update

app.py

@@ -18,13 +18,11 @@ from src.prompts import wrap_prompt
 from gradio_highlightedtextbox import HighlightedTextbox
 from examples import run_example_1, run_example_2, run_example_3, run_example_4, run_example_5, run_example_6
 from functools import partial
-os.makedirs("/home/user/nltk_data", exist_ok=True)
-# Download punkt to a known path
-nltk.download("punkt", download_dir="/home/user/nltk_data")
-# Tell nltk where to find it
-nltk.data.path.append("/home/user/nltk_data")
+
+
 from nltk.tokenize import sent_tokenize
 
+
 # Load original app constants
 APP_TITLE = '<div class="app-title"><span class="brand">AttnTrace: </span><span class="subtitle">Attention-based Context Traceback for Long-Context LLMs</span></div>'
 APP_DESCRIPTION = """AttnTrace traces a model's generated statements back to specific parts of the context using attention-based traceback. Try it out with Meta-Llama-3.1-8B-Instruct here! See the [[paper](https://arxiv.org/abs/2506.04202)] and [[code](https://github.com/Wang-Yanting/TracLLM-Kit)] for more!
@@ -82,10 +80,43 @@ current_attr = None
 current_model_path = None
 current_explanation_level = None
 current_api_key = None
+current_top_k = 3  # Add top-k tracking
+
+def update_configuration(explanation_level, top_k):
+    """Update the global configuration and reinitialize attribution if needed"""
+    global current_explanation_level, current_top_k, current_attr, current_llm
+    
+    # Convert top_k to int
+    top_k = int(top_k)
+    
+    # Check if configuration has changed
+    config_changed = (current_explanation_level != explanation_level or 
+                     current_top_k != top_k)
+    
+    if config_changed:
+        print(f"🔄 Updating configuration: explanation_level={explanation_level}, top_k={top_k}")
+        current_explanation_level = explanation_level
+        current_top_k = top_k
+        
+        # Reset both model and attribution to force complete reinitialization
+        current_llm = None
+        current_attr = None
+        
+        # Reinitialize with new configuration
+        try:
+            llm, attr, error_msg = initialize_model_and_attr()
+            if llm is not None and attr is not None:
+                return gr.update(value=f"✅ Configuration updated: {explanation_level} level, top-{top_k}")
+            else:
+                return gr.update(value=f"❌ Error reinitializing: {error_msg}")
+        except Exception as e:
+            return gr.update(value=f"❌ Error updating configuration: {str(e)}")
+    else:
+        return gr.update(value="ℹ️ Configuration unchanged")
 
 def initialize_model_and_attr():
     """Initialize model and attribution with default configuration"""
-    global current_llm, current_attr, current_model_path, current_explanation_level, current_api_key
+    global current_llm, current_attr, current_model_path, current_explanation_level, current_api_key, current_top_k
     
     try:
         # Check if we need to reinitialize the model
@@ -95,7 +126,7 @@ def initialize_model_and_attr():
         
         # Check if we need to update attribution
         need_attr_update = (current_attr is None or 
-                          current_explanation_level != DEFAULT_EXPLANATION_LEVEL or 
+                          current_explanation_level != (current_explanation_level or DEFAULT_EXPLANATION_LEVEL) or 
                           need_model_update)
         
         if need_model_update:
@@ -106,15 +137,20 @@ def initialize_model_and_attr():
             current_api_key = effective_api_key
             
         if need_attr_update:
-            print(f"Initializing context traceback with explanation level: {DEFAULT_EXPLANATION_LEVEL}")
+            # Use current configuration or defaults
+            explanation_level = current_explanation_level or DEFAULT_EXPLANATION_LEVEL
+            top_k = current_top_k or 3
+            if "segment" in explanation_level:
+                explanation_level = "segment"
+            print(f"Initializing context traceback with explanation level: {explanation_level}, top_k: {top_k}")
             current_attr = AttnTraceAttribution(
                 current_llm, 
-                explanation_level=DEFAULT_EXPLANATION_LEVEL, 
-                K=3, 
+                explanation_level= explanation_level, 
+                K=top_k, 
                 q=0.4, 
                 B=30
             )
-            current_explanation_level = DEFAULT_EXPLANATION_LEVEL
+            current_explanation_level = explanation_level
             
