Migrate tutorials to PINA-Tutorials and preserve legacy URLs

.github/CODEOWNERS

@@ -6,7 +6,6 @@
 pina/                    @PINA-org/pina-maintainers
 readme/                  @PINA-org/pina-maintainers
 tests/                   @PINA-org/pina-maintainers
-tutorials/               @PINA-org/pina-maintainers
 pyproject.toml           @PINA-org/pina-committee @ndem0
 
 # Owners for documentation

.github/workflows/deployer.yml

@@ -12,6 +12,11 @@ jobs:
     steps:
     - uses: actions/checkout@v4
 
+    - name: Set up Python
+      uses: actions/setup-python@v5
+      with:
+        python-version: '3.11'
+
     - name: Install Python dependencies
       run: python3 -m pip install .[doc]
 
@@ -55,4 +60,4 @@ jobs:
       if: startsWith(github.ref, 'refs/tags')
       uses: pypa/gh-action-pypi-publish@release/v1
       with:
-        password: ${{ secrets.PYPI_API_TOKEN }}
+        password: ${{ secrets.PYPI_API_TOKEN }}

README.md

@@ -60,6 +60,9 @@ SPDX-License-Identifier: Apache-2.0
 
 <div style="border: 1px solid #ddd; border-radius: 10px; padding: 14px; margin: 12px 0;">
   <ul style="margin: 0; padding-left: 18px; line-height: 1.55;">
+    <li>
+      <b>[v0.3.3]</b> – <b>Tutorial migration:</b> Our tutorials now have a dedicated home in <a href="https://github.com/PINA-org/PINA-Tutorials">PINA-Tutorials</a>. Visit the <a href="https://PINA-org.github.io/PINA-Tutorials/">tutorial website</a> to explore them, and please <a href="https://github.com/PINA-org/PINA-Tutorials/issues">report any broken links or other issues</a> to help us keep the migration smooth.
+    </li>
     <li>
       <b>[v0.3.2]</b> – <b>Agentic PINA:</b> Added AI agents that guide users through the PINA pipeline, with dedicated skills for problem setup, model and solver selection, and training configuration.
     </li>
@@ -203,7 +206,7 @@ flowchart LR
 
 <p>
 Want to dive deeper? Check out the official
-<a href="https://github.com/pina-org/PINA/tree/master/tutorials#pina-tutorials"><b>Tutorials</b></a>.
+<a href="https://PINA-org.github.io/PINA-Tutorials/"><b>Tutorials</b></a>.
 </p>
 
 <hr/>
@@ -213,7 +216,7 @@ Want to dive deeper? Check out the official
 <summary>
   <h2>PINA by Examples</h2>
   &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
-  <a href="https://github.com/pina-org/PINA/blob/master/tutorials/README.md">
+  <a href="https://PINA-org.github.io/PINA-Tutorials/">
   <img align="center" height="20" src="https://img.shields.io/badge/tutorial-fa9900?style=for-the-badge&logo=jupyter&logoColor=white&labelColor=555">
   </a>
 </summary>

docs/source/_quickstart.rst

@@ -99,6 +99,6 @@ After training, the model stores its solution in the solver. Evaluate at any poi
 What's next?
 ------------
 
-* Walk through the `Introductory Tutorial <tutorial17/tutorial.html>`_ for a deeper introduction.
+* Walk through the `Introductory Tutorial <https://PINA-org.github.io/PINA-Tutorials/tutorial17/tutorial.html>`_ for a deeper introduction.
 * Explore the :doc:`API reference </_rst/_code>` for all available components.
-* Read the :doc:`tutorials </_tutorial>` for domain-specific guides (Neural Operators, Supervised Learning, etc.).
+* Read the `tutorials <https://PINA-org.github.io/PINA-Tutorials/>`_ for domain-specific guides (Neural Operators, Supervised Learning, etc.).

docs/source/_static/custom.css

@@ -33,3 +33,8 @@
 .hero .btn:hover {
   color: #fff !important;
 }
+
+/* Hide external-link icons in navigation tabs only. */
+.nav-link.nav-external::after {
+  display: none;
+}

docs/source/_tutorial.rst

@@ -1,55 +1,19 @@
-.. docmeta::
-   :last_reviewed: 2026-06-24
+:orphan:
 
+PINA Tutorials have moved
+========================================
 
-Welcome to the PINA Tutorials
-==============================
+.. raw:: html
 
-This section collects step-by-step tutorials to help you understand the principles and potential of **PINA**.
-Whether you are just getting started or looking to deepen your understanding, these resources will guide you.
+   <script>
+     window.location.replace("https://PINA-org.github.io/PINA-Tutorials/" + window.location.search + window.location.hash);
+   </script>
 
