Update app.py

app.py

@@ -1,6 +1,5 @@
 # app.py
 # @title Beer Game Final Version (v12 - v3 Base + Logic/UI Fix)
-
 # -----------------------------------------------------------------------------
 # 1. Import Libraries
 # -----------------------------------------------------------------------------
@@ -47,9 +46,17 @@ LOCAL_LOG_DIR.mkdir(exist_ok=True)
 IMAGE_PATH = "beer_game_diagram.png"
 LEADERBOARD_FILE = "leaderboard.json"
 
+# --- 实验条件配置：新增常量 ---
+EXPERIMENT_SETTINGS = [
+    ('human_like', 'local'),
+    ('human_like', 'full'),
+    ('perfect_rational', 'local'),
+    ('perfect_rational', 'full'),
+]
 # --- API & Secrets Configuration ---
 try:
-    client = openai.OpenAI(api_key=st.secrets["OPENAI_API_KEY"])
+    # 注意：在多Space部署中，每个Space的secrets中只放一个API KEY
+    client = openai.OpenAI(api_key=st.secrets["OPENAI_API_KEY"]) 
     HF_TOKEN = st.secrets.get("HF_TOKEN")
     HF_REPO_ID = st.secrets.get("HF_REPO_ID")
     hf_api = HfApi() if HF_TOKEN else None
@@ -58,11 +65,9 @@ except Exception as e:
     client = None
 else:
     st.session_state.initialization_error = None
-
 # -----------------------------------------------------------------------------
 # 3. Core Game Logic Functions
 # -----------------------------------------------------------------------------
-
 def get_customer_demand(week: int) -> int:
     return 4 if week <= 4 else 8
 
@@ -70,7 +75,7 @@ def get_customer_demand(week: int) -> int:
 def init_game_state(llm_personality: str, info_sharing: str, participant_id: str):
     roles = ["Retailer", "Wholesaler", "Distributor", "Factory"]
     human_role = "Distributor" # Role is fixed
-    
+        
     st.session_state.game_state = {
         'game_running': True,
         'participant_id': participant_id,
@@ -83,7 +88,6 @@ def init_game_state(llm_personality: str, info_sharing: str, participant_id: str
         '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
     }
-
     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
@@ -98,9 +102,9 @@ def init_game_state(llm_personality: str, info_sharing: str, participant_id: str
         }
     st.info(f"New game started for **{participant_id}**! AI Mode: **{llm_personality} / {info_sharing}**. You are the **{human_role}**.")
 # ==============================================================================
-
 def get_llm_order_decision(prompt: str, echelon_name: str) -> (int, str):
     # This function remains correct.
+    # 注意：client 现在是全局的，所有用户的API请求都通过它进行。
     if not client: return 8, "NO_API_KEY_DEFAULT"
     with st.spinner(f"Getting AI decision for {echelon_name}..."):
         try:
@@ -121,7 +125,6 @@ def get_llm_order_decision(prompt: str, echelon_name: str) -> (int, str):
         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 (v4 - FIXES FOR OSCILLATION AND HUMAN-LIKE) ===============
 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.
@@ -136,7 +139,6 @@ def get_llm_prompt(echelon_state_decision_point: dict, week: int, llm_personalit
     else:
         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':
@@ -161,7 +163,7 @@ def get_llm_prompt(echelon_state_decision_point: dict, week: int, llm_personalit
             supply_line = sum(st.session_state.game_state['factory_production_pipeline'])
             inventory_position = (e_state['inventory'] - e_state['backlog'] + supply_line)
             inv_pos_components = f"(Inv={e_state['inventory']} - Backlog={e_state['backlog']} + InProd={supply_line})"
-        
+            
         elif e_state['name'] == 'Distributor':
             # Distributor pipeline: In Shipping (1 week) + In Production (1 week) + Order Delay (1 week)
             in_shipping = sum(e_state['incoming_shipments'])
@@ -169,17 +171,16 @@ def get_llm_prompt(echelon_state_decision_point: dict, week: int, llm_personalit
             supply_line = in_shipping + in_production + order_in_transit_to_supplier
             inventory_position = (e_state['inventory'] - e_state['backlog'] + supply_line)
             inv_pos_components = f"(Inv={e_state['inventory']} - Backlog={e_state['backlog']} + InTransitShip={in_shipping} + InProd={in_production} + OrderToSupplier={order_in_transit_to_supplier})"
-        
+            
         else: # Retailer and Wholesaler
             # R/W pipeline: In Shipping (2 weeks) + Order Delay (1 week)
             in_shipping = sum(e_state['incoming_shipments'])
             supply_line = in_shipping + order_in_transit_to_supplier
             inventory_position = (e_state['inventory'] - e_state['backlog'] + supply_line)
             inv_pos_components = f"(Inv={e_state['inventory']} - Backlog={e_state['backlog']} + InTransitShip={in_shipping} + 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']
@@ -190,7 +191,7 @@ def get_llm_prompt(echelon_state_decision_point: dict, week: int, llm_personalit
             # Factory can see its full (local) pipeline
             supply_line = sum(st.session_state.game_state['factory_production_pipeline'])
             supply_line_desc = "In Production"
-        
+            
         elif e_state['name'] == 'Distributor':
             # Distributor can *only* see its shipping queue (1 week)
             # It CANNOT see the factory pipeline or its own order delay
@@ -209,7 +210,6 @@ def get_llm_prompt(echelon_state_decision_point: dict, week: int, llm_personalit
         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 (that you can see). 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 ---
-    
     else: 
         DESIRED_INVENTORY = 12 # Matches initial inventory
         net_inventory = e_state['inventory'] - e_state['backlog']
@@ -230,28 +230,24 @@ def get_llm_prompt(echelon_state_decision_point: dict, week: int, llm_personalit
             anchor_demand = e_state['incoming_order']
             panicky_order = max(0, int(anchor_demand + stock_correction))
             panicky_order_calc = f"{anchor_demand} (Your Incoming Order) + {stock_correction} (Your Stock Correction)"
-
             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':
             # 1. HUMAN-LIKE / FULL (FIX v6): Anchors on an *average* of local panic and global reality
             local_anchor = e_state['incoming_order']
@@ -262,35 +258,30 @@ def get_llm_prompt(echelon_state_decision_point: dict, week: int, llm_personalit
             