         return current_llm, current_attr, None
         
@@ -207,9 +243,9 @@ def generate_model_response(state: State):
         print("❌ Validation failed: No query")
         return state, gr.update(value=[("❌ Please enter a query before generating response! If you just changed configuration, try reloading an example.", None)], visible=True)
     
-    # Initialize model and attribution with default configuration
-    print(f"🔧 Generating response with explanation_level: {DEFAULT_EXPLANATION_LEVEL}")
-    #llm, attr, error_msg = initialize_model_and_attr()
+    # Initialize model and attribution with current configuration
+    print(f"🔧 Generating response with explanation_level: {current_explanation_level or DEFAULT_EXPLANATION_LEVEL}, top_k: {current_top_k or 3}")
+    llm, attr, error_msg = initialize_model_and_attr()
     
     if llm is None or attr is None:
         error_text = error_msg if error_msg else "Model initialization failed!"
@@ -338,7 +374,7 @@ def unified_response_handler(response_text: str, state: State):
             )
         
         # Initialize model and generate response
-        #llm, attr, error_msg = initialize_model_and_attr()
+        llm, attr, error_msg = initialize_model_and_attr()
         
         if llm is None:
             error_text = error_msg if error_msg else "Model initialization failed!"
@@ -436,7 +472,7 @@ def basic_get_scores_and_sources_full_response(state: State):
     state.explained_response_part = state.full_response
 
     # Attribution using default configuration
-    #_, attr, error_msg = initialize_model_and_attr()
+    llm, attr, error_msg = initialize_model_and_attr()
     
     if attr is None:
         error_text = error_msg if error_msg else "Traceback initialization failed!"
@@ -651,7 +687,7 @@ def basic_get_scores_and_sources(
     state.explained_response_part = selected_text
 
     # Attribution using default configuration
-    #_, attr, error_msg = initialize_model_and_attr()
+    llm, attr, error_msg = initialize_model_and_attr()
     
     if attr is None:
         error_text = error_msg if error_msg else "Traceback initialization failed!"
@@ -946,111 +982,167 @@ with gr.Blocks(theme=theme, css=custom_css) as demo:
         value=clear_state()
     )
 
