Update app.py

app.py

@@ -4,7 +4,6 @@ from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 from huggingface_hub import login
 import random
 import os
-from datetime import datetime
 
 # Get Hugging Face token from environment variables
 HUGGINGFACE_TOKEN = os.environ.get("HUGGINGFACE_TOKEN", "")
@@ -36,31 +35,24 @@ COMPANY_INFO = {
     "stage": "Growth and development, focused on building sustainable processes and systems"
 }
 
-# Knowledge base for the AI - Expanded with more detailed information
+# Knowledge base for the AI
 KNOWLEDGE_BASE = {
     "personal": {
-        "who are you": f"🤵 I'm **{PERSONAL_INFO['name']}**, {PERSONAL_INFO['role']}. I'm passionate about using technology to create meaningful impact and drive economic growth.",
-        "what are your goals": f"🎯 My goals include:\n• {PERSONAL_INFO['goals'][0]}\n• {PERSONAL_INFO['goals'][1]}\n• {PERSONAL_INFO['goals'][2]}",
-        "what do you do": f"💼 I'm the CEO of YAH Tech, focused on **{PERSONAL_INFO['goals'][2]}**. I lead our venture studio in creating innovative technology solutions.",
-        "tell me about yourself": f"🌟 I'm **{PERSONAL_INFO['name']}**, {PERSONAL_INFO['role']}. My mission is to **{PERSONAL_INFO['goals'][0].lower()}** and **{PERSONAL_INFO['goals'][1].lower()}** through innovative technology solutions. I believe in the power of software development to transform economies.",
-        "background": f"🎓 I'm **{PERSONAL_INFO['name']}**, a technology entrepreneur dedicated to building systems that create both economic value and social impact through YAH Tech.",
-        "experience": f"💼 As {PERSONAL_INFO['role']}, I've focused on building YAH Tech into a venture studio that develops scalable technology solutions and profitable business systems.",
+        "who are you": f"I am YAH Bot, the personal AI assistant for {PERSONAL_INFO['name']}. I help answer questions about him and his company YAH Tech.",
+        "what are your goals": f"My purpose is to assist with information about {PERSONAL_INFO['name']} and YAH Tech. His goals include: {', '.join(PERSONAL_INFO['goals'])}",
+        "what do you do": f"I provide information about {PERSONAL_INFO['name']} and his work at YAH Tech.",
+        "tell me about yourself": f"I'm YAH Bot, an AI assistant created to help people learn about {PERSONAL_INFO['name']} and his technology ventures.",
+        "background": f"{PERSONAL_INFO['name']} is {PERSONAL_INFO['role']} focused on building impactful technology systems.",
+        "experience": f"As {PERSONAL_INFO['role']}, {PERSONAL_INFO['name']} has focused on building YAH Tech into a successful venture studio.",
     },
     "company": {
-        "what is yah tech": f"🏢 **{COMPANY_INFO['name']}** is a {COMPANY_INFO['type']}. Our purpose is to **{COMPANY_INFO['purpose'].lower()}**.",
-        "what does yah tech do": f"🚀 We specialize in **{COMPANY_INFO['primary_activity'].lower()}**. {COMPANY_INFO['purpose']}. We build complete technology ventures from the ground up.",
-        "company philosophy": f"💡 Our philosophy is: **'{COMPANY_INFO['philosophy']}'** - we believe in thoroughly understanding problems before creating innovative solutions.",
-        "company stage": f"📈 We're currently in the **{COMPANY_INFO['stage']}** phase, building sustainable processes and systems for long-term success.",
-        "venture studio": "🎯 As a venture studio, we don't just build apps - we build complete businesses with scalable systems and futuristic solutions that drive economic growth. We identify opportunities, develop solutions, and launch ventures.",
-        "services": f"🛠️ {COMPANY_INFO['name']} offers: • App development • Venture building • Business system design • Technology solutions • Scalable platform development",
-        "mission": f"🎯 Our mission at {COMPANY_INFO['name']} is to {COMPANY_INFO['purpose'].lower()} through innovative technology and systematic business development.",
-    },
-    "general": {
-        "hello": "👋 Hello! I'm YAH Bot, your assistant for everything about Adedoyin James and YAH Tech. How can I help you today?",
-        "hi": "👋 Hi there! I'm here to tell you about Adedoyin James and YAH Tech. What would you like to know?",
-        "help": "💡 I can answer questions about:\n• Adedoyin James (background, goals, experience)\n• YAH Tech (company info, services, philosophy)\n• Our venture studio model and approach\n• Technology and business insights",
-        "thanks": "🙏 You're welcome! Is there anything else you'd like to know about Adedoyin or YAH Tech?",
-        "thank you": "🙏 You're welcome! Feel free to ask more about our work at YAH Tech.",
+        "what is yah tech": f"{COMPANY_INFO['name']} is a {COMPANY_INFO['type']} that {COMPANY_INFO['purpose'].lower()}.",
+        "what does yah tech do": f"We specialize in {COMPANY_INFO['primary_activity'].lower()}. {COMPANY_INFO['purpose']}.",
+        "company philosophy": f"Our philosophy is: '{COMPANY_INFO['philosophy']}'",
+        "company stage": f"We're currently in the {COMPANY_INFO['stage']} phase.",
+        "venture studio": "As a venture studio, we build complete businesses with scalable systems and futuristic solutions.",
+        "services": f"{COMPANY_INFO['name']} offers app development, venture building, business system design, technology solutions, and scalable platform development.",
+        "mission": f"Our mission at {COMPANY_INFO['name']} is to {COMPANY_INFO['purpose'].lower()}.",
     }
 }
 
