Update app.py

app.py

@@ -1,6 +1,5 @@
 # app.py
-# @title Beer Game Final Version (v7 - THE REAL FIX: LT=3, Log Fix, Prompt Fix)
-
+# @title Beer Game Final Version (v4.21 - Removed Introduction)
 # -----------------------------------------------------------------------------
 # 1. Import Libraries
 # -----------------------------------------------------------------------------
@@ -15,10 +14,7 @@ import random
 import uuid
 from pathlib import Path
 from datetime import datetime
-from huggingface_hub import HfApi, hf_hub_download
-from huggingface_hub.utils import RepositoryNotFoundError, EntryNotFoundError
-import json
-import numpy as np
+from huggingface_hub import HfApi
 
 # -----------------------------------------------------------------------------
 # 0. Page Configuration (Must be the first Streamlit command)
@@ -35,10 +31,7 @@ INITIAL_BACKLOG = 0
 ORDER_PASSING_DELAY = 1 # Handled by last_week_orders
 SHIPPING_DELAY = 2 # General shipping delay (R->W, W->D)
 FACTORY_LEAD_TIME = 1
-# --------------------- THE REAL BUG FIX (LT=3) ---------------------
-# This MUST be 2 for LT=3. (Order W2 -> F Rec W3 -> F Prod W3 -> F Fin W4 -> F Ship W4 -> D Rec W5)
-FACTORY_SHIPPING_DELAY = 2 # Specific delay from Factory to Distributor
-# -------------------------------------------------------------------
+FACTORY_SHIPPING_DELAY = 1 # Specific delay from Factory to Distributor
 HOLDING_COST = 0.5
 BACKLOG_COST = 1.0
 
@@ -46,8 +39,7 @@ BACKLOG_COST = 1.0
 OPENAI_MODEL = "gpt-4o-mini"
 LOCAL_LOG_DIR = Path("logs")
 LOCAL_LOG_DIR.mkdir(exist_ok=True)
-IMAGE_PATH = "beer_game_diagram.png"
-LEADERBOARD_FILE = "leaderboard.json"
+IMAGE_PATH = "beer_game_diagram.png" # Path to your uploaded image
 
 # --- API & Secrets Configuration ---
 try:
@@ -64,45 +56,35 @@ else:
 # -----------------------------------------------------------------------------
 # 3. Core Game Logic Functions
 # -----------------------------------------------------------------------------
-
 def get_customer_demand(week: int) -> int:
     return 4 if week <= 4 else 8
 
-# =============== MODIFIED Initialization (v4.21 logic + v4.23 bugfix) ===============
-def init_game_state(llm_personality: str, info_sharing: str, participant_id: str):
+def init_game_state(llm_personality: str, info_sharing: str):
     roles = ["Retailer", "Wholesaler", "Distributor", "Factory"]
     human_role = "Distributor" # Role is fixed
-    
+    participant_id = str(uuid.uuid4())[:8]
     st.session_state.game_state = {
-        'game_running': True,
-        'participant_id': participant_id,
-        'week': 1,
+        'game_running': True, 'participant_id': participant_id, 'week': 1,
         'human_role': human_role, 'llm_personality': llm_personality,
         'info_sharing': info_sharing, 'logs': [], 'echelons': {},
         'factory_production_pipeline': deque([0] * FACTORY_LEAD_TIME, maxlen=FACTORY_LEAD_TIME),
         'decision_step': 'initial_order',
         'human_initial_order': None,
-        'current_ai_suggestion': None, # v4.23 Bugfix: 用于存储AI建议
-        'last_week_orders': {name: 0 for name in roles} # v4.21 Logic: 初始化为0
+        'last_week_orders': {name: 0 for name in roles}
     }
-
     for i, name in enumerate(roles):
         upstream = roles[i + 1] if i + 1 < len(roles) else None
         downstream = roles[i - 1] if i - 1 >= 0 else None
-        
-        # USE THE CORRECT DELAY
-        if name == "Distributor": shipping_weeks = FACTORY_SHIPPING_DELAY # This is 2
+        if name == "Distributor": shipping_weeks = FACTORY_SHIPPING_DELAY
         elif name == "Factory": shipping_weeks = 0
-        else: shipping_weeks = SHIPPING_DELAY # This is 2
-        
+        else: shipping_weeks = SHIPPING_DELAY
         st.session_state.game_state['echelons'][name] = {
             'name': name, 'inventory': INITIAL_INVENTORY, 'backlog': INITIAL_BACKLOG,
             'incoming_shipments': deque([0] * shipping_weeks, maxlen=shipping_weeks),
             'incoming_order': 0, 'order_placed': 0, 'shipment_sent': 0,
             'weekly_cost': 0, 'total_cost': 0, 'upstream_name': upstream, 'downstream_name': downstream,
         }
-    st.info(f"New game started for **{participant_id}**! AI Mode: **{llm_personality} / {info_sharing}**. You are the **{human_role}**.")
-# ==============================================================================
+    st.info(f"New game started! AI Mode: **{llm_personality} / {info_sharing}**. You are playing as the: **{human_role}**.")
 
 def get_llm_order_decision(prompt: str, echelon_name: str) -> (int, str):
     # This function remains correct.
@@ -122,20 +104,15 @@ def get_llm_order_decision(prompt: str, echelon_name: str) -> (int, str):
             match = re.search(r'\d+', raw_text)
             if match: return int(match.group(0)), raw_text
             st.warning(f"LLM for {echelon_name} did not return a valid number. Defaulting to 4. Raw Response: '{raw_text}'")
-            return 4, raw_text
+            return 4, raw_text # Default to 4
         except Exception as e:
             st.error(f"API call failed for {echelon_name}: {e}. Defaulting to 4.")
             return 4, f"API_ERROR: {e}"
 
-# =============== PROMPT FUNCTION (v3 - Sterman Heuristic + Demand Fix) ===============
 def get_llm_prompt(echelon_state_decision_point: dict, week: int, llm_personality: str, info_sharing: str, all_echelons_state_decision_point: dict) -> str:
-    # This function's logic is updated for "human_like" to follow a flawed Sterman heuristic.
+    # This function's logic remains correct (from v4.17).
     e_state = echelon_state_decision_point
     base_info = f"Your Current Status at the **{e_state['name']}** for **Week {week}** (Before Shipping):\n- On-hand inventory: {e_state['inventory']} units.\n- Backlog (total unfilled orders): {e_state['backlog']} units.\n- Incoming order this week (just received): {e_state['incoming_order']} units.\n"
-    
-    # --- PROMPT FIX: Get correct demand (current, not future) ---
-    current_stable_demand = get_customer_demand(week) # Use current week's demand
-    
     if e_state['name'] == 'Factory':
         task_word = "production quantity"
         base_info += f"- Your Production Pipeline (completing next week onwards): {list(st.session_state.game_state['factory_production_pipeline'])}"
@@ -143,15 +120,11 @@ def get_llm_prompt(echelon_state_decision_point: dict, week: int, llm_personalit
         task_word = "order quantity"
         base_info += f"- Shipments In Transit To You (arriving next week onwards): {list(e_state['incoming_shipments'])}"
 