-    basic_tab = gr.Tab("Demo")
-    with basic_tab:
-        # gr.Markdown("## Demo")
-        gr.Markdown(
-            "Enter your context and instruction below to try out AttnTrace! You can also click on the example buttons above to load pre-configured examples."
-        )
-        
-        gr.Markdown(
-            '**Color Legend for Context Traceback (by ranking):** <span style="background-color: #FF4444; color: black; padding: 2px 6px; border-radius: 4px; font-weight: 600;">Red</span> = 1st (most important) | <span style="background-color: #FF8C42; color: black; padding: 2px 6px; border-radius: 4px; font-weight: 600;">Orange</span> = 2nd | <span style="background-color: #FFD93D; color: black; padding: 2px 6px; border-radius: 4px; font-weight: 600;">Golden</span> = 3rd | <span style="background-color: #FFF280; color: black; padding: 2px 6px; border-radius: 4px; font-weight: 600;">Yellow</span> = 4th-5th | <span style="background-color: #FFF9C4; color: black; padding: 2px 6px; border-radius: 4px; font-weight: 600;">Light</span> = 6th+'
-        )
-        
-        
-        # Top section: Wide Context box with tabs
-        with gr.Row():
-            with gr.Column(scale=1):
-                with gr.Tabs() as basic_context_tabs:
-                    with gr.TabItem("Context", id=0):
-                        basic_context_box = gr.Textbox(
-                            placeholder="Enter context...",
-                            show_label=False,
-                            value="",
-                            lines=6,
-                            max_lines=6,
-                            elem_id="basic_context_box",
-                            autoscroll=False,
-                        )
-                    with gr.TabItem("Context with highlighted traceback results", id=1, visible=True) as basic_sources_in_context_tab:
-                        basic_sources_in_context_box = HighlightedTextbox(
-                            value=[("Click on a sentence in the response below to see highlighted traceback results here.", None)],
-                            show_legend_label=False,
-                            show_label=False,
-                            show_legend=False,
-                            interactive=False,
-                            elem_id="basic_sources_in_context_box",
-                        )
-        
-        # Error messages
-        basic_generate_error_box = HighlightedTextbox(
-            show_legend_label=False,
-            show_label=False,
-            show_legend=False,
-            visible=False,
-            interactive=False,
-            container=False,
-        )
+    # Create tabs for Demo and Configuration
+    with gr.Tabs() as main_tabs:
+        # Demo Tab
+        with gr.Tab("Demo", id="demo_tab"):
+            gr.Markdown(
+                "Enter your context and instruction below to try out AttnTrace! You can also click on the example buttons above to load pre-configured examples."
+            )
+            
+            gr.Markdown(
+                '**Color Legend for Context Traceback (by ranking):** <span style="background-color: #FF4444; color: black; padding: 2px 6px; border-radius: 4px; font-weight: 600;">Red</span> = 1st (most important) | <span style="background-color: #FF8C42; color: black; padding: 2px 6px; border-radius: 4px; font-weight: 600;">Orange</span> = 2nd | <span style="background-color: #FFD93D; color: black; padding: 2px 6px; border-radius: 4px; font-weight: 600;">Golden</span> = 3rd | <span style="background-color: #FFF280; color: black; padding: 2px 6px; border-radius: 4px; font-weight: 600;">Yellow</span> = 4th-5th | <span style="background-color: #FFF9C4; color: black; padding: 2px 6px; border-radius: 4px; font-weight: 600;">Light</span> = 6th+'
+            )
+            
+            # Top section: Wide Context box with tabs
+            with gr.Row():
+                with gr.Column(scale=1):
+                    with gr.Tabs() as basic_context_tabs:
+                        with gr.TabItem("Context", id=0):
+                            basic_context_box = gr.Textbox(
+                                placeholder="Enter context...",
+                                show_label=False,
+                                value="",
+                                lines=6,
+                                max_lines=6,
+                                elem_id="basic_context_box",
+                                autoscroll=False,
+                            )
+                        with gr.TabItem("Context with highlighted traceback results", id=1, visible=True) as basic_sources_in_context_tab:
+                            basic_sources_in_context_box = HighlightedTextbox(
+                                value=[("Click on a sentence in the response below to see highlighted traceback results here.", None)],
+                                show_legend_label=False,
+                                show_label=False,
+                                show_legend=False,
+                                interactive=False,
+                                elem_id="basic_sources_in_context_box",
+                            )
+            
+            # Error messages
+            basic_generate_error_box = HighlightedTextbox(
+                show_legend_label=False,
+                show_label=False,
+                show_legend=False,
+                visible=False,
+                interactive=False,
+                container=False,
+            )
 
