Update app.py

app.py

@@ -1,5 +1,5 @@
 # app.py
-# @title Beer Game Final Version (v4.21 - Corrected 3-Week Lead Time Logic&UI)
+# @title Beer Game Final Version (v4.23 - Fixed Final Decision State Bug)
 
 # -----------------------------------------------------------------------------
 # 1. Import Libraries
@@ -15,7 +15,10 @@ import random
 import uuid
 from pathlib import Path
 from datetime import datetime
-from huggingface_hub import HfApi
+from huggingface_hub import HfApi, hf_hub_download
+from huggingface_hub.utils import RepositoryNotFoundError, EntryNotFoundError
+import json
+import numpy as np
 
 # -----------------------------------------------------------------------------
 # 0. Page Configuration (Must be the first Streamlit command)
@@ -41,7 +44,8 @@ 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" # Path to your uploaded image
+IMAGE_PATH = "beer_game_diagram.png"
+LEADERBOARD_FILE = "leaderboard.json"
 
 # --- API & Secrets Configuration ---
 try:
@@ -63,38 +67,37 @@ else:
 def get_customer_demand(week: int) -> int:
     return 4 if week <= 4 else 8
 
-# =============== CORRECTED Initialization (v4.17 logic) ===============
-def init_game_state(llm_personality: str, info_sharing: str):
+# =============== MODIFIED Initialization (Added current_ai_suggestion) ===============
+def init_game_state(llm_personality: str, info_sharing: str, participant_id: 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,
-        # Initialize last week's orders to 0
+        'current_ai_suggestion': None, # 新增：用于存储AI建议
         '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
-
         if name == "Distributor": shipping_weeks = FACTORY_SHIPPING_DELAY
         elif name == "Factory": shipping_weeks = 0
         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! AI Mode: **{llm_personality} / {info_sharing}**. You are playing as the: **{human_role}**.")
+    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):
@@ -183,140 +186,78 @@ def get_llm_prompt(echelon_state_decision_point: dict, week: int, llm_personalit
         **React emotionally.** What is your knee-jerk {task_word}? Respond with a single integer.
         """
 
