[DOCS] separate OV integrations section

docs/articles_en/about-openvino.rst

@@ -29,36 +29,36 @@ deep learning models. Yet its feature set is much wider, offering various optimi
 
 To learn about the main properties of OpenVINO, see the :doc:`Key Features <about-openvino/key-features>`.
 
+
 Architecture
 ##############################################################
 
-To learn more about how OpenVINO works, read the Developer documentation on its `architecture <https://github.com/openvinotoolkit/openvino/blob/master/src/docs/architecture.md>`__ and `core components <https://github.com/openvinotoolkit/openvino/blob/master/src/README.md>`__.
-
-OpenVINO Ecosystem
-##############################################################
+To learn more about how OpenVINO works, read the Developer documentation on its
+`architecture <https://github.com/openvinotoolkit/openvino/blob/master/src/docs/architecture.md>`__
+and
+`core components <https://github.com/openvinotoolkit/openvino/blob/master/src/README.md>`__.
 
-Along with the primary components of model optimization and runtime, the toolkit also includes:
 
-* `Neural Network Compression Framework (NNCF) <https://github.com/openvinotoolkit/nncf>`__ - a tool for enhanced OpenVINO™ inference to get performance boost with minimal accuracy drop.
-* :doc:`Openvino Notebooks <learn-openvino/interactive-tutorials-python>`- Jupyter Python notebook, which demonstrate key features of the toolkit.
-* `OpenVINO Model Server <https://github.com/openvinotoolkit/model_server>`__ - a server that enables scalability via a serving microservice.
-* :doc:`OpenVINO Training Extensions  <documentation/openvino-ecosystem/openvino-training-extensions>` – a convenient environment to train Deep Learning models and convert them using the OpenVINO™ toolkit for optimized inference.
-* :doc:`Dataset Management Framework (Datumaro) <documentation/openvino-ecosystem/datumaro>` - a tool to build, transform, and analyze datasets.
 
 Community
 ##############################################################
 
-OpenVINO community plays a vital role in the growth and development of the open-sourced toolkit. Users can contribute to OpenVINO and get support using the following channels:
+OpenVINO community plays a vital role in the growth and development of the open-sourced toolkit.
+Users can contribute to OpenVINO and get support using the following channels:
 
 * `OpenVINO GitHub issues, discussions and pull requests <https://github.com/openvinotoolkit/openvino>`__
 * `OpenVINO Blog <https://blog.openvino.ai/>`__
 * `Community Forum <https://community.intel.com/t5/Intel-Distribution-of-OpenVINO/bd-p/distribution-openvino-toolkit>`__
 * `OpenVINO video <https://www.youtube.com/watch?v=_Jnjt21ZDS8&list=PLg-UKERBljNxdIQir1wrirZJ50yTp4eHv>`__
 * `Support Information <https://www.intel.com/content/www/us/en/support/products/96066/software/development-software/openvino-toolkit.html>`__
 
+
 Case Studies
 ##############################################################
 
-OpenVINO has been employed in various case studies across a wide range of industries and applications, including healthcare, retail, safety and security, transportation, and more. Read about how OpenVINO enhances efficiency, accuracy, and safety in different sectors on the `success stories page <https://www.intel.com/content/www/us/en/internet-of-things/ai-in-production/success-stories.html>`__.
+OpenVINO has been employed in various case studies across a wide range of industries and
+applications, including healthcare, retail, safety and security, transportation, and more.
+Read about how OpenVINO enhances efficiency, accuracy, and safety in different sectors on the
+`success stories page <https://www.intel.com/content/www/us/en/internet-of-things/ai-in-production/success-stories.html>`__.
 
 

docs/articles_en/about-openvino/compatibility-and-support/supported-devices.rst

@@ -46,7 +46,6 @@ Feature Support and API Coverage
  :doc:`Multi-stream execution <../../openvino-workflow/running-inference/optimize-inference/optimizing-throughput>`                       Yes     Yes        No
  :doc:`Model caching <../../openvino-workflow/running-inference/optimize-inference/optimizing-latency/model-caching-overview>`            Yes     Partial    Yes
  :doc:`Dynamic shapes <../../openvino-workflow/running-inference/dynamic-shapes>`                                                         Yes     Partial    No
- :doc:`Import/Export <../../documentation/openvino-ecosystem>`                                                                            Yes     Yes        Yes
  :doc:`Preprocessing acceleration <../../openvino-workflow/running-inference/optimize-inference/optimize-preprocessing>`                  Yes     Yes        No
  :doc:`Stateful models <../../openvino-workflow/running-inference/stateful-models>`                                                       Yes     Yes        Yes
  :doc:`Extensibility <../../documentation/openvino-extensibility>`                                                                        Yes     Yes        No

