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[release branch] [DOC] Links, typos and public package (#2506)
Fix links /nightly/ -> /2024/ Fix some of the links from /main/ to /releases/2024/2 Fix typos CVS-144337 Public OpenVINO link
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Makefile

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@@ -154,11 +154,11 @@ ifeq ($(findstring ubuntu,$(BASE_OS)),ubuntu)
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ifeq ($(BASE_OS_TAG),20.04)
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OS=ubuntu20
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INSTALL_DRIVER_VERSION ?= "22.43.24595"
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DLDT_PACKAGE_URL ?= http://s3.toolbox.iotg.sclab.intel.com/ov-packages/l_openvino_toolkit_ubuntu20_2024.2.0.15519.5c0f38f83f6_x86_64.tgz
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DLDT_PACKAGE_URL ?= https://storage.openvinotoolkit.org/repositories/openvino/packages/2024.2/linux/l_openvino_toolkit_ubuntu20_2024.2.0.15519.5c0f38f83f6_x86_64.tgz
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else ifeq ($(BASE_OS_TAG),22.04)
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OS=ubuntu22
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INSTALL_DRIVER_VERSION ?= "23.22.26516"
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DLDT_PACKAGE_URL ?= http://s3.toolbox.iotg.sclab.intel.com/ov-packages/l_openvino_toolkit_ubuntu22_2024.2.0.15519.5c0f38f83f6_x86_64.tgz
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DLDT_PACKAGE_URL ?= https://storage.openvinotoolkit.org/repositories/openvino/packages/2024.2/linux/l_openvino_toolkit_ubuntu22_2024.2.0.15519.5c0f38f83f6_x86_64.tgz
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endif
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endif
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ifeq ($(BASE_OS),redhat)
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endif
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DIST_OS=redhat
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INSTALL_DRIVER_VERSION ?= "23.22.26516"
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DLDT_PACKAGE_URL ?= http://s3.toolbox.iotg.sclab.intel.com/ov-packages/l_openvino_toolkit_rhel8_2024.2.0.15519.5c0f38f83f6_x86_64.tgz
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DLDT_PACKAGE_URL ?= https://storage.openvinotoolkit.org/repositories/openvino/packages/2024.2/linux/l_openvino_toolkit_rhel8_2024.2.0.15519.5c0f38f83f6_x86_64.tgz
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endif
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OVMS_CPP_DOCKER_IMAGE ?= openvino/model_server

