.

app.py

@@ -64,14 +64,53 @@ def generate_text_local(model_path, prompt, max_new_tokens=512, temperature=0.7,
         logger.error(f"Error in text generation with {model_path}: {str(e)}")
         return f"Error: {str(e)}"
 
+# Move the generate_responses function outside of create_demo
+def generate_responses(prompt, max_tokens, temperature, top_p, selected_models):
+    if len(selected_models) != 2:
+        return "Error: Please select exactly two models to compare.", ""
+    
+    if len(selected_models) == 0:
+        return "Error: Please select at least one model", ""
+    
+    # 選択されたモデルの結果を格納する辞書
+    responses = {}
+    futures_to_model = {}  # 各futureとモデルを紐づけるための辞書
+                
+    with ThreadPoolExecutor(max_workers=len(selected_models)) as executor:
+        # 各モデルに対してタスクを提出
+        futures = []
+        for model_name in selected_models:
+            model_path = model_options[model_name]
+            future = executor.submit(
+                generate_text_local, 
+                model_path, 
+                prompt, 
+                max_new_tokens=max_tokens,  # Fixed parameter name to match the function
+                temperature=temperature, 
+                top_p=top_p
+            )
+            futures.append(future)
+            futures_to_model[future] = model_name
+        
+        # 結果の収集
+        for future in as_completed(futures):
+            model_name = futures_to_model[future]
+            responses[model_name] = future.result()
+    
+    # モデル名を冒頭に付加して返す
+    model1_output = f"{selected_models[0]} Output:\n\n{responses.get(selected_models[0], '')}"
+    model2_output = f"{selected_models[1]} Output:\n\n{responses.get(selected_models[1], '')}"
+    
+    return model1_output, model2_output
+
 # Build Gradio app
 def create_demo():
     with gr.Blocks() as demo:
-        gr.Markdown("# AI Model Comparison Tool 🌟")
+        gr.Markdown("# AI Model Comparison Tool for Security Analysis 🔒")
         gr.Markdown(
             """
-            Compare responses from two AI models side-by-side.  
-            Select two models, ask a question, and compare their responses in real time!
+            Compare how different AI models analyze security vulnerabilities side-by-side.  
+            Select two models, input security-related text, and see how each model processes vulnerability information!
             """
         )
 
@@ -110,48 +149,6 @@ CVE-2015-10011 is a vulnerability about OpenDNS OpenResolve improper log output
         response_box1 = gr.Textbox(label="Response from Model 1", interactive=False)
         response_box2 = gr.Textbox(label="Response from Model 2", interactive=False)
 
-        # Function to generate responses
-        def generate_responses(
-            prompt, max_tokens, temperature, top_p, selected_models
-        ):
-            if len(selected_models) != 2:
-                return "Error: Please select exactly two models to compare.", ""
-            
-            if len(selected_models) == 0:
-                return "Error: Please select at least one model", ""
-            
-            # 選択されたモデルの結果を格納する辞書
-            responses = {}
-            futures_to_model = {}  # 各futureとモデルを紐づけるための辞書
-                        
-            with ThreadPoolExecutor(max_workers=len(selected_models)) as executor:
-                # 各モデルに対してタスクを提出
-                futures = []
-                for model_name in selected_models:
-                    model_path = model_options[model_name]
-                    future = executor.submit(
-                        generate_text_local, 
-                        model_path, 
-                        prompt, 
-                        max_new_tokens = max_new_tokens,
-                        do_sample = True,
-                        temperature = temperature, 
-                        top_p = top_p
-                    )
-                    futures.append(future)
-                    futures_to_model[future] = model_name
-                
-                # 結果の収集
-                for future in as_completed(futures):
-                    model_name = futures_to_model[future]
-                    responses[model_name] = future.result()
-            
-            # モデル名を冒頭に付加して返す
-            model1_output = f"{selected_models[0]} Output:\n\n{responses.get(selected_models[0], '')}"
-            model2_output = f"{selected_models[1]} Output:\n\n{responses.get(selected_models[1], '')}"
-            
-            return model1_output, model2_output
-            
         # Add a button for generating responses
         submit_button = gr.Button("Generate Responses")
         submit_button.click(