docs/articles_en/documentation.rst

@@ -14,22 +14,29 @@ Documentation
    API Reference <api/api_reference>
    OpenVINO IR format and Operation Sets <documentation/openvino-ir-format>
    Legacy Features <documentation/legacy-features>
-   Tool Ecosystem <documentation/openvino-ecosystem>
    OpenVINO Extensibility <documentation/openvino-extensibility>
-   OpenVINO™ Security <documentation/openvino-security>
+   OpenVINO Security <documentation/openvino-security>
 
 
-This section provides reference documents that guide you through the OpenVINO toolkit workflow, from preparing models, optimizing them, to deploying them in your own deep learning applications.
+This section provides reference documents for the OpenVINO toolkit, such as API and Operation
+listing.
 
 | :doc:`API Reference doc path <api/api_reference>`
-| A collection of reference articles for OpenVINO C++, C, and Python APIs.
+| A collection of reference articles for OpenVINO C++, C, Node.js, and Python APIs, as well as
+  the Python API for OpenVINO GenAI.
 
-| :doc:`OpenVINO Ecosystem <documentation/openvino-ecosystem>`
-| Apart from the core components, OpenVINO offers tools, plugins, and expansions revolving around it, even if not constituting necessary parts of its workflow. This section gives you an overview of what makes up the OpenVINO toolkit.
+| :doc:`OpenVINO IR format <documentation/openvino-ir-format>`
+| A section describing the OpenVINO IR model format and its opsets.
+
+| :doc:`Legacy Features <documentation/legacy-features>`
+| The information on all OpenVINO components that have recently been deprecated or discontinued.
 
 | :doc:`OpenVINO Extensibility Mechanism <documentation/openvino-extensibility>`
-| The Intel® Distribution of OpenVINO™ toolkit supports neural network models trained with various frameworks, including TensorFlow, PyTorch, ONNX, TensorFlow Lite, and PaddlePaddle. Learn how to extend OpenVINO functionality with custom settings.
+| The Intel® Distribution of OpenVINO™ toolkit supports neural network models trained with
+  various frameworks, including TensorFlow, PyTorch, ONNX, TensorFlow Lite, and PaddlePaddle.
+  Learn how to extend OpenVINO functionality with custom settings.
 
 | :doc:`OpenVINO™ Security <documentation/openvino-security>`
-| Learn how to use OpenVINO securely and protect your data to meet specific security and privacy requirements.
+| Learn how to use OpenVINO securely and protect your data to meet specific security and privacy
+  requirements.
 

docs/articles_en/documentation/openvino-security.rst

@@ -8,8 +8,8 @@ with encryption or other security tools.
 Actual security and privacy requirements depend on your unique deployment scenario.
 This section provides general guidance on using OpenVINO tools and libraries securely.
 The main security measure for OpenVINO is its
-:doc:`Security Add-on <openvino-ecosystem/openvino-security-add-on>`. You can find its description
-in the Ecosystem section.
+:doc:`Security Add-on <../openvino-ecosystem/openvino-project/openvino-security-add-on>`.
+You can find its description in the Ecosystem section.
 
 .. _encrypted-models:
 

docs/articles_en/openvino-ecosystem.rst

@@ -0,0 +1,31 @@
+OpenVINO Ecosystem
+==================
+
+.. meta::
+   :description: Explore the OpenVINO™ ecosystem of tools and resources for developing deep
+                 learning solutions.
+
+.. toctree::
+   :maxdepth: 1
+   :hidden:
+
+   OpenVINO Integrations <openvino-ecosystem/openvino-integrations>
+   The OpenVINO Project <openvino-ecosystem/openvino-project>
+   OpenVINO Adoptions <openvino-ecosystem/openvino-adoptions>
+
+
+OpenVINO™, as a toolkit should, involves multiple components and integrations that may be used
+in various areas of your Deep Learning pipelines. This section will give you an overview of a
+whole ecosystem of resources either developed under the OpenVINO umbrella, integrating it with
+external solutions, or utilizing its potential.
+
+| :doc:`OpenVINO Integrations <./openvino-ecosystem/openvino-integrations>`
+|     See what other tools OpenVINO is easily integrated with and how you can benefit from its
+      performance, without rewriting your software.
+
+| :doc:`The OpenVINO project <./openvino-ecosystem/openvino-project>`
+|     Check out the most noteworthy components of the OpenVINO project.
+
+| :doc:`OpenVINO adoptions <./openvino-ecosystem/openvino-adoptions>`
+|     Here, you will find information about a selection of software projects utilizing OpenVINO.
+

