Update app.py

app.py

@@ -1,5 +1,5 @@
 # app.py
-# @title Beer Game Final Version (v4.9 - Detailed Intro & Real-time Cost)
+# @title Beer Game Final Version (v4.10 - Added Arrival Log Column - Complete Code)
 
 # -----------------------------------------------------------------------------
 # 1. Import Libraries
@@ -31,9 +31,9 @@ WEEKS = 24
 INITIAL_INVENTORY = 12
 INITIAL_BACKLOG = 0
 ORDER_PASSING_DELAY = 1
-SHIPPING_DELAY = 2
+SHIPPING_DELAY = 2 # General shipping delay
 FACTORY_LEAD_TIME = 1
-FACTORY_SHIPPING_DELAY = 1
+FACTORY_SHIPPING_DELAY = 1 # Specific delay from Factory to Distributor
 HOLDING_COST = 0.5
 BACKLOG_COST = 1.0
 
@@ -57,7 +57,7 @@ else:
 
 
 # -----------------------------------------------------------------------------
-# 3. Core Game Logic Functions (No changes in this section)
+# 3. Core Game Logic Functions
 # -----------------------------------------------------------------------------
 
 def get_customer_demand(week: int) -> int:
@@ -80,10 +80,11 @@ def init_game_state(llm_personality: str, info_sharing: str):
     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
-        
+
+        # Determine shipping delay for incoming goods for this role
         if name == "Distributor": shipping_weeks = FACTORY_SHIPPING_DELAY
-        elif name == "Factory": shipping_weeks = 0
-        else: shipping_weeks = SHIPPING_DELAY
+        elif name == "Factory": shipping_weeks = 0 # Factory produces, doesn't receive shipments
+        else: shipping_weeks = SHIPPING_DELAY # Retailer/Wholesaler use general delay
 
         st.session_state.game_state['echelons'][name] = {
             'name': name, 'inventory': INITIAL_INVENTORY, 'backlog': INITIAL_BACKLOG,
@@ -110,23 +111,21 @@ def get_llm_order_decision(prompt: str, echelon_name: str) -> (int, str):
             raw_text = response.choices[0].message.content.strip()
             match = re.search(r'\d+', raw_text)
             if match: return int(match.group(0)), raw_text
-            return 8, raw_text
+            st.warning(f"LLM for {echelon_name} did not return a valid number. Defaulting to 8. Raw Response: '{raw_text}'")
+            return 8, raw_text # Default if no number found
         except Exception as e:
-            st.error(f"API call failed for {echelon_name}: {e}")
+            st.error(f"API call failed for {echelon_name}: {e}. Defaulting to 8.")
             return 8, f"API_ERROR: {e}"
 
 def get_llm_prompt(echelon_state: dict, week: int, llm_personality: str, info_sharing: str, all_echelons_state: dict) -> str:
-    """Generates the prompt for the LLM based on the game scenario."""
-    
+    # This function's logic remains correct.
     base_info = f"Your Current Status at the **{echelon_state['name']}** for **Week {week}**:\n- On-hand inventory: {echelon_state['inventory']} units.\n- Backlog (unfilled orders): {echelon_state['backlog']} units.\n- Incoming order this week (from your customer): {echelon_state['incoming_order']} units.\n"
-    
     if echelon_state['name'] == 'Factory':
         task_word = "production quantity"
         base_info += f"- Production pipeline (completing in future weeks): {list(st.session_state.game_state['factory_production_pipeline'])}"
     else:
         task_word = "order quantity"
         base_info += f"- Shipments on the way to you: {list(echelon_state['incoming_shipments'])}\n- Orders you have placed being processed by your supplier: {list(echelon_state['order_pipeline'])}"
-
     if llm_personality == 'perfect_rational' and info_sharing == 'full':
         stable_demand = 8
         if echelon_state['name'] == 'Factory': total_lead_time = FACTORY_LEAD_TIME
@@ -142,7 +141,6 @@ def get_llm_prompt(echelon_state: dict, week: int, llm_personality: str, info_sh
             inventory_position = (echelon_state['inventory'] - echelon_state['backlog'] + sum(echelon_state['incoming_shipments']) + sum(echelon_state['order_pipeline']))
         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 = echelon_state['incoming_order']
         inventory_correction = safety_stock - (echelon_state['inventory'] - echelon_state['backlog'])
@@ -155,7 +153,6 @@ def get_llm_prompt(echelon_state: dict, week: int, llm_personality: str, info_sh
         calculated_order = anchor_demand + inventory_correction - supply_line
         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 is {echelon_state['inventory'] - echelon_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 order.\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."
-
     elif llm_personality == 'human_like' and info_sharing == 'full':
         full_info_str = f"\n**Full Supply Chain Information:**\n- End-Customer Demand this week: {get_customer_demand(week)} units.\n"
         for name, e_state in all_echelons_state.items():
@@ -170,7 +167,6 @@ def get_llm_prompt(echelon_state: dict, week: int, llm_personality: str, info_sh
         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 {echelon_state['name']}.** You have a limited view and tend to over-correct based on fear.
@@ -181,34 +177,62 @@ def get_llm_prompt(echelon_state: dict, week: int, llm_personality: str, info_sh
         **React emotionally.** What is your knee-jerk {task_word}? Respond with a single integer.
         """
 