README.md

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@@ -15,22 +15,22 @@ OpenVINO™ Model Server (OVMS) is a high-performance system for serving mod
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![OVMS picture](docs/ovms_high_level.png)
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The models used by the server need to be stored locally or hosted remotely by object storage services. For more details, refer to [Preparing Model Repository](https://docs.openvino.ai/nightly/ovms_docs_models_repository.html) documentation. Model server works inside [Docker containers](https://docs.openvino.ai/nightly/ovms_docs_deploying_server.html#deploying-model-server-in-docker-container), on [Bare Metal](https://docs.openvino.ai/nightly/ovms_docs_deploying_server.html#deploying-model-server-on-baremetal-without-container), and in [Kubernetes environment](https://docs.openvino.ai/nightly/ovms_docs_deploying_server.html#deploying-model-server-in-kubernetes).
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Start using OpenVINO Model Server with a fast-forward serving example from the [Quickstart guide](https://docs.openvino.ai/nightly/ovms_docs_quick_start_guide.html) or explore [Model Server features](https://docs.openvino.ai/nightly/ovms_docs_features.html).
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The models used by the server need to be stored locally or hosted remotely by object storage services. For more details, refer to [Preparing Model Repository](https://docs.openvino.ai/2024/ovms_docs_models_repository.html) documentation. Model server works inside [Docker containers](https://docs.openvino.ai/2024/ovms_docs_deploying_server.html#deploying-model-server-in-docker-container), on [Bare Metal](https://docs.openvino.ai/2024/ovms_docs_deploying_server.html#deploying-model-server-on-baremetal-without-container), and in [Kubernetes environment](https://docs.openvino.ai/2024/ovms_docs_deploying_server.html#deploying-model-server-in-kubernetes).
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Start using OpenVINO Model Server with a fast-forward serving example from the [Quickstart guide](https://docs.openvino.ai/2024/ovms_docs_quick_start_guide.html) or explore [Model Server features](https://docs.openvino.ai/2024/ovms_docs_features.html).
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Read [release notes](https://github.com/openvinotoolkit/model_server/releases) to find out what’s new.
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### Key features:
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- **[NEW]** [Efficient Text Generation via OpenAI API - preview](https://docs.openvino.ai/nightly/ovms_docs_llm_reference.html)
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- [Python code execution](https://docs.openvino.ai/nightly/ovms_docs_python_support_reference.html)
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- [gRPC streaming](https://docs.openvino.ai/nightly/ovms_docs_streaming_endpoints.html)
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- [MediaPipe graphs serving](https://docs.openvino.ai/nightly/ovms_docs_mediapipe.html)
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- Model management - including [model versioning](https://docs.openvino.ai/nightly/ovms_docs_model_version_policy.html) and [model updates in runtime](https://docs.openvino.ai/nightly/ovms_docs_online_config_changes.html)
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- [Dynamic model inputs](https://docs.openvino.ai/nightly/ovms_docs_shape_batch_layout.html)
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- [Directed Acyclic Graph Scheduler](https://docs.openvino.ai/nightly/ovms_docs_dag.html) along with [custom nodes in DAG pipelines](https://docs.openvino.ai/nightly/ovms_docs_custom_node_development.html)
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- [Metrics](https://docs.openvino.ai/nightly/ovms_docs_metrics.html) - metrics compatible with Prometheus standard
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- **[NEW]** [Efficient Text Generation via OpenAI API - preview](https://docs.openvino.ai/2024/ovms_docs_llm_reference.html)
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- [Python code execution](https://docs.openvino.ai/2024/ovms_docs_python_support_reference.html)
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- [gRPC streaming](https://docs.openvino.ai/2024/ovms_docs_streaming_endpoints.html)
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- [MediaPipe graphs serving](https://docs.openvino.ai/2024/ovms_docs_mediapipe.html)
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- Model management - including [model versioning](https://docs.openvino.ai/2024/ovms_docs_model_version_policy.html) and [model updates in runtime](https://docs.openvino.ai/2024/ovms_docs_online_config_changes.html)
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- [Dynamic model inputs](https://docs.openvino.ai/2024/ovms_docs_shape_batch_layout.html)
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- [Directed Acyclic Graph Scheduler](https://docs.openvino.ai/2024/ovms_docs_dag.html) along with [custom nodes in DAG pipelines](https://docs.openvino.ai/2024/ovms_docs_custom_node_development.html)
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- [Metrics](https://docs.openvino.ai/2024/ovms_docs_metrics.html) - metrics compatible with Prometheus standard
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- Support for multiple frameworks, such as TensorFlow, PaddlePaddle and ONNX
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- Support for [AI accelerators](https://docs.openvino.ai/nightly/about-openvino/compatibility-and-support/supported-devices.html)
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- Support for [AI accelerators](https://docs.openvino.ai/2024/about-openvino/compatibility-and-support/supported-devices.html)
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**Note:** OVMS has been tested on RedHat, and Ubuntu. The latest publicly released docker images are based on Ubuntu and UBI.
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They are stored in:
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## Run OpenVINO Model Server
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A demonstration on how to use OpenVINO Model Server can be found in [our quick-start guide](https://docs.openvino.ai/nightly/ovms_docs_quick_start_guide.html).
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A demonstration on how to use OpenVINO Model Server can be found in [our quick-start guide](https://docs.openvino.ai/2024/ovms_docs_quick_start_guide.html).
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For more information on using Model Server in various scenarios you can check the following guides:
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* [Model repository configuration](https://docs.openvino.ai/nightly/ovms_docs_models_repository.html)
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* [Model repository configuration](https://docs.openvino.ai/2024/ovms_docs_models_repository.html)
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* [Deployment options](https://docs.openvino.ai/nightly/ovms_docs_deploying_server.html)
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* [Deployment options](https://docs.openvino.ai/2024/ovms_docs_deploying_server.html)
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* [Performance tuning](https://docs.openvino.ai/nightly/ovms_docs_performance_tuning.html)
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* [Performance tuning](https://docs.openvino.ai/2024/ovms_docs_performance_tuning.html)
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* [Directed Acyclic Graph Scheduler](https://docs.openvino.ai/nightly/ovms_docs_dag.html)
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* [Directed Acyclic Graph Scheduler](https://docs.openvino.ai/2024/ovms_docs_dag.html)
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* [Custom nodes development](https://docs.openvino.ai/nightly/ovms_docs_custom_node_development.html)
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* [Custom nodes development](https://docs.openvino.ai/2024/ovms_docs_custom_node_development.html)
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* [Serving stateful models](https://docs.openvino.ai/nightly/ovms_docs_stateful_models.html)
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* [Serving stateful models](https://docs.openvino.ai/2024/ovms_docs_stateful_models.html)
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* [Deploy using a Kubernetes Helm Chart](https://github.com/openvinotoolkit/operator/tree/main/helm-charts/ovms)
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* [Deployment using Kubernetes Operator](https://operatorhub.io/operator/ovms-operator)
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* [Using binary input data](https://docs.openvino.ai/nightly/ovms_docs_binary_input.html)
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* [Using binary input data](https://docs.openvino.ai/2024/ovms_docs_binary_input.html)
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* [RESTful API](https://restfulapi.net/)
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* [Benchmarking results](https://docs.openvino.ai/nightly/openvino_docs_performance_benchmarks.html)
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* [Benchmarking results](https://docs.openvino.ai/2024/openvino_docs_performance_benchmarks.html)
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* [Speed and Scale AI Inference Operations Across Multiple Architectures](https://techdecoded.intel.io/essentials/speed-and-scale-ai-inference-operations-across-multiple-architectures/?elq_cid=3646480_ts1607680426276&erpm_id=6470692_ts1607680426276) - webinar recording
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client/go/kserve-api/Dockerfile

