[Build] Add Benchmark dependencies to requirements/common.txt

[simon-mo]

Summary

• add pandas and datasets to common requirements for benchmark support otherwise a clean install will fail

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https://chatgpt.com/codex/tasks/task_e_68404dbc92f4832985a94abfa89e8fe9

[gemini-code-assist]

Hello @simon-mo, I'm Gemini Code Assist¹! I'm currently reviewing this 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!

Summary of Changes

Hello! Gemini here, providing a summary of this pull request authored by simon-mo. The primary goal of this PR is to prepare the project for benchmarking by adding necessary dependencies. Specifically, it adds pandas and datasets to the common requirements file, requirements/common.txt. This change is intended to ensure that the environment has the required libraries when running benchmark-related code.

Highlights

• Add Benchmark Dependencies: This pull request introduces pandas and datasets as dependencies by adding them to the requirements/common.txt file. These libraries are specified as being needed for the benchmarks module.

Changelog

• requirements/common.txt
  • Added pandas to the list of common requirements (line 51).
  • Added datasets to the list of common requirements (line 52).
  • Both dependencies are noted as being required for the benchmarks module.

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Deps are added now,
For benchmarks, they are needed,
Code can run faster.

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[gemini-code-assist]

Code Review

This pull request adds pandas and datasets as dependencies to support the benchmark module, which is a useful addition. The changes are straightforward, but there are a couple of points regarding dependency management that could be addressed to improve stability and maintainability. Specifically, considering version pinning for these new dependencies and evaluating if they should be optional dependencies rather than part of common.txt.

Summary of Findings

• Dependency Version Pinning: The newly added dependencies pandas and datasets in requirements/common.txt are not version-pinned. This could lead to instability or build issues if future versions introduce breaking changes. It's recommended to specify versions (e.g., pandas==X.Y.Z or pandas>=X.Y.Z).
• Placement of Benchmark-Specific Dependencies: pandas and datasets are noted as being for the 'benchmarks module'. Including them in common.txt makes them mandatory for all users. Consider making them optional dependencies (e.g., via extras_require in setup.py or a separate requirements-benchmark.txt) to keep the core installation lean.

Merge Readiness

The pull request aims to add necessary dependencies for benchmark support, which is valuable. However, there are a couple of concerns regarding dependency management:

1. Version Pinning: The new dependencies (pandas, datasets) should have their versions specified to ensure stability and reproducibility.
2. Optional Dependencies: Since these dependencies appear to be solely for benchmarks, they might be better suited as optional dependencies rather than being added to common.txt, which affects all users.

I recommend addressing these points before merging to maintain code quality and a lean core dependency set. As an AI reviewer, I am not authorized to approve pull requests; please ensure further review and approval from project maintainers after addressing the feedback.

[gemini-code-assist]

For consistency with other packages in this file (e.g., opentelemetry-sdk>=1.26.0, transformers >= 4.51.1) and to ensure reproducible builds and prevent unexpected breakages from upstream changes, would it be better to pin versions for pandas and datasets?

For example, you could specify the versions you tested with (e.g., pandas==X.Y.Z) or a minimum compatible version (e.g., pandas>=X.Y.Z). This helps maintain stability over time.

pandas==<version_tested_with>  # needed for benchmarks module
datasets==<version_tested_with>  # needed for benchmarks module

[simon-mo]

both are relatively stable and very widely used thus I prefer not to pin it to avoid conflicts.

[gemini-code-assist]

Given that pandas and datasets are specifically for the 'benchmarks module' (as per the comments and their usage with PlaceholderModule in vllm/benchmarks/datasets.py), should these be included in common.txt? Adding them here makes them mandatory for all installations of vLLM, even for users who don't run benchmarks.

Could these be moved to an optional dependency group (e.g., defined in setup.py under extras_require={'benchmark': ['pandas', 'datasets']} so users can install with pip install vllm[benchmark]) or a separate requirements file like requirements/benchmark.txt? This would help keep the core dependency set lighter for general users.

[simon-mo]

But they are imported in CLI on critical path rn.

[github-actions]

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[mgoin]

@simon-mo I would prefer to keep these dataset deps separate and optional as achieved in this PR by lazy importing them #19089
The breaking change on main was not intentional.