prune-savings-estimation完了

crates/llm-worker/src/prune.rs

@@ -14,18 +14,21 @@
 //! `min_savings` 判定や savings 推定もこの crate には置かず、上位層が
 //! usage 履歴ベースのトークン会計と組み合わせて行う。
 
-use std::ops::Range;
-
 use serde::{Deserialize, Serialize};
 
 use crate::llm_client::types::Item;
 
-/// Callback that estimates the token savings for dropping `history[range]`.
+/// Callback that estimates the token savings for projecting the
+/// `ToolResult.content` out of `history[i]` for each `i` in `indices`.
 ///
 /// Injected into [`crate::Worker`] via `set_savings_estimator` so the
 /// Worker can make `min_savings` decisions without knowing about usage
 /// measurement sources. Return `0` to signal "no data / refuse to prune".
-pub type SavingsEstimator = Box<dyn Fn(&[Item], Range<usize>) -> u64 + Send + Sync>;
+///
+/// 推定対象は「drop する範囲全体」ではなく「content を None にする差分」
+/// であることに注意。item 自体（summary 等）は残るので、この callback は
+/// 実際の projection と一致する savings を返す必要がある。
+pub type SavingsEstimator = Box<dyn Fn(&[Item], &[usize]) -> u64 + Send + Sync>;
 
 /// Configuration for the Prune algorithm.
 #[derive(Debug, Clone, Serialize, Deserialize)]

crates/llm-worker/src/worker.rs

@@ -717,9 +717,7 @@ impl<C: LlmClient, S: WorkerState> Worker<C, S> {
                 let candidates =
                     crate::prune::prunable_indices(&request_context, config.protected_turns);
                 if !candidates.is_empty() {
-                    let first = *candidates.first().unwrap();
-                    let last = *candidates.last().unwrap() + 1;
-                    let savings = estimator(&request_context, first..last);
+                    let savings = estimator(&request_context, &candidates);
                     if savings >= config.min_savings {
                         let pruned = crate::prune::project(&mut request_context, &candidates);
                         if pruned > 0 {