[Docs] Update README with uv recommendation and Python version requirements

[sjhddh]

Summary

Update the README.md "Getting Started" section to:

• Add Python version requirements (3.10 - 3.13) prominently
• Recommend uv as the preferred installation method
• Keep pip as an alternative for users who prefer it
• Update installation guide link to the general installation page

Motivation

• uv is significantly faster than pip for installing vLLM
• The docs already recommend uv, README should be consistent
• Python version requirements are important for new users
• Link to general installation page covers more platforms

Changes

**Requirements:** Python 3.10 - 3.13

Install vLLM with `uv` (recommended) or `pip`. For source builds...

# Recommended: using uv (https://docs.astral.sh/uv/)
uv pip install vllm --torch-backend=auto

# Alternative: using pip
pip install vllm

Test Plan

• Visual inspection of README rendering on GitHub
• Verify both installation commands work

Risk

• Low risk: documentation-only change
• Both pip and uv paths are preserved

[mergify]

Documentation preview: https://vllm--32987.org.readthedocs.build/en/32987/

[gemini-code-assist]

Code Review

This pull request updates the README.md to recommend uv for installation and to specify the required Python versions. The changes are clear and align with the project's move towards uv for a better user experience. I have one suggestion to improve the alternative pip installation instructions to prevent potential issues for new GPU users.

[gemini-code-assist]

The simple pip install vllm command that follows is likely to cause issues for GPU users, as pip may install a CPU-only version of PyTorch if a compatible GPU version isn't already installed. This can lead to runtime failures and a frustrating experience for new users.

To avoid this, I recommend adding a note to guide pip users to the detailed installation instructions, making it clear that the simple pip command has caveats for the primary use case (GPU acceleration).

Suggested change

	# Alternative: using pip
	# Alternative: using pip (see installation guide for GPU)