             panicky_order = max(0, int(anchor_demand + stock_correction))
             panicky_order_calc = f"{anchor_demand} (Conflicted Anchor) + {stock_correction} (Your Stock Correction)"
-
             # 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:**
             You are judged by *your own* performance. You can see the stable End-Customer Demand is **{global_anchor}**, but you just received a panicky order for **{local_anchor}**.
             Your "gut-instinct" is to split the difference, anchoring on an average of the two.
             You still ignore your supply line, focusing only on your local stock.
-
             **Your 'Panic' Calculation (Ignoring Supply Line, Averaging Anchors):**
             1.  **Anchor on Conflict:** (Your Incoming Order + End-Customer Demand) / 2
                 * Anchor = ({local_anchor} + {global_anchor}) / 2 = **{anchor_demand}** units.
             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:** (Conflicted Anchor) + (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.
             """
 # =========================================================
-
 # =============== STEP_GAME (v12) - Stable Logic + Correct Log Fix ===============
 def step_game(human_final_order: int, human_initial_order: int, ai_suggestion: int):
     # This is the correct logic from v4.17
@@ -299,51 +290,37 @@ def step_game(human_final_order: int, human_initial_order: int, ai_suggestion: i
     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 (v12): Capture arrival data BEFORE mutation ---
     arrived_this_week = {name: 0 for name in echelon_order}
     # This dict will store the value shown on the UI for "next week"
     opening_arriving_next_week_UI_VALUE = {name: 0 for name in echelon_order} 
-    
+        
     # Factory
     factory_q = state['factory_production_pipeline']
     if factory_q:
         arrived_this_week["Factory"] = factory_q[0] # Read before pop
     # "Next Week" for Factory is the order it just received (Distributor's last week order)
     opening_arriving_next_week_UI_VALUE["Factory"] = state['last_week_orders'].get("Distributor", 0)
-
     # R, W, D
     for name in ["Retailer", "Wholesaler", "Distributor"]:
         shipment_q = echelons[name]['incoming_shipments']
         if shipment_q:
             arrived_this_week[name] = shipment_q[0] # Read before pop
-        
+                
         # --- THIS IS THE REAL FIX V12 ---
         if name == 'Distributor':
             # "Next" for Distributor (maxlen=1) is the item that will arrive W+1
-            # At the start of W4, shipping_q = [4] (from W2). This item arrives W5.
-            # So, "Arriving Next Week" (W5) IS shipment_q[0].
             if shipment_q:
                 opening_arriving_next_week_UI_VALUE[name] = shipment_q[0]
         elif name in ("Retailer", "Wholesaler"):
             # "Next" for R/W (maxlen=2) is the item that will arrive W+1
-            # At start of W4, shipping_q = [0, 4]. [0] arrives W5, [1] arrives W6.
-            # "Arriving Next Week" (W5) IS shipment_q[0].
-            # (Wait, no, [0] arrives W4, [1] arrives W5)
-            # (Let's re-trace R/W)
-            # W2: D ships 4. R/W q.append(4) -> [0, 4]
-            # W3: R/W popleft() -> 0 arrives. q = [4].
-            # W3: D ships 8. R/W q.append(8) -> [4, 8]
-            # W4: R/W popleft() -> 4 arrives. q = [8].
-            # At start of W4, "Arriving Next Week" (W5) is q[0] = 8.
             if shipment_q:
                 opening_arriving_next_week_UI_VALUE[name] = shipment_q[0]
     # --- END OF LOG FIX (v12) ---
-
     # Now, the *actual* state mutation (popping)
     inventory_after_arrival = {}
     factory_state = echelons["Factory"]
@@ -351,7 +328,7 @@ def step_game(human_final_order: int, human_initial_order: int, ai_suggestion: i
     if state['factory_production_pipeline']:
         produced_units = state['factory_production_pipeline'].popleft()
     inventory_after_arrival["Factory"] = factory_state['inventory'] + produced_units
-    
+        
     # --- LOGIC FIX (v12) ---
     for name in ["Retailer", "Wholesaler", "Distributor"]:
         # Use the value we captured *before* popping
@@ -360,7 +337,7 @@ def step_game(human_final_order: int, human_initial_order: int, ai_suggestion: i
             echelons[name]['incoming_shipments'].popleft() # Now we pop
         inventory_after_arrival[name] = echelons[name]['inventory'] + arrived_shipment
     # --- END LOGIC FIX (v12) ---
-        
+            
     # (Rest of game logic)
     total_backlog_before_shipping = {}
     for name in echelon_order:
@@ -371,6 +348,7 @@ 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] = {
@@ -386,16 +364,19 @@ 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']
@@ -404,26 +385,24 @@ def step_game(human_final_order: int, human_initial_order: int, ai_suggestion: i
         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 (v12): 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[name] # Use captured value
-        
+                
         if name != 'Factory': 
             log_entry[f'{name}.arriving_next_week'] = opening_arriving_next_week_UI_VALUE[name]
         else: 
             log_entry[f'{name}.production_completing_next_week'] = opening_arriving_next_week_UI_VALUE[name]
         # --- END OF LOG FIX (v12) ---
-            
