Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,1056 @@
-import altair as alt
-import numpy as np
-import pandas as pd
-import streamlit as st
+# import altair as alt
+# import numpy as np
+# import pandas as pd
+# import streamlit as st
+
+# """
+# # Welcome to Streamlit!
+
+# Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
+# If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
+# forums](https://discuss.streamlit.io).
+
+# In the meantime, below is an example of what you can do with just a few lines of code:
+# """
+
+# num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
+# num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
+
+# indices = np.linspace(0, 1, num_points)
+# theta = 2 * np.pi * num_turns * indices
+# radius = indices
+
+# x = radius * np.cos(theta)
+# y = radius * np.sin(theta)
+
+# df = pd.DataFrame({
+#     "x": x,
+#     "y": y,
+#     "idx": indices,
+#     "rand": np.random.randn(num_points),
+# })
+
+# st.altair_chart(alt.Chart(df, height=700, width=700)
+#     .mark_point(filled=True)
+#     .encode(
+#         x=alt.X("x", axis=None),
+#         y=alt.Y("y", axis=None),
+#         color=alt.Color("idx", legend=None, scale=alt.Scale()),
+#         size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
+#     ))
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
 
-"""
-# Welcome to Streamlit!
 
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
 
-In the meantime, below is an example of what you can do with just a few lines of code:
+
+
+
+
+
+"""
+Advanced Business AI Assistant - Streamlit App
+Deployed on Hugging Face Spaces
+
+This comprehensive business assistant provides intelligent answers about your business,
+integrates with multiple AI providers, and includes support ticket functionality.
 """
 
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+import streamlit as st
+import time
+import json
+import os
+import requests
+from datetime import datetime, timedelta
+from typing import Dict, List, Optional, Any
+import uuid
+import hashlib
+
+# Import the streaming system
+try:
+    from streaming import AdvancedStreamingSystem, StreamProvider, StreamingConfig
+    STREAMING_AVAILABLE = True
+except ImportError:
+    STREAMING_AVAILABLE = False
+
+# Page configuration
+st.set_page_config(
+    page_title="AgentAI Business Assistant",
+    page_icon="🏢",
+    layout="wide",
+    initial_sidebar_state="expanded"
+)
+
+# Business Information Database
+BUSINESS_INFO = {
+    "company_name": "AgentAI Solutions",
+    "tagline": "Advanced AI Development & Consulting",
+    "description": "We specialize in cutting-edge AI solutions, machine learning implementations, and intelligent automation systems for businesses worldwide.",
+    
+    "contact": {
+        "phone": "+1 (555) 123-4567",
+        "email": "[email protected]",
+        "support_email": "[email protected]",
+        "website": "https://agentai-solutions.com",
+        "linkedin": "https://linkedin.com/company/agentai-solutions"
+    },
+    
+    "location": {
+        "address": "123 Innovation Drive, Tech District",
+        "city": "San Francisco",
+        "state": "CA",
+        "zip": "94105",
+        "country": "USA",
+        "timezone": "PST (UTC-8)",
+        "coordinates": {"lat": 37.7749, "lon": -122.4194}
+    },
+    
+    "hours": {
+        "monday": {"open": "9:00 AM", "close": "6:00 PM", "timezone": "PST"},
+        "tuesday": {"open": "9:00 AM", "close": "6:00 PM", "timezone": "PST"},
+        "wednesday": {"open": "9:00 AM", "close": "6:00 PM", "timezone": "PST"},
+        "thursday": {"open": "9:00 AM", "close": "6:00 PM", "timezone": "PST"},
+        "friday": {"open": "9:00 AM", "close": "6:00 PM", "timezone": "PST"},
+        "saturday": {"open": "10:00 AM", "close": "4:00 PM", "timezone": "PST"},
+        "sunday": "Closed",
+        "holidays": "Closed on major US holidays"
+    },
+    
+    "services": [
+        {
+            "name": "AI Development",
+            "description": "Custom AI solutions, machine learning models, and intelligent automation systems",
+            "duration": "2-12 weeks",
+            "price_range": "$10,000 - $100,000+"
+        },
+        {
+            "name": "AI Consulting",