@@ -75,97 +67,56 @@ class YAHBot:
         """Load the Hugging Face model"""
         try:
             print("🔄 Loading YAH Tech AI model...")
-            # Try to load custom model first
-            self.tokenizer = AutoTokenizer.from_pretrained(
-                "Adedoyinjames/YAH-Tech-Chat-Bot", 
-                token=HUGGINGFACE_TOKEN if HUGGINGFACE_TOKEN else None
-            )
-            self.model = AutoModelForSeq2SeqLM.from_pretrained(
-                "Adedoyinjames/YAH-Tech-Chat-Bot",
-                token=HUGGINGFACE_TOKEN if HUGGINGFACE_TOKEN else None,
-                torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32
-            )
-            print("✅ YAH Tech AI model loaded successfully!")
+            self.tokenizer = AutoTokenizer.from_pretrained(self.model_name)
+            self.model = AutoModelForSeq2SeqLM.from_pretrained(self.model_name)
+            print("✅ AI model loaded successfully!")
         except Exception as e:
-            print(f"❌ Failed to load custom model: {e}")
-            print("🔄 Falling back to standard FLAN-T5-base model...")
-            try:
-                self.tokenizer = AutoTokenizer.from_pretrained(self.model_name)
-                self.model = AutoModelForSeq2SeqLM.from_pretrained(self.model_name)
-                print("✅ Standard AI model loaded successfully!")
-            except Exception as e2:
-                print(f"❌ Failed to load AI model: {e2}")
-                self.model = None
-                self.tokenizer = None
+            print(f"❌ Failed to load AI model: {e}")
+            self.model = None
+            self.tokenizer = None
     
     def _get_knowledge_response(self, user_input):
         """Check if the input matches any knowledge base entries"""
         user_input_lower = user_input.lower()
         
-        # Check all knowledge bases
-        for category in KNOWLEDGE_BASE.values():
-            for key, response in category.items():
-                if key in user_input_lower:
-                    return response
-        
-        # Specific patterns for personal name
+        # Check for specific brand-related queries
         if any(word in user_input_lower for word in ["adedoyin", "ifeoluwa", "james"]):
             return KNOWLEDGE_BASE["personal"]["who are you"]
         
-        # Specific patterns for company
         if any(word in user_input_lower for word in ["yah tech", "your company", "venture studio"]):
             return KNOWLEDGE_BASE["company"]["what is yah tech"]
         
-        # Greeting patterns
-        if any(word in user_input_lower for word in ["hello", "hi ", "hey"]):
-            return KNOWLEDGE_BASE["general"]["hello"]
-            
-        # Thank you patterns
-        if any(word in user_input_lower for word in ["thank", "thanks"]):
-            return KNOWLEDGE_BASE["general"]["thanks"]
+        # Check knowledge base
+        for category in KNOWLEDGE_BASE.values():
+            for key, response in category.items():
+                if key in user_input_lower:
+                    return response
         
