Merge branch 'master' into master

Author: vijaykr338

README.md

@@ -102,7 +102,7 @@ OpenVINO supports the CPU, GPU, and NPU [devices](https://docs.openvino.ai/2025/
 
 Get started with the OpenVINO GenAI [installation](https://docs.openvino.ai/2025/get-started/install-openvino/install-openvino-genai.html) and refer to the [detailed guide](https://docs.openvino.ai/2025/openvino-workflow-generative/generative-inference.html) to explore the capabilities of Generative AI using OpenVINO.
 
-Learn how to run LLMs and GenAI with [Samples](https://github.com/openvinotoolkit/openvino.genai/tree/master/samples) in the [OpenVINO™ GenAI repo](https://github.com/openvinotoolkit/openvino.genai). See GenAI in action with Jupyter notebooks: [LLM-powered Chatbot](https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/llm-chatbot/README.md) and [LLM Instruction-following pipeline](https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/llm-question-answering/README.md).
+Learn how to run LLMs and GenAI with [Samples](https://github.com/openvinotoolkit/openvino.genai/tree/master/samples) in the [OpenVINO™ GenAI repo](https://github.com/openvinotoolkit/openvino.genai). See GenAI in action with Jupyter notebooks: [LLM-powered Chatbot](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/llm-chatbot) and [LLM Instruction-following pipeline](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/llm-question-answering).
 
 ## Documentation
 

docs/CMakeLists.txt

@@ -70,15 +70,6 @@ function(build_docs)
         list(APPEND commands COMMAND ${CMAKE_COMMAND} -E cmake_echo_color --green "FINISHED preprocessing OpenVINO Python API")
     endif()
 
-    if(${ENABLE_NOTEBOOKS})
-        set(NBDOC_SCRIPT "${DOCS_SOURCE_DIR}/nbdoc/nbdoc.py")
-        list(PREPEND commands COMMAND ${CMAKE_COMMAND} -E cmake_echo_color --green "STARTED preprocessing OpenVINO notebooks")
-        list(PREPEND commands
-            COMMAND ${Python3_EXECUTABLE} "${NBDOC_SCRIPT}" "${DOCS_SOURCE_DIR}/notebooks" "${SPHINX_SOURCE_DIR}/notebooks"
-        )
-        list(PREPEND commands COMMAND ${CMAKE_COMMAND} -E cmake_echo_color --green "FINISHED preprocessing OpenVINO notebooks")
-    endif()
-
     if(${ENABLE_OVMS})
         list(APPEND commands COMMAND ${CMAKE_COMMAND} -E cmake_echo_color --green "STARTED preprocessing OVMS")
         list(APPEND commands COMMAND ${Python3_EXECUTABLE} ${FILE_HELPER_SCRIPT}

docs/articles_en/about-openvino/openvino-ecosystem/openvino-integrations.rst

@@ -27,7 +27,7 @@ OpenVINO™ Integrations
    .. grid-item::
 
       * :doc:`Run inference with HuggingFace and Optimum Intel <../../openvino-workflow-generative/inference-with-optimum-intel>`
-      * `A notebook example: llm-chatbot <https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/254-llm-chatbot>`__
+      * `A notebook example: llm-chatbot <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/llm-chatbot>`__
       * `Hugging Face Inference documentation <https://huggingface.co/docs/optimum/main/intel/openvino/inference>`__
       * `Hugging Face Compression documentation <https://huggingface.co/docs/optimum/main/intel/openvino/optimization>`__
       * `Hugging Face Reference Documentation <https://huggingface.co/docs/optimum/main/intel/openvino/reference>`__

docs/articles_en/get-started.rst

@@ -21,7 +21,7 @@ GET STARTED
    <link rel="stylesheet" type="text/css" href="_static/css/getstarted_style.css">
 
    <p id="GSG_introtext">Welcome to OpenVINO! This guide introduces installation and learning materials for Intel® Distribution of OpenVINO™ toolkit. The guide walks through the following steps:<br />
-     <a href="notebooks/vision-monodepth-with-output.html" >Quick Start Example</a>
+     <a href="https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/vision-monodepth" >Quick Start Example</a>
      <a href="get-started/install-openvino.html" >Install OpenVINO</a>
      <a href="#learn-openvino" >Learn OpenVINO</a>
    </p>
@@ -40,7 +40,8 @@ For a quick reference, check out
 .. image:: https://user-images.githubusercontent.com/15709723/127752390-f6aa371f-31b5-4846-84b9-18dd4f662406.gif
    :width: 400
 
-Try out OpenVINO's capabilities with this `quick start example <notebooks/vision-monodepth-with-output.html>`__ that estimates depth in a scene using an OpenVINO monodepth model to quickly see how to load a model, prepare an image, inference the image, and display the result.
+Try out OpenVINO's capabilities with this `quick start example <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/vision-monodepth>`__
+that estimates depth in a scene using an OpenVINO monodepth model to quickly see how to load a model, prepare an image, inference the image, and display the result.
 