-# =============== CORRECTED step_game FUNCTION (Fixed Lead Time Logic) ===============
 def step_game(human_final_order: int, human_initial_order: int, ai_suggestion: int):
+    # 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 = {}
-
-    # Store state at the very beginning of the week (End of last week)
     opening_inventories = {name: e['inventory'] for name, e in echelons.items()}
     opening_backlogs = {name: e['backlog'] for name, e in echelons.items()}
     arrived_this_week = {name: 0 for name in echelon_order}
-
-    # --- Game Simulation Steps ---
-
-    # Step 1a: Factory Production completes
+    inventory_after_arrival = {}
     factory_state = echelons["Factory"]
     produced_units = 0
     if state['factory_production_pipeline']:
-        produced_units = state['factory_production_pipeline'].popleft() # Pop completed production
+        produced_units = state['factory_production_pipeline'].popleft()
         arrived_this_week["Factory"] = produced_units
-    inventory_after_arrival = {} # Store intermediate inventory state
     inventory_after_arrival["Factory"] = factory_state['inventory'] + produced_units
-
-    # Step 1b: Shipments arrive at downstream echelons
     for name in ["Retailer", "Wholesaler", "Distributor"]:
         arrived_shipment = 0
         if echelons[name]['incoming_shipments']:
-            arrived_shipment = echelons[name]['incoming_shipments'].popleft() # Pop arrived shipment
+            arrived_shipment = echelons[name]['incoming_shipments'].popleft()
             arrived_this_week[name] = arrived_shipment
         inventory_after_arrival[name] = echelons[name]['inventory'] + arrived_shipment
-
-    # Step 2: Orders Arrive from Downstream
-    total_backlog_before_shipping = {} # Store intermediate backlog state
+    total_backlog_before_shipping = {}
     for name in echelon_order:
         incoming_order_for_this_week = 0
-        if name == "Retailer":
-            incoming_order_for_this_week = get_customer_demand(week)
+        if name == "Retailer": incoming_order_for_this_week = get_customer_demand(week)
         else:
             downstream_name = echelons[name]['downstream_name']
-            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 # Store for logging/UI this week
+            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
-
-    # --- Create State Snapshot for AI/Human Decision Point ---
     decision_point_states = {}
     for name in echelon_order:
          decision_point_states[name] = {
-             'name': name,
-             'inventory': inventory_after_arrival[name], # Inventory available
-             'backlog': total_backlog_before_shipping[name], # Total demand to meet
-             'incoming_order': echelons[name]['incoming_order'], # Order received this week
+             '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(),
          }
-
-    # --- Step 4: Agent Decisions (Place Orders / Schedule Production) ---
-    current_week_orders = {} # Store THIS week's decisions
+    current_week_orders = {}
     for name in echelon_order:
-        e = echelons[name]
-        prompt_state = decision_point_states[name]
-
-        if name == human_role:
-            order_amount, raw_resp = human_final_order, "HUMAN_FINAL_INPUT"
+        e = echelons[name]; prompt_state = decision_point_states[name]
+        if name == human_role: order_amount, raw_resp = human_final_order, "HUMAN_FINAL_INPUT"
         else:
             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'] # Store for NEXT week's Step 2
-
-    # --- Step 3 (Logic Moved): Fulfill orders (Ship Beer) ---
-    # This MUST happen BEFORE Step 5 (Pipelines Advance)
+        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'] # Store temporarily
-
-        # Update the main state dict's inventory and backlog to reflect END OF WEEK state
-        e['inventory'] = available_inv - e['shipment_sent']
-        e['backlog'] = demand_to_meet - e['shipment_sent']
-
-    # --- Step 5: Advance Pipelines (New Logic) ---
-    # Factory's decision ('order_placed') from this week enters the production pipeline
-    # This simulates the FACTORY_LEAD_TIME
-    state['factory_production_pipeline'].append(echelons["Factory"]['order_placed'])
-
-    # Items shipped in Step 3 now enter their respective shipping pipelines
-    # Factory -> Distributor (uses FACTORY_SHIPPING_DELAY)
-    if units_shipped["Factory"] > 0:
-        echelons['Distributor']['incoming_shipments'].append(units_shipped["Factory"])
-    # Distributor -> Wholesaler (uses SHIPPING_DELAY)
-    if units_shipped['Distributor'] > 0:
-         echelons['Wholesaler']['incoming_shipments'].append(units_shipped['Distributor'])
-    # Wholesaler -> Retailer (uses SHIPPING_DELAY)
-    if units_shipped['Wholesaler'] > 0:
-         echelons['Retailer']['incoming_shipments'].append(units_shipped['Wholesaler'])
-
-    # --- Calculate Costs & Log (End of Week) ---
+        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'])
     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']
-
+    if 'current_ai_suggestion' in log_entry: del log_entry['current_ai_suggestion'] # Clean up
     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']
-
-        log_entry[f'{name}.inventory'] = e['inventory']; log_entry[f'{name}.backlog'] = e['backlog']
-        log_entry[f'{name}.incoming_order'] = e['incoming_order']; log_entry[f'{name}.order_placed'] = e['order_placed']
-        log_entry[f'{name}.shipment_sent'] = e['shipment_sent']; log_entry[f'{name}.weekly_cost'] = e['weekly_cost']
-        log_entry[f'{name}.total_cost'] = e['total_cost']; log_entry[f'{name}.llm_raw_response'] = llm_raw_responses.get(name, "")
+        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_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
-
+        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)
-
-    # --- Advance Week ---
     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.
@@ -353,10 +294,19 @@ def plot_results(df: pd.DataFrame, title: str, human_role: str):
 
