Python Bootstrap

Skill: Python Package Bootstrap

Install packages only when they are actually needed for a step. Do not pre-install everything upfront.

Path A — No source build (core-opspec, transformation, frontend, npu)

Use this path when the agent does not compile OpenVINO from source. The openvino release wheel provides the runtime needed for tests and conversion checks.

pip install openvino optimum-intel torch \
    --extra-index-url https://download.pytorch.org/whl/cpu

For frontend agents that also need ONNX or TensorFlow:

pip install onnx onnxruntime
pip install tensorflow  # only if testing TF frontend

Path B — Source build (cpu, gpu)

Use this path when the agent builds OpenVINO from source.

Do NOT pip install openvino when a source build is present in the same environment. Installing the release wheel alongside a dev build creates two openvino packages that shadow each other, producing confusing import errors and incorrect test results.

Install only the packages that are not produced by the OV build:

pip install torch \
    --extra-index-url https://download.pytorch.org/whl/cpu
pip install optimum-intel pytest
# Do NOT add 'openvino' here — use the build output instead

After building OpenVINO, add the build's Python bindings to the path:

# Point Python at the locally built openvino package
export PYTHONPATH="<build_dir>/src/bindings/python:$PYTHONPATH"
# or install the wheel produced by the build
pip install <build_dir>/wheels/openvino-*.whl

General rules

• Install packages on demand per step, not all at once.
• If a package install fails, note it in agent-results/<agent>/session.md and continue — do not abort the entire pipeline over a missing optional dep.
• Never install from untrusted or unofficial indexes beyond the PyTorch CPU wheel server listed above.