 .. _install-openvino-gsg:
 
@@ -70,10 +71,12 @@ Interactive Tutorials - Jupyter Notebooks
 
 Start with :doc:`interactive Python <get-started/learn-openvino/interactive-tutorials-python>` that show the basics of model inference, the OpenVINO API, how to convert models to OpenVINO format, and more.
 
-* `Hello Image Classification <notebooks/hello-world-with-output.html>`__ - Load an image classification model in OpenVINO and use it to apply a label to an image
-* `OpenVINO Runtime API Tutorial <notebooks/openvino-api-with-output.html>`__ - Learn the basic Python API for working with models in OpenVINO
-* `Convert TensorFlow Models to OpenVINO <notebooks/tensorflow-classification-to-openvino-with-output.html>`__
-* `Convert PyTorch Models to OpenVINO <notebooks/pytorch-onnx-to-openvino-with-output.html>`__
+* `Hello Image Classification <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/hello-world>`__
+  - Load an image classification model in OpenVINO and use it to apply a label to an image
+* `OpenVINO Runtime API Tutorial <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/openvino-api>`__
+  - Learn the basic Python API for working with models in OpenVINO
+* `Convert TensorFlow Models to OpenVINO <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/tensorflow-classification-to-openvino>`__
+* `Convert PyTorch Models to OpenVINO <https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/pytorch-to-openvino/pytorch-onnx-to-openvino.ipynb>`__
 
 .. _code-samples:
 
@@ -101,8 +104,8 @@ Model Compression and Quantization
 
 Use OpenVINO’s model compression tools to reduce your model’s latency and memory footprint while maintaining good accuracy.
 
-* Tutorial - `Quantization-Aware Training in TensorFlow with OpenVINO NNCF <notebooks/tensorflow-quantization-aware-training-with-output>`__
-* Tutorial - `Quantization-Aware Training in PyTorch with NNCF <notebooks/pytorch-quantization-aware-training-with-output>`__
+* Tutorial - `Quantization-Aware Training in TensorFlow with OpenVINO NNCF <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/tensorflow-quantization-aware-training>`__
+* Tutorial - `Quantization-Aware Training in PyTorch with NNCF <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/pytorch-quantization-aware-training>`__
 * :doc:`Model Optimization Guide <openvino-workflow/model-optimization>`
 
 Automated Device Configuration

docs/articles_en/get-started/install-openvino/install-openvino-archive-linux.rst

@@ -218,17 +218,17 @@ Learn more about how to integrate a model in OpenVINO applications by trying out
    .. tab-item:: Get started with Python
       :sync: get-started-py
 
-      Try the `Python Quick Start Example <../../notebooks/vision-monodepth-with-output.html>`__
+      Try the `Python Quick Start Example <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/vision-monodepth>`__
       to estimate depth in a scene using an OpenVINO monodepth model in a Jupyter Notebook inside your web browser.
 
       .. image:: https://user-images.githubusercontent.com/15709723/127752390-f6aa371f-31b5-4846-84b9-18dd4f662406.gif
          :width: 400
 
       Visit the :doc:`Tutorials <../../../get-started/learn-openvino/interactive-tutorials-python>` page for more Jupyter Notebooks to get you started with OpenVINO, such as:
 
-      * `OpenVINO Python API Tutorial <../../notebooks/openvino-api-with-output.html>`__
-      * `Basic image classification program with Hello Image Classification <../../notebooks/hello-world-with-output.html>`__
-      * `Convert a PyTorch model and use it for image background removal <../../notebooks/vision-background-removal-with-output.html>`__
+      * `OpenVINO Python API Tutorial <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/openvino-api>`__
+      * `Basic image classification program with Hello Image Classification <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/hello-world>`__
+      * `Convert a PyTorch model and use it for image background removal <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/vision-background-removal>`__
 
 
    .. tab-item:: Get started with C++

docs/articles_en/get-started/install-openvino/install-openvino-archive-macos.rst

@@ -140,16 +140,16 @@ Now that you've installed OpenVINO Runtime, you're ready to run your own machine
    .. tab-item:: Get started with Python
       :sync: get-started-py
 
-      Try the `Python Quick Start Example <../../notebooks/vision-monodepth-with-output.html>`__ to estimate depth in a scene using an OpenVINO monodepth model in a Jupyter Notebook inside your web browser.
+      Try the `Python Quick Start Example <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/vision-monodepth>`__ to estimate depth in a scene using an OpenVINO monodepth model in a Jupyter Notebook inside your web browser.
 