docs/articles_en/openvino-ecosystem/openvino-adoptions.rst

@@ -0,0 +1,63 @@
+OpenVINO Adoptions
+==========================
+
+OpenVINO has been adopted by multiple AI projects in various areas. For an extensive list of
+community-based projects involving OpenVINO, see the
+`Awesome OpenVINO repository <https://github.com/openvinotoolkit/awesome-openvino>`__.
+
+Here is a small selection of adoptions, including proprietary and commercial tools:
+
+
+
+
+| **DaVinCI Resolve**
+| :bdg-link-info:`Official Website <https://www.blackmagicdesign.com/products/davinciresolve>`
+
+DaVinci resolve is a professional video editing suite by Blackmagicdesign. It uses OpenVINO to
+run some of its industry-leading AI features.
+|hr|
+
+| **OpenVINO AI Plugins for GIMP**
+| :bdg-link-dark:`Official Repository <https://github.com/intel/openvino-ai-plugins-gimp>`
+
+Gimp is an image editor that has promoted open source values for over two decades. Now, you can
+use generative AI directly in the application, thanks to the OpenVINO plugin, just like in the
+leading graphics suites.
+|hr|
+
+| **OpenVINO AI Plugins for Audacity**
+| :bdg-link-info:`Official Website <https://www.audacityteam.org/download/openvino/>`
+  :bdg-link-dark:`Official Repository <https://github.com/intel/openvino-plugins-ai-audacity>`
+
+Audacity is a hugely popular audio editing and recording application. Now, it offers AI-based
+plugins running on OpenVINO, providing new effects, generators, and analyzers.
+|hr|
+
+
+| **VisionGuard**
+| :bdg-link-dark:`Official Repository <https://github.com/inbasperu/VisionGuard>`
+
+A desktop tool developed within Google Summer of Code. Its aim is to help computer users battle
+eye strain, utilizing gaze estimation.
+|hr|
+
+| **OpenVINO Code**
+| :bdg-link-dark:`Official Repository <https://github.com/openvinotoolkit/openvino_contrib/tree/master/modules/openvino_code>`
+
+A coding assistant. A community-developed extension for Visual Studio Code, aiming to help
+programmers by providing code completion and suggestions.
+|hr|
+
+| **NVIDIA GPU Plugin**
+| :bdg-link-dark:`Official Repository <https://github.com/openvinotoolkit/openvino_contrib/tree/master/modules/nvidia_plugin>`
+
+A device plugin for OpenVINO. A community-developed extension, enabling inference using
+NVIDIA GPUs.
+|hr|
+
+
+
+
+.. |hr| raw:: html
+
+   <hr style="margin-top:-12px!important;border-top:1px solid #383838;">

