Update app.py

app.py

@@ -1,5 +1,6 @@
 # app.py
-# @title Beer Game Final Version (v4.21 - Removed Introduction)
+# @title Beer Game Final Version (v4.21 - Corrected 3-Week Lead Time Logic & UI)
+
 # -----------------------------------------------------------------------------
 # 1. Import Libraries
 # -----------------------------------------------------------------------------
@@ -21,6 +22,7 @@ from huggingface_hub import HfApi
 # -----------------------------------------------------------------------------
 st.set_page_config(page_title="Beer Game: Human-AI Collaboration", layout="wide")
 
+
 # -----------------------------------------------------------------------------
 # 2. Game Parameters & API Configuration
 # -----------------------------------------------------------------------------
@@ -53,16 +55,20 @@ except Exception as e:
 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
 
+# =============== CORRECTED Initialization (v4.17 logic) ===============
 def init_game_state(llm_personality: str, info_sharing: str):
     roles = ["Retailer", "Wholesaler", "Distributor", "Factory"]
     human_role = "Distributor" # Role is fixed
     participant_id = str(uuid.uuid4())[:8]
+
     st.session_state.game_state = {
         'game_running': True, 'participant_id': participant_id, 'week': 1,
         'human_role': human_role, 'llm_personality': llm_personality,
@@ -70,14 +76,18 @@ def init_game_state(llm_personality: str, info_sharing: str):
         '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
         '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),
@@ -85,6 +95,7 @@ def init_game_state(llm_personality: str, info_sharing: str):
             '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}**.")
+# ==============================================================================
 
 def get_llm_order_decision(prompt: str, echelon_name: str) -> (int, str):
     # This function remains correct.
@@ -119,7 +130,6 @@ 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'])}"
-
     if llm_personality == 'perfect_rational' and info_sharing == 'full':
         stable_demand = 8
         if e_state['name'] == 'Factory': total_lead_time = FACTORY_LEAD_TIME
@@ -136,7 +146,6 @@ def get_llm_prompt(echelon_state_decision_point: dict, week: int, llm_personalit
             inv_pos_components = f"(Inv={e_state['inventory']} - Backlog={e_state['backlog']} + InTransitShip={sum(e_state['incoming_shipments'])} + OrderToSupplier={order_in_transit_to_supplier})"
         optimal_order = max(0, int(target_inventory_level - inventory_position))
         return f"**You are a perfectly rational supply chain AI with full system visibility.**\nYour only goal is to maintain stability and minimize costs based on mathematical optimization.\n**System Analysis:**\n* **Known Stable End-Customer Demand:** {stable_demand} units/week.\n* **Your Current Total Inventory Position:** {inventory_position} units. {inv_pos_components}\n* **Optimal Target Inventory Level:** {target_inventory_level} units (Target for {total_lead_time} weeks lead time).\n* **Mathematically Optimal {task_word.title()}:** The optimal decision is **{optimal_order} units**.\n**Your Task:** Confirm this optimal {task_word}. Respond with a single integer."
-
     elif llm_personality == 'perfect_rational' and info_sharing == 'local':
         safety_stock = 4; anchor_demand = e_state['incoming_order']
         inventory_correction = safety_stock - (e_state['inventory'] - e_state['backlog'])
@@ -150,7 +159,6 @@ def get_llm_prompt(echelon_state_decision_point: dict, week: int, llm_personalit
         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 (before shipping) is {e_state['inventory'] - e_state['backlog']}. You need to order an extra **{inventory_correction} units** to correct this.\n3.  **Account for {supply_line_desc}:** You already have **{supply_line} units** being processed. These should be subtracted from your new decision.\n\n**Final Calculation:**\n* Decision = (Anchor Demand) + (Inventory Adjustment) - ({supply_line_desc})\n* Decision = {anchor_demand} + {inventory_correction} - {supply_line} = **{rational_local_order} units**.\n**Your Task:** Confirm this locally rational {task_word}. Respond with a single integer."
-
     elif llm_personality == 'human_like' and info_sharing == 'full':
         full_info_str = f"\n**Full Supply Chain Information (State Before Shipping):**\n- End-Customer Demand this week: {get_customer_demand(week)} units.\n"
         for name, other_e_state in all_echelons_state_decision_point.items():
@@ -165,7 +173,6 @@ def get_llm_prompt(echelon_state_decision_point: dict, week: int, llm_personalit
         You are still human and might get anxious about your own stock levels.
         What {task_word} should you decide on this week? Respond with a single integer.
         """
-
     elif llm_personality == 'human_like' and info_sharing == 'local':
         return f"""
         **You are a reactive supply chain manager for the {e_state['name']}.** You have a limited view and tend to over-correct based on fear.
@@ -176,88 +183,139 @@ 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}
-    inventory_after_arrival = {}
 
