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1"""Pruning types and enums for context pruning.""" 

2 

3from __future__ import annotations 

4 

5from dataclasses import dataclass, field 

6from enum import StrEnum 

7 

8 

9class PruningStrategy(StrEnum): 

10 """Enum of pruning scoring strategies. 

11 

12 Attributes: 

13 RECENCY: Keep most recent entries by timestamp. 

14 RELEVANCE: Keep highest-relevance entries (placeholder for future embedding-based scoring). 

15 HYBRID: Weighted blend of recency and relevance (content length as proxy). 

16 """ 

17 

18 RECENCY = "recency" 

19 RELEVANCE = "relevance" 

20 HYBRID = "hybrid" 

21 

22 

23@dataclass(frozen=True) 

24class PruningResult: 

25 """Result of a context pruning operation. 

26 

27 Attributes: 

28 kept: List of MemoryEntry items kept (score-ordered, highest first). 

29 pruned_count: Number of entries that were removed. 

30 original_count: Number of entries that came in. 

31 token_budget: The token budget that was applied. 

32 strategy: The pruning strategy used. 

33 metadata: Optional metadata dictionary with additional pruning details. 

34 """ 

35 

36 kept: list 

37 pruned_count: int 

38 original_count: int 

39 token_budget: int 

40 strategy: PruningStrategy 

41 metadata: dict = field(default_factory=dict)