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

@@ -0,0 +1,182 @@
+OpenVINO™ Integrations
+==============================
+
+
+.. meta::
+   :description: Check a list of integrations between OpenVINO and other Deep Learning solutions.
+
+
+
+.. = 1 ========================================================================================
+
+**Hugging Face Optimum-Intel**
+
+|hr|
+
+.. grid:: 1 1 2 2
+   :gutter: 4
+
+   .. grid-item::
+
+      | Grab and use models leveraging OpenVINO within the Hugging Face API.
+        The repository hosts pre-optimized OpenVINO IR models, so that you can use
+        them in your projects without the need for any adjustments.
+      | Benefits:
+      | - Minimize complex coding for Generative AI.
+
+   .. grid-item::
+
+      * :doc:`Run inference with HuggingFace and Optimum Intel <../learn-openvino/llm_inference_guide/llm-inference-hf>`
+      * `A notebook example: llm-chatbot <https://github.com/openvinotoolkit/openvino_notebooks/tree/main/notebooks/254-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>`__
+
+.. dropdown:: Check example code
+   :animate: fade-in-slide-down
+   :color: secondary
+
+   .. code-block:: py
+
+      -from transformers import AutoModelForCausalLM
+      +from optimum.intel.openvino import OVModelForCausalLM
+
+      from transformers import AutoTokenizer, pipeline
+      model_id = "togethercomputer/RedPajama-INCITE-Chat-3B-v1"
+
+      -model = AutoModelForCausalLM.from_pretrained(model_id)
+      +model = OVModelForCausalLM.from_pretrained(model_id, export=True)
+
+
+.. = 2 ========================================================================================
+
+**OpenVINO Execution Provider for ONNX Runtime**
+
+|hr|
+
+.. grid:: 1 1 2 2
+   :gutter: 4
+
+   .. grid-item::
+
+      | Utilize OpenVINO as a backend with your existing ONNX Runtime code.
+      | Benefits:
+      | - Enhanced inference performance on Intel hardware with minimal code modifications.
+
+   .. grid-item::
+
+      * A notebook example: YOLOv8 object detection
+      * `ONNX User documentation <https://onnxruntime.ai/docs/execution-providers/OpenVINO-ExecutionProvider.html>`__
+      * `Build ONNX RT with OV EP <https://oliviajain.github.io/onnxruntime/docs/build/eps.html#openvino>`__
+      * `ONNX Examples <https://onnxruntime.ai/docs/execution-providers/OpenVINO-ExecutionProvider.html#openvino-execution-provider-samples-tutorials>`__
+
+
+.. dropdown:: Check example code
+   :animate: fade-in-slide-down
+   :color: secondary
+
+   .. code-block:: cpp
+
+      device = `CPU_FP32`
+      # Set OpenVINO as the Execution provider to infer this model
+      sess.set_providers([`OpenVINOExecutionProvider`], [{device_type` : device}])
+
+
+.. = 3 ========================================================================================
+
+**Torch.compile with OpenVINO**
+
+|hr|
+
+.. grid:: 1 1 2 2
+   :gutter: 4
+
+   .. grid-item::
+
+      | Use OpenVINO for Python-native applications by JIT-compiling code into optimized kernels.
+      | Benefits:
+      | - Enhanced inference performance on Intel hardware with minimal code modifications.
+
+   .. grid-item::
+
+      * :doc:`PyTorch Deployment via torch.compile <../openvino-workflow/torch-compile>`
+      * A notebook example: n.a.
+      * `torch.compiler documentation <https://pytorch.org/docs/stable/torch.compiler.html>`__
+      * `torch.compiler API reference <https://pytorch.org/docs/stable/torch.compiler_api.html>`__
+
+.. dropdown:: Check example code
+   :animate: fade-in-slide-down
+   :color: secondary
+
+   .. code-block:: python
+
+      import openvino.torch
+
+      ...
+      model = torch.compile(model, backend='openvino')
+      ...
+
+
+
+.. = 4 ========================================================================================
+
+**OpenVINO LLMs with LlamaIndex**
+
+|hr|
+
+.. grid:: 1 1 2 2
+   :gutter: 4
+
+   .. grid-item::
+
+      | Build context-augmented GenAI applications with the LlamaIndex framework and enhance
+        runtime performance with OpenVINO.
+      | Benefits:
+      | - Minimize complex coding for Generative AI.
+
+   .. grid-item::
+
+      * :doc:`LLM inference with Optimum-intel <../learn-openvino/llm_inference_guide/llm-inference-hf>`
+      * `A notebook example: llm-agent-rag <https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/llm-agent-react/llm-agent-rag-llamaindex.ipynb>`__
+      *
+      * `Inference documentation <https://docs.llamaindex.ai/en/stable/examples/llm/openvino/>`__
+      * `Rerank documentation <https://docs.llamaindex.ai/en/stable/examples/node_postprocessor/openvino_rerank/>`__
+      * `Embeddings documentation <https://docs.llamaindex.ai/en/stable/examples/embeddings/openvino/>`__
+      * `API Reference <https://docs.llamaindex.ai/en/stable/api_reference/llms/openvino/>`__
+
+.. dropdown:: Check example code
+   :animate: fade-in-slide-down
+   :color: secondary
+
+   .. code-block:: python
+
+      ov_config = {
+          "PERFORMANCE_HINT": "LATENCY",
+          "NUM_STREAMS": "1",
+          "CACHE_DIR": "",
+      }
+
+      ov_llm = OpenVINOLLM(
+          model_id_or_path="HuggingFaceH4/zephyr-7b-beta",
+          context_window=3900,
+          max_new_tokens=256,
+          model_kwargs={"ov_config": ov_config},
+          generate_kwargs={"temperature": 0.7, "top_k": 50, "top_p": 0.95},
+          messages_to_prompt=messages_to_prompt,
+          completion_to_prompt=completion_to_prompt,
+          device_map="cpu",
+      )
+
+
+
+
+
+
+
+
+
+.. ============================================================================================
+
+.. |hr| raw:: html
+
+   <hr style="margin-top:-12px!important;border-top:1px solid #383838;">