重构: F-09 batch5 llm_concurrency会话级改造(决策c)

- state.rs: per_conv HashMap<conv_id,Semaphore>(每对话permits=2) + per_conv_permits热改 + acquire_per_conv(conv_id) + release_conv
- agentic.rs: loop入口acquire_global+acquire_per_conv(conv_id)整loop持有(会话级并发上限3) + 删每轮acquire/drop
- compress/title/knowledge_inject: acquire_per_conv(conv_id)+签名conv_id
- project.rs: 扫描合成key + ai_conversation_delete release_conv
global: LLM调用并发→并发会话数上限;F-260616-12 retry permit自洽
主代兜底: cargo check --workspace 0 + test 96 + grep印证

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

@@ -122,7 +122,7 @@ pub(crate) async fn ensure_conversation_title(
     // 超时或返回 None 均保留上方已落的 extract 兜底,不覆盖。
     let title = match tokio::time::timeout(
         std::time::Duration::from_secs(20),
-        generate_title_via_llm(&*provider, &title_model, summary_msgs, &llm_concurrency),
+        generate_title_via_llm(&*provider, &title_model, summary_msgs, conv_id, &llm_concurrency),
     ).await {
         Ok(Some(t)) => t,
         Ok(None) => {
@@ -167,6 +167,7 @@ async fn generate_title_via_llm(
     provider: &dyn LlmProvider,
     model: &str,
     msgs: Vec<ChatMessage>,
+    conv_id: &str,
     llm_concurrency: &LlmConcurrency,
 ) -> Option<String> {
     let mut prompt = vec![ChatMessage::system(
@@ -184,8 +185,9 @@ async fn generate_title_via_llm(
         reasoning_content: None,
     };
     // LLM 并发限流（标题生成属独立调用，纳入双层 Semaphore）
+    // F-09 B 批5: per_conv 改 HashMap<conv_id>,标题针对本对话,用 conv_id 共享限流槽。
     let _global_permit = llm_concurrency.acquire_global().await;
-    let _per_conv_permit = llm_concurrency.acquire_per_conv().await;
+    let _per_conv_permit = llm_concurrency.acquire_per_conv(conv_id).await;
     let resp = provider.complete(request).await.ok()?;
     Some(clean_title(&resp.text))
 }