update

demo.py

@@ -756,7 +756,9 @@ def get_routed_llm(query: str, config_path: str = None) -> Tuple[str, str, str]:
         selection_info = f"""
 🔄 **Fallback Mode**: Graph router not available
 🤖 **Selected LLM**: llama-3.1-8b-instruct (Default)
+🔗 **API Model**: meta/llama-3.1-8b-instruct
 📝 **Task Description**: General query processing
+📋 **LLM Details**: Meta's 8B Llama-3 series for chat & reasoning; $0.20/M input and $0.20/M output
 ⚠️ **Note**: Using fallback system due to missing graph router components
         """
         return "llama-3.1-8b-instruct", "General query processing", selection_info
@@ -819,17 +821,57 @@ def get_routed_llm(query: str, config_path: str = None) -> Tuple[str, str, str]:
             routed_llm_name = router.test_GNN()
             print(f"Graph router selected: {routed_llm_name}")
             
-            # Create detailed selection info
-            api_model = map_llm_to_api(routed_llm_name)
-            selection_info = f"""
+            # Load LLM descriptions to get detailed information
+            try:
+                with open(config['llm_description_path'], 'r', encoding='utf-8') as f:
+                    llm_descriptions = json.load(f)
+                
+                # Get LLM details
+                llm_info = llm_descriptions.get(routed_llm_name, {})
+                llm_feature = llm_info.get('feature', 'No description available')
+                input_price = llm_info.get('input_price', 'Unknown')
+                output_price = llm_info.get('output_price', 'Unknown')
+                
+                # Determine if it's a think mode model
+                think_mode = routed_llm_name.endswith('_think')
+                base_model_name = routed_llm_name[:-6] if think_mode else routed_llm_name
+                
+                # Create detailed selection info with enhanced LLM information
+                api_model = map_llm_to_api(routed_llm_name)
+                selection_info = f"""
 🎯 **Graph Router Analysis Complete**
 
 🤖 **Selected LLM**: {routed_llm_name}
+🔗 **API Model**: {api_model}
 📝 **Task Description**: {user_task_description}
 ✅ **Routing Method**: Advanced Graph Neural Network
 📊 **Analysis**: Query analyzed for optimal model selection
 ⚡ **Performance**: Cost-performance optimized routing
-            """
+
+**📋 LLM Details:**
+• **Model**: {base_model_name}
+• **Mode**: {'Think Mode (Step-by-step reasoning)' if think_mode else 'Standard Mode'}
+• **Features**: {llm_feature}
+• **Pricing**: ${input_price}/M input tokens, ${output_price}/M output tokens
+• **Provider**: {api_model.split('/')[0] if '/' in api_model else 'Unknown'}
+
+**🎯 Selection Rationale:**
+The Graph Neural Network analyzed your query and determined this model provides the best balance of performance, cost, and capability for your specific task type.
+                """
+            except Exception as e:
+                print(f"Warning: Could not load LLM descriptions: {e}")
+                # Fallback to basic information
+                api_model = map_llm_to_api(routed_llm_name)
+                selection_info = f"""
+🎯 **Graph Router Analysis Complete**
+
+🤖 **Selected LLM**: {routed_llm_name}
+🔗 **API Model**: {api_model}
+📝 **Task Description**: {user_task_description}
+✅ **Routing Method**: Advanced Graph Neural Network
+📊 **Analysis**: Query analyzed for optimal model selection
+⚡ **Performance**: Cost-performance optimized routing
+                """
             
             return routed_llm_name, user_task_description, selection_info
             
@@ -843,8 +885,9 @@ def get_routed_llm(query: str, config_path: str = None) -> Tuple[str, str, str]:
 ❌ **Configuration Error**: {str(e)}
 🔄 **Fallback**: Using default LLM
 🤖 **Selected LLM**: llama-3.1-8b-instruct (Default)
-📝 **Task Description**: General query processing
 🔗 **API Model**: meta/llama-3.1-8b-instruct
+📝 **Task Description**: General query processing
+📋 **LLM Details**: Meta's 8B Llama-3 series for chat & reasoning; $0.20/M input and $0.20/M output
         """
         return "llama-3.1-8b-instruct", "General query processing", selection_info
         
@@ -854,8 +897,9 @@ def get_routed_llm(query: str, config_path: str = None) -> Tuple[str, str, str]:
 ❌ **Graph Router Error**: {str(e)}
 🔄 **Fallback**: Using default LLM
 🤖 **Selected LLM**: llama-3.1-8b-instruct (Default)
-📝 **Task Description**: General query processing
 🔗 **API Model**: meta/llama-3.1-8b-instruct
+📝 **Task Description**: General query processing
+📋 **LLM Details**: Meta's 8B Llama-3 series for chat & reasoning; $0.20/M input and $0.20/M output
 ⚠️ **Note**: Advanced routing failed, using fallback system
         """
         return "llama-3.1-8b-instruct", "General query processing", selection_info