       .. image:: https://user-images.githubusercontent.com/15709723/127752390-f6aa371f-31b5-4846-84b9-18dd4f662406.gif
          :width: 400
 
       Visit the :doc:`Tutorials <../../../get-started/learn-openvino/interactive-tutorials-python>` page for more Jupyter Notebooks to get you started with OpenVINO, such as:
 
-      * `OpenVINO Python API Tutorial <../../notebooks/openvino-api-with-output.html>`__
-      * `Basic image classification program with Hello Image Classification <../../notebooks/hello-world-with-output.html>`__
-      * `Convert a PyTorch model and use it for image background removal <../../notebooks/vision-background-removal-with-output.html>`__
+      * `OpenVINO Python API Tutorial <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/openvino-api>`__
+      * `Basic image classification program with Hello Image Classification <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/hello-world>`__
+      * `Convert a PyTorch model and use it for image background removal <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/vision-background-removal>`__
 
    .. tab-item:: Get started with C++
       :sync: get-started-cpp

docs/articles_en/get-started/install-openvino/install-openvino-archive-windows.rst

@@ -156,16 +156,16 @@ Now that you've installed OpenVINO Runtime, you're ready to run your own machine
    .. tab-item:: Get started with Python
       :sync: get-started-py
 
-      Try the `Python Quick Start Example <../../notebooks/vision-monodepth-with-output.html>`__ to estimate depth in a scene using an OpenVINO monodepth model in a Jupyter Notebook inside your web browser.
+      Try the `Python Quick Start Example <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/vision-monodepth>`__ to estimate depth in a scene using an OpenVINO monodepth model in a Jupyter Notebook inside your web browser.
 
       .. image:: https://user-images.githubusercontent.com/15709723/127752390-f6aa371f-31b5-4846-84b9-18dd4f662406.gif
          :width: 400
 
       Visit the :doc:`Tutorials <../../../get-started/learn-openvino/interactive-tutorials-python>` page for more Jupyter Notebooks to get you started with OpenVINO, such as:
 
-      * `OpenVINO Python API Tutorial <../../notebooks/openvino-api-with-output.html>`__
-      * `Basic image classification program with Hello Image Classification <../../notebooks/hello-world-with-output.html>`__
-      * `Convert a PyTorch model and use it for image background removal <../../notebooks/vision-background-removal-with-output.html>`__
+      * `OpenVINO Python API Tutorial <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/openvino-api>`__
+      * `Basic image classification program with Hello Image Classification <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/hello-world>`__
+      * `Convert a PyTorch model and use it for image background removal <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/vision-background-removal>`__
 
    .. tab-item:: Get started with C++
       :sync: get-started-cpp

docs/articles_en/get-started/install-openvino/install-openvino-genai.rst

@@ -9,9 +9,9 @@ and returns the generated content. For a quickstart guide, refer to the
 :doc:`GenAI API Guide <../../openvino-workflow-generative/inference-with-genai>`.
 
 To see OpenVINO GenAI in action, check these Jupyter notebooks:
-`LLM-powered Chatbot <https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/llm-chatbot/README.md>`__
+`LLM-powered Chatbot <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/llm-chatbot>`__
 and
-`LLM Instruction-following pipeline <https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/llm-question-answering/README.md>`__.
+`LLM Instruction-following pipeline <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/llm-question-answering>`__.
 