+    # --- Game Simulation Steps ---
+
+    # Step 1a: Factory Production completes
     factory_state = echelons["Factory"]
     produced_units = 0
     if state['factory_production_pipeline']:
-        produced_units = state['factory_production_pipeline'].popleft()
+        produced_units = state['factory_production_pipeline'].popleft() # Pop completed production
         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()
+            arrived_shipment = echelons[name]['incoming_shipments'].popleft() # Pop arrived shipment
             arrived_this_week[name] = arrived_shipment
         inventory_after_arrival[name] = echelons[name]['inventory'] + arrived_shipment
 
-    total_backlog_before_shipping = {}
+    # Step 2: Orders Arrive from Downstream
+    total_backlog_before_shipping = {} # Store intermediate backlog state
     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
+            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
         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],
-             'backlog': total_backlog_before_shipping[name], 'incoming_order': echelons[name]['incoming_order'],
+             '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
              'incoming_shipments': echelons[name]['incoming_shipments'].copy() if name != "Factory" else deque(),
          }
 
-    current_week_orders = {}
+    # --- Step 4: Agent Decisions (Place Orders / Schedule Production) ---
+    current_week_orders = {} # Store THIS week's decisions
     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']
 
-    state['factory_production_pipeline'].append(echelons["Factory"]['order_placed'])
+        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) ---
     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']
+        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'])
 
-    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'])
+    # 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) ---
     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']
+
     for name in echelon_order:
-        e = echelons[name]; e['weekly_cost'] = (e['inventory'] * HOLDING_COST) + (e['backlog'] * BACKLOG_COST); e['total_cost'] += e['weekly_cost']
-        for key in ['inventory', 'backlog', 'incoming_order', 'order_placed', 'shipment_sent', 'weekly_cost', 'total_cost']: log_entry[f'{name}.{key}'] = e[key]
-        log_entry[f'{name}.llm_raw_response'] = llm_raw_responses.get(name, "")
+        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, "")
         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
     if state['week'] > WEEKS: state['game_running'] = False
+# ==============================================================================
+
 