-    log_entry[f'{human_role}.initial_order'] = human_initial_order; log_entry[f'{human_role}.ai_suggestion'] = ai_suggestion
+                
+        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.
     fig, axes = plt.subplots(4, 1, figsize=(12, 22))
@@ -453,8 +432,6 @@ def plot_results(df: pd.DataFrame, title: str, human_role: str):
     except (KeyError, ValueError) as plot_err:
         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 (MODIFIED) ===============
 @st.cache_data(ttl=60)
 def load_leaderboard_data():
@@ -468,7 +445,6 @@ def load_leaderboard_data():
     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:
@@ -479,20 +455,17 @@ def save_leaderboard_data(data):
         st.cache_data.clear()
     except Exception as e:
         st.sidebar.error(f"Failed to upload leaderboard: {e}")
-
 # ---------- MODIFIED FUNCTION (v2) ----------
 def display_rankings(df, top_n=10):
     if df.empty:
         st.info("No completed games for this category yet. Be the first!")
         return
-    
+        
     # 为新旧数据列进行数值转换
     df['distributor_cost'] = pd.to_numeric(df.get('total_cost'), errors='coerce') # 'total_cost' 是旧的 distributor_cost
     df['total_chain_cost'] = pd.to_numeric(df.get('total_chain_cost'), errors='coerce')
     df['order_std_dev'] = pd.to_numeric(df.get('order_std_dev'), errors='coerce')
-
     c1, c2, c3 = st.columns(3)
-
     # 排行榜 1: 总供应链成本 (新)
     with c1:
         st.subheader("🏆 Supply Chain Champions")
@@ -505,33 +478,30 @@ def display_rankings(df, top_n=10):
             champs_df['total_chain_cost'] = champs_df['total_chain_cost'].map('${:,.2f}'.format)
             champs_df.rename(columns={'id': 'Participant', 'total_chain_cost': 'Total Chain Cost'}, inplace=True)
             st.dataframe(champs_df[['Participant', 'Total Chain Cost']], use_container_width=True, hide_index=True)
-
     # 排行榜 2: 你的 (Distributor) 成本 (修改)
     with c2:
         st.subheader("👤 Distributor Champions")
         st.caption(f"Top {top_n} - Lowest **Your** (Distributor) Cost")
         dist_df = df.dropna(subset=['distributor_cost']).sort_values('distributor_cost', ascending=True).head(top_n).copy()
-        
+                
         if dist_df.empty:
             st.info("No data for this category yet.")
         else:
             dist_df['distributor_cost'] = dist_df['distributor_cost'].map('${:,.2f}'.format)
             dist_df.rename(columns={'id': 'Participant', 'distributor_cost': 'Your Cost'}, inplace=True)
             st.dataframe(dist_df[['Participant', 'Your Cost']], use_container_width=True, hide_index=True)
-
     # 排行榜 3: 订单平滑度 (不变)
     with c3:
         st.subheader("🧘 Mr. Smooth")
         st.caption(f"Top {top_n} - Lowest Order Variation (Std. Dev.)")
         smooth_df = df.dropna(subset=['order_std_dev']).sort_values('order_std_dev', ascending=True).head(top_n).copy()
-        
+                
         if smooth_df.empty:
             st.info("No data for this category yet.")
         else:
             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")
@@ -543,12 +513,12 @@ def show_leaderboard_ui():
         try:
             df = pd.DataFrame(leaderboard_data.values())
             if 'id' not in df.columns and not df.empty: df['id'] = list(leaderboard_data.keys())
-            
+                        
             # 检查旧列是否存在即可
             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)
@@ -559,7 +529,6 @@ def show_leaderboard_ui():
         except Exception as e:
             st.error(f"Error displaying leaderboard: {e}")
             st.dataframe(leaderboard_data)
-
 # ---------- MODIFIED FUNCTION (v2) ----------
 def save_logs_and_upload(state: dict):
     if not state.get('logs'):
@@ -588,21 +557,21 @@ def save_logs_and_upload(state: dict):
     st.subheader("Updating Leaderboard...")
     try:
         human_role = state['human_role']
-        
+                
         # 1. 计算你的 (Distributor) 成本
         distributor_cost = logs_df[f'{human_role}.total_cost'].iloc[-1]
-        
+                
         # 2. 计算总供应链成本
         r_cost = logs_df['Retailer.total_cost'].iloc[-1]
         w_cost = logs_df['Wholesaler.total_cost'].iloc[-1]
         f_cost = logs_df['Factory.total_cost'].iloc[-1]
         total_chain_cost = r_cost + w_cost + distributor_cost + f_cost
-        
+                
         # 3. 计算订单标准差
         order_std_dev = logs_df[f'{human_role}.order_placed'].std()
-        
+                
         setting_name = f"{state['llm_personality']} / {state['info_sharing']}"
-        
+                
         # 4. 创建新的条目
         new_entry = {
             'id': participant_id, 
@@ -611,20 +580,18 @@ def save_logs_and_upload(state: dict):
             'total_chain_cost': float(total_chain_cost), # 新增: 总成本
             '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}")
 # ==============================================================================
-
 # -----------------------------------------------------------------------------
 # 4. Streamlit UI (Applying v4.22 + v4.23 fixes)
 # -----------------------------------------------------------------------------
 st.title("🍺 The Beer Game: A Human-AI Collaboration Challenge")
-
 if st.session_state.get('initialization_error'):
     st.error(st.session_state.initialization_error)
 else:
@@ -634,16 +601,27 @@ else:
         st.markdown("---")
         st.header("⚙️ Game Configuration")
         