 OpenVINO GenAI is available for installation via PyPI and Archive distributions.
 A `detailed guide <https://github.com/openvinotoolkit/openvino.genai/blob/releases/2025/0/src/docs/BUILD.md>`__

docs/articles_en/get-started/install-openvino/install-openvino-pip.rst

@@ -84,7 +84,7 @@ Use the following command:
 Step 4. Install the Package
 +++++++++++++++++++++++++++
 
-Use the following command to install OpenVINO Base or OpenVINO GenAI package:
+Use the following command to install either the base or GenAI OpenVINO package:
 
 .. code-block:: python
 
@@ -141,7 +141,7 @@ the following tutorials.
 .. image:: https://user-images.githubusercontent.com/15709723/127752390-f6aa371f-31b5-4846-84b9-18dd4f662406.gif
    :width: 400
 
-Try the `Python Quick Start Example <https://docs.openvino.ai/2025/notebooks/vision-monodepth-with-output.html>`__
+Try the `Python Quick Start Example <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/vision-monodepth>`__
 to estimate depth in a scene using an OpenVINO monodepth model in a Jupyter Notebook inside
 your web browser.
 
@@ -152,9 +152,9 @@ Get started with Python
 Visit the :doc:`Tutorials <../../../get-started/learn-openvino/interactive-tutorials-python>` page for more
 Jupyter Notebooks to get you started with OpenVINO, such as:
 
-* `OpenVINO Python API Tutorial <https://docs.openvino.ai/2025/notebooks/openvino-api-with-output.html>`__
-* `Basic image classification program with Hello Image Classification <https://docs.openvino.ai/2025/notebooks/hello-world-with-output.html>`__
-* `Convert a PyTorch model and use it for image background removal <https://docs.openvino.ai/2025/notebooks/vision-background-removal-with-output.html>`__
+* `OpenVINO Python API Tutorial <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/openvino-api>`__
+* `Basic image classification program with Hello Image Classification <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/hello-world>`__
+* `Convert a PyTorch model and use it for image background removal <https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/vision-background-removal>`__
 
 
 

docs/articles_en/get-started/learn-openvino/interactive-tutorials-python.rst

@@ -14,28 +14,38 @@ Interactive Tutorials (Python)
    :hidden:
 
    interactive-tutorials-python/notebooks-installation
+   interactive-tutorials-python/run-notebooks
 
 
-Jupyter notebooks show how to use various OpenVINO features to run optimized deep learning
-inference with Python. Notebooks with |binder logo| and |colab logo| buttons can be run in the
-browser, no installation required. Just choose a tutorial and click the button.
-
-`Binder <https://mybinder.org/>`__ and `Google Colab <https://colab.research.google.com/>`__
-are free online services with limited resources. For the best performance
-and more control, you should run the notebooks locally. Follow the
-:doc:`Installation Guide <interactive-tutorials-python/notebooks-installation>` in order to get information
-on how to run and manage the notebooks on your system.
+The tutorials show how to use various OpenVINO Python API features to run
+optimized deep learning inference. They are not maintained on this website,
+however, you can use the selector below to reach Jupyter notebooks from the
+`openvino_notebooks <https://github.com/openvinotoolkit/openvino_notebooks>`__ repository.
 
 .. raw:: html
 
    <script type="module" crossorigin src="https://openvinotoolkit.github.io/openvino_notebooks/assets/embedded.js"></script>
    <iframe id="notebooks-selector" src="https://openvinotoolkit.github.io/openvino_notebooks/" style="width: 100%; border: none;" title="OpenVINO™ Notebooks - Jupyter notebook tutorials for OpenVINO™"></iframe>
 
 
-.. note::
-   If you have any issues with the notebooks, refer to the **Troubleshooting** and **FAQ**
-   sections in the :doc:`Installation Guide <interactive-tutorials-python/notebooks-installation>` or start a GitHub
-   `discussion <https://github.com/openvinotoolkit/openvino_notebooks/discussions>`__.
+Notebooks with |binder logo| and |colab logo| buttons can be run in the
+browser, no installation required. Just choose a tutorial and click the button.
+
+`Binder <https://mybinder.org/>`__ and `Google Colab <https://colab.research.google.com/>`__
+are free online services with limited resources. For the best performance
+and more control, you should run the notebooks locally. Follow the
+:doc:`Installation Guide <interactive-tutorials-python/notebooks-installation>` in order
+to get information on how to run and manage the notebooks on your system.
+
+
+If you have any issues with the notebooks, refer to the
+`Troubleshooting <https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/README.md#%EF%B8%8F-troubleshooting>`__
+and
+`FAQ <https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/README.md#-faq>`__
+sections in the
+`Installation Guide <https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/README.md#-installation-guide>`__
+or start a GitHub
+`discussion <https://github.com/openvinotoolkit/openvino_notebooks/discussions>`__.
 
 
 Additional Resources