Update app.py

app.py

@@ -3,6 +3,7 @@ from huggingface_hub import InferenceClient
 import json
 from typing import Dict, List, Any
 import time
+import random
 
 # Initialize the client with retries
 MAX_RETRIES = 3
@@ -13,7 +14,7 @@ def create_client(retries=MAX_RETRIES):
     for attempt in range(retries):
         try:
             return InferenceClient(
-                "HuggingFaceH4/zephyr-7b-beta",
+                "mistralai/Mistral-7B-Instruct-v0.2",  # Updated to a more capable model
                 timeout=30
             )
         except Exception as e:
@@ -35,6 +36,26 @@ def load_site_content() -> Dict[str, Any]:
         print(f"Error loading JSON: {e}")
         return {}
 
+def get_engagement_prompt(content):
+    """Generate a random friendly greeting."""
+    prompts = [
+        "👋 Welcome to SletcherSystems! How can I assist you today?",
+        "🇿🇦 Hello from SletcherSystems in South Africa! How may I help you?",
+        "👨‍💻 Need help with AI solutions or educational technology? I'm here to assist!",
+        "🚀 Looking to transform your business with AI? Let me know what you're interested in!",
+        "🌍 Greetings! I'm your SletcherSystems virtual assistant. What can I help you with?"
+    ]
+    
+    # Add product-specific prompts if available
+    products = content.get('products', [])
+    if products and isinstance(products, list):
+        product_count = min(2, len(products))  # Get up to 2 products
+        for i in range(product_count):
+            product = products[i]
+            prompts.append(f"🔍 Interested in our {product.get('name', '')}? Feel free to ask about it!")
+    
+    return random.choice(prompts)
+
 def get_relevant_context(query: str, data: Dict[str, Any]) -> str:
     """Get relevant context based on the query keywords."""
     query = query.lower()
@@ -94,8 +115,19 @@ Company Information:
   Features: {', '.join(spec_data.get('core_features', []))}
   Technologies: {', '.join(spec_data.get('key_technologies', []))}""")
 
+    # Products information
+    if any(word in query for word in ['product', 'pricing', 'cost', 'buy', 'purchase', 'student', 'enterprise', 'personal']):
+        products = data.get('products', [])
+        context_parts.append("\nOur Products:")
+        for product in products:
+            context_parts.append(f"""
+- {product.get('name', '')}
+  Description: {product.get('description', '')}
+  Price: {product.get('price', 'Contact for pricing')}
+  Features: {', '.join(product.get('features', []))}""")
+
     # Add payment information for relevant queries
-    if any(word in query for word in ['payment', 'pay', 'cost', 'pricing', 'bank', 'bitcoin', 'eth', 'btc']):
+    if any(word in query for word in ['payment', 'pay', 'cost', 'pricing', 'bank', 'bitcoin', 'eth', 'btc', 'crypto']):
         info = data.get('company_info', {})
         context_parts.append(f"\nPayment Information: {info.get('payment', '')}")
 
@@ -135,19 +167,19 @@ def respond(
     # Get relevant context
     context = get_relevant_context(message, content)
     
-    # Enhanced system message with strict instructions
+    # Enhanced system message with conversation guidance
     enhanced_system_message = f"""{system_message}
 IMPORTANT CONTEXT - USE THIS INFORMATION ONLY:
 {context}
-STRICT INSTRUCTIONS:
-1. ONLY use information from the context provided above
-2. If information isn't in the context, say "I don't have that specific information"
-3. NEVER make assumptions about location - we are a proudly South African company
-4. NEVER invent services or capabilities not listed
-5. Be accurate about our AI and educational technology focus
-6. Acknowledge our cryptocurrency acceptance when relevant
-7. Use exact statistics when they're provided in the context
-8. Always acknowledge Wayne Sletcher as CEO and Founder when relevant"""
+CONVERSATION GUIDELINES:
+1. Be warm, friendly, and conversational - feel free to use emoji occasionally 🇿🇦
+2. ONLY use information from the context provided above
+3. If information isn't in the context, politely say you don't have that specific information
+4. We are a proudly South African company - incorporate this identity naturally
+5. Avoid technical jargon unless directly relevant to the question
+6. Keep responses concise and focused on helping the user
+7. For product inquiries, mention relevant features and pricing
+8. Acknowledge Wayne Sletcher as CEO and Founder when contextually appropriate"""
 