-    # --- PERFECT RATIONAL (NORMATIVE) PROMPTS ---
-    
     if llm_personality == 'perfect_rational' and info_sharing == 'full':
-        stable_demand = current_stable_demand # Use the correct demand
-        # --------------------- LT=3 FIX ---------------------
-        if e_state['name'] == 'Factory': total_lead_time = FACTORY_LEAD_TIME # 1
-        elif e_state['name'] == 'Distributor': total_lead_time = ORDER_PASSING_DELAY + FACTORY_LEAD_TIME + FACTORY_SHIPPING_DELAY # 1+1+2 = 4
-        else: total_lead_time = ORDER_PASSING_DELAY + SHIPPING_DELAY # 1+2 = 3
-        # ----------------------------------------------------
+        stable_demand = 8
+        if e_state['name'] == 'Factory': total_lead_time = FACTORY_LEAD_TIME
+        elif e_state['name'] == 'Distributor': total_lead_time = ORDER_PASSING_DELAY + FACTORY_LEAD_TIME + FACTORY_SHIPPING_DELAY
+        else: total_lead_time = ORDER_PASSING_DELAY + SHIPPING_DELAY
         safety_stock = 4
         target_inventory_level = (stable_demand * total_lead_time) + safety_stock
         if e_state['name'] == 'Factory':
@@ -163,7 +136,7 @@ def get_llm_prompt(echelon_state_decision_point: dict, week: int, llm_personalit
             inv_pos_components = f"(Inv={e_state['inventory']} - Backlog={e_state['backlog']} + InTransitShip={sum(e_state['incoming_shipments'])} + OrderToSupplier={order_in_transit_to_supplier})"
         optimal_order = max(0, int(target_inventory_level - inventory_position))
         return f"**You are a perfectly rational supply chain AI with full system visibility.**\nYour only goal is to maintain stability and minimize costs based on mathematical optimization.\n**System Analysis:**\n* **Known Stable End-Customer Demand:** {stable_demand} units/week.\n* **Your Current Total Inventory Position:** {inventory_position} units. {inv_pos_components}\n* **Optimal Target Inventory Level:** {target_inventory_level} units (Target for {total_lead_time} weeks lead time).\n* **Mathematically Optimal {task_word.title()}:** The optimal decision is **{optimal_order} units**.\n**Your Task:** Confirm this optimal {task_word}. Respond with a single integer."
-    
+
     elif llm_personality == 'perfect_rational' and info_sharing == 'local':
         safety_stock = 4; anchor_demand = e_state['incoming_order']
         inventory_correction = safety_stock - (e_state['inventory'] - e_state['backlog'])
@@ -178,142 +151,59 @@ def get_llm_prompt(echelon_state_decision_point: dict, week: int, llm_personalit
         rational_local_order = max(0, int(calculated_order))
         return f"**You are a perfectly rational supply chain AI with ONLY LOCAL information.**\nYou must use a logical heuristic to make a stable decision. A proven method is \"Anchoring and Adjustment\".\n\n{base_info}\n\n**Rational Calculation (Anchoring & Adjustment):**\n1.  **Anchor on Demand:** Your best guess for future demand is your last incoming order: **{anchor_demand} units**.\n2.  **Adjust for Inventory:** You want to hold a safety stock of {safety_stock} units. Your current stock (before shipping) is {e_state['inventory'] - e_state['backlog']}. You need to order an extra **{inventory_correction} units** to correct this.\n3.  **Account for {supply_line_desc}:** You already have **{supply_line} units** being processed. These should be subtracted from your new decision.\n\n**Final Calculation:**\n* Decision = (Anchor Demand) + (Inventory Adjustment) - ({supply_line_desc})\n* Decision = {anchor_demand} + {inventory_correction} - {supply_line} = **{rational_local_order} units**.\n**Your Task:** Confirm this locally rational {task_word}. Respond with a single integer."
 