+            "description": "Strategic AI planning, feasibility studies, and implementation roadmaps",
+            "duration": "1-4 weeks",
+            "price_range": "$5,000 - $25,000"
+        },
+        {
+            "name": "Model Training",
+            "description": "Custom model training, fine-tuning, and optimization services",
+            "duration": "1-6 weeks",
+            "price_range": "$3,000 - $50,000"
+        },
+        {
+            "name": "AI Integration",
+            "description": "Seamless integration of AI solutions into existing business systems",
+            "duration": "2-8 weeks",
+            "price_range": "$7,500 - $75,000"
+        }
+    ],
+    
+    "team": [
+        {"name": "Alex Chen", "role": "CEO & AI Architect", "expertise": "Machine Learning, Deep Learning"},
+        {"name": "Sarah Johnson", "role": "CTO & Lead Developer", "expertise": "MLOps, Cloud Architecture"},
+        {"name": "Dr. Michael Rodriguez", "role": "Head of Research", "expertise": "NLP, Computer Vision"},
+        {"name": "Emily Zhang", "role": "AI Consultant", "expertise": "Business Strategy, AI Ethics"}
+    ],
+    
+    "support": {
+        "response_time": "24 hours for general inquiries, 4 hours for urgent issues",
+        "channels": ["Email", "Phone", "Live Chat", "Support Tickets"],
+        "emergency_contact": "+1 (555) 123-4567 ext. 911"
+    }
+}
+
+# Custom CSS for professional styling
+st.markdown("""
+<style>
+    .main-header {
+        font-size: 3rem;
+        color: #1E3A8A;
+        text-align: center;
+        margin-bottom: 1rem;
+        font-weight: bold;
+    }
+    .sub-header {
+        font-size: 1.2rem;
+        color: #64748B;
+        text-align: center;
+        margin-bottom: 2rem;
+    }
+    .business-card {
+        background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+        color: white;
+        padding: 2rem;
+        border-radius: 1rem;
+        margin: 1rem 0;
+        box-shadow: 0 10px 25px rgba(0,0,0,0.1);
+    }
+    .info-card {
+        background: white;
+        padding: 1.5rem;
+        border-radius: 0.8rem;
+        border-left: 4px solid #3B82F6;
+        margin: 1rem 0;
+        box-shadow: 0 4px 12px rgba(0,0,0,0.1);
+    }
+    .chat-message {
+        padding: 1rem;
+        border-radius: 0.8rem;
+        margin: 0.5rem 0;
+        box-shadow: 0 2px 8px rgba(0,0,0,0.1);
+    }
+    .user-message {
+        background: linear-gradient(135deg, #E3F2FD 0%, #BBDEFB 100%);
+        border-left: 4px solid #2196F3;
+        margin-left: 2rem;
+    }
+    .assistant-message {
+        background: linear-gradient(135deg, #F3E5F5 0%, #E1BEE7 100%);
+        border-left: 4px solid #9C27B0;
+        margin-right: 2rem;
+    }
+    .support-ticket {
+        background: linear-gradient(135deg, #FFF3E0 0%, #FFCC80 100%);
+        padding: 1.5rem;
+        border-radius: 0.8rem;
+        border-left: 4px solid #FF9800;
+        margin: 1rem 0;
+    }
+    .status-indicator {
+        display: inline-block;
+        width: 12px;
+        height: 12px;
+        border-radius: 50%;
+        margin-right: 8px;
+    }
+    .status-open { background-color: #4CAF50; }
+    .status-closed { background-color: #F44336; }
+    .status-pending { background-color: #FF9800; }
+    .metric-card {
+        background: white;
+        padding: 1rem;
+        border-radius: 0.8rem;
+        text-align: center;
+        box-shadow: 0 4px 12px rgba(0,0,0,0.1);
+    }
+</style>
+""", unsafe_allow_html=True)
+
+# Session state initialization
+def initialize_session_state():
+    """Initialize session state variables."""
+    if 'conversation' not in st.session_state:
+        st.session_state.conversation = []
+    
+    if 'support_tickets' not in st.session_state:
+        st.session_state.support_tickets = []
+    
+    if 'business_assistant' not in st.session_state:
+        st.session_state.business_assistant = None
+    
+    if 'user_session_id' not in st.session_state:
+        st.session_state.user_session_id = str(uuid.uuid4())
+    
+    if 'chat_analytics' not in st.session_state:
+        st.session_state.chat_analytics = []
+
+class BusinessKnowledgeBase:
+    """Advanced business knowledge base with intelligent query processing."""