 def plot_results(df: pd.DataFrame, title: str, human_role: str):
     # This function remains correct.
@@ -318,16 +376,41 @@ 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):
-        
-        # --- Introduction Section Removed as Requested ---
-        
+
+        # --- Introduction Section (Remains Correct) ---
+        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. **You do not need any prior knowledge to play.** Please read these instructions carefully.")
+        st.subheader("1. Your Goal: Minimize Costs")
+        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:** **${HOLDING_COST:,.2f} per unit per week.** (Cost applies to inventory left *after* shipping)\n- **Backlog (Unfilled Orders):** **${BACKLOG_COST:,.2f} per unit per week.** (Cost applies to orders you couldn't fill *after* shipping)")
+        with st.expander("Click to see a cost calculation example"):
+            st.markdown(f"Imagine at the **end** of Week 5, *after* you shipped beer to the Wholesaler, your final state is:\n- Inventory: 10 units\n- Backlog: 0 units\nYour cost for Week 5 would be calculated *at this point*:\n- `(10 units of Inventory * ${HOLDING_COST:,.2f})` = $5.00\n- `(0 units of Backlog * ${BACKLOG_COST:,.2f})` = $0.00\n- **Total Weekly Cost:** = **$5.00**\nThis cost is added to your cumulative total.")
+        st.subheader("2. Your Role: The Distributor")
+        st.markdown("You will always play as the **Distributor**. The other 3 roles are played by AI.\n- **Retailer (AI):** Sells to the final customer.\n- **Wholesaler (AI):** Sells to the Retailer.\n- **Distributor (You):** You sell to the Wholesaler.\n- **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.")
+        st.subheader("3. The Core Challenge: Delays!")
+        st.warning(f"It takes **{ORDER_PASSING_DELAY + FACTORY_LEAD_TIME + FACTORY_SHIPPING_DELAY} weeks** for an order you place to arrive in your inventory.")
+        with st.expander("Click to see a detailed example of the 3-week delay"):
+            st.markdown(f"* **Week 10 (You):** You place an order for **50**.\n* **Week 11 (System):** Your order arrives at the Factory (**{ORDER_PASSING_DELAY}w Order Delay**). Factory AI decides to produce 50.\n* **Week 12 (System):** Factory finishes producing 50 (**{FACTORY_LEAD_TIME}w Production Delay**) & ships it.\n* **Week 13 (System):** The 50 units arrive at your warehouse (**{FACTORY_SHIPPING_DELAY}w Shipping Delay**).\n**Conclusion:** Think 3 weeks ahead! Your order in Week 10 arrives at the start of Week 13.")
+        st.subheader("4. Understanding Inventory & Backlog")
+        st.markdown("Managing your inventory and backlog is key to minimizing costs. Here's how they work:\n* **Effective \"Orders to Fill\":** Each week, the total demand you need to satisfy is your `Incoming Order` for the week PLUS any `Backlog` carried over from the previous week.\n* **If you DON'T have enough inventory:**\n    * You ship **all** the inventory you have (after receiving any arrivals for the week).\n    * The remaining unfilled \"Orders to Fill\" becomes your **new Backlog** for next week.\n    * **Backlog is cumulative!** If you start Week 10 with a backlog of 5, get an order for 8 (total needed = 13), receive 10 units, and ship those 10 units, your new backlog for Week 11 is `13 - 10 = 3`.\n* **If you DO have enough inventory:**\n    * You ship all the \"Orders to Fill\".\n    * Your Backlog becomes 0.\n    * The remaining inventory is carried over to next week (and incurs holding costs).")
+        st.subheader("5. The Bullwhip Effect (What to Avoid)")
+        st.markdown("The \"Bullwhip Effect\" happens when small changes in customer demand cause **amplified**, chaotic swings in orders further up the supply chain (like you and the Factory). This often leads to cycles of **panic ordering** (ordering too much when out of stock) followed by **massive inventory pile-ups** (when late orders arrive). This cycle is very expensive. Try to order smoothly.")
+        st.subheader("6. How Each Week Works & Understanding Your Dashboard")
+        st.markdown(f"Your main job is simple: place one order each week based on the dashboard presented to you.\n\n**A) At the start of every week, BEFORE your turn:**\n* **(Step 1) Shipments Arrive:** Beer you ordered {ORDER_PASSING_DELAY + FACTORY_LEAD_TIME + FACTORY_SHIPPING_DELAY} weeks ago arrives.\n* **(Step 2) New Orders Arrive:** You receive a new order from the Wholesaler (their order from *last* week).\n* **(Step 3) You Ship Beer (Automatically):** The system ships beer *immediately* based on your inventory *after* Step 1 and the total demand *after* Step 2.\n\n**B) Your Dashboard (What You See for Your Turn):**\nThe dashboard shows your status **at the start of the week, BEFORE Steps 1, 2, and 3 happen**:\n* `Inventory (Opening)`: Your stock **at the beginning of the week**.\n* `Backlog (Opening)`: Unfilled orders **carried over from the end of last week**.\n* `Incoming Order (This Week)`: The specific order quantity that **will arrive** from the Wholesaler *during* this week (Step 2).\n* `Arriving This Week`: The shipment from the Factory that **will arrive** *during* this week (Step 1).\n* `Arriving Next Week`: The quantity scheduled to arrive at the start of the **next week**.\n\n**C) Your Decision (Step 4 - Two Parts):**\nNow, looking at the dashboard, you decide how much to order:\n* **(Step 4a - Initial Order):** Submit your first estimate. Input box starts blank.\n* **(Step 4b - Final Order):** See the AI's suggestion, then submit your final decision. This order will arrive in 3 weeks.\n\nSubmitting your final order ends the week. The system then calculates your `Weekly Cost` based on your inventory/backlog *after* Step 3 shipping, logs everything, and advances to the next week.")
+
+        # --- Game Configuration ---
+        st.markdown("---")
         st.header("⚙️ Game Configuration")
         c1, c2 = st.columns(2)
         with c1:
              llm_personality = st.selectbox("AI Agent 'Personality'", ('human_like', 'perfect_rational'), format_func=lambda x: x.replace('_', ' ').title(), help="**Human-like:** Tends to react emotionally, potentially over-ordering. **Perfect Rational:** Uses a mathematical heuristic to make stable, logical decisions.")
         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()
@@ -337,38 +420,30 @@ else:
         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}** | AI Mode: **{state['llm_personality'].replace('_', ' ')}** | Information: **{state['info_sharing']}**")
         st.markdown("---")
-        
         st.subheader("Supply Chain Status (Start of Week State)") # Clarified Timing
-        
+
+        # =============== MODIFIED UI LOGIC (v4.21) ===============
         if info_sharing == 'full':
             cols = st.columns(4)
-            for i, name in enumerate(echelon_order): # Use the defined echelon_order
+            for i, name in enumerate(echelon_order):
                 with cols[i]:
-                    e = echelons[name] # Get the echelon state
+                    e = echelons[name]
                     icon = "👤" if name == human_role else "🤖"
-                    
-                    # =============== UI CHANGE: Highlight Player ===============
+
                     if name == human_role:
-                        # Use markdown with HTML/CSS for highlighting
                         st.markdown(f"##### **<span style='border: 1px solid #FF4B4B; padding: 2px 5px; border-radius: 3px;'>{icon} {name} (You)</span>**", unsafe_allow_html=True)
                     else:
                         st.markdown(f"##### {icon} {name}")
-                    # ========================================================
                     