 @st.cache_data(ttl=60) # 缓存1分钟
 def load_leaderboard_data():
-    if not hf_api or not HF_REPO_ID: return {}
+    """从Hugging Face Hub下载并加载排行榜数据。"""
+    if not hf_api or not HF_REPO_ID:
+        return {} # 没有HF连接，返回空
     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)
+        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" # 明确指定缓存目录
+        )
+        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 {}
@@ -365,27 +315,44 @@ def load_leaderboard_data():
         return {}
 
 def save_leaderboard_data(data):
-    if not hf_api or not HF_REPO_ID or not HF_TOKEN: return
+    """将更新后的排行榜数据保存到Hugging Face Hub。"""
+    if not hf_api or not HF_REPO_ID or not HF_TOKEN:
+        st.sidebar.warning("Cannot save leaderboard. HF credentials missing.")
+        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")
+        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()
+        st.cache_data.clear() # 清除缓存
     except Exception as e:
         st.sidebar.error(f"Failed to upload leaderboard: {e}")
 
 def display_rankings(df, top_n=10):
+    """在UI上显示三个排名的辅助函数。"""
     if df.empty:
         st.info("No completed games for this category yet. Be the first!")
         return
+
+    # 数据清洗：确保成本和标准差是数字
     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")
@@ -393,6 +360,7 @@ def display_rankings(df, top_n=10):
         champs_df['total_cost'] = champs_df['total_cost'].map('${:,.2f}'.format)
         champs_df.rename(columns={'id': 'Participant', 'total_cost': 'Total Cost'}, inplace=True)
         st.dataframe(champs_df[['Participant', 'Total Cost']], use_container_width=True, hide_index=True)
+    
     with c2:
         st.subheader("👑 Bullwhip Kings")
         st.caption(f"Top {top_n} - Highest Total Cost")
@@ -400,6 +368,7 @@ def display_rankings(df, top_n=10):
         kings_df['total_cost'] = kings_df['total_cost'].map('${:,.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.)")
@@ -409,46 +378,62 @@ def display_rankings(df, top_n=10):
         st.dataframe(smooth_df[['Participant', 'Order Std. Dev.']], use_container_width=True, hide_index=True)
 
 def show_leaderboard_ui():
+    """加载数据并显示完整的排行榜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())
+            # 确保id列存在
+            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)
+            
+            with tabs[0]: # Overall
+                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)
+            st.dataframe(leaderboard_data) # 原始数据以供调试
 # ==============================================================================
 
+
+# =============== MODIFIED Function (Updates Leaderboard) ===============
 def save_logs_and_upload(state: dict):
-    # This function is now responsible for CSV *and* leaderboard updates.
     if not state.get('logs'):
         st.warning("No log data to save.")
         return
-    participant_id = state['participant_id']
+    
+    participant_id = state['participant_id'] # 这是您输入的自定义ID
     logs_df = None
+    
+    # 1. Save individual log CSV
     try:
         logs_df = pd.json_normalize(state['logs'])
+        # 确保文件名安全
         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)
         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..."):
                 try:
@@ -457,28 +442,40 @@ def save_logs_and_upload(state: dict):
                 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
+        return # Don't proceed to leaderboard if CSV failed
+
+    # 2. Update and upload leaderboard.json
+    if logs_df is None: return # Ensure logs_df was created
+
     st.subheader("Updating Leaderboard...")
     try:
         human_role = state['human_role']
+        
+        # Calculate metrics
         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
+            'id': participant_id, # 使用自定义ID
+            'setting': setting_name,
+            'total_cost': float(total_cost), # 确保是JSON兼容的float
+            'order_std_dev': float(order_std_dev) if pd.notna(order_std_dev) else 0.0 # 处理NaN
         }
+
+        # Load, update, save
         leaderboard_data = load_leaderboard_data()
+        # 使用ID作为键来允许覆盖/更新 (同名/同组名的人会更新成绩)
         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 (Adjusted for Custom ID, Leaderboard, and UI Fixes)
+# 4. Streamlit UI (Adjusted for Custom ID and Leaderboard)
 # -----------------------------------------------------------------------------
 st.title("🍺 The Beer Game: A Human-AI Collaboration Challenge")
 