-        # =============== NEW: Participant ID Input ===============
+        # =============== 1. NEW: Participant ID Input ===============
         participant_id = st.text_input("Enter Your Name or Team ID:", key="participant_id_input", placeholder="e.g., Team A")
         # =======================================================
         
-        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.")
-        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.")
-
+        # =============== 1. MODIFIED: 自动分配逻辑 (移除手动选择) ===============
+        if participant_id:
+            # 使用哈希和模运算，将用户均匀分配到 4 个实验组
+            setting_index = hash(participant_id) % len(EXPERIMENT_SETTINGS) 
+            llm_personality, info_sharing = EXPERIMENT_SETTINGS[setting_index]
+        else:
+            # 默认值，如果未输入ID
+            llm_personality, info_sharing = ('human_like', 'local') 
+            
+        st.info(f"You will be automatically assigned to the condition: **{llm_personality.replace('_', ' ').title()} / {info_sharing.title()}**.")
+        # =================================================================
+        
+        # 移除原有的 c1, c2 和 selectbox 
+        # c1, c2 = st.columns(2)
+        # with c1:
+        # with c2:
+        
         # =============== MODIFIED: Start Game Button ===============
         if st.button("🚀 Start Game", type="primary", disabled=(client is None)):
             if not participant_id:
@@ -655,7 +633,7 @@ else:
                     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)
+                        init_game_state(llm_personality, info_sharing, participant_id) # 使用自动分配的值
                         st.rerun()
                     else:
                         st.session_state['last_id_warning'] = participant_id
@@ -664,242 +642,187 @@ 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)
+                    init_game_state(llm_personality, info_sharing, participant_id) # 使用自动分配的值
                     st.rerun()
         # ===========================================================
         