-    # --- HUMAN-LIKE (DESCRIPTIVE) PROMPTS ---
-    # (These are NEW and implement a flawed, panicky Sterman-style heuristic)
-    
-    else: # Catches both 'human_like' / 'local' and 'human_like' / 'full'
-        
-        # This is the flawed Sterman heuristic
-        DESIRED_INVENTORY = 12 # Matches initial inventory
-        anchor_demand = e_state['incoming_order']
-        net_inventory = e_state['inventory'] - e_state['backlog']
-        stock_correction = DESIRED_INVENTORY - net_inventory
-        panicky_order = max(0, int(anchor_demand + stock_correction))
-        panicky_order_calc = f"{anchor_demand} (Your Incoming Order) + {stock_correction} (Your Stock Correction)"
-        
-        # Get supply line info *just to show* the AI it's being ignored
-        if e_state['name'] == 'Factory':
-            supply_line = sum(st.session_state.game_state['factory_production_pipeline'])
-            supply_line_desc = "In Production"
-        else:
-            order_in_transit_to_supplier = st.session_state.game_state['last_week_orders'].get(e_state['name'], 0)
-            supply_line = sum(e_state['incoming_shipments']) + order_in_transit_to_supplier
-            supply_line_desc = "Supply Line"
-
-        if info_sharing == 'local':
-            return f"""
-            **You are a reactive supply chain manager for the {e_state['name']}.** You have a limited (local) view.
-            You tend to make **reactive, 'gut-instinct' decisions** (like the classic Sterman 1989 model) that cause the Bullwhip Effect.
-            
-            {base_info}
-
-            **Your Flawed 'Human' Heuristic:**
-            Your gut tells you to fix your entire inventory problem *right now*, and you're afraid of your backlog.
-            A 'rational' player would account for their {supply_line_desc} (which is {supply_line} units), but you're too busy panicking to trust that.
-
-            **Your 'Panic' Calculation (Ignoring the Supply Line):**
-            1.  **Anchor on Demand:** You just got an order for **{anchor_demand}** units. You'll order *at least* that.
-            2.  **Correct for Stock:** Your desired 'safe' inventory is {DESIRED_INVENTORY}. Your current net inventory is {net_inventory}. You need to order **{stock_correction}** more units to feel safe again.
-            3.  **Ignore Supply Line:** You'll ignore the **{supply_line} units** already in your pipeline.
-
-            **Final Panic Order:** (Your Incoming Order) + (Your Stock Correction)
-            * Order = {panicky_order_calc} = **{panicky_order} units**.
-            
-            **Your Task:** Confirm this 'gut-instinct' {task_word}. Respond with a single integer.
-            """
-        
-        elif info_sharing == 'full':
-            # Build the "Full Info" string just for context
-            full_info_str = f"\n**Full Supply Chain Information (State Before Shipping):**\n- End-Customer Demand this week: {current_stable_demand} units.\n"
-            for name, other_e_state in all_echelons_state_decision_point.items():
-                if name != e_state['name']: full_info_str += f"- {name}: Inv={other_e_state['inventory']}, Backlog={other_e_state['backlog']}\n"
-
-            return f"""
-            **You are a supply chain manager ({e_state['name']}) with full system visibility.**
-            {base_info}
-            {full_info_str}
-            
-            **A "Human-like" Flawed Decision:**
-            Even though you have full information, you are judged by *your own* performance (your inventory, your backlog).
-            You tend to react to your *local* situation (like the classic Sterman 1989 model) instead of using the complex full-system data.
-            A 'rational' player would use the end-customer demand ({current_stable_demand}) and account for the *entire* system, but your gut-instinct is to panic about *your* numbers.
-
-            **Your 'Panic' Calculation (Ignoring Full Info and Your Supply Line):**
-            1.  **Anchor on *Your* Demand:** You just got an order for **{anchor_demand}** units. You react to this, not the end-customer demand.
-            2.  **Correct for *Your* Stock:** Your desired 'safe' inventory is {DESIRED_INVENTORY}. Your current net inventory is {net_inventory}. You need to order **{stock_correction}** more units.
-            3.  **Ignore *Your* Supply Line:** You'll ignore the **{supply_line} units** in your own pipeline ({supply_line_desc}).
-
-            **Final Panic Order:** (Your Incoming Order) + (Your Stock Correction)
-            * Order = {panicky_order_calc} = **{panicky_order} units**.
-            
-            **Your Task:** Confirm this 'gut-instinct', locally-focused {task_word}. Respond with a single integer.
-            """
-# =========================================================
+    elif llm_personality == 'human_like' and info_sharing == 'full':
+        full_info_str = f"\n**Full Supply Chain Information (State Before Shipping):**\n- End-Customer Demand this week: {get_customer_demand(week)} units.\n"
+        for name, other_e_state in all_echelons_state_decision_point.items():
+            if name != e_state['name']: full_info_str += f"- {name}: Inv={other_e_state['inventory']}, Backlog={other_e_state['backlog']}\n"
+        return f"""
+        **You are a supply chain manager ({e_state['name']}) with full system visibility.**
+        You can see everyone's current inventory and backlog before shipping, and the real customer demand.
+        {base_info}
+        {full_info_str}
+        **Your Task:** Your primary responsibility is to meet the demand from your direct customer (your `Incoming order this week`: **{e_state['incoming_order']}** units), which contributes to your total current backlog of {e_state['backlog']}.
+        While you can see the stable end-customer demand ({get_customer_demand(week)} units), your priority is to fulfill the order you just received and manage your inventory/backlog.
+        You are still human and might get anxious about your own stock levels.
+        What {task_word} should you decide on this week? Respond with a single integer.
+        """
+
+    elif llm_personality == 'human_like' and info_sharing == 'local':
+        return f"""
+        **You are a reactive supply chain manager for the {e_state['name']}.** You have a limited view and tend to over-correct based on fear.
+        Your top priority is to NOT have a backlog.
+        {base_info}
+        **Your Task:** You just received an incoming order for **{e_state['incoming_order']}** units, adding to your total backlog.
+        Your gut instinct is to panic and {task_word.split(' ')[0]} enough to ensure you are never caught with a backlog again, considering your current inventory.
+        **React emotionally.** What is your knee-jerk {task_word}? Respond with a single integer.
+        """
 
-# =============== STEP_GAME (v8) - Stable Logic + Correct Log Fix ===============
 def step_game(human_final_order: int, human_initial_order: int, ai_suggestion: int):
-    # This version uses the stable v2 game logic AND the correct v5 logging fix
+    # This function's logic remains correct (from v4.17).
     state = st.session_state.game_state
     week, echelons, human_role = state['week'], state['echelons'], state['human_role']
     llm_personality, info_sharing = state['llm_personality'], state['info_sharing']
     echelon_order = ["Retailer", "Wholesaler", "Distributor", "Factory"]
     llm_raw_responses = {}
-    
-    # Capture opening state for logging
+
     opening_inventories = {name: e['inventory'] for name, e in echelons.items()}
     opening_backlogs = {name: e['backlog'] for name, e in echelons.items()}
 