-                    # Display the END OF LAST WEEK state (which is OPENING state for this week)
                     st.metric("Inventory (Opening)", e['inventory'])
                     st.metric("Backlog (Opening)", e['backlog'])
-                    
-                    # =============== UI CHANGE: Removed Costs ===============
-                    # Costs are no longer displayed on the main dashboard
-                    # =======================================================
-                    
-                    # Display info about THIS week's events / NEXT week's arrivals
-                    # Calculate the INCOMING order for THIS week
+
+                    # --- Calculate and Display This Week's Events ---
+                    # Incoming Order (arriving in Step 2)
                     current_incoming_order = 0
                     if name == "Retailer":
                         current_incoming_order = get_customer_demand(week)
@@ -376,40 +451,51 @@ 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}**") # Display calculated order
-                    
-                    # Display prediction for NEXT week's arrivals
+                    st.write(f"Incoming Order (This Week): **{current_incoming_order}**")
+
                     if name == "Factory":
-                        prod_completing_next = list(state['factory_production_pipeline'])[0] if state['factory_production_pipeline'] else 0
+                        # Production completing THIS week (Step 1a)
+                        arriving_this_week = list(state['factory_production_pipeline'])[0] if state['factory_production_pipeline'] else 0
+                        st.write(f"Completing This Week: **{arriving_this_week}**")
+                        # Production completing NEXT week
+                        prod_completing_next = list(state['factory_production_pipeline'])[1] if len(state['factory_production_pipeline']) > 1 else 0
                         st.write(f"Completing Next Week: **{prod_completing_next}**")
                     else:
-                        arriving_next = list(e['incoming_shipments'])[0] if e['incoming_shipments'] else 0
+                        # Shipment arriving THIS week (Step 1b)
+                        arriving_this_week = list(e['incoming_shipments'])[0] if e['incoming_shipments'] else 0
+                        st.write(f"Arriving This Week: **{arriving_this_week}**")
+                        # Shipment arriving NEXT week
+                        arriving_next = list(e['incoming_shipments'])[1] if len(e['incoming_shipments']) > 1 else 0
                         st.write(f"Arriving Next Week: **{arriving_next}**")
+        
         else: # Local Info Mode
             st.info("In Local Information mode, you can only see your own status dashboard.")
             e = echelons[human_role]
-            st.markdown(f"### 👤 **<span style='color:#FF4B4B;'>{human_role} (Your Dashboard - Start of Week State)</span>**", unsafe_allow_html=True) # Highlight self
-            col1, col2, col3, col4 = st.columns(4)
-            
-            # Display OPENING state
-            col1.metric("Inventory (Opening)", e['inventory'])
-            col2.metric("Backlog (Opening)", e['backlog'])
-            
-            # Display info about THIS week's events / NEXT week's arrivals
-            # Calculate the INCOMING order for THIS week
-            current_incoming_order = 0
-            downstream_name = e['downstream_name'] # Wholesaler
-            if downstream_name:
-                 current_incoming_order = state['last_week_orders'].get(downstream_name, 0)
-            
-            col3.write(f"**Incoming Order (This Week):**\n# {current_incoming_order}") # Display calculated order
-            col4.write(f"**Shipment Arriving (Next Week):**\n# {list(e['incoming_shipments'])[0] if e['incoming_shipments'] else 0}")
+            st.markdown(f"### 👤 **<span style='color:#FF4B4B;'>{human_role} (Your Dashboard - Start of Week State)</span>**", unsafe_allow_html=True)
+
+            col1, col2 = st.columns(2)
+            with col1:
+                st.metric("Inventory (Opening)", e['inventory'])
+                st.metric("Backlog (Opening)", e['backlog'])
             
