Use vLLM to load LLMs

[kyriediculous]

This PR upgrades the LLM pipeline to use vLLM to load and perform inference on models using optimised batching and other features that come with vLLM.

Dependencies have been upgraded to be compatible with vLLM 0.6.3, these new dependency versions are untested with other pipelines (though could benefit them as well)

• Both fp16 and 8 bit quantization is still supported, but could be further optimized by detecting GPUs on the machine and adjusting quantization methods to be used accordingly.

• Docker file has been updated to use newer pip and torch

• Docker file has been udpated to respect CUDA_PCI_BUS_ORDER , ensuring the same develop experience as go-livepeer when specifying GPU id's found in nvidia-smi

• Adds Top_P and Top_K parameters to the LLM route