-    # --- LOG FIX (v8): Capture UI-visible values BEFORE any pops ---
-    arrived_this_week_LOG = {name: 0 for name in echelon_order}
-    arriving_next_week_LOG = {name: 0 for name in echelon_order}
-    factory_q = state['factory_production_pipeline']
-    
-    # Factory UI Values
-    if factory_q:
-        arrived_this_week_LOG["Factory"] = factory_q[0] # Arrives this week
-    arriving_next_week_LOG["Factory"] = state['last_week_orders'].get("Distributor", 0) # Arrives next week
-    
-    # R, W, D UI Values
-    for name in ["Retailer", "Wholesaler", "Distributor"]:
-        shipment_q = echelons[name]['incoming_shipments']
-        if shipment_q:
-            arrived_this_week_LOG[name] = shipment_q[0] # Arrives this week (W+0)
-        
-        # This logic MUST match the UI logic (v8)
-        if name == 'Distributor':
-            # "Next" for Distributor is the *second* item in its queue (or factory pipeline)
-            # --------------------- LT=3 FIX ---------------------
-            # With maxlen=2, the queue [0, 4] -> [0] is this week, [1] is next week
-            if len(shipment_q) > 1:
-                arriving_next_week_LOG[name] = shipment_q[1]
-            # ----------------------------------------------------
-        elif name in ("Retailer", "Wholesaler"):
-            # "Next" for R/W is the *second* item in their queue
-            if len(shipment_q) > 1:
-                arriving_next_week_LOG[name] = shipment_q[1]
-    # --- END LOG FIX (v8) ---
-
-
-    # === NOW, THE STABLE (v2) GAME LOGIC ===
-    # This block is separate from the logging block above.
-    # It uses its *own* variables to run the game.
-    arrived_this_week_GAME = {name: 0 for name in echelon_order} # Use a fresh dict for game logic
+    arrived_this_week = {name: 0 for name in echelon_order}
     inventory_after_arrival = {}
+
     factory_state = echelons["Factory"]
     produced_units = 0
     if state['factory_production_pipeline']:
-        produced_units = state['factory_production_pipeline'].popleft() # POP
-        arrived_this_week_GAME["Factory"] = produced_units
+        produced_units = state['factory_production_pipeline'].popleft()
+        arrived_this_week["Factory"] = produced_units
     inventory_after_arrival["Factory"] = factory_state['inventory'] + produced_units
-    
+
     for name in ["Retailer", "Wholesaler", "Distributor"]:
         arrived_shipment = 0
         if echelons[name]['incoming_shipments']:
-            arrived_shipment = echelons[name]['incoming_shipments'].popleft() # POP
-            arrived_this_week_GAME[name] = arrived_shipment
+            arrived_shipment = echelons[name]['incoming_shipments'].popleft()
+            arrived_this_week[name] = arrived_shipment
         inventory_after_arrival[name] = echelons[name]['inventory'] + arrived_shipment
-    # === END STABLE (v2) GAME LOGIC ===
-        
+
     total_backlog_before_shipping = {}
     for name in echelon_order:
         incoming_order_for_this_week = 0
@@ -323,13 +213,15 @@ def step_game(human_final_order: int, human_initial_order: int, ai_suggestion: i
             if downstream_name: incoming_order_for_this_week = state['last_week_orders'].get(downstream_name, 0)
         echelons[name]['incoming_order'] = incoming_order_for_this_week
         total_backlog_before_shipping[name] = echelons[name]['backlog'] + incoming_order_for_this_week
+
     decision_point_states = {}
     for name in echelon_order:
-        decision_point_states[name] = {
-            'name': name, 'inventory': inventory_after_arrival[name],
-            'backlog': total_backlog_before_shipping[name], 'incoming_order': echelons[name]['incoming_order'],
-            'incoming_shipments': echelons[name]['incoming_shipments'].copy() if name != "Factory" else deque()
-        }
+         decision_point_states[name] = {
+             'name': name, 'inventory': inventory_after_arrival[name],
+             'backlog': total_backlog_before_shipping[name], 'incoming_order': echelons[name]['incoming_order'],
+             'incoming_shipments': echelons[name]['incoming_shipments'].copy() if name != "Factory" else deque(),
+         }
+
     current_week_orders = {}
     for name in echelon_order:
         e = echelons[name]; prompt_state = decision_point_states[name]
@@ -338,43 +230,34 @@ def step_game(human_final_order: int, human_initial_order: int, ai_suggestion: i
             prompt = get_llm_prompt(prompt_state, week, llm_personality, info_sharing, decision_point_states)
             order_amount, raw_resp = get_llm_order_decision(prompt, name)
         llm_raw_responses[name] = raw_resp; e['order_placed'] = max(0, order_amount); current_week_orders[name] = e['order_placed']
+
     state['factory_production_pipeline'].append(echelons["Factory"]['order_placed'])
+
     units_shipped = {name: 0 for name in echelon_order}
     for name in echelon_order:
         e = echelons[name]; demand_to_meet = total_backlog_before_shipping[name]; available_inv = inventory_after_arrival[name]
         e['shipment_sent'] = min(available_inv, demand_to_meet); units_shipped[name] = e['shipment_sent']
         e['inventory'] = available_inv - e['shipment_sent']; e['backlog'] = demand_to_meet - e['shipment_sent']
+
     if units_shipped["Factory"] > 0: echelons['Distributor']['incoming_shipments'].append(units_shipped["Factory"])
     if units_shipped['Distributor'] > 0: echelons['Wholesaler']['incoming_shipments'].append(units_shipped['Distributor'])
     if units_shipped['Wholesaler'] > 0: echelons['Retailer']['incoming_shipments'].append(units_shipped['Wholesaler'])
-    
-    # (Logging)
+
     log_entry = {'timestamp': datetime.utcnow().isoformat() + "Z", 'week': week, **state}
     del log_entry['echelons'], log_entry['factory_production_pipeline'], log_entry['logs'], log_entry['last_week_orders']
-    if 'current_ai_suggestion' in log_entry: del log_entry['current_ai_suggestion']
     for name in echelon_order:
         e = echelons[name]; e['weekly_cost'] = (e['inventory'] * HOLDING_COST) + (e['backlog'] * BACKLOG_COST); e['total_cost'] += e['weekly_cost']
         for key in ['inventory', 'backlog', 'incoming_order', 'order_placed', 'shipment_sent', 'weekly_cost', 'total_cost']: log_entry[f'{name}.{key}'] = e[key]
         log_entry[f'{name}.llm_raw_response'] = llm_raw_responses.get(name, "")
-        
-        # --- LOG FIX (v8): Use captured values ---
-        log_entry[f'{name}.opening_inventory'] = opening_inventories[name]
-        log_entry[f'{name}.opening_backlog'] = opening_backlogs[name]
-        log_entry[f'{name}.arrived_this_week'] = arrived_this_week_LOG[name] # Use captured
-        
-        if name != 'Factory': 
-            log_entry[f'{name}.arriving_next_week'] = arriving_next_week_LOG[name] # Use captured
-        else: 
-            log_entry[f'{name}.production_completing_next_week'] = arriving_next_week_LOG[name] # Use captured
-        # --- END OF LOG FIX (v8) ---
-            
+        log_entry[f'{name}.opening_inventory'] = opening_inventories[name]; log_entry[f'{name}.opening_backlog'] = opening_backlogs[name]
+        log_entry[f'{name}.arrived_this_week'] = arrived_this_week[name]
+        if name != 'Factory': log_entry[f'{name}.arriving_next_week'] = list(e['incoming_shipments'])[0] if e['incoming_shipments'] else 0
+        else: log_entry[f'{name}.production_completing_next_week'] = list(state['factory_production_pipeline'])[0] if state['factory_production_pipeline'] else 0
     log_entry[f'{human_role}.initial_order'] = human_initial_order; log_entry[f'{human_role}.ai_suggestion'] = ai_suggestion
     state['logs'].append(log_entry)
+
     state['week'] += 1; state['decision_step'] = 'initial_order'; state['last_week_orders'] = current_week_orders
-    state['current_ai_suggestion'] = None # Clean up
     if state['week'] > WEEKS: state['game_running'] = False
-# ==============================================================================
-
 
 def plot_results(df: pd.DataFrame, title: str, human_role: str):
     # This function remains correct.
@@ -406,134 +289,27 @@ def plot_results(df: pd.DataFrame, title: str, human_role: str):
         axes[3].set_title(f'Analysis of Your ({human_role}) Decisions - Error Plotting Data'); axes[3].text(0.5, 0.5, f"Error: {plot_err}", ha='center', va='center'); axes[3].grid(True, linestyle='--'); axes[3].set_xlabel('Week')
     plt.tight_layout(rect=[0, 0, 1, 0.96]); return fig
 