+# =============== CORRECTED step_game FUNCTION ===============
 def step_game(human_final_order: int, human_initial_order: int, ai_suggestion: int):
-    # This core logic function remains correct and unchanged.
     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 pre-step state for logging
     pre_step_inventory = echelons[human_role]['inventory']
     pre_step_backlog = echelons[human_role]['backlog']
+    # Store arriving shipment amount *before* it's added to inventory
+    arriving_shipment_this_week = list(echelons[human_role]['incoming_shipments'])[0] if echelons[human_role]['incoming_shipments'] else 0
 
+    # --- Game Simulation Steps ---
+    # Step 1a: Factory Production completes and adds to Factory inventory
     factory_state = echelons["Factory"]
-    if state['factory_production_pipeline']: factory_state['inventory'] += state['factory_production_pipeline'].popleft()
+    produced_units = 0
+    if state['factory_production_pipeline']:
+        produced_units = state['factory_production_pipeline'].popleft()
+        factory_state['inventory'] += produced_units
+
+    # Step 1b: Shipments arrive at downstream echelons
     for name in ["Retailer", "Wholesaler", "Distributor"]:
-        if echelons[name]['incoming_shipments']: echelons[name]['inventory'] += echelons[name]['incoming_shipments'].popleft()
+        arrived_shipment = 0
+        if echelons[name]['incoming_shipments']:
+            arrived_shipment = echelons[name]['incoming_shipments'].popleft() # Pop shipment for current week
+            echelons[name]['inventory'] += arrived_shipment
+
+    # Step 2: Orders arrive from downstream partners
     for name in echelon_order:
-        if name == "Retailer": echelons[name]['incoming_order'] = get_customer_demand(week)
+        if name == "Retailer":
+            echelons[name]['incoming_order'] = get_customer_demand(week)
         else:
             downstream = echelons[name]['downstream_name']
+            order_from_downstream = 0
             if downstream and echelons[downstream]['order_pipeline']:
-                echelons[name]['incoming_order'] = echelons[downstream]['order_pipeline'].popleft()
-    for name in echelon_order:
-        e = echelons[name]; demand = e['incoming_order'] + e['backlog']
-        e['shipment_sent'] = min(e['inventory'], demand); e['inventory'] -= e['shipment_sent']; e['backlog'] = demand - e['shipment_sent']
-    for sender in ["Factory", "Distributor", "Wholesaler"]:
-        receiver = echelons[sender]['downstream_name']
-        if receiver: echelons[receiver]['incoming_shipments'].append(echelons[sender]['shipment_sent'])
+                order_from_downstream = echelons[downstream]['order_pipeline'].popleft()
+            echelons[name]['incoming_order'] = order_from_downstream
 
