[rollout,sglang] fix: get_tool_call_parser_type for gpt-oss models in sglang rollout

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The problem is in the get_tool_call_parser_type function in sglang_rollout.py (lines 225-246). The function is checking if parser.bot_token.strip() exists as a single token in the tokenizer's vocabulary, but for the gpt-oss parser type, the bot_token is <|start|>assistant<|channel|>commentary, which is a compound token sequence rather than a single special token. For gpt-oss models,

parser.bot_token.strip() = <|start|>assistant<|channel|>commentary
This gets tokenized as [200006, 173781, 200005, 12606, 815] (5 tokens)

The check parser.bot_token.strip() in tokenizer_vocab returns False because it's looking for this entire string as a single vocabulary entry
The current logic assumes that bot_token should be a single special token that exists in the vocabulary, but for GPT-OSS models, it's actually a sequence of tokens that need to be tokenized.

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[gemini-code-assist]

Code Review

This pull request addresses a bug in get_tool_call_parser_type for gpt-oss models, where the tool call parser was not correctly identified due to its multi-token bot_token. The fix introduces a special check for gpt-oss models based on their name_or_path. While this is a pragmatic solution, my review highlights the maintainability concerns of this hardcoded approach and suggests improvements to the logging.