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# Compile API
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RUN wget https://raw.githubusercontent.com/openvinotoolkit/model_server/main/src/kfserving_api/grpc_predict_v2.proto
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RUN wget https://raw.githubusercontent.com/openvinotoolkit/model_server/releases/2024/2/src/kfserving_api/grpc_predict_v2.proto
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RUN echo 'option go_package = "./grpc-client";' >> grpc_predict_v2.proto
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RUN protoc --go_out="./" --go-grpc_out="./" ./grpc_predict_v2.proto
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client/java/kserve-api/pom.xml

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</goals>
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<configuration>
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<url>
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https://raw.githubusercontent.com/openvinotoolkit/model_server/main/src/kfserving_api/grpc_predict_v2.proto</url>
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https://raw.githubusercontent.com/openvinotoolkit/model_server/releases/2024/2/src/kfserving_api/grpc_predict_v2.proto</url>
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<outputFileName>grpc_predict_v2.proto</outputFileName>
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<outputDirectory>src/main/proto</outputDirectory>
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</configuration>

client/python/ovmsclient/lib/README.md

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As OpenVINO Model Server API is compatible with TensorFlow Serving, it's possible to use `ovmsclient` with TensorFlow Serving instances on: Predict, GetModelMetadata and GetModelStatus endpoints.
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See [API documentation](https://github.com/openvinotoolkit/model_server/blob/main/client/python/ovmsclient/lib/docs/README.md) for details on what the library provides.
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See [API documentation](https://github.com/openvinotoolkit/model_server/blob/releases/2024/2/client/python/ovmsclient/lib/docs/README.md) for details on what the library provides.
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```bash
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For more details on `ovmsclient` see [API reference](https://github.com/openvinotoolkit/model_server/blob/main/client/python/ovmsclient/lib/docs/README.md)
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For more details on `ovmsclient` see [API reference](https://github.com/openvinotoolkit/model_server/blob/releases/2024/2/client/python/ovmsclient/lib/docs/README.md)

client/python/ovmsclient/lib/docs/pypi_overview.md

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The `ovmsclient` can replace `tensorflow-serving-api` package with reduced footprint and simplified interface.
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See [API reference](https://github.com/openvinotoolkit/model_server/blob/releases/2024/2/client/python/ovmsclient/lib/docs/README.md) for usage details.
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Learn more on `ovmsclient` [documentation site](https://github.com/openvinotoolkit/model_server/tree/releases/2024/2/client/python/ovmsclient/lib).

client/python/ovmsclient/lib/ovmsclient/custom/management_client.py

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Exceptions for different serving responses...
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Exceptions for different serving responses...
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