         # =============== NEW: Show Leaderboard on Start Page ===============
         show_leaderboard_ui()
         # =================================================================
-
     # --- 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.markdown("---")
-        st.subheader("Supply Chain Status (Start of Week State)") 
-
-        # =============== MODIFIED UI LOGIC (v12) ===============
-        if info_sharing == 'full':
-            cols = st.columns(4)
-            for i, name in enumerate(echelon_order):
-                with cols[i]:
-                    e = echelons[name]
-                    icon = "👤" if name == human_role else "🤖"
-
-                    if name == human_role:
-                        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}")
-                    
+        
+        # =============== 2. IMAGE SIZE MODIFICATION (使用 st.columns) ===============
+        col_main, col_sidebar_image = st.columns([4, 1]) # 增大主内容区，同时保持侧边栏用于放置图表
+        
+        with col_main:
+            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.markdown("---")
+            st.subheader("Supply Chain Status (Start of Week State)") 
+            
+            # ... (UI LOGIC REMAINS HERE) ...
+            
+            # --- MODIFIED UI LOGIC (v12) ---
+            if info_sharing == 'full':
+                cols = st.columns(4)
+                for i, name in enumerate(echelon_order):
+                    with cols[i]:
+                        e = echelons[name]
+                        icon = "👤" if name == human_role else "🤖"
+                        if name == human_role:
+                            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}")
+                                            
+                        st.metric("Inventory (Opening)", e['inventory'])
+                        st.metric("Backlog (Opening)", e['backlog'])
+                                            
+                        current_incoming_order = 0
+                        if name == "Retailer":
+                            current_incoming_order = get_customer_demand(week)
+                        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}**")
+                                            
+                        if name == "Factory":
+                            prod_completing_next = state['last_week_orders'].get("Distributor", 0)
+                            st.write(f"Completing Next Week: **{prod_completing_next}**")
+                        else:
+                            arriving_next = 0
+                            q = e['incoming_shipments']
+                            if q: arriving_next = list(q)[0] # Read W+1
+                            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'])
-                    
+                            
+                with col2:
                     current_incoming_order = 0
-                    if name == "Retailer":
-                        current_incoming_order = get_customer_demand(week)
-                    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}**") 
-                                            
-                    if name == "Factory":
-                        prod_completing_next = state['last_week_orders'].get("Distributor", 0)
-                        st.write(f"Completing Next Week: **{prod_completing_next}**")
-                    else:
-                        arriving_next = 0
-                        
-                        # --- UI FIX V12 ---
-                        q = e['incoming_shipments']
-                        if name == 'Distributor':
-                            # "Next" for Distributor (maxlen=1) is q[0]
-                            if q: arriving_next = list(q)[0]
-                        elif name in ('Wholesaler', 'Retailer'):
-                            # "Next" for R/W (maxlen=2) is q[0]
-                            # No, it's q[1].
-                            # W3: q=[4,8]. ArrivedThisWeek=4. ArrivingNextWeek=8
-                            # We pop 4. q=[8].
-                            # W4: q=[8]. ArrivedThisWeek=8.
-                            if len(q) > 1:
-                                arriving_next = list(q)[1] # Read W+2
+                    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:
+                    arriving_next = 0
+                    q = e['incoming_shipments']
+                    if q: 
+                        arriving_next = list(q)[0]
+                    st.write(f"**Shipment Arriving (Next Week):**\n# {arriving_next}")
+            
+            # --- Decision Logic (Remainging the Same) ---
+            st.markdown("---")
+            st.header("Your Decision (Step 4)")
+            
+            # Prepare state snapshot for the AI prompt (logic remains identical)
+            all_decision_point_states = {}
+            for name in echelon_order:
+                e_curr = echelons[name] 
+                arrived = 0
+                if name == "Factory":
+                    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]
                             