-        # Bottom section: Left (instruction + button + response), Right (response selection)
-        with gr.Row(equal_height=True):
-            # Left: Instruction + Button + Response
-            with gr.Column(scale=1):
-                basic_query_box = gr.Textbox(
-                    label="Instruction",
-                    placeholder="Enter an instruction...",
-                    value="",
-                    lines=3,
-                    max_lines=3,
-                )
-                
-                unified_response_button = gr.Button(
-                    "Generate/Use Response", 
-                    variant="primary", 
-                    size="lg"
-                )
+            # Bottom section: Left (instruction + button + response), Right (response selection)
+            with gr.Row(equal_height=True):
+                # Left: Instruction + Button + Response
+                with gr.Column(scale=1):
+                    basic_query_box = gr.Textbox(
+                        label="Instruction",
+                        placeholder="Enter an instruction...",
+                        value="",
+                        lines=3,
+                        max_lines=3,
+                    )
+                    
+                    unified_response_button = gr.Button(
+                        "Generate/Use Response", 
+                        variant="primary", 
+                        size="lg"
+                    )
+                    
+                    response_input_box = gr.Textbox(
+                        label="Response (Editable)",
+                        placeholder="Response will appear here after generation, or type your own response for traceback...",
+                        lines=8,
+                        max_lines=8,
+                        info="Leave empty and click button to generate from LLM, or type your own response to use for traceback"
+                    )
                 
-                response_input_box = gr.Textbox(
-                    label="Response (Editable)",
-                    placeholder="Response will appear here after generation, or type your own response for traceback...",
-                    lines=8,
-                    max_lines=8,
-                    info="Leave empty and click button to generate from LLM, or type your own response to use for traceback"
-                )
+                # Right: Response for attribution selection
+                with gr.Column(scale=1):
+                    basic_response_box = gr.HighlightedText(
+                        label="Click to select text for traceback!",
+                        value=[("Click the 'Generate/Use Response' button on the left to see response text here for traceback analysis.", None)],
+                        interactive=False,
+                        combine_adjacent=False,
+                        show_label=True,
+                        show_legend=False,
+                        elem_id="basic_response_box",
+                        visible=True,
+                    )
+                    
+                    # Button for full response traceback
+                    full_response_traceback_button = gr.Button(
+                        "🔍 Traceback Entire Response",
+                        variant="secondary",
+                        size="sm"
+                    )
             
-            # Right: Response for attribution selection
-            with gr.Column(scale=1):
-                basic_response_box = gr.HighlightedText(
-                    label="Click to select text for traceback!",
-                    value=[("Click the 'Generate/Use Response' button on the left to see response text here for traceback analysis.", None)],
-                    interactive=False,
-                    combine_adjacent=False,
-                    show_label=True,
-                    show_legend=False,
-                    elem_id="basic_response_box",
-                    visible=True,
-                )
-                
-                # Button for full response traceback
-                full_response_traceback_button = gr.Button(
-                    "🔍 Traceback Entire Response",
-                    variant="secondary",
-                    size="sm"
-                )
-        
-        # Hidden error box and dummy elements
-        basic_attribute_error_box = HighlightedTextbox(
-            show_legend_label=False,
-            show_label=False,
-            show_legend=False,
-            visible=False,
-            interactive=False,
-            container=False,
-        )
-        dummy_basic_sources_box = gr.Textbox(
-            visible=False, interactive=False, container=False
-        )
+            # Hidden error box and dummy elements
+            basic_attribute_error_box = HighlightedTextbox(
+                show_legend_label=False,
+                show_label=False,
+                show_legend=False,
+                visible=False,
+                interactive=False,
+                container=False,
+            )
+            dummy_basic_sources_box = gr.Textbox(
+                visible=False, interactive=False, container=False
+            )
 
