[Bugfix] llm.chat bos token duplicate

[nike00811]

When using llm.chat, the conversation is first converted into a string and then passed to self.generate for completion generation. This causes apply_chat_template to prepend a bos token at the beginning of prompt_data. Subsequently, converting prompt_data into prompt_token_ids adds another bos token, resulting in two consecutive bos tokens at the start of the final prompt.
I changed the default value of tokenize and added a new parameter to llm.chat, allowing users to decide whether to enable tokenization.

>>> from vllm import LLM
>>> llm = LLM(model="meta-llama/Llama-3.1-8B-Instruct")
>>> tokenizer = llm.get_tokenizer()
>>> conversation = [
>>>     {"role": "system", "content": "You are a helpful assistant"},
>>>     {"role": "user", "content": "Hello"},
>>>     {"role": "assistant", "content": "Hello! How can I assist you today?"},
>>>     {"role": "user", "content": "Write an essay about the importance of higher education."},
>>> ]
>>> outputs = llm.chat(conversation)

Before fix: (tokenize = False)

>>> print(output.prompt_token_ids[:10])
>>> print('{!r}'.format(tokenizer.decode(output.prompt_token_ids[:10])))
[128000, 128000, 128006, 9125, 128007, 271, 38766, 1303, 33025, 2696]
'<|begin_of_text|><|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nCutting Knowledge Date'

After fix: (tokenize = True)

>>> print(output.prompt_token_ids[:10])
>>> print('{!r}'.format(tokenizer.decode(output.prompt_token_ids[:10])))
[128000, 128006, 9125, 128007, 271, 38766, 1303, 33025, 2696, 25]
'<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nCutting Knowledge Date:'

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[DarkLight1337]

This is a somewhat complicated issue, see #9519 and #11432 for discussion. Can you add tests to avoid future regressions?

[njhill]

Thanks @nike00811, this will be addressed by #16081.