+    # Step 3: Fulfill orders (Ship Beer)
+    for name in echelon_order:
+        e = echelons[name]
+        demand_to_meet = e['incoming_order'] + e['backlog']
+        e['shipment_sent'] = min(e['inventory'], demand_to_meet)
+        e['inventory'] -= e['shipment_sent']
+        e['backlog'] = demand_to_meet - e['shipment_sent']
+
+    # Step 3b: Place shipped items into the *end* of the downstream partner's incoming shipment queue
+    for sender_name in ["Factory", "Distributor", "Wholesaler"]:
+        sender = echelons[sender_name]
+        receiver_name = sender['downstream_name']
+        if receiver_name:
+            echelons[receiver_name]['incoming_shipments'].append(sender['shipment_sent'])
+
+    # --- Step 4: Agent Decisions (Place Orders / Schedule Production) ---
     for name in echelon_order:
         e = echelons[name]
         if name == human_role:
@@ -217,42 +241,67 @@ def step_game(human_final_order: int, human_initial_order: int, ai_suggestion: i
             prompt = get_llm_prompt(e, week, llm_personality, info_sharing, echelons)
             order_amount, raw_resp = get_llm_order_decision(prompt, name)
         llm_raw_responses[name] = raw_resp
-        e['order_placed'] = max(0, order_amount)
-        if name != "Factory": e['order_pipeline'].append(e['order_placed'])
+        e['order_placed'] = max(0, order_amount) # This is the order/production decision for the week
+
+        # Place the order into the *end* of the current player's own order pipeline (for upstream player to receive later)
+        if name != "Factory":
+            e['order_pipeline'].append(e['order_placed'])
 
+    # Factory schedules production based on its 'order_placed' decision
     state['factory_production_pipeline'].append(echelons["Factory"]['order_placed'])
 
+    # --- Logging (End of Week) ---
     log_entry = {'timestamp': datetime.utcnow().isoformat() + "Z", 'week': week, **state}
+    # Remove complex objects before logging
     del log_entry['echelons'], log_entry['factory_production_pipeline'], log_entry['logs']
+
     for name in echelon_order:
         e = echelons[name]
+        # Calculate costs based on inventory/backlog AFTER shipping step
         e['weekly_cost'] = (e['inventory'] * HOLDING_COST) + (e['backlog'] * BACKLOG_COST); e['total_cost'] += e['weekly_cost']
+
+        # Log core metrics (state at the END of the week)
         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, "")
-    
+
+        # *** Explicitly log the value for 'Arriving Next Week' ***
+        # This reads the state of the queues *after* all steps for the week are done.
+        if name != 'Factory':
+             # The next item in incoming_shipments is what arrives at the start of next week
+             log_entry[f'{name}.arriving_next_week'] = list(e['incoming_shipments'])[0] if e['incoming_shipments'] else 0
+        else:
+             # For factory, log what completes production next week
+             log_entry[f'{name}.production_completing_next_week'] = list(state['factory_production_pipeline'])[0] if state['factory_production_pipeline'] else 0
+
+    # Log human-specific metrics recorded DURING the week
     log_entry[f'{human_role}.opening_inventory'] = pre_step_inventory
     log_entry[f'{human_role}.opening_backlog'] = pre_step_backlog
-    log_entry[f'{human_role}.initial_order'] = human_initial_order
-    log_entry[f'{human_role}.ai_suggestion'] = ai_suggestion
-    
+    log_entry[f'{human_role}.arrived_this_week'] = arriving_shipment_this_week # Log the shipment that arrived in Step 1
+    log_entry[f'{human_role}.initial_order'] = human_initial_order # Log Step 4a decision
+    log_entry[f'{human_role}.ai_suggestion'] = ai_suggestion # Log Step 4b suggestion
+
     state['logs'].append(log_entry)
 
+    # --- Advance Week ---
     state['week'] += 1
     state['decision_step'] = 'initial_order'
     if state['week'] > WEEKS: state['game_running'] = False
+# ==============================================================================
 
 def plot_results(df: pd.DataFrame, title: str, human_role: str):
     fig, axes = plt.subplots(4, 1, figsize=(12, 22))
     fig.suptitle(title, fontsize=16)
     echelons = ['Retailer', 'Wholesaler', 'Distributor', 'Factory']
-    
+
     plot_data = []
     for _, row in df.iterrows():
         for e in echelons:
-            plot_data.append({'week': row['week'], 'echelon': e,
-                'inventory': row[f'{e}.inventory'], 'order_placed': row[f'{e}.order_placed'],
-                'total_cost': row[f'{e}.total_cost']})
+            # Safely access keys, provide default if missing (e.g., first few weeks)
+            plot_data.append({'week': row.get('week', 0), 'echelon': e,
+                'inventory': row.get(f'{e}.inventory', 0),
+                'order_placed': row.get(f'{e}.order_placed', 0),
+                'total_cost': row.get(f'{e}.total_cost', 0)})
     plot_df = pd.DataFrame(plot_data)
 