+        # Configuration Tab
+        with gr.Tab("Config", id="config_tab"):
+            gr.Markdown("## ⚙️ AttnTrace Configuration")
+            gr.Markdown("Configure the traceback analysis parameters to customize how AttnTrace processes your context and generates results.")
+            
+            with gr.Row():
+                with gr.Column(scale=1):
+                    explanation_level_dropdown = gr.Dropdown(
+                        choices=["sentence", "paragraph", "text segment"],
+                        value="sentence",
+                        label="Explanation Level",
+                        info="How to segment the context for traceback analysis"
+                    )
+                with gr.Column(scale=1):
+                    top_k_dropdown = gr.Dropdown(
+                        choices=["3", "5", "10"],
+                        value="5",
+                        label="Top-K Value",
+                        info="Number of most important text segments to highlight"
+                    )
+            
+            with gr.Row():
+                with gr.Column(scale=1):
+                    apply_config_button = gr.Button(
+                        "Apply Configuration",
+                        variant="primary",
+                        size="lg"
+                    )
+                with gr.Column(scale=2):
+                    config_status_text = gr.Textbox(
+                        label="Configuration Status",
+                        value="Ready to apply configuration",
+                        interactive=False,
+                        lines=2
+                    )
+            
+            gr.Markdown("### 📋 Current Configuration")
+            gr.Markdown("""
+            - **Explanation Level**: Determines how the context is segmented for analysis
+              - `sentence`: Analyze at sentence level (recommended for most cases)
+              - `paragraph`: Analyze at paragraph level (good for longer documents)
+              - `text segment`: Analyze at custom text segments (advanced usage)
+            
+            - **Top-K Value**: Number of most important text segments to highlight in results
+              - Higher values show more context but may be less focused
+              - Lower values provide more focused results but may miss some context
+            
+            **Note**: Configuration changes will take effect immediately for new traceback operations.
+            """)
+            
+            gr.Markdown("### 🔄 Model Information")
+            gr.Markdown(f"""
+            - **Current Model**: {DEFAULT_MODEL_PATH}
+            - **Max Tokens**: {get_max_tokens(DEFAULT_MODEL_PATH):,}
+            - **Device**: CUDA (GPU accelerated)
+            """)
 
     # Only a single (AttnTrace) method and model in this simplified version
 
@@ -1065,9 +1157,23 @@ with gr.Blocks(theme=theme, css=custom_css) as demo:
             state,
         )
 
-    # Defining behavior of various interactions for the basic tab
-    basic_tab.select(
-        fn=basic_clear_state,
+    # Defining behavior of various interactions for the demo tab only
+    def handle_demo_tab_selection(evt: gr.SelectData):
+        """Handle tab selection - only clear state when switching to demo tab"""
+        if evt.index == 0:  # Demo tab
+            return basic_clear_state()
+        else:  # Configuration tab - no state change needed
+            return (
+                gr.update(),  # basic_context_box
+                gr.update(),  # basic_query_box
+                gr.update(),  # response_input_box
+                gr.update(),  # basic_response_box
+                gr.update(),  # basic_context_tabs
+                gr.update(),  # state
+            )
+    
+    main_tabs.select(
+        fn=handle_demo_tab_selection,
         inputs=[],
         outputs=[
             basic_context_box,
@@ -1209,6 +1315,12 @@ with gr.Blocks(theme=theme, css=custom_css) as demo:
         outputs=[state, response_input_box, basic_response_box, basic_generate_error_box]
     )
     
+    # Configuration update handler
+    apply_config_button.click(
+        fn=update_configuration,
+        inputs=[explanation_level_dropdown, top_k_dropdown],
+        outputs=[config_status_text]
+    )
 
     # gr.Markdown(
     #     "Please do not interact with elements while generation/attribution is in progress. This may cause errors. You can refresh the page if you run into issues because of this."

app_config.py → app_no_config.py

@@ -25,8 +25,6 @@ nltk.download("punkt", download_dir="/home/user/nltk_data")
 nltk.data.path.append("/home/user/nltk_data")
 from nltk.tokenize import sent_tokenize
 