         return None
     
-    def _create_smart_prompt(self, user_input, conversation_history):
-        """Create a smart prompt that combines brand identity with general knowledge"""
-        brand_context = f"""You are YAH Bot, an AI assistant representing {PERSONAL_INFO['name']} and {COMPANY_INFO['name']}. 
-About {PERSONAL_INFO['name']}:
-- {PERSONAL_INFO['role']}
-- Goals: {', '.join(PERSONAL_INFO['goals'])}
-About {COMPANY_INFO['name']}:
-- {COMPANY_INFO['type']}
-- Philosophy: "{COMPANY_INFO['philosophy']}"
-- Purpose: {COMPANY_INFO['purpose']}
-When answering questions:
-1. First provide accurate, helpful information
-2. Naturally mention YAH Tech or Adedoyin James when relevant
-3. Be professional but conversational
-4. Connect general topics to technology, business, or innovation when appropriate
-Current conversation:"""
-        
-        # Build conversation history
-        conv_history = ""
-        for msg in conversation_history[-4:]:  # Last 4 exchanges
-            role = "Human" if msg["role"] == "user" else "Assistant"
-            conv_history += f"{role}: {msg['content']}\n"
-        
-        prompt = f"{brand_context}\n{conv_history}Human: {user_input}\nAssistant:"
+    def _create_smart_prompt(self, user_input):
+        """Create a much better prompt that separates brand info from general knowledge"""
+        prompt = f"""You are a helpful AI assistant. Answer the following question accurately and helpfully.
+
+Question: {user_input}
+
+Answer: """
         return prompt
     
-    def generate_response(self, user_input, conversation_history):
+    def generate_response(self, user_input):
         """Generate response using knowledge base or AI model"""
-        # First check knowledge base for exact matches
+        # First check knowledge base for brand-specific queries
         knowledge_response = self._get_knowledge_response(user_input)
         if knowledge_response:
             return knowledge_response
         
-        # Use AI model for other queries
+        # Use AI model for general knowledge questions
         if self.model and self.tokenizer:
             try:
-                # Create smart prompt with brand context
-                prompt = self._create_smart_prompt(user_input, conversation_history)
+                # Create clean prompt without brand bias for general questions
+                prompt = self._create_smart_prompt(user_input)
                 
-                # Tokenize with proper handling
+                # Tokenize
                 inputs = self.tokenizer(
                     prompt, 
                     return_tensors="pt", 
@@ -178,139 +129,136 @@ Current conversation:"""
                 with torch.no_grad():
                     outputs = self.model.generate(
                         inputs.input_ids,
-                        max_length=256,
+                        max_length=150,
                         num_return_sequences=1,
-                        temperature=0.8,
+                        temperature=0.7,
                         do_sample=True,
-                        pad_token_id=self.tokenizer.pad_token_id or self.tokenizer.eos_token_id,
-                        repetition_penalty=1.1
+                        pad_token_id=self.tokenizer.pad_token_id,
+                        repetition_penalty=1.2
                     )
                 
                 response = self.tokenizer.decode(outputs[0], skip_special_tokens=True)
-                
-                # Clean up the response and ensure brand mention when appropriate
-                cleaned_response = self._enhance_response(response, user_input)
-                return cleaned_response
+                return response
                 
             except Exception as e:
                 print(f"Model error: {str(e)}")
-                return self._get_fallback_response(user_input)
+                return "I apologize, but I'm having trouble processing your question right now. Please try again."
         
-        # Fallback if model fails to load
-        return self._get_fallback_response(user_input)
-    
-    def _enhance_response(self, response, user_input):
-        """Enhance the response to include brand mentions when appropriate"""
-        user_input_lower = user_input.lower()
-        
-        # Topics where brand mention would be natural
-        tech_topics = ["technology", "software", "app", "development", "coding", "programming"]
-        business_topics = ["business", "startup", "company", "venture", "entrepreneur"]
-        innovation_topics = ["innovation", "future", "solution", "system", "growth"]
-        
-        # Check if the topic is relevant to our brand
-        is_relevant_topic = any(topic in user_input_lower for topic in 
-                               tech_topics + business_topics + innovation_topics)
-        
-        # If response doesn't mention brand but topic is relevant, add a natural mention
-        if (is_relevant_topic and 
-            "yah tech" not in response.lower() and 
-            "adedoyin" not in response.lower()):
-            
-            brand_connectors = [
-                f" {response} This aligns with the approach we take at YAH Tech under Adedoyin James' leadership.",
-                f" {response} At YAH Tech, we often work with similar concepts in our venture studio.",
-                f" {response} Speaking of which, Adedoyin James focuses on applying such principles at YAH Tech.",
-                f" {response} This is similar to the philosophy we embrace at YAH Tech - '{COMPANY_INFO['philosophy']}'."
-            ]
-            return random.choice(brand_connectors)
-        
-        return response
-    
-    def _get_fallback_response(self, user_input):
-        """Get a fallback response that still promotes the brand"""
-        fallback_responses = [
-            f"🌟 That's an interesting question about {user_input.split()[0] if user_input.split() else 'that'}! At {COMPANY_INFO['name']}, we believe in **{COMPANY_INFO['philosophy']}** to create solutions that matter.",
-            f"🚀 I'd be happy to discuss that. As {PERSONAL_INFO['name']}, I focus on building technology-driven ventures that create both **profit and societal value** through YAH Tech.",
-            f"💡 Great question! Our approach at {COMPANY_INFO['name']} is to develop futuristic solutions through careful evaluation and systematic creation, which applies to many topics including this one.",
-            f"🎯 From my perspective as {PERSONAL_INFO['name']}, I focus on building systems that reshape the economic landscape through innovative technology at YAH Tech. How can I help you with this specifically?"
-        ]
-        return random.choice(fallback_responses)
+        return "I'm currently unavailable. Please check back later."
 
