gemini-code-assist[bot] commented on PR #36451:
URL: https://github.com/apache/beam/pull/36451#issuecomment-3384189889
## Summary of Changes
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pull request and will post my feedback shortly. In the meantime, here's a
summary to help you and other reviewers quickly get up to speed!
This pull request by Amar3tto addresses a vLLM Gemma issue (#30644) and
introduces a `vllm` extra to the Apache Beam Python SDK. Key changes include
defining the `vllm` extra and its dependencies in `setup.py`, updating the
`vllm.dockerfile` to leverage this extra, adding `dill` to test requirements,
and modifying build scripts (`common.gradle`, `run_generate_requirements.sh`)
to properly handle `vllm` dependencies, including a conditional `torch`
installation to prevent known issues. The PR also integrates changes from
#36420.
### Highlights
* **Intent**: This pull request aims to fix an issue related to vLLM Gemma
(addressing #30644) and introduce a new `vllm` extra for the Apache Beam Python
SDK. It also incorporates changes from a related pull request (#36420).
* **Changes Overview**: The changes primarily focus on integrating vLLM
support more robustly into the Beam Python SDK. This includes defining a new
`vllm` extra in `setup.py` with its specific dependencies (`openai`, `vllm`,
`triton`). The `vllm.dockerfile` for test resources is updated to use this new
extra, simplifying dependency installation. Additionally, `dill` is added to
`vllm_tests_requirements.txt`, and the `common.gradle` script is modified to
generate `gpu_image_requirements.txt` that includes the `vllm` extra. A
conditional `torch` installation is added to `run_generate_requirements.sh` to
mitigate a known issue when `vllm` extra is used.
* **Reviewer Activity**: No specific reviewer activity has been noted yet
for this pull request.
<details>
<summary><b>Ignored Files</b></summary>
* **Ignored by pattern:** `.github/workflows/**` (1)
*
.github/workflows/load-tests-pipeline-options/beam_Inference_Python_Benchmarks_Dataflow_VLLM_Gemma_Batch.txt
</details>
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