优化: aichat效率批(save无变化捷径/断路器尾窗/system缓存指纹/会话列表刷新收敛) + 新增 LLM prompt caching(cache_control开关默认关/system稳定段易变段分离治缓存命中率) + 销账

src-tauri/src/commands/ai/knowledge_inject.rs

@@ -351,6 +351,39 @@ pub(crate) async fn build_knowledge_context(
     out
 }
 
+/// 取末条 active user 消息文本 + id,构建知识库上下文段(DRY:注入 [`inject_knowledge_into_prompt`]
+/// 与 Anthropic prompt caching 易变段共用)。
+///
+/// 同一条消息取 text + id(②口径修复):单次反向扫描,避免 text 过滤 is_active 而 id 不过滤
+/// 导致两值取自不同消息。auto_inject 关 / 无命中返回空串。
+pub(crate) async fn build_knowledge_context_for_conv(
+    state: &AppState,
+    conv_id: &str,
+    config: &crate::state::KnowledgeConfig,
+) -> String {
+    let (last_user_text, user_message_id) = {
+        let __lock_t = std::time::Instant::now();
+        let session = state.ai_session.lock().await;
+        let msgs = session
+            .conv_read(conv_id)
+            .map(|c| c.messages.all_messages_clone())
+            .unwrap_or_default();
+        let found = msgs
+            .iter()
+            .rev()
+            .find(|m| matches!(m.role, MessageRole::User) && m.is_active());
+        let __hold = __lock_t.elapsed();
+        if __hold > std::time::Duration::from_millis(30) {
+            eprintln!("[LOCK-SLOW] build_knowledge_context_for_conv 持锁 {:?} (含 lock 等待)", __hold);
+        }
+        match found {
+            Some(m) => (m.content.clone(), m.id.clone()),
+            None => (String::new(), None),
+        }
+    };
+    build_knowledge_context(state, conv_id, &last_user_text, config, user_message_id.as_deref()).await
+}
+
 /// 知识注入 system prompt 的单一入口(DRY:F-09 agentic + chat 五处合一)。
 ///
 /// 把原本散落在 `try_continue_agent_loop`(agentic/mod.rs)+ `ai_chat_send` /
@@ -378,30 +411,7 @@ pub(crate) async fn inject_knowledge_into_prompt(
     system_prompt: String,
     config: &crate::state::KnowledgeConfig,
 ) -> String {
-    // 同一条消息取 text + id(②口径修复):单次反向扫描,避免 text 过滤 is_active 而 id 不过滤
-    // 导致两值取自不同消息。
-    let (last_user_text, user_message_id) = {
-        let __lock_t = std::time::Instant::now();
-        let session = state.ai_session.lock().await;
-        let msgs = session
-            .conv_read(conv_id)
-            .map(|c| c.messages.all_messages_clone())
-            .unwrap_or_default();
-        let found = msgs
-            .iter()
-            .rev()
-            .find(|m| matches!(m.role, MessageRole::User) && m.is_active());
-        let __hold = __lock_t.elapsed();
-        if __hold > std::time::Duration::from_millis(30) {
-            eprintln!("[LOCK-SLOW] build_system_prompt_with_knowledge:383 持锁 {:?} (含 lock 等待)", __hold);
-        }
-        match found {
-            Some(m) => (m.content.clone(), m.id.clone()),
-            None => (String::new(), None),
-        }
-    };
-    let knowledge_context =
-        build_knowledge_context(state, conv_id, &last_user_text, config, user_message_id.as_deref()).await;
+    let knowledge_context = build_knowledge_context_for_conv(state, conv_id, config).await;
     if knowledge_context.is_empty() {
         system_prompt
     } else {