feat: upgrade memory flush system

- Use LLM to summarize discarded context into concise daily memory entries
- Batch trim to half when exceeding max_turns/max_tokens, reducing flush frequency
- Run summarization asynchronously in background thread, no blocking on replies
- Add daily scheduled flush (23:55) as fallback for low-activity days
- Sync trimmed messages back to agent to keep context state consistent

agent/memory/config.py

@@ -48,9 +48,6 @@ class MemoryConfig:
     enable_auto_sync: bool = True
     sync_on_search: bool = True
     
-    # Memory flush config (独立于模型 context window)
-    flush_token_threshold: int = 50000  # 50K tokens 触发 flush
-    flush_turn_threshold: int = 20  # 20 轮对话触发 flush (用户+AI各一条为一轮)
     
     def get_workspace(self) -> Path:
         """Get workspace root directory"""