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[FEATURE]: implement smart pruning #4509

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opened 2026-02-16 17:44:26 -05:00 by yindo · 1 comment
yindo commented 2026-02-16 17:44:26 -05:00
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Originally created by @processtrader on GitHub (Jan 9, 2026).

Originally assigned to: @thdxr on GitHub.

Feature hasn't been suggested before.

  • I have verified this feature I'm about to request hasn't been suggested before.

Describe the enhancement you want to request

Currently prune is a basic remove after X amount of tokens have been reached, with a very basic filter of the latest operations. This is not enough when interleave thinking models are debugging complex/deep problems on their big context windows. Removing outputs/results from important steps is making them feel dumb or force them to hallucinate. By implementing a summary and smarter mechanism of that, keeping the feature of reducing unnecessary tokens, we can improve the interaction with the LLM

Originally created by @processtrader on GitHub (Jan 9, 2026). Originally assigned to: @thdxr on GitHub. ### Feature hasn't been suggested before. - [x] I have verified this feature I'm about to request hasn't been suggested before. ### Describe the enhancement you want to request Currently prune is a basic remove after X amount of tokens have been reached, with a very basic filter of the latest operations. This is not enough when interleave thinking models are debugging complex/deep problems on their big context windows. Removing outputs/results from important steps is making them feel _dumb_ or _force_ them to hallucinate. By implementing a summary and smarter mechanism of that, keeping the feature of reducing unnecessary tokens, we can improve the interaction with the LLM
yindo added the discussion label 2026-02-16 17:44:26 -05:00
yindo commented 2026-02-16 17:44:26 -05:00
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@github-actions[bot] commented on GitHub (Jan 9, 2026):

This issue might be a duplicate of or closely related to existing issues. Please check:

  • #4659: [FEATURE] Sliding window context management for long-running sessions - proposes a more sophisticated context management system with inception messages and chess-clock time-based pruning
  • #4317: Feature: generic /compact command, auto-compaction, and fork-aware conversations - discusses provider-agnostic compaction and auto-compaction support
  • #3032: Soft compaction / AI global workspace metabolism - suggests a softer approach to pruning that preserves context better by allowing the model to intelligently select what to remove
  • #4895: Excluding reasoning context to reduce token usage - asks about excluding AI reasoning content from prompts and session compaction
  • #5970: Research subagent exceeded the context window and silently failed - documents issues when context windows are exceeded
  • #5577: DeepSeek V3.2 : reasoning_content not cleared from message history on new turns - specifically addresses token waste with interleaved thinking models

These issues discuss various approaches to improving context management, pruning strategies, and handling of thinking/reasoning content in long-running sessions. Feel free to ignore if your specific use case differs from these.

@github-actions[bot] commented on GitHub (Jan 9, 2026): This issue might be a duplicate of or closely related to existing issues. Please check: - #4659: [FEATURE] Sliding window context management for long-running sessions - proposes a more sophisticated context management system with inception messages and chess-clock time-based pruning - #4317: Feature: generic /compact command, auto-compaction, and fork-aware conversations - discusses provider-agnostic compaction and auto-compaction support - #3032: Soft compaction / AI global workspace metabolism - suggests a softer approach to pruning that preserves context better by allowing the model to intelligently select what to remove - #4895: Excluding reasoning context to reduce token usage - asks about excluding AI reasoning content from prompts and session compaction - #5970: Research subagent exceeded the context window and silently failed - documents issues when context windows are exceeded - #5577: DeepSeek V3.2 : reasoning_content not cleared from message history on new turns - specifically addresses token waste with interleaved thinking models These issues discuss various approaches to improving context management, pruning strategies, and handling of thinking/reasoning content in long-running sessions. Feel free to ignore if your specific use case differs from these.
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Reference: anomalyco/opencode#4509
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