Fix: Output text is always truncated in some models

[HyperdriveHustle]

When I use Yi-34B-Chat for inference based on vllm==0.3.2, the text in CompletionOutput is always truncated (see the example below). This PR ensures that when stop_token_ids is configured in the sampling_params, it first checks for the existence of the stop_str before truncating the sequence.

Truncated CompletionOutput example:

CompletionOutput(index=17, text='\n你好！我是一个人工智能助手，由零一万物训练，专门设计用来回答问题和提供信息。你可以问我任何问题，我会尽力帮助你。有什', token_ids=[144, 25902, 103, 59646, 4748, 13992, 44307, 101, 59903, 60738, 59625, 24018, 6994, 101, 11515, 2958, 13231, 8992, 53032, 2479, 2530, 102, 14760, 22126, 3944, 1650, 101, 14107, 32151, 4002, 59725, 102, 9300, 29287, 21645, 19610, 104, 7], cumulative_logprob=-11.930044378333832, logprobs=None, finish_reason=stop)

[HyperdriveHustle]

fix #3026 and #3034

[learninmou]

This PR solved my accuracy issue on my eval task, thanks .

[WoosukKwon]

LGTM. Thanks for submitting the PR!

[currenttime]

output = llm.generate(text, sampling_params=SamplingParams(max_tokens=512))