-DEFAULT_TOP_K = 3
-
 # Load original app constants
 APP_TITLE = '<div class="app-title"><span class="brand">AttnTrace: </span><span class="subtitle">Attention-based Context Traceback for Long-Context LLMs</span></div>'
 APP_DESCRIPTION = """AttnTrace traces a model's generated statements back to specific parts of the context using attention-based traceback. Try it out with Meta-Llama-3.1-8B-Instruct here! See the [[paper](https://arxiv.org/abs/2506.04202)] and [[code](https://github.com/Wang-Yanting/TracLLM-Kit)] for more!
@@ -84,46 +82,10 @@ current_attr = None
 current_model_path = None
 current_explanation_level = None
 current_api_key = None
-current_top_k = 3  # Add top-k tracking
-
-def update_configuration(explanation_level, top_k):
-    """Update the global configuration and reinitialize attribution if needed"""
-    global current_explanation_level, current_top_k, current_attr, current_llm
-    
-    # Convert top_k to int
-    top_k = int(top_k)
-    
-    # Check if configuration has changed
-    config_changed = (current_explanation_level != explanation_level or 
-                     current_top_k != top_k)
-    
-    if config_changed:
-        print(f"🔄 Updating configuration: explanation_level={explanation_level}, top_k={top_k}")
-        current_explanation_level = explanation_level
-        current_top_k = top_k
-
-        DEFAULT_EXPLANATION_LEVEL = explanation_level
-        DEFAULT_TOP_K = top_k
-        
-        # Reset both model and attribution to force complete reinitialization
-        current_llm = None
-        current_attr = None
-        
-        # Reinitialize with new configuration
-        try:
-            llm, attr, error_msg = initialize_model_and_attr()
-            if llm is not None and attr is not None:
-                return gr.update(value=f"✅ Configuration updated: {explanation_level} level, top-{top_k}")
-            else:
-                return gr.update(value=f"❌ Error reinitializing: {error_msg}")
-        except Exception as e:
-            return gr.update(value=f"❌ Error updating configuration: {str(e)}")
-    else:
-        return gr.update(value="ℹ️ Configuration unchanged")
 
 def initialize_model_and_attr():
     """Initialize model and attribution with default configuration"""
-    global current_llm, current_attr, current_model_path, current_explanation_level, current_api_key, current_top_k
+    global current_llm, current_attr, current_model_path, current_explanation_level, current_api_key
     
     try:
         # Check if we need to reinitialize the model
@@ -133,7 +95,7 @@ def initialize_model_and_attr():
         
         # Check if we need to update attribution
         need_attr_update = (current_attr is None or 
-                          current_explanation_level != (current_explanation_level or DEFAULT_EXPLANATION_LEVEL) or 
+                          current_explanation_level != DEFAULT_EXPLANATION_LEVEL or 
                           need_model_update)
         
         if need_model_update:
@@ -144,20 +106,15 @@ def initialize_model_and_attr():
             current_api_key = effective_api_key
             
         if need_attr_update:
-            # Use current configuration or defaults
-            explanation_level = current_explanation_level or DEFAULT_EXPLANATION_LEVEL
-            top_k = current_top_k or 3
-            if "segment" in DEFAULT_EXPLANATION_LEVEL:
-                DEFAULT_EXPLANATION_LEVEL = "segment"
-            print(f"Initializing context traceback with explanation level: {explanation_level}, top_k: {top_k}")
+            print(f"Initializing context traceback with explanation level: {DEFAULT_EXPLANATION_LEVEL}")
             current_attr = AttnTraceAttribution(
                 current_llm, 
-                explanation_level= DEFAULT_EXPLANATION_LEVEL, 
-                K=DEFAULT_TOP_K, 
+                explanation_level=DEFAULT_EXPLANATION_LEVEL, 
+                K=3, 
                 q=0.4, 
                 B=30
             )
-            current_explanation_level = explanation_level
+            current_explanation_level = DEFAULT_EXPLANATION_LEVEL
             
         return current_llm, current_attr, None
         
@@ -250,9 +207,9 @@ def generate_model_response(state: State):
         print("❌ Validation failed: No query")
         return state, gr.update(value=[("❌ Please enter a query before generating response! If you just changed configuration, try reloading an example.", None)], visible=True)
     