-
-# =============== NEW: Leaderboard Functions ===============
-@st.cache_data(ttl=60)
-def load_leaderboard_data():
-    if not hf_api or not HF_REPO_ID: return {}
-    try:
-        local_path = hf_hub_download(repo_id=HF_REPO_ID, repo_type="dataset", filename=LEADERBOARD_FILE, token=HF_TOKEN, cache_dir=LOCAL_LOG_DIR / "hf_cache")
-        with open(local_path, 'r', encoding='utf-8') as f: return json.load(f)
-    except EntryNotFoundError:
-        st.sidebar.info("Leaderboard file not found. A new one will be created.")
-        return {}
-    except Exception as e:
-        st.sidebar.error(f"Could not load leaderboard: {e}")
-        return {}
-
-def save_leaderboard_data(data):
-    if not hf_api or not HF_REPO_ID or not HF_TOKEN: return
-    try:
-        local_path = LOCAL_LOG_DIR / LEADERBOARD_FILE
-        with open(local_path, 'w', encoding='utf-8') as f: json.dump(data, f, indent=2, ensure_ascii=False)
-        hf_api.upload_file(path_or_fileobj=str(local_path), path_in_repo=LEADERBOARD_FILE, repo_id=HF_REPO_ID, repo_type="dataset", token=HF_TOKEN, commit_message="Update leaderboard")
-        st.sidebar.success("Leaderboard updated!")
-        st.cache_data.clear()
-    except Exception as e:
-        st.sidebar.error(f"Failed to upload leaderboard: {e}")
-
-def display_rankings(df, top_n=10):
-    if df.empty:
-        st.info("No completed games for this category yet. Be the first!")
-        return
-    df['total_cost'] = pd.to_numeric(df['total_cost'], errors='coerce')
-    df['order_std_dev'] = pd.to_numeric(df['order_std_dev'], errors='coerce')
-    df = df.dropna(subset=['total_cost', 'order_std_dev'])
-    if df.empty:
-        st.info("No valid completed games for this category yet.")
-        return
-    c1, c2, c3 = st.columns(3)
-    with c1:
-        st.subheader("🏆 Supply Chain Champions")
-        st.caption(f"Top {top_n} - Lowest Total Cost")
-        champs_df = df.sort_values('total_cost', ascending=True).head(top_n).copy()
-        champs_df['total_cost'] = champs_df['total_cost'].map('${:,.2f}'.format)
-        champs_df.rename(columns={'id': 'Participant', 'total_cost': 'Total Cost'}, inplace=True)
-        st.dataframe(champs_df[['Participant', 'Total Cost']], use_container_width=True, hide_index=True)
-    with c2:
-        st.subheader("👑 Bullwhip Kings")
-        st.caption(f"Top {top_n} - Highest Total Cost")
-        kings_df = df.sort_values('total_cost', ascending=False).head(top_n).copy()
-        kings_df['total_cost'] = kings_df['total_cost'].map('${:,.2f}'.format)
-        kings_df.rename(columns={'id': 'Participant', 'total_cost': 'Total Cost'}, inplace=True)
-        st.dataframe(kings_df[['Participant', 'Total Cost']], use_container_width=True, hide_index=True)
-    with c3:
-        st.subheader("🧘 Mr. Smooth")
-        st.caption(f"Top {top_n} - Lowest Order Variation (Std. Dev.)")
-        smooth_df = df.sort_values('order_std_dev', ascending=True).head(top_n).copy()
-        smooth_df['order_std_dev'] = smooth_df['order_std_dev'].map('{:,.2f}'.format)
-        smooth_df.rename(columns={'id': 'Participant', 'order_std_dev': 'Order Std. Dev.'}, inplace=True)
-        st.dataframe(smooth_df[['Participant', 'Order Std. Dev.']], use_container_width=True, hide_index=True)
-
-def show_leaderboard_ui():
-    st.markdown("---")
-    st.header("📊 The Bullwhip Leaderboard")
-    st.caption("Leaderboard updates after you finish a game. Cached for 60 seconds.")
-    leaderboard_data = load_leaderboard_data()
-    if not leaderboard_data:
-        st.info("No leaderboard data yet. Be the first to finish a game!")
-    else:
-        try:
-            df = pd.DataFrame(leaderboard_data.values())
-            if 'id' not in df.columns and not df.empty: df['id'] = list(leaderboard_data.keys())
-            if 'total_cost' not in df.columns or 'order_std_dev' not in df.columns or 'setting' not in df.columns:
-                st.error("Leaderboard data is corrupted or incomplete.")
-                return
-            groups = sorted(df.setting.unique())
-            tabs = st.tabs(["**Overall**"] + groups)
-            with tabs[0]: display_rankings(df)
-            for i, group_name in enumerate(groups):
-                with tabs[i+1]:
-                    df_group = df[df.setting == group_name].copy()
-                    display_rankings(df_group)
-        except Exception as e:
-            st.error(f"Error displaying leaderboard: {e}")
-            st.dataframe(leaderboard_data)
-
 def save_logs_and_upload(state: dict):
-    if not state.get('logs'):
-        st.warning("No log data to save.")
-        return
+    # This function remains correct.
+    if not state.get('logs'): return
     participant_id = state['participant_id']
-    logs_df = None
     try:
-        logs_df = pd.json_normalize(state['logs'])
-        safe_participant_id = re.sub(r'[^a-zA-Z0-9_-]', '_', participant_id)
-        fname = LOCAL_LOG_DIR / f"log_{safe_participant_id}_{int(time.time())}.csv"
-        for col in logs_df.select_dtypes(include=['object']).columns: logs_df[col] = logs_df[col].astype(str)
-        logs_df.to_csv(fname, index=False)
+        df = pd.json_normalize(state['logs'])
+        fname = LOCAL_LOG_DIR / f"log_{participant_id}_{int(time.time())}.csv"
+        for col in df.select_dtypes(include=['object']).columns: df[col] = df[col].astype(str)
+        df.to_csv(fname, index=False)
         st.success(f"Log successfully saved locally: `{fname}`")
         with open(fname, "rb") as f: st.download_button("📥 Download Log CSV", data=f, file_name=fname.name, mime="text/csv")
         if HF_TOKEN and HF_REPO_ID and hf_api:
-            with st.spinner("Uploading log CSV to Hugging Face Hub..."):
+            with st.spinner("Uploading log to Hugging Face Hub..."):
                 try:
                     url = hf_api.upload_file( path_or_fileobj=str(fname), path_in_repo=f"logs/{fname.name}", repo_id=HF_REPO_ID, repo_type="dataset", token=HF_TOKEN)
-                    st.success(f"✅ Log CSV successfully uploaded! [View File]({url})")
+                    st.success(f"✅ Log successfully uploaded to Hugging Face! [View File]({url})")
                 except Exception as e_upload: st.error(f"Upload to Hugging Face failed: {e_upload}")
-    except Exception as e_save:
-        st.error(f"Error processing or saving log CSV: {e_save}")
-        return
-    if logs_df is None: return
-    st.subheader("Updating Leaderboard...")
-    try:
-        human_role = state['human_role']
-        total_cost = logs_df[f'{human_role}.total_cost'].iloc[-1]
-        order_std_dev = logs_df[f'{human_role}.order_placed'].std()
-        setting_name = f"{state['llm_personality']} / {state['info_sharing']}"
-        new_entry = {
-            'id': participant_id, 'setting': setting_name,
-            'total_cost': float(total_cost),
-            'order_std_dev': float(order_std_dev) if pd.notna(order_std_dev) else 0.0
-        }
-        leaderboard_data = load_leaderboard_data()
-        leaderboard_data[participant_id] = new_entry 
-        save_leaderboard_data(leaderboard_data)
-    except Exception as e_board:
-        st.error(f"Error calculating or saving leaderboard score: {e_board}")
-# ==============================================================================
+    except Exception as e_save: st.error(f"Error processing or saving log data: {e_save}")
 