-                            # Let's retry R/W logic
-                            # W3: q=[4,8]. ArrivedThisWeek=4 (from [0]). ANW=8 (from [1])
-                            # W4: D ships 16. q.popleft() (4). q.append(16). q=[8,16]
-                            # W4 start: ArrivedThisWeek=8 (from [0]). ANW=16 (from [1])
-                            if len(q) > 1:
-                                arriving_next = list(q)[1]
+                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
                             
-                            # Let's retry Distributor logic (maxlen=1)
-                            # W3: F ships 4. q.append(4). q=[4]
-                            # W4: ArrivedThisWeek=4 (from [0]). ANW=??
-                            # W4: F ships 8. q.popleft() (4). q.append(8). q=[8]
-                            # W5: ArrivedThisWeek=8 (from [0]).
-                            # "Arriving Next Week" for Distributor (W+1) is ALWAYS list(q)[0]
-                            if q: arriving_next = list(q)[0]
-                        
-                        # --- RETHINK UI V12 ---
-                        # For R/W (maxlen=2), q[0] is W+1, q[1] is W+2
-                        # For D (maxlen=1), q[0] is W+1
-                        
-                        if name in ('Wholesaler', 'Retailer'):
-                            q = e['incoming_shipments']
-                            if q: arriving_next = list(q)[0] # Read W+1
-                        elif name == 'Distributor':
-                            q = e['incoming_shipments']
-                            if q: arriving_next = list(q)[0] # Read W+1
-                        # --- END RETHINK V12 ---
-                        
-                        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'])
-            
-            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 V12 ---------------------
-                # "Arriving Next Week" for Distributor in LOCAL mode.
-                # Read W+1 item from its own shipping queue
-                arriving_next = 0
-                q = e['incoming_shipments']
-                if q:
-                     arriving_next = list(q)[0]
-                st.write(f"**Shipment Arriving (Next Week):**\n# {arriving_next}")
-                # -----------------------------------------------------------
-
-        # =======================================================
-                
-        st.markdown("---")
-        st.header("Your Decision (Step 4)")
-
-        # Prepare the state snapshot for the AI prompt (State AFTER arrivals/orders, BEFORE shipping)
-        all_decision_point_states = {}
-        for name in echelon_order:
-            e_curr = echelons[name] # This is END OF LAST WEEK state
-            arrived = 0
-            if name == "Factory":
-                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]
+                all_decision_point_states[name] = {
+                    'name': name, 'inventory': inv_after_arrival, 'backlog': backlog_after_new_order,
+                    'incoming_order': inc_order_this_week, 
+                    'incoming_shipments': e_curr['incoming_shipments'].copy() if name != "Factory" else deque()
+                }
+            human_echelon_state_for_prompt = all_decision_point_states[human_role]
             
