[jiapingW]

Motivation

LingParser differs from ThinkingParser only by explicitly passing enable_thinking=False. This model-specific subclass is unnecessary if the shared
parser can distinguish between leaving the tokenizer default unchanged and explicitly disabling thinking.

This PR consolidates both parsers while preserving the existing Ling rendering and loss-mask behavior.

Modifications

• Make ChatTemplate.enable_thinking optional:
  • None: leave the thinking argument unchanged.
  • False: explicitly disable thinking.
• Remove LingParser and its dispatch branch; use ThinkingParser for both Ling-3.0 templates.
• Migrate Kimi-K3 to None to preserve its previous behavior of not passing a thinking flag.
• Add tests for all three states and argument precedence, and update template registration assertions.

Related Issues

Follow-up to #870.

Accuracy Test

Benchmark & Profiling

Checklist

• [✅] Format your code according to the Code Formatting with Pre-Commit.
• [✅] Add unit tests as outlined in the Running Unit Tests.
• Update documentation / docstrings / example tutorials as needed, according to Writing Documentation.
• Provide throughput / latency benchmark results and accuracy evaluation results as needed, according to Benchmark and Profiling and Accuracy Results.
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[curnane-lab]

Could you confirm whether this change is necessary and whether the Kimi-K3-related tests still pass?

[jiapingW]

Kimi-K3 ignores enable_thinking; the parameter that actually takes effect is thinking. Therefore, changing it to None avoids explicitly passing the argument, allowing the tokenizer's default settings to be used instead.

[curnane-lab]

lgtm, avoids maintaining a model-specific parser for a single model, resulting in cleaner abstraction.