Update app.py with mock ingredients

app.py

@@ -1,46 +1,74 @@
 import gradio as gr
 import pandas as pd
-import json
 
-# Placeholder processing function mimicking an edge asset inspection pipeline
-def process_fridge_survey(input_image):
-    # This structure mirrors how an industrial site survey maps physical gear to JSON
+# =====================================================================
+# 🔀 LOCAL DETERMINISTIC LOGISTICS & RESOURCE ROUTING ENGINE
+# =====================================================================
+def process_kitchen_operations(input_image, budget, days):
+    # 1. Physical Edge Ingestion Simulation (Assets parsed from the scan)
     mock_detected_assets = {
         "assets": [
-            {"ingredient": "Greek Yogurt", "qty": "0.5 Liters", "status": "Fresh", "est_cost_usd": 2.50},
-            {"ingredient": "Baby Spinach", "qty": "1 Bag", "status": "Wilting (Use Immediately)", "est_cost_usd": 3.00},
-            {"ingredient": "Chicken Breast", "qty": "400 Grams", "status": "Fresh", "est_cost_usd": 6.50},
-            {"ingredient": "Yellow Onion", "qty": "1 Whole", "status": "Fresh", "est_cost_usd": 0.80}
+            {"ingredient": "Greek Yogurt", "qty": "0.5 Liters", "status": "Fresh", "est_cost_usd": 2.50, "calories": 300},
+            {"ingredient": "Baby Spinach", "qty": "1 Bag", "status": "Wilting (Critical)", "est_cost_usd": 3.00, "calories": 50},
+            {"ingredient": "Chicken Breast", "qty": "400 Grams", "status": "Fresh", "est_cost_usd": 6.50, "calories": 650},
+            {"ingredient": "Yellow Onion", "qty": "1 Whole", "status": "Fresh", "est_cost_usd": 0.80, "calories": 40}
         ]
     }
     
-    # Map the unstructured visual results directly into our Digital Twin Dataframe
+    # 2. Map unstructured results directly into our Digital Twin Dataframe format
     df_rows = [
         [item['ingredient'], item['qty'], item['status'], f"${item['est_cost_usd']:.2f}"] 
         for item in mock_detected_assets['assets']
     ]
-    return df_rows
+    
+    # 3. Constraint-Based Routing Optimization Logic (Local Math Execution)
+    daily_budget_allowance = budget / days
+    total_asset_value = sum(item['est_cost_usd'] for item in mock_detected_assets['assets'])
+    
+    # Prioritization check for expiring assets (The Wilting Spinach)
+    critical_items = [item['ingredient'] for item in mock_detected_assets['assets'] if "Wilting" in item['status']]
+    
+    # Generate the dynamic markdown operational blueprint
+    blueprint_md = f"### 🛠️ Logistics Routing Strategy Generated\n"
+    blueprint_md += f"**Operational Horizon:** {days} Days | **Daily Financial Ceiling:** ${daily_budget_allowance:.2f}/day\n\n"
+    
+    blueprint_md += "#### 🚨 High-Priority Asset Despatches (Use Immediately):\n"
+    for item in critical_items:
+        blueprint_md += f"- **{item}** showing high decay telemetry. Scheduled for immediate integration into Day 1.\n"
+        
+    blueprint_md += "\n#### 📋 Cook Execution Pathway:\n"
+    blueprint_md += f"- **Day 1 (Asset Optimization):** Creamy Spinach & Chicken Skillet. *Saves {critical_items[0] if critical_items else 'assets'} from spoiling. Uses $0.00 extra out-of-pocket budget.*\n"
+    
+    if daily_budget_allowance < 5.00:
+        blueprint_md += "- **Day 2-3 (Scarcity Protocol):** Greek Yogurt Marinated Chicken bites with caramelized onions. *Hyper-low resource allocation mode engaged to preserve budget runway.*"
+    else:
+        blueprint_md += "- **Day 2-3 (Nominal Operations):** Chicken Prep over balanced greens. *Nominal baseline strategy.*"
+        
+    return df_rows, blueprint_md
 
-# Build out the Operational Control Center Dashboard Layout
-with gr.Blocks(theme=gr.themes.Monochrome()) as demo:
+# =====================================================================
+# 🎨 GRADIO 6.0 OPERATIONS CENTER DESIGN
+# =====================================================================
+# Notice: Removed theme option from here to fix the startup crash
+with gr.Blocks() as demo:
     gr.Markdown("# 🛰️ Parallel Plate: Kitchen Operations & Visual Logistics Engine")
-    gr.Markdown("### *Physical-to-Digital Twin Asset Management Pipeline (Sub-32B Model Framework)*")
+    gr.Markdown("### *Physical-to-Digital Twin Asset Management Pipeline (Badge Tier: 🔌 Off the Grid)*")
     
     with gr.Row():
-        # Left Column: Optical Ingestion Layer (The "Drone Site Survey" equivalent)
+        # Left Operational Node: Sensory Edge Scanning
         with gr.Column(scale=1):
             gr.Markdown("### 📸 1. Physical Edge Ingestion")
             image_input = gr.Image(label="Upload Fridge Optical Survey Scan", type="pil")
             
             with gr.Row():
-                budget_slider = gr.Slider(minimum=5, maximum=100, value=25, step=5, label="Remaining Runway Budget ($ USD)")
+                budget_slider = gr.Slider(minimum=5, maximum=100, value=25, step=5, label="Runway Budget ($ USD)")
                 days_slider = gr.Slider(minimum=1, maximum=7, value=3, step=1, label="Target Horizon (Days)")
                 
             scan_btn = gr.Button("🚀 Initialize Asset Optimization Scan", variant="primary")
             
-        # Right Column: The Asset Manifest State Machine (The Digital Twin Dashboard)
+        # Right Operational Node: Real-time State Machine Telemetry
         with gr.Column(scale=1):
-            gr.Markdown("### 📊 2. Active Kitchen Digital Twin")
+            gr.Markdown("### 📊 2. Active Refrigerator Digital Twin")
             inventory_df = gr.Dataframe(
                 headers=["Ingredient Asset", "Current Volume / Qty", "Telemetry Status", "Book Value (Est)"],
                 datatype=["str", "str", "str", "str"],
@@ -48,19 +76,19 @@ with gr.Blocks(theme=gr.themes.Monochrome()) as demo:
                 interactive=True
             )
             
-            gr.Markdown("### 🛠️ 3. Resource Routing & Recipe Output")
+            gr.Markdown("### 🔀 3. Resource Routing & Recipe Output")
             output_text = gr.Markdown("*Awaiting asset telemetry mapping to generate optimal cooking execution paths...*")
 
-    # Define the trigger mapping link
+    # Wire up the execution event trigger loop
     scan_btn.click(
-        fn=process_fridge_survey,
-        inputs=[image_input],
-        outputs=[inventory_df]
+        fn=process_kitchen_operations,
+        inputs=[image_input, budget_slider, days_slider],
+        outputs=[inventory_df, output_text]
     )
 
-# Launch the engine
 if __name__ == "__main__":
-    demo.launch()
+    # Theme configuration parameters are passed cleanly here to meet Gradio 6.0 strict specs
+    demo.launch(theme=gr.themes.Monochrome())
 
 ## trial 1
 # import gradio as gr