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Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## master #40838 +/- ##
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+ Coverage 0 79.90% +79.90%
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Files 0 493 +493
Lines 0 83479 +83479
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+ Hits 0 66703 +66703
- Misses 0 16776 +16776
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📋 Review Summary
This PR updates vllm.dockerfile to install Python 3.11 via the deadsnakes PPA and copy the Python 3.11 Beam SDK harness, aligning the container runtime with the Python 3.11 environment used by the Dataflow inference benchmark workflow (beam_Inference_Python_Benchmarks_Dataflow.yml).
🔍 General Feedback
- The changes are clean, minimal, and directly resolve the SDK version mismatch between the job submission environment and the worker container.
- The image build, symlink configuration, and SDK harness path (
gcr.io/apache-beam-testing/beam-sdk/beam_python3.11_sdk:latest) are all consistent with Python 3.11.
💡 Tip: Comment /gemini review on this pull request to trigger a new Gemini code review.
The inference benchmark workflow submits with Python 3.11, but its vLLM image still installs Python 3.10 and copies that version's SDK harness. The SDK rejects the mismatch, so later benchmarks are skipped (failure).
Use Python 3.11 and its matching Beam harness throughout the image, following the existing deadsnakes installation recipe for the Ubuntu base.
Validated a full image build from a fresh SDK source distribution at this PR head. The image runs Python 3.11.18, the SDK compatibility check accepts a Python 3.11 descriptor and rejects a Python 3.10 control, the worker pool responds to its gRPC API, and the vLLM server CLI starts successfully. Container smoke checks used no network access or model downloads.
pip checkreports the same existing PyGObject/pycairo dependency issue on the original Python 3.10 Dockerfile prefix and the updated image. GPU model inference and Dataflow were not run.