 # -----------------------------------------------------------------------------
-# 4. Streamlit UI (Applying v4.22 + v4.23 fixes)
+# 4. Streamlit UI (Adjusted Dashboard Labels & Logic)
 # -----------------------------------------------------------------------------
 st.title("🍺 The Beer Game: A Human-AI Collaboration Challenge")
 
@@ -543,75 +319,56 @@ else:
     # --- Game Setup & Instructions ---
     if 'game_state' not in st.session_state or not st.session_state.game_state.get('game_running', False):
         
-        st.markdown("---")
-        st.header("⚙️ Game Configuration")
-        
-        # =============== NEW: Participant ID Input ===============
-        participant_id = st.text_input("Enter Your Name or Team ID:", key="participant_id_input", placeholder="e.g., Team A")
-        # =======================================================
+        # --- Introduction Section Removed as Requested ---
         
+        st.header("⚙️ Game Configuration")
         c1, c2 = st.columns(2)
         with c1:
-            llm_personality = st.selectbox("AI Agent 'Personality'", ('human_like', 'perfect_rational'), format_func=lambda x: x.replace('_', ' ').title(), help="**Human-like:** Tends to react emotionally, potentially over-ordering. **Perfect Rational:** Uses a mathematical heuristic to make stable, logical decisions.")
+             llm_personality = st.selectbox("AI Agent 'Personality'", ('human_like', 'perfect_rational'), format_func=lambda x: x.replace('_', ' ').title(), help="**Human-like:** Tends to react emotionally, potentially over-ordering. **Perfect Rational:** Uses a mathematical heuristic to make stable, logical decisions.")
         with c2:
             info_sharing = st.selectbox("Information Sharing Level", ('local', 'full'), format_func=lambda x: x.title(), help="**Local:** You and the AI agents can only see your own inventory and incoming orders. **Full:** Everyone can see the entire supply chain's status and the true end-customer demand.")
-
-        # =============== MODIFIED: Start Game Button ===============
-        if st.button("🚀 Start Game", type="primary", disabled=(client is None)):
-            if not participant_id:
-                st.error("Please enter a Name or Team ID to start!")
-            else:
-                existing_data = load_leaderboard_data()
-                if participant_id in existing_data:
-                    # 如果ID已存在，添加一个session_state标志，要求再次点击
-                    if st.session_state.get('last_id_warning') == participant_id:
-                        # 这是第二次点击，确认覆盖
-                        st.session_state.pop('last_id_warning', None)
-                        init_game_state(llm_personality, info_sharing, participant_id)
-                        st.rerun()
-                    else:
-                        st.session_state['last_id_warning'] = participant_id
-                        st.warning(f"ID '{participant_id}' already exists! Your score will be overwritten. Click 'Start Game' again to confirm.")
-                else:
-                    # 新ID，直接开始
-                    if 'last_id_warning' in st.session_state:
-                        del st.session_state['last_id_warning']
-                    init_game_state(llm_personality, info_sharing, participant_id)
-                    st.rerun()
-        # ===========================================================
         
-        # =============== NEW: Show Leaderboard on Start Page ===============
-        show_leaderboard_ui()
-        # =================================================================
+        if st.button("🚀 Start Game", type="primary", disabled=(client is None)):
+            init_game_state(llm_personality, info_sharing)
+            st.rerun()
 
     # --- Main Game Interface ---
     elif 'game_state' in st.session_state and st.session_state.game_state.get('game_running'):
         state = st.session_state.game_state
         week, human_role, echelons, info_sharing = state['week'], state['human_role'], state['echelons'], state['info_sharing']
         echelon_order = ["Retailer", "Wholesaler", "Distributor", "Factory"] # Define here for UI
-
-
+        
         st.header(f"Week {week} / {WEEKS}")
-        st.subheader(f"Your Role: **{human_role}** ({state['participant_id']}) | AI Mode: **{state['llm_personality'].replace('_', ' ')}** | Information: **{state['info_sharing']}**")
+        st.subheader(f"Your Role: **{human_role}** | AI Mode: **{state['llm_personality'].replace('_', ' ')}** | Information: **{state['info_sharing']}**")
         st.markdown("---")
-        st.subheader("Supply Chain Status (Start of Week State)") 
-
-        # =============== MODIFIED UI LOGIC (v8) ===============
+        
+        st.subheader("Supply Chain Status (Start of Week State)") # Clarified Timing
+        
         if info_sharing == 'full':
             cols = st.columns(4)
-            for i, name in enumerate(echelon_order):
+            for i, name in enumerate(echelon_order): # Use the defined echelon_order
                 with cols[i]:
-                    e = echelons[name]
+                    e = echelons[name] # Get the echelon state
                     icon = "👤" if name == human_role else "🤖"
-
+                    
+                    # =============== UI CHANGE: Highlight Player ===============
                     if name == human_role:
+                        # Use markdown with HTML/CSS for highlighting
                         st.markdown(f"##### **<span style='border: 1px solid #FF4B4B; padding: 2px 5px; border-radius: 3px;'>{icon} {name} (You)</span>**", unsafe_allow_html=True)
                     else:
                         st.markdown(f"##### {icon} {name}")
+                    # ========================================================
                     