     inventory_pivot = plot_df.pivot(index='week', columns='echelon', values='inventory').reindex(columns=echelons)
@@ -261,15 +310,24 @@ def plot_results(df: pd.DataFrame, title: str, human_role: str):
     order_pivot = plot_df.pivot(index='week', columns='echelon', values='order_placed').reindex(columns=echelons)
     order_pivot.plot(ax=axes[1], style='--'); axes[1].plot(range(1, WEEKS + 1), [get_customer_demand(w) for w in range(1, WEEKS + 1)], label='Customer Demand', color='black', lw=2.5); axes[1].set_title('Order Quantities (The Bullwhip Effect)'); axes[1].grid(True, linestyle='--'); axes[1].legend(); axes[1].set_ylabel('Ordered (Units)')
 
-    total_costs = plot_df.groupby('echelon')['total_cost'].max().reindex(echelons)
+    # Ensure total_cost calculation handles potential missing data gracefully
+    total_costs = plot_df.loc[plot_df.groupby('echelon')['week'].idxmax()] # Get row with max week for each echelon
+    total_costs = total_costs.set_index('echelon')['total_cost'].reindex(echelons, fill_value=0)
     total_costs.plot(kind='bar', ax=axes[2], rot=0); axes[2].set_title('Total Cumulative Cost'); axes[2].set_ylabel('Cost ($)')
 
-    human_df = df[['week', f'{human_role}.initial_order', f'{human_role}.ai_suggestion', f'{human_role}.order_placed']].copy()
+    # Safely access human decision columns
+    human_cols = [f'{human_role}.initial_order', f'{human_role}.ai_suggestion', f'{human_role}.order_placed']
+    human_df_cols = ['week'] + [col for col in human_cols if col in df.columns]
+    human_df = df[human_df_cols].copy()
     human_df.rename(columns={
         f'{human_role}.initial_order': 'Your Initial Order', f'{human_role}.ai_suggestion': 'AI Suggestion', f'{human_role}.order_placed': 'Your Final Order'
     }, inplace=True)
-    human_df.plot(x='week', ax=axes[3], marker='o', linestyle='-'); axes[3].set_title(f'Analysis of Your ({human_role}) Decisions'); axes[3].set_ylabel('Order Quantity'); axes[3].grid(True, linestyle='--'); axes[3].set_xlabel('Week')
-    
+    if len(human_df.columns) > 1: # Check if there's data to plot
+        human_df.plot(x='week', ax=axes[3], marker='o', linestyle='-'); axes[3].set_title(f'Analysis of Your ({human_role}) Decisions'); axes[3].set_ylabel('Order Quantity'); axes[3].grid(True, linestyle='--'); axes[3].set_xlabel('Week')
+    else:
+        axes[3].set_title(f'Analysis of Your ({human_role}) Decisions - No Data'); axes[3].grid(True, linestyle='--'); axes[3].set_xlabel('Week')
+
+
     plt.tight_layout(rect=[0, 0, 1, 0.96]); return fig
 
 def save_logs_and_upload(state: dict):
@@ -299,37 +357,43 @@ if st.session_state.get('initialization_error'):
 else:
     # --- Game Setup & Instructions ---
     if 'game_state' not in st.session_state or not st.session_state.game_state.get('game_running', False):
-        
-        # =============== NEW DETAILED INTRODUCTION ===============
+
         st.markdown("---")
         st.header("📖 Welcome to the Beer Game!")
-        st.markdown("This is a simulation of a supply chain. You will play against 3 AI agents. ** Please read these instructions carefully.")
+        st.markdown("This is a simulation of a supply chain. You will play against 3 AI agents. **You do not need any prior knowledge to play.** Please read these instructions carefully.")
 