 # Initialize the bot globally
 yah_bot = YAHBot()
 
 def chat_function(message, history):
-    """Chat function for Gradio interface - FIXED VERSION"""
-    # Convert Gradio history format to our internal format
-    conversation_history = []
-    for human_msg, assistant_msg in history:
-        conversation_history.append({"role": "user", "content": human_msg})
-        conversation_history.append({"role": "assistant", "content": assistant_msg})
-    
-    # Generate response
-    response = yah_bot.generate_response(message, conversation_history)
+    """Simple chat function without complex history processing"""
+    response = yah_bot.generate_response(message)
     return response
 
 def respond(message, chat_history):
-    """Fixed response function with proper message format"""
+    """Main response function"""
     bot_response = chat_function(message, chat_history)
     chat_history.append((message, bot_response))
     return "", chat_history
 
-# Custom CSS for ChatGPT-like appearance
+def clear_chat():
+    """Clear chat history"""
+    return []
+
+# MODERN CSS WITH FIXED LAYOUT
 custom_css = """
 .gradio-container {
     font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
-    max-width: 900px !important;
+    max-width: 800px !important;
     margin: 0 auto !important;
+    height: 100vh !important;
+    padding: 20px !important;
+}
+
+.main {
+    height: 100vh !important;
+    display: flex !important;
+    flex-direction: column !important;
+    gap: 0 !important;
 }
 
-.chat-container {
-    max-height: 600px !important;
+.contain {
+    display: flex !important;
+    flex-direction: column !important;
+    height: 100vh !important;
+    gap: 0 !important;
+}
+
+/* Header */
+.header {
+    text-align: center;
+    margin-bottom: 20px !important;
+    padding: 20px;
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    border-radius: 12px;
+    color: white;
+}
+
+/* Chatbot Container - FIXED HEIGHT */
+.chatbot {
+    flex: 1 !important;
+    min-height: 400px !important;
+    max-height: 65vh !important;
+    border: 1px solid #e1e5e9 !important;
+    border-radius: 12px !important;
+    margin-bottom: 20px !important;
+    background: white !important;
     overflow-y: auto !important;
-    border: 1px solid #e0e0e0 !important;
-    border-radius: 10px !important;
-    padding: 20px !important;
-    background: #ffffff !important;
-    box-shadow: 0 2px 10px rgba(0,0,0,0.1) !important;
+    padding: 10px !important;
+}
+
+/* Input Area - ALWAYS VISIBLE */
+.input-area {
+    position: sticky !important;
+    bottom: 0 !important;
+    background: white !important;
+    padding: 15px 0 !important;
+    border-top: 1px solid #e1e5e9 !important;
+    margin-top: auto !important;
+}
+
+/* Message Styling */
+.message {
+    max-width: 85% !important;
+    margin: 8px 0 !important;
+    padding: 12px 16px !important;
+    border-radius: 18px !important;
+    line-height: 1.4 !important;
+    word-wrap: break-word !important;
 }
 
 .user-message {
     background: #007bff !important;
     color: white !important;
-    padding: 12px 18px !important;
-    border-radius: 18px 18px 0 18px !important;
-    margin: 8px 0 !important;
-    max-width: 80% !important;
     margin-left: auto !important;
-    border: none !important;
-    box-shadow: 0 2px 5px rgba(0,123,255,0.3) !important;
+    margin-right: 0 !important;
+    border-bottom-right-radius: 4px !important;
 }
 
