Add Multi-Environment Support for Nano-vLLM

[BaoZhuhan]

Summary

This PR adds comprehensive multi-environment support to Nano-vLLM, enabling easier deployment and reproducibility across different platforms. The changes include pip, conda, and Docker installation methods while maintaining the existing core functionality.

Changes Made

• requirements.txt: Added pip requirements file with all necessary dependencies for easy pip installation
• environment.yml: Created conda environment configuration with Python 3.12, PyTorch, CUDA support, and optimized channels (including Tsinghua mirrors for faster downloads)
• Dockerfile: Provided containerized deployment with NVIDIA GPU support, volume mapping, and example execution
• README.md: Updated installation section with detailed instructions for all three deployment methods (pip, conda, Docker)

Testing

• Verified Python version compatibility (requires Python >=3.10, <3.13)
• Environment files generated based on pyproject.toml dependencies
• Documentation updated with clear installation steps

Motivation

Enhances project accessibility by providing multiple deployment options, making it easier for users to set up and reproduce the Nano-vLLM environment locally or in production.