+If you want to use your own custom model, you will need to write it in TreePPL
+language and pass it to an R object that contains either the full path to the
 `.tppl` file containing the model, or a string with the full model.
 
 ```r
@@ -91,7 +91,7 @@ exe_path <- tp_compile(model = model_path, method = "mcmc-lightweight",
 ```
 
 
-## Running 
+## Running
 
 Now you are ready to run your analysis. All you have to do is to pass your data
 to the compiled executable and choose how many independent runs you want to do.
@@ -122,4 +122,3 @@ output_df_mcmc <- tp_parse_mcmc(output)
 
 Different models produce different outputs and thus require different post-processing.
 See the model-specific tutorials for ways to process your TreePPL output.
-
diff --git a/docusaurus.config.js b/docusaurus.config.js
index f6a1502..f8bb319 100644
--- a/docusaurus.config.js
+++ b/docusaurus.config.js
@@ -18,9 +18,14 @@ const config = {
   trailingSlash: false,
   deploymentBranch: 'gh-pages',
   onBrokenLinks: 'throw',
-  onBrokenMarkdownLinks: 'throw',
   favicon: 'img/favicon.ico',
 
+  markdown: {
+    hooks: {
+      onBrokenMarkdownLinks: 'throw',
+    },
+  },
+
   presets: [
     [
       '@docusaurus/preset-classic',
@@ -89,24 +94,24 @@ const config = {
       algolia: {
         // The application ID provided by Algolia
         appId: 'GMDMVF6JJU',
-  
+
         // Public API key: it is safe to commit it
         apiKey: '893a4c3bf8a2be3d557fca8a80ab4471',
-  
+
         indexName: 'treeppl',
-  
+
         // Optional: see doc section below
         contextualSearch: true,
-  
+
         // Optional: Algolia search parameters
         searchParameters: {},
-  
+
         // Optional: path for search page that enabled by default (`false` to disable it)
         searchPagePath: 'search',
-  
+
         // Optional: whether the insights feature is enabled or not on Docsearch (`false` by default)
         insights: false,
-  
+
         //... other Algolia params
       },
       footer: {