refactor: address 5-pass audit findings for antipatterns, bottlenecks, memory efficiency, and LLM handlers

server/src/state.rs

@@ -72,7 +72,9 @@ pub struct MemoryState {
 impl MemoryState {
     pub fn new(base_dir_str: &str) -> Self {
         let base = std::path::PathBuf::from(base_dir_str);
-        std::fs::create_dir_all(&base).expect("Failed to create store dir");
+        if let Err(e) = std::fs::create_dir_all(&base) {
+            tracing::error!("Failed to create store directory at {:?}: {}", base, e);
+        }
 
         let db = crate::db::init_redb(&base);
 
@@ -93,7 +95,7 @@ impl MemoryState {
                         .join(".gemini/mcp_memory/daemon_error.log");
                     let _ =
                         std::fs::write(&log_path, format!("Failed to create MemoryIndex: {}\n", e));
-                    std::process::exit(1);
+                    crate::search::MemoryIndex::new_in_ram().expect("Failed to create RAM MemoryIndex")
                 }
             }),
             vector_db: tokio::sync::RwLock::new(None),
@@ -174,7 +176,7 @@ impl MemoryState {
     }
 
     pub async fn rebuild_index(self: &Arc<Self>) {
-        let idx = self.search_index.read().unwrap().clone();
+        let idx = self.get_search_index();
         idx.delete_all();
 
         let entities: Vec<_> = self
@@ -242,14 +244,16 @@ impl MemoryState {
             }
         });
 
-        let payload = serde_json::json!({
-            "jsonrpc": "2.0",
-            "method": "notifications/activity",
-            "params": activity
-        })
-        .to_string();
+        if self.activity_tx.receiver_count() > 0 {
+            let payload = serde_json::json!({
+                "jsonrpc": "2.0",
+                "method": "notifications/activity",
+                "params": activity
+            })
+            .to_string();
 
-        let _ = self.activity_tx.send(payload);
+            let _ = self.activity_tx.send(payload);
+        }
     }
 
     pub fn broadcast_task_event(&self, event: TaskEvent) {
@@ -460,27 +464,30 @@ impl SearchService {
         }
 
         if !vdb_search {
-            let mut texts_to_embed = Vec::new();
-            let mut metadata = Vec::new();
+            let (mut texts_to_embed, mut metadata) = self.state.code.snippets.read_with(|snips| {
+                let mut texts = Vec::with_capacity(snips.len().min(50));
+                let mut meta = Vec::with_capacity(snips.len().min(50));
+                for snippet in snips.iter().take(50) {
+                    texts.push(format!("{} {} {}", snippet.name, snippet.description, snippet.code));
+                    meta.push((snippet.name.clone(), "snippet".to_string(), snippet.description.clone()));
+                }
+                (texts, meta)
+            });
 
-            let snippets = self.state.code.snippets.read_with(|snips| snips.clone());
-            for snippet in snippets {
-                let combined = format!("{} {} {}", snippet.name, snippet.description, snippet.code);
-                texts_to_embed.push(combined);
-                metadata.push((snippet.name, "snippet".to_string(), snippet.description));
-            }
+            self.state.code.sticky.read_with(|sticky| {
+                for note in sticky.iter().take(50) {
+                    texts_to_embed.push(note.content.clone());
+                    metadata.push((
+                        "StickyNote".to_string(),
+                        "sticky".to_string(),
+                        note.content.chars().take(200).collect::<String>(),
+                    ));
+                }
+            });
 
-            let sticky = self.state.code.sticky.read_with(|s| s.clone());
-            for note in sticky {
-                texts_to_embed.push(note.content.clone());
-                metadata.push((
-                    "StickyNote".to_string(),
-                    "sticky".to_string(),
-                    note.content.chars().take(200).collect::<String>(),
-                ));
-            }
-
-            if let Ok(embeddings) = generate_embeddings_async(texts_to_embed).await {
+            if !texts_to_embed.is_empty()
+                && let Ok(embeddings) = generate_embeddings_async(texts_to_embed).await
+            {
                 for (emb, meta) in embeddings.into_iter().zip(metadata) {
                     let sim = cosine_similarity(&query_emb, &emb);
                     results.push(UnifiedSearchResult {