fix: Handle empty config values for LLM server arguments

The config_manager.get_config() can return Ok("") for empty config values,
which would pass through unwrap_or_else() without using the default.

Added checks after config retrieval to use defaults when config values
are empty strings:
- gpu_layers: "20" (default for GPU layers)
- n_moe: "4" (default for MoE)
- parallel: "1" (default for parallel)
- n_predict: "50" (default for predict)
- n_ctx_size: "32000" (default for context size)

This fixes the error: "error while handling argument --n-gpu-layers: stoi"

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

src/llm/local.rs

@@ -348,31 +348,46 @@ pub fn start_llm_server(
     let n_moe = config_manager
         .get_config(&default_bot_id, "llm-server-n-moe", None)
         .unwrap_or_else(|_| "4".to_string());
+    let n_moe = if n_moe.is_empty() { "4".to_string() } else { n_moe };
+
     let parallel = config_manager
         .get_config(&default_bot_id, "llm-server-parallel", None)
         .unwrap_or_else(|_| "1".to_string());
+    let parallel = if parallel.is_empty() { "1".to_string() } else { parallel };
+
     let cont_batching = config_manager
         .get_config(&default_bot_id, "llm-server-cont-batching", None)
         .unwrap_or_else(|_| "true".to_string());
+    let cont_batching = if cont_batching.is_empty() { "true".to_string() } else { cont_batching };
+
     let mlock = config_manager
         .get_config(&default_bot_id, "llm-server-mlock", None)
         .unwrap_or_else(|_| "true".to_string());
+    let mlock = if mlock.is_empty() { "true".to_string() } else { mlock };
+
     let no_mmap = config_manager
         .get_config(&default_bot_id, "llm-server-no-mmap", None)
         .unwrap_or_else(|_| "true".to_string());
+    let no_mmap = if no_mmap.is_empty() { "true".to_string() } else { no_mmap };
+
     let gpu_layers = config_manager
         .get_config(&default_bot_id, "llm-server-gpu-layers", None)
         .unwrap_or_else(|_| "20".to_string());
+    let gpu_layers = if gpu_layers.is_empty() { "20".to_string() } else { gpu_layers };
+
     let reasoning_format = config_manager
         .get_config(&default_bot_id, "llm-server-reasoning-format", None)
         .unwrap_or_else(|_| String::new());
+
     let n_predict = config_manager
         .get_config(&default_bot_id, "llm-server-n-predict", None)
         .unwrap_or_else(|_| "50".to_string());
+    let n_predict = if n_predict.is_empty() { "50".to_string() } else { n_predict };
 
     let n_ctx_size = config_manager
         .get_config(&default_bot_id, "llm-server-ctx-size", None)
         .unwrap_or_else(|_| "32000".to_string());
+    let n_ctx_size = if n_ctx_size.is_empty() { "32000".to_string() } else { n_ctx_size };
 
     let mut args = format!(
         "-m {model_path} --host 0.0.0.0 --port {port} --top_p 0.95 --temp 0.6 --repeat-penalty 1.2 --n-gpu-layers {gpu_layers} --ubatch-size 2048"