-            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
+            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
+                    if st.form_submit_button("Submit Initial Order & See AI Suggestion", type="primary"):
+                        state['human_initial_order'] = int(initial_order) if initial_order is not None else 0
+                        state['decision_step'] = 'final_order'
+                        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.")
+                ai_suggestion = state.get('current_ai_suggestion', 4) # Read stored value
+                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
+                                    
+                    if st.form_submit_button("Submit Final Order & Advance to Next Week"):
+                        final_order_value = st.session_state.get('final_order_input', 0)
+                        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)
+                                                    
+                        if 'final_order_input' in st.session_state: del st.session_state.final_order_input
+                        st.rerun()
             
-            # 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_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
-                if st.form_submit_button("Submit Initial Order & See AI Suggestion", type="primary"):
-                    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.")
+            st.markdown("---")
+            with st.expander("📖 Your Weekly Decision Log", expanded=False):
+                if not state.get('logs'):
+                    st.write("Your weekly history will be displayed here after you complete the first week.")
+                else:
+                    try:
+                        history_df = pd.json_normalize(state['logs'])
+                        human_cols = {
+                            'week': 'Week', f'{human_role}.opening_inventory': 'Opening Inv.',
+                            f'{human_role}.opening_backlog': 'Opening Backlog', 
+                            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',
+                        }
+                        ordered_display_cols_keys = [
+                            'week', f'{human_role}.opening_inventory', f'{human_role}.opening_backlog',
+                            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.")
+                        else:
+                            display_df = history_df[final_cols_to_display].rename(columns=human_cols)
+                            if 'Weekly Cost' in display_df.columns:
+                                display_df['Weekly Cost'] = display_df['Weekly Cost'].apply(lambda x: f"${x:,.2f}" if isinstance(x, (int, float)) else "")
+                            st.dataframe(display_df.sort_values(by="Week", ascending=False), hide_index=True, use_container_width=True)
+                    except Exception as e:
+                        st.error(f"Error displaying weekly log: {e}")
+        
+        # 将原来的侧边栏内容移入 col_sidebar_image
+        with col_sidebar_image:
+            st.header("Game Info")
+            st.markdown(f"**Game ID**: `{state['participant_id']}`\n\n**Current Week**: {week}")
+            # --- 放大图片 ---
+            try: st.image(IMAGE_PATH, caption="Supply Chain Reference", use_column_width=True) 
+            except FileNotFoundError: st.warning("Image file not found.")
+            # --- 放大图片 ---
             
-            # --- NEW: Read stored suggestion ---
-            ai_suggestion = state.get('current_ai_suggestion', 4) # Read stored value
-            # -----------------------------------
-
-            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
-                
-                if st.form_submit_button("Submit Final Order & Advance to Next Week"):
-                    final_order_value = st.session_state.get('final_order_input', 0)
-                    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)
-                    
-                    if 'final_order_input' in st.session_state: del st.session_state.final_order_input
-                    st.rerun()
-
-        st.markdown("---")
-        with st.expander("📖 Your Weekly Decision Log", expanded=False):
-            if not state.get('logs'):
-                st.write("Your weekly history will be displayed here after you complete the first week.")
-            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}.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}.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.")
-                    else:
-                        display_df = history_df[final_cols_to_display].rename(columns=human_cols)
-                        if 'Weekly Cost' in display_df.columns:
-                            display_df['Weekly Cost'] = display_df['Weekly Cost'].apply(lambda x: f"${x:,.2f}" if isinstance(x, (int, float)) else "")
-                        st.dataframe(display_df.sort_values(by="Week", ascending=False), hide_index=True, use_container_width=True)
-                except Exception as e:
-                    st.error(f"Error displaying weekly log: {e}")
-
-        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()
+            if st.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()
 
     # --- Game Over Interface ---
     if 'game_state' in st.session_state and not st.session_state.game_state.get('game_running', False) and st.session_state.game_state['week'] > WEEKS:
@@ -916,9 +839,7 @@ else:
             save_logs_and_upload(state) # This now also updates the leaderboard
         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()