+                    # Display the END OF LAST WEEK state (which is OPENING state for this week)
                     st.metric("Inventory (Opening)", e['inventory'])
                     st.metric("Backlog (Opening)", e['backlog'])
                     
+                    # =============== UI CHANGE: Removed Costs ===============
+                    # Costs are no longer displayed on the main dashboard
+                    # =======================================================
+                    
+                    # Display info about THIS week's events / NEXT week's arrivals
+                    # Calculate the INCOMING order for THIS week
                     current_incoming_order = 0
                     if name == "Retailer":
                         current_incoming_order = get_customer_demand(week)
@@ -619,57 +376,40 @@ else:
                         downstream_name = e['downstream_name']
                         if downstream_name:
                             current_incoming_order = state['last_week_orders'].get(downstream_name, 0)
-                    st.write(f"Incoming Order (This Week): **{current_incoming_order}**") 
-                                            
+                    
+                    st.write(f"Incoming Order (This Week): **{current_incoming_order}**") # Display calculated order
+                    
+                    # Display prediction for NEXT week's arrivals
                     if name == "Factory":
-                        prod_completing_next = state['last_week_orders'].get("Distributor", 0)
+                        prod_completing_next = list(state['factory_production_pipeline'])[0] if state['factory_production_pipeline'] else 0
                         st.write(f"Completing Next Week: **{prod_completing_next}**")
                     else:
-                        arriving_next = 0
-                        
-                        # This logic matches the v8 Log Fix
-                        if name == 'Distributor':
-                            # --------------------- LT=3 FIX ---------------------
-                            q = e['incoming_shipments']
-                            if len(q) > 1: arriving_next = list(q)[1]
-                            # ----------------------------------------------------
-                        elif name in ('Wholesaler', 'Retailer'):
-                            # "Next" for R/W is the *second* item in their queue
-                            q = e['incoming_shipments']
-                            if len(q) > 1: arriving_next = list(q)[1]
-                        
+                        arriving_next = list(e['incoming_shipments'])[0] if e['incoming_shipments'] else 0
                         st.write(f"Arriving Next Week: **{arriving_next}**")
-        
         else: # Local Info Mode
             st.info("In Local Information mode, you can only see your own status dashboard.")
-            e = echelons[human_role] # Distributor
-            st.markdown(f"### 👤 **<span style='color:#FF4B4B;'>{human_role} (Your Dashboard - Start of Week State)</span>**", unsafe_allow_html=True)
-
-            col1, col2, col3 = st.columns(3)
-            with col1:
-                st.metric("Inventory (Opening)", e['inventory'])
-                st.metric("Backlog (Opening)", e['backlog'])
+            e = echelons[human_role]
+            st.markdown(f"### 👤 **<span style='color:#FF4B4B;'>{human_role} (Your Dashboard - Start of Week State)</span>**", unsafe_allow_html=True) # Highlight self
+            col1, col2, col3, col4 = st.columns(4)
             
-            with col2:
-                current_incoming_order = 0
-                downstream_name = e['downstream_name'] # Wholesaler
-                if downstream_name:
-                    current_incoming_order = state['last_week_orders'].get(downstream_name, 0)
-                st.write(f"**Incoming Order (This Week):**\n# {current_incoming_order}")
-                
-            with col3:
-                # --------------------- LOCAL UI FIX V8 ---------------------
-                # "Arriving Next Week" for Distributor in LOCAL mode.
-                # With LT=3 (maxlen=2), we can now show list(q)[1]
-                arriving_next = 0
-                q = e['incoming_shipments']
-                if len(q) > 1:
-                     arriving_next = list(q)[1]
-                st.write(f"**Shipment Arriving (Next Week):**\n# {arriving_next}")
-                # -----------------------------------------------------------
-
-        # =======================================================
-                
+            # Display OPENING state
+            col1.metric("Inventory (Opening)", e['inventory'])
+            col2.metric("Backlog (Opening)", e['backlog'])
+            
+            # Display info about THIS week's events / NEXT week's arrivals
+            # Calculate the INCOMING order for THIS week
+            current_incoming_order = 0
+            downstream_name = e['downstream_name'] # Wholesaler
+            if downstream_name:
+                 current_incoming_order = state['last_week_orders'].get(downstream_name, 0)
+            
+            col3.write(f"**Incoming Order (This Week):**\n# {current_incoming_order}") # Display calculated order
+            col4.write(f"**Shipment Arriving (Next Week):**\n# {list(e['incoming_shipments'])[0] if e['incoming_shipments'] else 0}")
+            
+            # =============== UI CHANGE: Removed Costs ===============
+            # Costs are no longer displayed on the main dashboard
+            # =======================================================
+
         st.markdown("---")
         st.header("Your Decision (Step 4)")
 
@@ -678,63 +418,66 @@ else:
         for name in echelon_order:
             e_curr = echelons[name] # This is END OF LAST WEEK state
             arrived = 0
+            # Peek at what *will* arrive this week (Step 1) based on current queues
             if name == "Factory":
-                if state['factory_production_pipeline']: arrived = list(state['factory_production_pipeline'])[0]
+                 if state['factory_production_pipeline']: arrived = list(state['factory_production_pipeline'])[0]
             else:
-                if e_curr['incoming_shipments']: arrived = list(e_curr['incoming_shipments'])[0]
+                 if e_curr['incoming_shipments']: arrived = list(e_curr['incoming_shipments'])[0]
             
+            # Calculate the state AFTER arrivals and incoming orders for the prompt
+            inv_after_arrival = e_curr['inventory'] + arrived
+            
+            # Determine incoming order for *this* week again for prompt state
             inc_order_this_week = 0
             if name == "Retailer": inc_order_this_week = get_customer_demand(week)
             else:
                 ds_name = e_curr['downstream_name']
                 if ds_name: inc_order_this_week = state['last_week_orders'].get(ds_name, 0)
-
-            inv_after_arrival = e_curr['inventory'] + arrived
+            
             backlog_after_new_order = e_curr['backlog'] + inc_order_this_week
             