@@ -509,19 +506,24 @@ else:
                 # 检查ID是否已存在
                 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)
+                    st.warning(f"ID '{participant_id}' already exists! Your score will be overwritten. Click 'Start Game' again to confirm.")
+                    # 简单地要求再次点击，或者可以添加一个复选框
+                    # 为了课堂使用，我们先假设他们会自己协调
+                    # 或者让他们加个后缀，比如 "Team A - 2"
+                    # 我们允许覆盖，但给出警告
+                    if "confirm_overwrite" not in st.session_state:
+                        st.session_state.confirm_overwrite = False
+                    
+                    if st.session_state.get(f"last_clicked_id") == participant_id:
+                        # 如果他们再次点击（ID没变）
                         init_game_state(llm_personality, info_sharing, participant_id)
+                        st.session_state.pop("last_clicked_id", None)
                         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.")
+                        st.session_state[f"last_clicked_id"] = participant_id
+
                 else:
-                    # 新ID，直接开始
-                    if 'last_id_warning' in st.session_state:
-                         del st.session_state['last_id_warning']
+                    # Pass the participant_id to the init function
                     init_game_state(llm_personality, info_sharing, participant_id)
                     st.rerun()
         # ===========================================================
@@ -538,15 +540,16 @@ else:
 
 
         st.header(f"Week {week} / {WEEKS}")
+        # 显示自定义ID
         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)") # 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 "🤖"
 
                     if name == human_role:
@@ -556,10 +559,10 @@ else:
                     
                     st.metric("Inventory (Opening)", e['inventory'])
                     st.metric("Backlog (Opening)", e['backlog'])
-                    
+
                     # 移除成本显示
                     
-                    # --- UI FIX: Display "Arrived This Week" ---
+                    # --- NEW: Added Arriving This Week ---
                     current_incoming_order = 0
                     if name == "Retailer":
                         current_incoming_order = get_customer_demand(week)
@@ -583,18 +586,14 @@ else:
                             arriving_next = list(e['incoming_shipments'])[1]
                         # 修正 2-week delay (R/W) 的显示
                         elif name in ('Wholesaler', 'Retailer') and len(e['incoming_shipments']) > 0 and e['incoming_shipments'].maxlen == 2:
-                             # 如果队列长度为1但最大长度为2，说明下一个是0
-                             if len(e['incoming_shipments']) == 1:
-                                 arriving_next = 0
-                             else: # 这种情况不应该发生，但作为保险
-                                 arriving_next = list(e['incoming_shipments'])[0]
+                            arriving_next = 0 # Peek at index 1 is correct, if it's not there, it's 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]
-            st.markdown(f"### 👤 **<span style='color:#FF4B4B;'>{human_role} (Your Dashboard - Start of Week State)</span>**", unsafe_allow_html=True)
+            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 = st.columns(3)
             with col1:
@@ -614,9 +613,7 @@ else:
                 st.write(f"**Shipment Arriving (This Week):**\n# {arriving_this_week}")
                 
                 # Arriving NEXT week (Peek at the next item in the 1-week delay queue)
-                arriving_next = 0
-                if len(e['incoming_shipments']) > 1: # 仅当队列中有多于1个元素时，才显示 [1]
-                    arriving_next = list(e['incoming_shipments'])[1]
+                arriving_next = list(e['incoming_shipments'])[1] if len(e['incoming_shipments']) > 1 else 0
                 st.write(f"**Shipment Arriving (Next Week):**\n# {arriving_next}")
 
         st.markdown("---")
@@ -684,6 +681,7 @@ else:
                     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
+                    if 'current_ai_suggestion' in state: del state['current_ai_suggestion'] # Clean up
                     st.rerun()
 
         st.markdown("---")