         st.subheader("1. Your Goal: Minimize Costs")
-        st.success("**Your goal is to: Minimize the total cost for your position in the supply chain.**")
+        st.success("**Your single, most important goal is to: Minimize the total cost for your position in the supply chain.**")
         st.markdown("You get costs from two things every week:")
         st.markdown(f"""
-        - **Holding Inventory:** **${HOLDING_COST:,.2f} per unit per week.
-        - **Backlog (Unfilled Orders):** **${BACKLOG_COST:,.2f} per unit per week.
+        - **Holding Inventory:** **${HOLDING_COST:,.2f} per unit per week.** (Holding 10 units costs $5.00)
+        - **Backlog (Unfilled Orders):** **${BACKLOG_COST:,.2f} per unit per week.** (Having 5 unfilled orders costs $5.00)
         """)
-        
+        with st.expander("Click to see a cost calculation example"):
+            st.markdown(f"""
+            Imagine at the end of Week 5, your dashboard shows:
+            - `Current Inventory: 20`
+            - `Current Backlog: 3`
+            Your cost for Week 5 would be:
+            - `(20 units of Inventory * ${HOLDING_COST:,.2f})` = $10.00
+            - `(3 units of Backlog * ${BACKLOG_COST:,.2f})` = $3.00
+            - **Total Weekly Cost:** = **$13.00**
+            Your goal is to keep this number as low as possible, every week.
+            """)
+
         st.subheader("2. Your Role: The Distributor")
         st.markdown("""
         You will always play as the **Distributor**. The other 3 roles are played by AI.
-        
-        - **Retailer (AI):** Fulfills end-customer demand. Orders from the Wholesaler.
-        - **Wholesaler (AI):** Fulfills Retailer orders. Orders from the Distributor.
-        - **Distributor (You):** Fulfills Wholesaler orders. Orders from the Factory.
-        - **Factory (AI):** Fulfills your orders. Produces new beer.
+        - **Retailer (AI):** Sells to the final customer.
+        - **Wholesaler (AI):** Sells to the Retailer.
+        - **Distributor (You):** You sell to the Wholesaler.
+        - **Factory (AI):** You order from the Factory.
         """)
-        try:
-            st.image(IMAGE_PATH, caption="You are the Distributor. You get orders from the Wholesaler and place orders to the Factory.")
-        except FileNotFoundError:
-            st.warning("Image file not found. Please ensure 'beer_game_diagram.png' is uploaded to the repository.")
-            
+        try: st.image(IMAGE_PATH, caption="You are the Distributor. You get orders from the Wholesaler and place orders to the Factory.")
+        except FileNotFoundError: st.warning("Image file not found.")
+
         st.subheader("3. The Core Challenge: Delays!")
         st.warning(f"This is the most important rule: **It takes {ORDER_PASSING_DELAY + FACTORY_LEAD_TIME + FACTORY_SHIPPING_DELAY} weeks for an order you place to actually arrive in your inventory.**")
-        
         with st.expander("Click to see a detailed example of the 3-week delay"):
             st.markdown(f"""
             Let's follow a single order you place:
@@ -337,32 +401,27 @@ else:
             * **Week 11 (System):** Your order of 50 *arrives* at the Factory. (This is the **{ORDER_PASSING_DELAY} week Order Delay**). The Factory AI sees your order and decides to produce 50.
             * **Week 12 (System):** The Factory *finishes* producing the 50 units. (This is the **{FACTORY_LEAD_TIME} week Production Delay**). The Factory ships the 50 units to you.
             * **Week 13 (System):** The 50 units *arrive* at your warehouse. (This is the **{FACTORY_SHIPPING_DELAY} week Shipping Delay**). You can now use this inventory.
-            
             **Conclusion:** You must always think 3 weeks ahead. The order you place in Week 10 will not help you until Week 13.
             """)
-        
-        #st.subheader("4. The Bullwhip Effect (What to Avoid)")
-        #st.markdown("""
-        #The "Bullwhip Effect" is the main challenge of this game. It describes how small, normal changes in customer demand (at the Retailer) get **amplified** into huge, chaotic swings in orders as they move up the supply chain.
-        
-        #This often leads to a cycle of **panic ordering** (ordering way too much because you are out of stock) followed by a **massive pile-up of inventory** (when all your late orders finally arrive). This cycle is extremely expensive. Your goal is to avoid it by ordering smoothly.
-        #""")
-
-        st.subheader("4. How Each Week Works (Your Task)")
+
+        st.subheader("4. The Bullwhip Effect (What to Avoid)")
+        st.markdown("""
+        The "Bullwhip Effect" is the main challenge of this game. It describes how small, normal changes in customer demand (at the Retailer) get **amplified** into huge, chaotic swings in orders as they move up the supply chain.
+        This often leads to a cycle of **panic ordering** (ordering way too much because you are out of stock) followed by a **massive pile-up of inventory** (when all your late orders finally arrive). This cycle is extremely expensive. Your goal is to avoid it by ordering smoothly.