-Getting started with PINA
--------------------------
+The tutorials are now hosted on the
+`PINA Tutorials website <https://PINA-org.github.io/PINA-Tutorials/>`_.
+If you are not redirected automatically, follow that link or select a category:
 
-- `Introductory Tutorial: A Beginner's Guide to PINA <tutorial17/tutorial.html>`_
-- `How to build a Problem in PINA <tutorial16/tutorial.html>`_
-- `Introduction to Solver classes <tutorial18/tutorial.html>`_
-- `Introduction to Trainer class <tutorial11/tutorial.html>`_
-- `Data structure for SciML: Tensor, LabelTensor, Data and Graph <tutorial19/tutorial.html>`_
-- `Building geometries with DomainInterface class <tutorial6/tutorial.html>`_
-- `Introduction to PINA Equation class <tutorial12/tutorial.html>`_
-
-Physics Informed Neural Networks
---------------------------------
-
-- `Introductory Tutorial: Physics Informed Neural Networks with PINA <tutorial1/tutorial.html>`_
-- `Enhancing PINNs with Extra Features to solve the Poisson Problem <tutorial2/tutorial.html>`_
-- `Applying Hard Constraints in PINNs to solve the Wave Problem <tutorial3/tutorial.html>`_
-- `Applying Periodic Boundary Conditions in PINNs to solve the Helmholtz Problem <tutorial9/tutorial.html>`_
-- `Inverse Problem Solving with Physics-Informed Neural Network <tutorial7/tutorial.html>`_
-- `Learning Multiscale PDEs Using Fourier Feature Networks <tutorial13/tutorial.html>`_
-- `Learning Bifurcating PDE Solutions with Physics-Informed Deep Ensembles <tutorial14/tutorial.html>`_
-
-Neural Operator Learning
-------------------------
-
-- `Introductory Tutorial: Neural Operator Learning with PINA <tutorial21/tutorial.html>`_
-- `Modeling 2D Darcy Flow with the Fourier Neural Operator <tutorial5/tutorial.html>`_
-- `Solving the Kuramoto-Sivashinsky Equation with Averaging Neural Operator <tutorial10/tutorial.html>`_
-- `Advection Equation with data driven DeepONet <tutorial24/tutorial.html>`_
-
-Supervised Learning
--------------------
-
-- `Introductory Tutorial: Supervised Learning with PINA <tutorial20/tutorial.html>`_
-- `Chemical Properties Prediction with Graph Neural Networks <tutorial15/tutorial.html>`_
-- `Reduced Order Model with Graph Neural Networks for Unstructured Domains <tutorial22/tutorial.html>`_
-- `Data-driven System Identification with SINDy <tutorial23/tutorial.html>`_
-- `Unstructured Convolutional Autoencoders with Continuous Convolution <tutorial4/tutorial.html>`_
-- `Reduced Order Modeling with POD-RBF and POD-NN Approaches for Fluid Dynamics <tutorial8/tutorial.html>`_
-
-See Also
---------
-
-* :doc:`Quickstart guide <_quickstart>`
-* :doc:`API Reference <_rst/_code>`
+* `Getting started with PINA <https://PINA-org.github.io/PINA-Tutorials/#getting-started-with-pina>`_
+* `Physics Informed Neural Networks <https://PINA-org.github.io/PINA-Tutorials/#physics-informed-neural-networks>`_
+* `Neural Operator Learning <https://PINA-org.github.io/PINA-Tutorials/#neural-operator-learning>`_
+* `Supervised Learning <https://PINA-org.github.io/PINA-Tutorials/#supervised-learning>`_

docs/source/index.rst

@@ -148,7 +148,7 @@ Physics-Informed Neural Networks (PINNs), Neural Operators, and more.
       Complete API docs for problems, solvers, models, and more.
 
    .. grid-item-card:: 🎓 Tutorials
-      :link: _tutorial.html
+      :link: https://PINA-org.github.io/PINA-Tutorials/
       :class-card: sd-shadow-sm
 
       Step-by-step tutorials covering PINNs, Neural Operators, and more.
@@ -183,7 +183,7 @@ Physics-Informed Neural Networks (PINNs), Neural Operators, and more.
 
    Quickstart <_quickstart>
    API <_rst/_code>
-   Tutorials <_tutorial>
+   Tutorials <https://PINA-org.github.io/PINA-Tutorials/>
    Contributing <_contributing>
    Team & Fundings <_team.rst>
    Installing <_installation>