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2.**`model_converter`** — Create the environment and install the development requirements:
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```bash
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uv sync --all-extras
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uv --directory model_converter sync --group tests
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```
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</details>
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### Making Changes
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1.**Write Code:** Follow the project's coding standards and write your code with clear intent. Ensure your code is well-documented and includes examples where appropriate. For code quality we use ruff, whose configuration is in [`pyproject.toml`](pyproject.toml)file.
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1.**Write Code:** Follow the project's coding standards and write your code with clear intent. Ensure your code is well-documented and includes examples where appropriate. For code quality we use ruff, whose configuration is in each subproject's `pyproject.toml` file: [`model_api/pyproject.toml`](model_api/pyproject.toml)and [`model_converter/pyproject.toml`](model_converter/pyproject.toml).
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2.**Add Tests:** If your code includes new functionality, add corresponding tests using [pytest](https://docs.pytest.org/en/7.4.x/) to maintain coverage and reliability.
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@@ -55,11 +69,12 @@ Set up your development environment to start contributing. This involves install
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```bash
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uvx pre-commit run --all-files
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uv run pytest tests/unit
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uv run python tests/accuracy/download_models.py -d data -j tests/precommit/public_scope.json -l
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uv run pytest --data=./data tests/functional
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uv run python tests/accuracy/download_models.py -d data -j tests/accuracy/public_scope.json -l
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uv run pytest --data=./data tests/accuracy/test_accuracy.py
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uv --directory model_api run pytest tests/unit
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uv --directory model_api run python tests/accuracy/download_models.py -d data -j tests/precommit/public_scope.json -l
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uv --directory model_api run pytest --data=./data tests/functional
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uv --directory model_api run python tests/accuracy/download_models.py -d data -j tests/accuracy/public_scope.json -l
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uv --directory model_api run pytest --data=./data tests/accuracy/test_accuracy.py
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uv --directory model_converter run model-converter examples/config.json --list
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```
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5.**Update the Changelog:** For significant changes, add a summary to the [CHANGELOG](CHANGELOG.md).
Copy file name to clipboardExpand all lines: README.md
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@@ -36,6 +36,16 @@ Training Extensions embed all the metadata required for inference into model fil
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`pip install openvino-model-api`
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## Repository layout
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This repository contains two independently installable Python subprojects:
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-`model_api/` — the inference library published as `openvino-model-api` with a minimal runtime dependency set.
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-`model_converter/` — conversion tooling published as `openvino-model-converter`, with conversion-time dependencies such as PyTorch, TorchVision, OpenVINO, ONNX, and NNCF.
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Each subproject owns its own `pyproject.toml` and `uv.lock`.
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Shared repository files, including this `README.md`, `LICENSE`, `CONTRIBUTING.md`, `SECURITY.md`, and CI workflows, remain at the repository root.
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