+        """)
+
+        st.subheader("5. How Each Week Works (Your Task)")
         st.markdown(f"""
         Your main job is simple: place one order each week.
-        
         **A) At the start of every week, the system automatically does 3 things:**
-        * **(Step 1) Your Shipments Arrive:** The beer you ordered 3 weeks ago arrives and is added to your `Current Inventory`.
+        * **(Step 1) Your Shipments Arrive:** The beer you ordered {ORDER_PASSING_DELAY + FACTORY_LEAD_TIME + FACTORY_SHIPPING_DELAY} weeks ago arrives and is added to your `Current Inventory`.
         * **(Step 2) New Orders Arrive:** You receive a new `Incoming Order` from the Wholesaler.
         * **(Step 3) You Ship Beer:** The system automatically ships as much beer as possible from your inventory to fulfill the Wholesaler's order (plus any old `Backlog`).
-        
         **B) After this, you will see your new dashboard and must make your 2-part decision:**
         * **Step 4a (Initial Order):** Based on your new status, submit your **initial order** to the Factory.
         * **Step 4b (Final Order):** You will then see an **AI suggestion**. Review it, then submit your **final order** to end the week.
         """)
-        # =======================================================
-        
+
         st.markdown("---")
         st.header("⚙️ Game Configuration")
         c1, c2 = st.columns(2)
@@ -370,7 +429,7 @@ else:
              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.")
-        
+
         if st.button("🚀 Start Game", type="primary", disabled=(client is None)):
             init_game_state(llm_personality, info_sharing)
             st.rerun()
@@ -379,7 +438,7 @@ else:
     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']
-        
+
         st.header(f"Week {week} / {WEEKS}")
         st.subheader(f"Your Role: **{human_role}** | AI Mode: **{state['llm_personality'].replace('_', ' ')}** | Information: **{state['info_sharing']}**")
         st.markdown("---")
@@ -391,12 +450,7 @@ else:
                     e, icon = echelons[name], "👤" if name == human_role else "🤖"
                     st.markdown(f"##### {icon} {name} {'(You)' if name == human_role else ''}")
                     st.metric("Inventory", e['inventory']); st.metric("Backlog", e['backlog'])
-                    
-                    # =============== NEW: REAL-TIME COST METRIC ===============
-                    if name == human_role:
-                        st.metric("Your Total Cost", f"${e['total_cost']:,.2f}")
-                    # =========================================================
-                        
+                    if name == human_role: st.metric("Your Total Cost", f"${e['total_cost']:,.2f}")
                     st.write(f"Incoming Order: **{e['incoming_order']}**")
                     if name == "Factory":
                         prod_completing = list(state['factory_production_pipeline'])[0] if state['factory_production_pipeline'] else 0
@@ -406,18 +460,15 @@ else:
                         st.write(f"Arriving Next Week: **{arriving}**")
         else:
             st.info("In Local Information mode, you can only see your own status dashboard.")
-            e = echelons[human_role] # This is always the Distributor
+            e = echelons[human_role]
             st.markdown(f"### 👤 {human_role} (Your Dashboard)")
             col1, col2, col3, col4 = st.columns(4)
             col1.metric("Current Inventory", e['inventory'])
             col2.metric("Current Backlog", e['backlog'])
             col3.write(f"**Incoming Order (This Week):**\n# {e['incoming_order']}")
             col4.write(f"**Shipment Arriving (Next Week):**\n# {list(e['incoming_shipments'])[0] if e['incoming_shipments'] else 0}")
-            
-            # =============== NEW: REAL-TIME COST METRIC ===============
             st.metric("Your Total Cumulative Cost", f"${e['total_cost']:,.2f}")
-            # =========================================================
-        
+
         st.markdown("---")
         st.header("Your Decision (Step 4)")
         human_echelon_state = echelons[human_role]
@@ -430,12 +481,12 @@ else:
                     state['human_initial_order'] = int(initial_order)
                     state['decision_step'] = 'final_order'
                     st.rerun()
-        
+
         elif state['decision_step'] == 'final_order':
             st.success(f"Your initial order was: **{state['human_initial_order']}** units.")
             prompt_sugg = get_llm_prompt(human_echelon_state, week, state['llm_personality'], state['info_sharing'], echelons)
             ai_suggestion, _ = get_llm_order_decision(prompt_sugg, f"{human_role} (Suggestion)")
-            
+
             if 'final_order_input' not in st.session_state:
                 st.session_state.final_order_input = ai_suggestion
 