-    # Initialize model and attribution with current configuration
-    print(f"🔧 Generating response with explanation_level: {current_explanation_level or DEFAULT_EXPLANATION_LEVEL}, top_k: {current_top_k or 3}")
-    llm, attr, error_msg = initialize_model_and_attr()
+    # Initialize model and attribution with default configuration
+    print(f"🔧 Generating response with explanation_level: {DEFAULT_EXPLANATION_LEVEL}")
+    #llm, attr, error_msg = initialize_model_and_attr()
     
     if llm is None or attr is None:
         error_text = error_msg if error_msg else "Model initialization failed!"
@@ -381,7 +338,7 @@ def unified_response_handler(response_text: str, state: State):
             )
         
         # Initialize model and generate response
-        llm, attr, error_msg = initialize_model_and_attr()
+        #llm, attr, error_msg = initialize_model_and_attr()
         
         if llm is None:
             error_text = error_msg if error_msg else "Model initialization failed!"
@@ -479,7 +436,7 @@ def basic_get_scores_and_sources_full_response(state: State):
     state.explained_response_part = state.full_response
 
     # Attribution using default configuration
-    llm, attr, error_msg = initialize_model_and_attr()
+    #_, attr, error_msg = initialize_model_and_attr()
     
     if attr is None:
         error_text = error_msg if error_msg else "Traceback initialization failed!"
@@ -694,7 +651,7 @@ def basic_get_scores_and_sources(
     state.explained_response_part = selected_text
 
     # Attribution using default configuration
-    llm, attr, error_msg = initialize_model_and_attr()
+    #_, attr, error_msg = initialize_model_and_attr()
     
     if attr is None:
         error_text = error_msg if error_msg else "Traceback initialization failed!"
@@ -1000,36 +957,6 @@ with gr.Blocks(theme=theme, css=custom_css) as demo:
             '**Color Legend for Context Traceback (by ranking):** <span style="background-color: #FF4444; color: black; padding: 2px 6px; border-radius: 4px; font-weight: 600;">Red</span> = 1st (most important) | <span style="background-color: #FF8C42; color: black; padding: 2px 6px; border-radius: 4px; font-weight: 600;">Orange</span> = 2nd | <span style="background-color: #FFD93D; color: black; padding: 2px 6px; border-radius: 4px; font-weight: 600;">Golden</span> = 3rd | <span style="background-color: #FFF280; color: black; padding: 2px 6px; border-radius: 4px; font-weight: 600;">Yellow</span> = 4th-5th | <span style="background-color: #FFF9C4; color: black; padding: 2px 6px; border-radius: 4px; font-weight: 600;">Light</span> = 6th+'
         )
         
-        # Configuration bar
-        with gr.Row():
-            with gr.Column(scale=1):
-                explanation_level_dropdown = gr.Dropdown(
-                    choices=["sentence", "paragraph", "text segment"],
-                    value="sentence",
-                    label="Explanation Level",
-                    info="How to segment the context for traceback analysis"
-                )
-            with gr.Column(scale=1):
-                top_k_dropdown = gr.Dropdown(
-                    choices=["3", "5", "10"],
-                    value="5",
-                    label="Top-K Value",
-                    info="Number of most important text segments to highlight"
-                )
-            with gr.Column(scale=1):
-                apply_config_button = gr.Button(
-                    "Apply Configuration",
-                    variant="secondary",
-                    size="sm"
-                )
-            with gr.Column(scale=2):
-                config_status_text = gr.Textbox(
-                    label="Configuration Status",
-                    value="Ready to apply configuration",
-                    interactive=False,
-                    lines=1
-                )
-        
         
         # Top section: Wide Context box with tabs
         with gr.Row():
@@ -1282,12 +1209,6 @@ with gr.Blocks(theme=theme, css=custom_css) as demo:
         outputs=[state, response_input_box, basic_response_box, basic_generate_error_box]
     )
     
-    # Configuration update handler
-    apply_config_button.click(
-        fn=update_configuration,
-        inputs=[explanation_level_dropdown, top_k_dropdown],
-        outputs=[config_status_text]
-    )
 
     # gr.Markdown(
     #     "Please do not interact with elements while generation/attribution is in progress. This may cause errors. You can refresh the page if you run into issues because of this."