     try:
         # Format conversation history
@@ -177,24 +209,76 @@ STRICT INSTRUCTIONS:
         client = create_client()
         yield "I apologize, but I encountered an error. Please try your question again."
 
-# Create the Gradio interface
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(
-            value="You are the official AI assistant for SletcherSystems, a proudly South African technology company. Provide accurate, specific information based only on the provided context.",
-            label="System message"
-        ),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=1.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"
-        ),
-    ],
-    title="SletcherSystems AI Assistant",
-    description="Welcome! I'm here to help you learn about SletcherSystems, a proudly South African technology company.",
-    theme=gr.themes.Soft()
-)
+def create_chat_interface():
+    content = load_site_content()
+    
+    with gr.Blocks(theme=gr.themes.Soft()) as demo:
+        with gr.Row():
+            with gr.Column(scale=3):
+                chatbot = gr.Chatbot(
+                    label="SletcherSystems Assistant",
+                    height=500,
+                    avatar_images=["https://api.dicebear.com/7.x/bottts/svg?seed=user", "https://api.dicebear.com/7.x/bottts/svg?seed=sletcher"]
+                )
+        
+        with gr.Row():
+            msg = gr.Textbox(
+                placeholder="Ask me about SletcherSystems...",
+                label="Your message",
+                scale=8
+            )
+            submit = gr.Button("Send", variant="primary", scale=1)
+            clear = gr.Button("Clear", variant="secondary", scale=1)
+        
+        with gr.Accordion("Advanced Settings", open=False):
+            system_message = gr.Textbox(
+                value="You are the official AI assistant for SletcherSystems, a proudly South African technology company. Provide helpful, friendly information based on the context provided.",
+                label="System message"
+            )
+            max_tokens = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max tokens")
+            temperature = gr.Slider(minimum=0.1, maximum=1.0, value=0.8, step=0.1, label="Temperature")
+            top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p")
+        
+        # Add initial greeting
+        def show_greeting():
+            greeting = "👋 Welcome to SletcherSystems! How can I assist you today?"
+            try:
+                if content:
+                    greeting = get_engagement_prompt(content)
+            except Exception as e:
+                print(f"Error generating greeting: {e}")
+            return [[None, greeting]]
+        
+        def user_submit(message, chat_history):
+            return "", chat_history + [[message, None]]
+        
+        def bot_response(chat_history, system_msg, max_tok, temp, top_probability):
+            if chat_history and chat_history[-1][1] is None:
+                user_message = chat_history[-1][0]
+                chat_history[-1][1] = ""  # Initialize bot response
+                
+                for chunk in respond(user_message, chat_history[:-1], system_msg, max_tok, temp, top_probability):
+                    chat_history[-1][1] = chunk
+                    yield chat_history
+            else:
+                yield chat_history
+        
+        # Set up event handlers
+        msg.submit(user_submit, [msg, chatbot], [msg, chatbot]).then(
+            bot_response, [chatbot, system_message, max_tokens, temperature, top_p], [chatbot]
+        )
+        
+        submit.click(user_submit, [msg, chatbot], [msg, chatbot]).then(
+            bot_response, [chatbot, system_message, max_tokens, temperature, top_p], [chatbot]
+        )
+        
+        clear.click(lambda: (None, []), None, [msg, chatbot], queue=False)
+        
+        # Show initial greeting on load
+        demo.load(show_greeting, None, chatbot)
+    
+    return demo
 
 if __name__ == "__main__":
+    demo = create_chat_interface()
     demo.launch()