feat(llm): add model selection and response processing

Added support for selecting an LLM model based on configuration and processing the raw response. The execute_llm_generation function now:
1. Fetches the configured model using ConfigManager
2. Gets the appropriate handler for the model
3. Processes the raw response through the handler before returning

This provides more flexibility in model selection and allows for model-specific response handling.

src/basic/keywords/llm_keyword.rs

@@ -2,6 +2,7 @@ use crate::shared::models::UserSession;
 use crate::shared::state::AppState;
 use log::{error, info};
 use rhai::{Dynamic, Engine};
+use uuid::Uuid;
 use std::sync::Arc;
 use std::time::Duration;
 
@@ -80,10 +81,16 @@ pub async fn execute_llm_generation(
     state: Arc<AppState>,
     prompt: String,
 ) -> Result<String, Box<dyn std::error::Error + Send + Sync>> {
+    let config_manager = crate::config::ConfigManager::new(Arc::clone(&state.conn));
+    let model = config_manager
+        .get_config(&Uuid::nil(), "llm-model", None)
+        .unwrap_or_default();
 
-    state
+    let handler = crate::llm_models::get_handler(&model);
+    let raw_response = state
         .llm_provider
         .generate(&prompt, &serde_json::Value::Null)
-        .await
-        .map_err(|e| format!("LLM call failed: {}", e).into())
+        .await?;
+
+    Ok(handler.process_content(&raw_response))
 }