[I] feat(models): allow configurable context targets for large-context models [maka]

["lhpqaq (via GitHub)" <gi...@apache.org>]

lhpqaq opened a new issue, #4870:
URL: https://github.com/apache/maka/issues/4870

   ### Problem
   
   Some models offer a large context window, such as 1M tokens, but I do not always need that much conversation history for a task. I would like to use a smaller working context, such as 256K or 512K, to reduce the input tokens carried into later requests.
   
   There is no convenient way to choose this from the conversation controls for a model whose maximum context is already known. Changing the thinking level does not control how much history is retained.
   
   ### Desired outcome
   
   - Choose a smaller context target without changing the model's advertised maximum.
   - Have Maka compact history earlier when the target is reached.
   - Save the setting per connection and model, accessible from both Desktop and CLI.
   - Restore automatic behavior when a custom target is no longer needed.
   - Keep the conversation controls compact.
   
   The goal is to reduce unnecessary token usage, not to guarantee a fixed cost reduction or impose a hard per-request token limit.
   
   ### Alternatives or workarounds
   
   Manual compaction or starting a new task can keep history shorter, but both require intervention and may interrupt the workflow. Editing internal connection configuration is less convenient than a visible control.
   
   AI assistance: OpenAI Codex helped prepare this issue.


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Re: [I] feat(models): allow configurable context targets for large-context models [maka]

["lhpqaq (via GitHub)" <gi...@apache.org>]

lhpqaq commented on issue #4870:
URL: https://github.com/apache/maka/issues/4870#issuecomment-5554103504

   take


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