Support auto-upgrading model selection when context fills (instead of compaction)

### Describe the feature or problem you'd like to solve

Some of the models I have access to support multiple context window sizes. I want to start with the smaller context window, then upgrade to the next larger context window size for the same model type instead of compacting when the context fills up.

### Proposed solution

Add a configuration setting with similar placement to "continueOnAutoMode" - instead of triggering on rate limiting and switching to auto model, trigger on full context (which would normally compact) and switch to larger context version of same model if available, only compacting if already on the largest context available for that model.

### Example prompts or workflows

This would allow starting with a smaller context and seamlessly upgrading within the session if needed. Currently if I start with the smaller context and hit the limit, I have to manually switch then additionally prompt to attempt recovery of the context that was lost by compaction.

### Additional context

Under the premium requests model, smaller context was typically half the multiplier of larger context - I'm assuming that AI credits work similarly. If not, and larger context model scales credit usage based on the actual context used instead of the max, then this feature is unnecessary as I can just start with the larger context every time.

首先阅读现有的 continueOnAutoMode 配置，以及当前会导致压缩的 context-full 路径。跟踪同一模型类型的更大上下文变体是如何表示的；完成标准是：当上下文耗尽时，某个设置可以选择下一个可用大小，并且仅在最大大小时进行压缩。

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