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.

先閱讀現有的 continueOnAutoMode 設定，以及目前會導向壓縮的 context-full 路徑。追蹤相同模型類型的較大上下文變體是如何表示的；完成條件是：上下文耗盡時，某個設定可以選擇下一個可用大小，並且只在最大大小時進行壓縮。

由索引模型根據 Issue 內容生成。