-            # This is the state used for the prompt, it's calculated BEFORE the pop
             all_decision_point_states[name] = {
                 'name': name, 'inventory': inv_after_arrival, 'backlog': backlog_after_new_order,
-                'incoming_order': inc_order_this_week, 
+                'incoming_order': inc_order_this_week, # Use the correctly calculated incoming order
                 'incoming_shipments': e_curr['incoming_shipments'].copy() if name != "Factory" else deque()
             }
+        
         human_echelon_state_for_prompt = all_decision_point_states[human_role]
 
-
         if state['decision_step'] == 'initial_order':
             with st.form(key="initial_order_form"):
                 st.markdown("#### **Step 4a:** Based on the dashboard, submit your **initial** order to the Factory.")
-                initial_order = st.number_input("Your Initial Order Quantity:", min_value=0, step=1, value=None) # Start blank
+                # =============== UI CHANGE: Removed Default Value ===============
+                initial_order = st.number_input("Your Initial Order Quantity:", min_value=0, step=1) # No 'value' argument
+                # ===============================================================
                 if st.form_submit_button("Submit Initial Order & See AI Suggestion", type="primary"):
+                    # Handle case where user leaves it blank (input returns None)
                     state['human_initial_order'] = int(initial_order) if initial_order is not None else 0
                     state['decision_step'] = 'final_order'
-                    
-                    # --- NEW: Calculate and store suggestion ONCE ---
-                    prompt_sugg = get_llm_prompt(human_echelon_state_for_prompt, week, state['llm_personality'], state['info_sharing'], all_decision_point_states)
-                    ai_suggestion, _ = get_llm_order_decision(prompt_sugg, f"{human_role} (Suggestion)")
-                    state['current_ai_suggestion'] = ai_suggestion # Store it
-                    # ------------------------------------------------
-                    
                     st.rerun()
 
         elif state['decision_step'] == 'final_order':
             st.success(f"Your initial order was: **{state['human_initial_order']}** units.")
             
-            # --- NEW: Read stored suggestion ---
-            ai_suggestion = state.get('current_ai_suggestion', 4) # Read stored value
-            # -----------------------------------
-
+            # Use the correctly timed state for the prompt
+            prompt_sugg = get_llm_prompt(human_echelon_state_for_prompt, week, state['llm_personality'], state['info_sharing'], all_decision_point_states)
+            ai_suggestion, _ = get_llm_order_decision(prompt_sugg, f"{human_role} (Suggestion)")
+            
             with st.form(key="final_order_form"):
                 st.markdown(f"#### **Step 4b:** The AI suggests ordering **{ai_suggestion}** units.")
                 st.markdown("Considering the AI's advice, submit your **final** order to end the week. (This order will arrive in 3 weeks).")
-                st.number_input("Your Final Order Quantity:", min_value=0, step=1, key='final_order_input', value=None) # Start blank
+                # =============== UI CHANGE: Removed Default Value ===============
+                st.number_input("Your Final Order Quantity:", min_value=0, step=1, key='final_order_input') # No 'value' argument
+                # ===============================================================
                 
                 if st.form_submit_button("Submit Final Order & Advance to Next Week"):
-                    final_order_value = st.session_state.get('final_order_input', 0)
+                    # Handle case where user leaves it blank
+                    final_order_value = st.session_state.get('final_order_input', 0) # Use .get with default
                     final_order_value = int(final_order_value) if final_order_value is not None else 0
-                                            
+                    
                     step_game(final_order_value, state['human_initial_order'], ai_suggestion)
                     
+                    # Clean up session state for the input key
                     if 'final_order_input' in st.session_state: del st.session_state.final_order_input
                     st.rerun()
 
@@ -745,25 +488,22 @@ else:
             else:
                 try:
                     history_df = pd.json_normalize(state['logs'])
-                    # FIX: Removed 'Arrived This Week' from log UI
                     human_cols = {
                         'week': 'Week', f'{human_role}.opening_inventory': 'Opening Inv.',
-                        f'{human_role}.opening_backlog': 'Opening Backlog', 
+                        f'{human_role}.opening_backlog': 'Opening Backlog', f'{human_role}.arrived_this_week': 'Arrived This Week',
                         f'{human_role}.incoming_order': 'Incoming Order', f'{human_role}.initial_order': 'Your Initial Order',
                         f'{human_role}.ai_suggestion': 'AI Suggestion', f'{human_role}.order_placed': 'Your Final Order',
                         f'{human_role}.arriving_next_week': 'Arriving Next Week', f'{human_role}.weekly_cost': 'Weekly Cost',
                     }
-                    # FIX: Removed 'Arrived This Week' from log UI
                     ordered_display_cols_keys = [
                         'week', f'{human_role}.opening_inventory', f'{human_role}.opening_backlog',
-                        f'{human_role}.incoming_order',
+                        f'{human_role}.arrived_this_week', f'{human_role}.incoming_order',
                         f'{human_role}.initial_order', f'{human_role}.ai_suggestion', f'{human_role}.order_placed',
                         f'{human_role}.arriving_next_week', f'{human_role}.weekly_cost'
-                    ]
+                     ]
                     final_cols_to_display = [col for col in ordered_display_cols_keys if col in history_df.columns]
-
                     if not final_cols_to_display:
-                        st.write("No data columns available to display.")
+                         st.write("No data columns available to display.")
                     else:
                         display_df = history_df[final_cols_to_display].rename(columns=human_cols)
                         if 'Weekly Cost' in display_df.columns:
@@ -774,12 +514,10 @@ else:
 
         try: st.sidebar.image(IMAGE_PATH, caption="Supply Chain Reference")
         except FileNotFoundError: st.sidebar.warning("Image file not found.")
-
         st.sidebar.header("Game Info")
         st.sidebar.markdown(f"**Game ID**: `{state['participant_id']}`\n\n**Current Week**: {week}")
         if st.sidebar.button("🔄 Reset Game"):
             if 'final_order_input' in st.session_state: del st.session_state.final_order_input
-            if 'current_ai_suggestion' in st.session_state.game_state: del st.session_state.game_state['current_ai_suggestion']
             del st.session_state.game_state
             st.rerun()
 
@@ -795,12 +533,10 @@ else:
                 state['human_role']
             )
             st.pyplot(fig)
-            save_logs_and_upload(state) # This now also updates the leaderboard
+            save_logs_and_upload(state)
         except Exception as e:
             st.error(f"Error generating final report: {e}")
 
-        show_leaderboard_ui()
-
         if st.button("✨ Start a New Game"):
             del st.session_state.game_state
             st.rerun()