Update app.py

app.py

@@ -16,7 +16,7 @@ import requests
 import os  # Import the os module to access environment variables
 
 # Hugging Face API configuration
-HUGGINGFACE_API_URL = "https://router.huggingface.co/hf-inference/models/google-bert/bert-base-multilingual-cased"  # Corrected URL
+HUGGINGFACE_API_URL = "https://api-inference.huggingface.co/models/gpt2"  # Replace with the desired model
 HUGGINGFACE_API_KEY = os.environ["HUGGINGFACE_API_KEY"]  # Access the API key from environment variables
 
 # Hugging Face Chatbot Function
@@ -243,23 +243,74 @@ with gr.Blocks() as app:
     """)
     gr.Markdown("# 🔐 Circular Economy Marketplace")
     
-    # Existing tabs (Login/Register, Product Lifecycle Prediction, etc.)
+    # Login/Register Tab
     with gr.Tab("Login/Register"):
-        # ... (existing code)
-
+        with gr.Tab("Register"):
+            reg_username = gr.Textbox(label="Username")
+            reg_password = gr.Textbox(label="Password", type="password")
+            reg_btn = gr.Button("Register")
+            reg_output = gr.Textbox()
+            reg_btn.click(register, inputs=[reg_username, reg_password], outputs=reg_output)
+        with gr.Tab("Login"):
+            log_username = gr.Textbox(label="Username")
+            log_password = gr.Textbox(label="Password", type="password")
+            log_btn = gr.Button("Login")
+            log_output = gr.Textbox()
+            log_btn.click(login, inputs=[log_username, log_password], outputs=log_output)
+
+    # Product Lifecycle Prediction Tab
     with gr.Tab("Product Lifecycle Prediction"):
-        # ... (existing code)
-
+        lifecycle_inputs = [
+            gr.Dropdown(["Plastic", "Metal", "Wood", "Composite", "Electronics"], label="Category"),
+            gr.Textbox(label="Product Name"),
+            gr.Number(label="Price"),
+            gr.Number(label="Rating"),
+            gr.Number(label="NumReviews"),
+            gr.Number(label="StockQuantity"),
+            gr.Number(label="Discount")
+        ]
+        lifecycle_output = gr.Textbox(label="Prediction")
+        lifecycle_btn = gr.Button("Predict")
+        lifecycle_btn.click(predict_lifecycle, inputs=lifecycle_inputs, outputs=lifecycle_output)
+
+    # Dynamic Pricing Tab
     with gr.Tab("Dynamic Pricing"):
-        # ... (existing code)
-
+        pricing_inputs = [
+            gr.Dropdown(["iPhone 13", "Nike Shoes", "Samsung TV", "Adidas Jacket", "Dell Laptop", "Sony Headphones", "Apple Watch",
+                         "LG Refrigerator", "HP Printer", "Bose Speaker"], label="Product Name"),
+            gr.Dropdown(["Electronics", "Fashion", "Home Appliances"], label="Category"),
+            gr.Number(label="Base Price"),
+            gr.Number(label="Competitor Price"),
+            gr.Dropdown(["Low", "Medium", "High"], label="Demand"),
+            gr.Number(label="Stock"),
+            gr.Number(label="Reviews"),
+            gr.Number(label="Rating"),
+            gr.Dropdown(["Holiday", "Summer", "Winter", "Off-season"], label="Season"),
+            gr.Number(label="Discount (%)")
+        ]
+        pricing_output = gr.Textbox(label="Predicted Price")
+        pricing_btn = gr.Button("Predict")
+        pricing_btn.click(predict_price, inputs=pricing_inputs, outputs=pricing_output)
+
+    # Product Recommendation Tab
     with gr.Tab("Product Recommendation"):
-        # ... (existing code)
+        recommendation_input = gr.Dropdown(choices=df_recommendation['category'].unique().tolist(), label="Select Product Category")
+        recommendation_output = gr.Dataframe()
+        recommendation_btn = gr.Button("Recommend")
+        recommendation_btn.click(recommend_products, inputs=recommendation_input, outputs=recommendation_output)
 
+    # Circular Economy Analytics Tab
     with gr.Tab("Circular Economy Analytics"):
-        # ... (existing code)
-
-    # Add a new tab for the Hugging Face Chatbot
+        dashboard_outputs = [
+            gr.Plot(label="Product Lifecycle Analytics"),
+            gr.Plot(label="Dynamic Pricing Insights"),
+            gr.Plot(label="User Engagement Trends"),
+            gr.Plot(label="Sustainability & Recycling Insights")
+        ]
+        dashboard_btn = gr.Button("Generate Dashboard")
+        dashboard_btn.click(generate_dashboard, inputs=[], outputs=dashboard_outputs)
+
+    # AI Chatbot Tab
     with gr.Tab("AI Chatbot"):
         gr.Markdown("""
         <div style="text-align: center;">