By name: python-bootstrap description: Install Python dependencies before running verification or test steps. Choose the correct path depending on whether the agent builds OpenVINO from source or not.
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 openvinowhen a source build is present in the same environment. Installing the release wheel alongside a dev build creates twoopenvinopackages 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.mdand 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.