-            # =============== UI CHANGE: Removed Costs ===============
-            # Costs are no longer displayed on the main dashboard
-            # =======================================================
+            with col2:
+                # Calculate Incoming Order for this week
+                current_incoming_order = 0
+                downstream_name = e['downstream_name'] # Wholesaler
+                if downstream_name:
+                     current_incoming_order = state['last_week_orders'].get(downstream_name, 0)
+                st.write(f"**Incoming Order (This Week):**\n# {current_incoming_order}")
+                
+                # Arriving THIS week (Step 1)
+                arriving_this_week = list(e['incoming_shipments'])[0] if e['incoming_shipments'] else 0
+                st.write(f"**Shipment Arriving (This Week):**\n# {arriving_this_week}")
+                
+                # Arriving NEXT week
+                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("---")
         st.header("Your Decision (Step 4)")
 
@@ -418,66 +504,57 @@ else:
         for name in echelon_order:
             e_curr = echelons[name] # This is END OF LAST WEEK state
             arrived = 0
-            # Peek at what *will* arrive this week (Step 1) based on current queues
             if name == "Factory":
                  if state['factory_production_pipeline']: arrived = list(state['factory_production_pipeline'])[0]
             else:
                  if e_curr['incoming_shipments']: arrived = list(e_curr['incoming_shipments'])[0]
             
-            # Calculate the state AFTER arrivals and incoming orders for the prompt
-            inv_after_arrival = e_curr['inventory'] + arrived
-            
-            # Determine incoming order for *this* week again for prompt state
             inc_order_this_week = 0
             if name == "Retailer": inc_order_this_week = get_customer_demand(week)
             else:
                 ds_name = e_curr['downstream_name']
                 if ds_name: inc_order_this_week = state['last_week_orders'].get(ds_name, 0)
-            
+
+            inv_after_arrival = e_curr['inventory'] + arrived
             backlog_after_new_order = e_curr['backlog'] + inc_order_this_week
             
             all_decision_point_states[name] = {
                 'name': name, 'inventory': inv_after_arrival, 'backlog': backlog_after_new_order,
-                'incoming_order': inc_order_this_week, # Use the correctly calculated incoming 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.")
                 # =============== UI CHANGE: Removed Default Value ===============
-                initial_order = st.number_input("Your Initial Order Quantity:", min_value=0, step=1) # No 'value' argument
+                initial_order = st.number_input("Your Initial Order Quantity:", min_value=0, step=1) # No 'value'
                 # ===============================================================
                 if st.form_submit_button("Submit Initial Order & See AI Suggestion", type="primary"):
-                    # Handle case where user leaves it blank (input returns None)
                     state['human_initial_order'] = int(initial_order) if initial_order is not None else 0
                     state['decision_step'] = 'final_order'
                     st.rerun()
 
         elif state['decision_step'] == 'final_order':
             st.success(f"Your initial order was: **{state['human_initial_order']}** units.")
-            
-            # Use the correctly timed state for the prompt
             prompt_sugg = get_llm_prompt(human_echelon_state_for_prompt, week, state['llm_personality'], state['info_sharing'], all_decision_point_states)
             ai_suggestion, _ = get_llm_order_decision(prompt_sugg, f"{human_role} (Suggestion)")
-            
+
             with st.form(key="final_order_form"):
                 st.markdown(f"#### **Step 4b:** The AI suggests ordering **{ai_suggestion}** units.")
                 st.markdown("Considering the AI's advice, submit your **final** order to end the week. (This order will arrive in 3 weeks).")
                 # =============== UI CHANGE: Removed Default Value ===============
-                st.number_input("Your Final Order Quantity:", min_value=0, step=1, key='final_order_input') # No 'value' argument
+                st.number_input("Your Final Order Quantity:", min_value=0, step=1, key='final_order_input') # No 'value'
                 # ===============================================================
                 
                 if st.form_submit_button("Submit Final Order & Advance to Next Week"):
-                    # Handle case where user leaves it blank
-                    final_order_value = st.session_state.get('final_order_input', 0) # Use .get with default
+                    final_order_value = 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)
                     
-                    # Clean up session state for the input key
                     if 'final_order_input' in st.session_state: del st.session_state.final_order_input
                     st.rerun()
 
@@ -502,6 +579,7 @@ else:
                         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:
@@ -514,6 +592,7 @@ else:
 
         try: st.sidebar.image(IMAGE_PATH, caption="Supply Chain Reference")
         except FileNotFoundError: st.sidebar.warning("Image file not found.")
+
         st.sidebar.header("Game Info")
         st.sidebar.markdown(f"**Game ID**: `{state['participant_id']}`\n\n**Current Week**: {week}")
         if st.sidebar.button("🔄 Reset Game"):