conversation_summary

You can summarize long dialogue history by compressing recent interactions into concise 3-5 sentence rolling summaries that preserve emotional context. This prevents AI context drift when dialogue histories grow unwieldy, ensuring key information is retained for memory stability.

You should compress dialogue history into rolling memory summaries when your recent history log exceeds 30 entries. Triggering summary updates at this threshold prevents context loss while ensuring summaries reflect recent interactions and user validations.

Yes, you can preserve existing session summaries during dialogue history updates. The summarization process implements safe, non-destructive updates that respect existing summaries and prevent overwriting valuable memory data already stored.

The best way to maintain emotional context in long AI conversations is generating rolling 3-5 sentence summaries that capture emotional threads alongside key information. These compressed summaries preserve the emotional trajectory of interactions for ongoing memory stability.

Dialogue history summarization integrates with memory distillation workflows by writing rolling summaries to session memory files, which then support memory distillation and user memory checks. This ensures summaries reflect recent interactions and user validations before trimming begins.

You should avoid trimming recent dialogue history before summary quality stabilizes because premature trimming risks losing context that has not yet been adequately captured. The process guides trimming only after summaries reliably preserve emotional threads and key information.