Fix links in docs

Author: MalloryWittwer

README.md

@@ -3,19 +3,19 @@
 
 Turn Python-based image processing workflows into **algorithms** that gain extra functionalities.
 
-- [**Turn your algorithms into web servers**]() and run computations from [QuPath](https://github.com/Imaging-Server-Kit/qupath-extension-serverkit), [Napari](https://github.com/Imaging-Server-Kit/napari-serverkit), or [Python](08_python) via HTTP requests.
+- [**Turn your algorithms into web servers**](https://imaging-server-kit.github.io/imaging-server-kit/sections/07_server.html) and run computations from [QuPath](https://github.com/Imaging-Server-Kit/qupath-extension-serverkit), [Napari](https://github.com/Imaging-Server-Kit/napari-serverkit), or [Python](./sections/08_python) via HTTP requests.
 
 https://github.com/user-attachments/assets/36bda69d-996e-4240-9a53-7e76d9ea3894
 
-- [**Generate dock widgets**]() to run your algorithms interactively in Napari.
+- [**Generate dock widgets**](https://imaging-server-kit.github.io/imaging-server-kit/sections/01_algorithm.html) to run your algorithms interactively in Napari.
 
 https://github.com/user-attachments/assets/1ff572f7-f159-4f5a-afd4-7a157de3d9f8
 
-- Run your algorithms [**tile-by-tile**]() on the input data.
+- Run your algorithms [**tile-by-tile**](https://imaging-server-kit.github.io/imaging-server-kit/sections/06_tiled.html) on the input data.
 
 https://github.com/user-attachments/assets/47c2f734-5683-49d9-8aea-388c3a2bc16d
 
-- [**Stream results**]() to inspect them in real-time.
+- [**Stream results**](https://imaging-server-kit.github.io/imaging-server-kit/sections/05_streams.html) to inspect them in real-time.
 
 https://github.com/user-attachments/assets/a3f69a9f-fb68-4580-a804-6c57d5807b9a
 

docs/index.md

@@ -12,33 +12,33 @@ Server Kit algorithms are versatile objects that allow you run computations in a
 
 For example, you can
 
-- [**Turn your algorithm into a web server**](07_server), connect to it and run computations from [QuPath](https://github.com/Imaging-Server-Kit/qupath-extension-serverkit), [Napari](https://github.com/Imaging-Server-Kit/napari-serverkit), or [Python](08_python) via HTTP requests.
+- [**Turn your algorithm into a web server**](./sections/07_server.md), connect to it and run computations from [QuPath](https://github.com/Imaging-Server-Kit/qupath-extension-serverkit), [Napari](https://github.com/Imaging-Server-Kit/napari-serverkit), or [Python](./sections/08_python) via HTTP requests.
 
 <video width=512 controls loop autoplay>
   <source src="./_static/stardist_blobs.mp4" type="video/mp4">
 </video>
 
-- [**Generate a dock widget**](01_algorithm) to run your algorithm interactively in Napari.
+- [**Generate a dock widget**](./sections/01_algorithm) to run your algorithm interactively in Napari.
 
 <video width=512 controls loop autoplay>
   <source src="./_static/oripy_threshold.mp4" type="video/mp4">
 </video>
 
-- Run your algorithm [**tile-by-tile**](06_tiled) on the input image.
+- Run your algorithm [**tile-by-tile**](./sections/06_tiled) on the input image.
 
 <video width=512 controls loop autoplay>
   <source src="./_static/tiles.mp4" type="video/mp4">
 </video>
 
-- [**Stream results**](05_streams) to inspect them in real-time.
+- [**Stream results**](./sections/05_streams) to inspect them in real-time.
 
 <video width=512 controls loop autoplay>
   <source src="./_static/yolo-stream.mp4" type="video/webm">
 </video>
 
-On top of that, you can [**validate data**](08_python) passed as algorithm parameters, provide [**samples**](02_samples), and generate [**documentation**](03_metadata) for your algorithm that you can share with users.
+On top of that, you can [**validate data**](./sections/08_python) passed as algorithm parameters, provide [**samples**](./sections/02_samples), and generate [**documentation**](./sections/03_metadata) for your algorithm that you can share with users.
 
-This documentation will give you a conceptual overview of the package, and walk you through the steps to learn [how to create an algorithm](01_algorithm), and give you some [suggestions of use cases](11_examples).
+This documentation will give you a conceptual overview of the package, and walk you through the steps to learn [how to create an algorithm](./sections/01_algorithm), and give you some [suggestions of use cases](./sections/11_examples).
 
 ## Contents
 

docs/sections/01_algorithm.ipynb

@@ -229,7 +229,7 @@
     "- `step` (for UI sliders)\n",
     "- `name` (label next to the parameter)\n",
     "\n",
-    "There are many more data layers available. For a full list, see: [Data layers](10_types)\n",
+    "There are many more data layers available. For a full list, see: [Data layers](./10_types)\n",
     "```\n",
     "\n",
     "While `parameters={}` is the most explicit and reliable annotation method, you can also use:\n",

docs/sections/08_python.ipynb

@@ -170,7 +170,7 @@
     "## Using `sk.Client`\n",
     "\n",
     "````{note}\n",
-    "You need to run the \"server-side\" code from this section in a Python script (not a Jupyter notebook) as explained in [Serving algorithms](07_server) via:\n",
+    "You need to run the \"server-side\" code from this section in a Python script (not a Jupyter notebook) as explained in [Serving algorithms](./07_server) via:\n",
     "\n",
     "```python\n",
     "...\n",

docs/sections/09_docker.md

@@ -53,5 +53,5 @@ Congratulations! You have seen all of the main features of *Imaging Server Kit*.
 
 The last two sections of this documentation explore:
 
-- [Data layers](10_types) - A reference of all available data layers.
-- [Examples](11_examples) - A gallery of example Server Kit algorithms for selected projects.
+- [Data layers](./10_types) - A reference of all available data layers.
+- [Examples](./11_examples) - A gallery of example Server Kit algorithms for selected projects.