Update app.py

app.py

@@ -12,6 +12,33 @@ import plotly.express as px
 import time
 import threading
 import random
+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"
+
+HUGGINGFACE_API_KEY = os.environ["HUGGINGFACE_API_KEY"]  # Access the API key from environment variables
+
+# Hugging Face Chatbot Function
+def huggingface_chatbot(user_input):
+    try:
+        headers = {
+            "Authorization": f"Bearer {HUGGINGFACE_API_KEY}",
+            "Content-Type": "application/json"
+        }
+        data = {
+            "inputs": user_input,
+            "parameters": {
+                "max_length": 100,  # Adjust as needed
+                "temperature": 0.7  # Adjust as needed
+            }
+        }
+        response = requests.post(HUGGINGFACE_API_URL, headers=headers, json=data)
+        response.raise_for_status()  # Raise an error for bad status codes
+        return response.json()[0]["generated_text"]
+    except Exception as e:
+        return f"Error: {str(e)}"
 
 # Database setup for user authentication
 def init_db():
@@ -216,81 +243,34 @@ with gr.Blocks() as app:
     </div>
     """)
     gr.Markdown("# 🔐 Circular Economy Marketplace")
+    
+    # Existing tabs (Login/Register, Product Lifecycle Prediction, etc.)
     with gr.Tab("Login/Register"):
-        # Add an image to the Login/Register tab
-        gr.Markdown("""
-        <div style="text-align: center;">
-            <img src="https://miro.medium.com/v2/resize:fit:1157/0*DmOXUHYIA7vl5QgR.jpeg?text=Login+or+Register" alt="Login/Register" style="width: 100%; max-width: 400px;">
-        </div>
-        """)
-        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)
+        # ... (existing code)
+
     with gr.Tab("Product Lifecycle Prediction"):
-        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)
+        # ... (existing code)
+
     with gr.Tab("Dynamic Pricing"):
-        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)
+        # ... (existing code)
+
     with gr.Tab("Product Recommendation"):
-        # Add an image to the Product Recommendation tab
-        gr.Markdown("""
-        <div style="text-align: center;">
-            <img src="https://wizzy.ai/blog/wp-content/uploads/2021/04/Product-Recommendation-Implementation.jpg?text=Product+Recommendations" alt="Product Recommendations" style="width: 100%; max-width: 400px;">
-        </div>
-        """)
-        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)
+        # ... (existing code)
+
     with gr.Tab("Circular Economy Analytics"):
-        # Add an image to the Analytics tab
+        # ... (existing code)
+
+    # Add a new tab for the Hugging Face Chatbot
+    with gr.Tab("AI Chatbot"):
         gr.Markdown("""
         <div style="text-align: center;">
-            <img src="https://www.pngrepo.com/download/219294/analysis-chart.png?text=Analytics+Dashboard" alt="Analytics" style="width: 100%; max-width: 400px;">
+            <img src="https://via.placeholder.com/400x200.png?text=AI+Chatbot" alt="Chatbot" style="width: 100%; max-width: 400px;">
         </div>
         """)
-        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)
+        chatbot_input = gr.Textbox(label="Ask me anything about circular economy, product lifecycle, dynamic pricing, and recommendations!")
+        chatbot_output = gr.Textbox(label="AI Response")
+        chatbot_btn = gr.Button("Ask")
+        chatbot_btn.click(huggingface_chatbot, inputs=chatbot_input, outputs=chatbot_output)
 
 # Simulate real-time data updates
 def live_update():