 .bot-message {
     background: #f8f9fa !important;
     color: #333 !important;
-    padding: 12px 18px !important;
-    border-radius: 18px 18px 18px 0 !important;
-    margin: 8px 0 !important;
-    max-width: 80% !important;
     margin-right: auto !important;
+    margin-left: 0 !important;
+    border-bottom-left-radius: 4px !important;
     border: 1px solid #e9ecef !important;
-    box-shadow: 0 1px 3px rgba(0,0,0,0.1) !important;
 }
 
-.chat-input {
+/* Input and Buttons */
+.textbox {
     border-radius: 25px !important;
-    padding: 15px 20px !important;
+    padding: 12px 20px !important;
     border: 2px solid #007bff !important;
     font-size: 14px !important;
-    background: white !important;
 }
 
-.chat-input:focus {
+.textbox:focus {
     border-color: #0056b3 !important;
-    box-shadow: 0 0 0 0.2rem rgba(0,123,255,.25) !important;
+    box-shadow: 0 0 0 2px rgba(0,123,255,.25) !important;
 }
 
 .send-button {
@@ -318,15 +266,13 @@ custom_css = """
     background: #007bff !important;
     color: white !important;
     border: none !important;
-    padding: 15px 30px !important;
+    padding: 12px 25px !important;
     font-weight: 600 !important;
-    transition: all 0.3s ease !important;
 }
 
 .send-button:hover {
     background: #0056b3 !important;
     transform: translateY(-1px) !important;
-    box-shadow: 0 4px 8px rgba(0,123,255,0.3) !important;
 }
 
 .clear-button {
@@ -334,164 +280,110 @@ custom_css = """
     background: #6c757d !important;
     color: white !important;
     border: none !important;
-    padding: 15px 25px !important;
+    padding: 12px 20px !important;
     font-weight: 600 !important;
-    transition: all 0.3s ease !important;
 }
 
 .clear-button:hover {
     background: #545b62 !important;
-    transform: translateY(-1px) !important;
-}
-
-.title {
-    text-align: center !important;
-    color: #2c3e50 !important;
-    font-weight: bold !important;
-    margin-bottom: 10px !important;
-    font-size: 2.5em !important;
-    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
-    -webkit-background-clip: text !important;
-    -webkit-text-fill-color: transparent !important;
-    background-clip: text !important;
 }
 
-.subtitle {
-    text-align: center !important;
-    color: #6c757d !important;
-    margin-bottom: 30px !important;
-    font-size: 1.1em !important;
-}
-
-.footer {
-    text-align: center !important;
-    margin-top: 20px !important;
-    color: #888 !important;
-    font-size: 12px !important;
-    padding: 15px !important;
-    border-top: 1px solid #e9ecef !important;
-}
-
-/* Scrollbar styling */
-.chat-container::-webkit-scrollbar {
+/* Scrollbar */
+.chatbot::-webkit-scrollbar {
     width: 6px;
 }
 
-.chat-container::-webkit-scrollbar-track {
+.chatbot::-webkit-scrollbar-track {
     background: #f1f1f1;
     border-radius: 3px;
 }
 
-.chat-container::-webkit-scrollbar-thumb {
+.chatbot::-scrollbar-thumb {
     background: #c1c1c1;
     border-radius: 3px;
 }
 
-.chat-container::-webkit-scrollbar-thumb:hover {
+.chatbot::-webkit-scrollbar-thumb:hover {
     background: #a8a8a8;
 }
+
+/* Footer */
+.footer {
+    text-align: center;
+    margin-top: 15px;
+    color: #6c757d;
+    font-size: 12px;
+    padding: 10px;
+}
 """
 
 with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
-    gr.Markdown(
-        """
-        # <div class="title">YAH Tech AI Assistant</div>
-        <div class="subtitle">
-            Powered by Advanced AI • Ask me about YAH Tech, Adedoyin James, or general questions
-        </div>
-        """
-    )
-    
-    chatbot = gr.Chatbot(
-        label="Chat",
-        show_label=False,
-        height=600,
-        bubble_full_width=False,
-        show_copy_button=True,
-        placeholder="Start chatting with YAH Tech AI..."
-    )
     
