优化: aichat效率剩余(压缩后台化防阻塞/审计批量事务/只读缓存轮内去重/流式增量渲染/AiCommandOutput合批/双渲染合并) + 跨端加固(df-project路径保留大小写/tunnel文档更正supervisor重连/relay固定时间比较与帧上限/启动校验) + 销账

src-tauri/src/commands/ai/audit/record.rs

@@ -24,10 +24,50 @@ use crate::state::AppState;
 
 use super::risk_str;
 
-/// 写一条工具执行审计记录（insert 失败不阻断主流程，故 `let _ =`）
+/// 构造一条工具执行审计记录(纯函数,单条 [`audit_tool_call`] / 批量插入路径共用)。
 ///
-/// `decided_by` 有值（auto/human）= 已决策执行 → 记 executed_at；
-/// `None`（pending 待审批）→ executed_at 留空，待 audit_finalize 回填。
+/// `decided_by` 有值(auto/human)= 已决策执行 → 记 executed_at;
+/// `None`(pending 待审批)→ executed_at 留空,待 audit_finalize 回填。
+pub(crate) fn build_audit_record(
+    conv_id: &str,
+    tool_call_id: &str,
+    tool_name: &str,
+    arguments: &str,
+    status: &str,
+    risk_level: RiskLevel,
+    result: Option<String>,
+    decided_by: Option<&str>,
+    message_id: Option<&str>,
+) -> AiToolExecutionRecord {
+    let executed_at = if decided_by.is_some() { Some(now_millis()) } else { None };
+    AiToolExecutionRecord {
+        id: new_id(),
+        conversation_id: Some(conv_id.to_string()),
+        // P1 消息级溯源:message_id 由调用方(process_tool_calls)从
+        // ContextManager 取当前 assistant 消息 id 传入(LLM 返回带 tool_calls 的
+        // assistant 消息已 push 到 per_conv.messages,入口取末条 assistant id)。
+        // None 表示无 assistant 消息(异常路径/老数据无 id),展示侧兼容。
+        message_id: message_id.map(|s| s.to_string()),
+        tool_call_id: tool_call_id.to_string(),
+        tool_name: tool_name.to_string(),
+        arguments: arguments.to_string(),
+        result,
+        status: status.to_string(),
+        risk_level: risk_str(risk_level).to_string(),
+        requested_at: now_millis(),
+        executed_at,
+        decided_by: decided_by.map(|s| s.to_string()),
+    }
+}
+
+/// 写一条工具执行审计记录(insert 失败不阻断主流程,故 `let _ =`)
+///
+/// 单条写入路径。批量路径(audit/mod.rs process_tool_calls 回填循环)经
+/// [`build_audit_record`] 收集记录后调 `AiToolExecutionRepo::insert_batch`
+/// 单事务批量插入(治 aichat 效率 AC-EFF-T1-1,N 次串行 INSERT → 一次事务)。
+///
+/// `decided_by` 有值(auto/human)= 已决策执行 → 记 executed_at;
+/// `None`(pending 待审批)→ executed_at 留空,待 audit_finalize 回填。
 pub(crate) async fn audit_tool_call(
     repo: &AiToolExecutionRepo,
     conv_id: &str,
@@ -40,28 +80,11 @@ pub(crate) async fn audit_tool_call(
     decided_by: Option<&str>,
     message_id: Option<&str>,
 ) {
-    let executed_at = if decided_by.is_some() { Some(now_millis()) } else { None };
-    if let Err(e) = repo
-        .insert(AiToolExecutionRecord {
-            id: new_id(),
-            conversation_id: Some(conv_id.to_string()),
-            // P1 消息级溯源:message_id 由调用方(process_tool_calls)从
-            // ContextManager 取当前 assistant 消息 id 传入(LLM 返回带 tool_calls 的
-            // assistant 消息已 push 到 per_conv.messages,入口取末条 assistant id)。
-            // None 表示无 assistant 消息(异常路径/老数据无 id),展示侧兼容。
-            message_id: message_id.map(|s| s.to_string()),
-            tool_call_id: tool_call_id.to_string(),
-            tool_name: tool_name.to_string(),
-            arguments: arguments.to_string(),
-            result,
-            status: status.to_string(),
-            risk_level: risk_str(risk_level).to_string(),
-            requested_at: now_millis(),
-            executed_at,
-            decided_by: decided_by.map(|s| s.to_string()),
-        })
-        .await
-    {
+    let record = build_audit_record(
+        conv_id, tool_call_id, tool_name, arguments,
+        status, risk_level, result, decided_by, message_id,
+    );
+    if let Err(e) = repo.insert(record).await {
         tracing::error!(
             "audit_tool_call: 写审计记录失败(conv={}, tool_call_id={}, tool={}): {}",
             conv_id,