@@ -450,34 +501,65 @@ else:
                     st.rerun()
 
         st.markdown("---")
+        # =============== CORRECTED LOG DISPLAY BLOCK ===============
         with st.expander("📖 Your Weekly Decision Log", expanded=False):
-            if not state['logs']:
+            if not state.get('logs'): # Use .get() for safety
                 st.write("Your weekly history will be displayed here after you complete the first week.")
             else:
-                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',
-                }
-                display_cols = [col for col in human_cols.keys() if col in history_df.columns]
-                display_df = history_df[display_cols].rename(columns=human_cols)
-                if 'Weekly Cost' in display_df:
-                    display_df['Weekly Cost'] = display_df['Weekly Cost'].apply(lambda x: f"${x:,.2f}")
-                st.dataframe(display_df.sort_values(by="Week", ascending=False), hide_index=True, use_container_width=True)
+                try: # Add error handling for data processing
+                    history_df = pd.json_normalize(state['logs'])
+
+                    # Define all desired columns and their display names
+                    human_cols = {
+                        'week': 'Week',
+                        f'{human_role}.opening_inventory': 'Opening Inv.',
+                        f'{human_role}.opening_backlog': 'Opening Backlog',
+                        f'{human_role}.arrived_this_week': 'Arrived This Week', # Shipment that arrived at Step 1
+                        f'{human_role}.incoming_order': 'Incoming Order', # Order received at Step 2
+                        f'{human_role}.initial_order': 'Your Initial Order', # Step 4a
+                        f'{human_role}.ai_suggestion': 'AI Suggestion', # Step 4b
+                        f'{human_role}.order_placed': 'Your Final Order', # Step 4b (Order for Week+3)
+                        f'{human_role}.arriving_next_week': 'Arriving Next Week', # What will arrive in Step 1 of NEXT week
+                        f'{human_role}.weekly_cost': 'Weekly Cost', # Calculated at end of week
+                    }
+
+                    # Define the desired order of columns
+                    ordered_display_cols_keys = [
+                        'week', f'{human_role}.opening_inventory', f'{human_role}.opening_backlog',
+                        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'
+                     ]
+
+                    # Filter the desired columns based on what actually exists in the log data
+                    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:
+                        # Select and rename the columns that exist
+                        display_df = history_df[final_cols_to_display].rename(columns=human_cols)
+
+                        # Format the cost column
+                        if 'Weekly Cost' in display_df.columns:
+                            # Apply formatting safely, handling potential non-numeric data
+                            display_df['Weekly Cost'] = display_df['Weekly Cost'].apply(lambda x: f"${x:,.2f}" if isinstance(x, (int, float)) else "")
+
+                        # Display the dataframe
+                        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}")
+                    st.write("Log data structure might be inconsistent.")
+        # =======================================================
+
+        try: st.sidebar.image(IMAGE_PATH, caption="Supply Chain Reference")
+        except FileNotFoundError: st.sidebar.warning("Image file not found.")
 
-        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 'final_order_input' in st.session_state: del st.session_state.final_order_input
             del st.session_state.game_state
             st.rerun()
 
@@ -485,16 +567,19 @@ else:
     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:
         st.header("🎉 Game Over!")
         state = st.session_state.game_state
-        logs_df = pd.json_normalize(state['logs'])
-        
-        fig = plot_results(
-            logs_df, 
-            f"Beer Game (Human: {state['human_role']})\n(AI: {state['llm_personality']} | Info: {state['info_sharing']})", 
-            state['human_role']
-        )
-        
-        st.pyplot(fig)
-        save_logs_and_upload(state)
+        try: # Add error handling for final plot/save
+            logs_df = pd.json_normalize(state['logs'])
+            fig = plot_results(
+                logs_df,
+                f"Beer Game (Human: {state['human_role']})\n(AI: {state['llm_personality']} | Info: {state['info_sharing']})",
+                state['human_role']
+            )
+            st.pyplot(fig)
+            save_logs_and_upload(state)
+        except Exception as e:
+            st.error(f"Error generating final report: {e}")
+            st.write("Log data might be corrupted or incomplete.")
+
         if st.button("✨ Start a New Game"):
             del st.session_state.game_state
             st.rerun()