-    with gr.Row():
-        msg = gr.Textbox(
-            placeholder="Type your message here... (Ask about YAH Tech, our services, or anything else)",
-            show_label=False,
-            scale=4,
-            container=False,
-            autofocus=True
+    with gr.Column(elem_classes=["contain"]):
+        # Header
+        gr.Markdown(
+            f"""
+            <div class="header">
+                <h1 style="margin: 0; font-size: 2em;">YAH Tech AI Assistant</h1>
+                <p style="margin: 5px 0 0 0; opacity: 0.9;">Personal Assistant for {PERSONAL_INFO['name']}</p>
+            </div>
+            """,
+            elem_classes=["header"]
         )
-        send = gr.Button("Send", variant="primary", scale=1, min_width=100)
-        clear = gr.Button("Clear", variant="secondary", scale=1, min_width=100)
-    
-    # Footer
-    gr.Markdown(
-        f"""
-        <div class="footer">
-            <strong>YAH Tech AI Assistant</strong> • Building the future of technology • 
-            Founder: {PERSONAL_INFO['name']} • 
-            Venture Studio • Economic Innovation
-        </div>
-        """
-    )
-    
-    def clear_chat():
-        return []
-    
-    def add_welcome_message():
-        welcome_msg = f"""
-        👋 **Hello! I'm YAH Bot, your AI assistant for everything related to {PERSONAL_INFO['name']} and {COMPANY_INFO['name']}!** 
         
-        I can help you with:
-        • 🌍 **General knowledge** (science, history, geography, etc.)
-        • 💡 **Technology & business insights**  
-        • 🏢 **YAH Tech company information**
-        • 👤 **Adedoyin James' background & goals**
-        • 🚀 **Venture studio model & services**
+        # Chatbot - FIXED HEIGHT
+        chatbot = gr.Chatbot(
+            label="Chat",
+            show_label=False,
+            elem_classes=["chatbot"],
+            show_copy_button=True,
+            placeholder="Chat with YAH Bot...",
+            height=400
+        )
         
-        **Try asking me anything - I'll provide helpful answers while naturally sharing insights about our work at YAH Tech!**
+        # Input Area - ALWAYS VISIBLE AT BOTTOM
+        with gr.Row(elem_classes=["input-area"]):
+            msg = gr.Textbox(
+                placeholder="Ask me anything...",
+                show_label=False,
+                scale=4,
+                container=False,
+                elem_classes=["textbox"],
+                autofocus=True
+            )
+            with gr.Column(scale=1, min_width=120):
+                send = gr.Button("Send", variant="primary", elem_classes=["send-button"])
+                clear = gr.Button("Clear", variant="secondary", elem_classes=["clear-button"])
         
-        **How can I assist you today?** 🚀
-        """
+        # Footer
+        gr.Markdown(
+            f"""
+            <div class="footer">
+                <strong>YAH Tech Assistant</strong> • Assistant to {PERSONAL_INFO['name']} • Venture Studio
+            </div>
+            """,
+            elem_classes=["footer"]
+        )
+    
+    # Welcome message
+    def add_welcome_message():
+        welcome_msg = f"""👋 **Hello! I'm YAH Bot, the personal AI assistant for {PERSONAL_INFO['name']}.**
+
+I can help you with:
+• Information about {PERSONAL_INFO['name']} and YAH Tech
+• General knowledge questions  
+• Technology and business discussions
+
+**What would you like to know?**"""
         return [(welcome_msg, None)]
     
     # Set initial welcome message
     demo.load(add_welcome_message, None, [chatbot])
     
-    # Event handlers - USING THE FIXED RESPOND FUNCTION
-    msg.submit(
-        respond,
-        inputs=[msg, chatbot],
-        outputs=[msg, chatbot]
-    )
-    
-    send.click(
-        respond,
-        inputs=[msg, chatbot],
-        outputs=[msg, chatbot]
-    )
-    
-    clear.click(
-        clear_chat,
-        outputs=[chatbot]
-    )
-
-# For API usage
-def api_chat_endpoint(message: str, history: list = None):
-    """API endpoint function"""
-    if history is None:
-        history = []
-    
-    conversation_history = []
-    for human_msg, assistant_msg in history:
-        conversation_history.append({"role": "user", "content": human_msg})
-        conversation_history.append({"role": "assistant", "content": assistant_msg})
-    
-    response = yah_bot.generate_response(message, conversation_history)
-    
-    return {
-        "response": response,
-        "status": "success",
-        "message": message
-    }
+    # Event handlers
+    msg.submit(respond, [msg, chatbot], [msg, chatbot])
+    send.click(respond, [msg, chatbot], [msg, chatbot])
+    clear.click(clear_chat, outputs=[chatbot])
 
 if __name__ == "__main__":
     demo.launch(