+    
+    def __init__(self, business_info: Dict):
+        self.business_info = business_info
+        self.knowledge_patterns = self._build_knowledge_patterns()
+    
+    def _build_knowledge_patterns(self) -> Dict[str, Any]:
+        """Build patterns for intelligent query matching."""
+        return {
+            "hours": {
+                "keywords": ["hours", "open", "close", "time", "schedule", "when", "operating"],
+                "context": "business hours and schedule"
+            },
+            "location": {
+                "keywords": ["location", "address", "where", "directions", "map", "office"],
+                "context": "business location and address"
+            },
+            "contact": {
+                "keywords": ["phone", "email", "contact", "call", "reach", "number"],
+                "context": "contact information"
+            },
+            "services": {
+                "keywords": ["services", "what", "offer", "do", "provide", "solutions", "products"],
+                "context": "services and offerings"
+            },
+            "team": {
+                "keywords": ["team", "staff", "who", "people", "employees", "founders"],
+                "context": "team information"
+            },
+            "support": {
+                "keywords": ["support", "help", "assistance", "problem", "issue", "ticket"],
+                "context": "support and assistance"
+            },
+            "pricing": {
+                "keywords": ["price", "cost", "pricing", "fee", "rates", "budget"],
+                "context": "pricing information"
+            }
+        }
+    
+    def search_knowledge(self, query: str) -> Dict[str, Any]:
+        """Search knowledge base for relevant information."""
+        query_lower = query.lower()
+        matches = {}
+        
+        for category, pattern in self.knowledge_patterns.items():
+            score = sum(1 for keyword in pattern["keywords"] if keyword in query_lower)
+            if score > 0:
+                matches[category] = {
+                    "score": score,
+                    "context": pattern["context"],
+                    "data": self._get_category_data(category)
+                }
+        
+        return dict(sorted(matches.items(), key=lambda x: x[1]["score"], reverse=True))
+    
+    def _get_category_data(self, category: str) -> Any:
+        """Get data for a specific category."""
+        category_mapping = {
+            "hours": self.business_info["hours"],
+            "location": self.business_info["location"],
+            "contact": self.business_info["contact"],
+            "services": self.business_info["services"],
+            "team": self.business_info["team"],
+            "support": self.business_info["support"],
+            "pricing": [service for service in self.business_info["services"]]
+        }
+        return category_mapping.get(category, {})
+    
+    def generate_business_context(self) -> str:
+        """Generate comprehensive business context for AI queries."""
+        context_parts = [
+            f"Company: {self.business_info['company_name']}",
+            f"Description: {self.business_info['description']}",
+            f"Location: {self.business_info['location']['address']}, {self.business_info['location']['city']}, {self.business_info['location']['state']}",
+            f"Phone: {self.business_info['contact']['phone']}",
+            f"Email: {self.business_info['contact']['email']}",
+            f"Website: {self.business_info['contact']['website']}",
+            "",
+            "Business Hours:",
+        ]
+        
+        for day, hours in self.business_info["hours"].items():
+            if day != "holidays":
+                if isinstance(hours, dict):
+                    context_parts.append(f"  {day.title()}: {hours['open']} - {hours['close']} {hours['timezone']}")
+                else:
+                    context_parts.append(f"  {day.title()}: {hours}")
+        
+        context_parts.extend([
+            "",
+            "Services:",
+        ])
+        
+        for service in self.business_info["services"]:
+            context_parts.append(f"  - {service['name']}: {service['description']} (Duration: {service['duration']}, Price: {service['price_range']})")
+        
+        return "\n".join(context_parts)
+
+class SupportTicketManager:
+    """Advanced support ticket management system."""
+    
+    def __init__(self):
+        self.ticket_categories = [
+            "General Inquiry",
+            "Technical Support",
+            "Billing Question",
+            "Service Request",
+            "Bug Report",
+            "Feature Request",
+            "Emergency"
+        ]
+        self.priorities = ["Low", "Medium", "High", "Critical"]
+    
+    def create_ticket(self, title: str, description: str, category: str, priority: str, 
+                     contact_info: Dict, user_session_id: str) -> Dict[str, Any]:
+        """Create a new support ticket."""
+        ticket = {
+            "id": self._generate_ticket_id(),
+            "title": title,
+            "description": description,
+            "category": category,
+            "priority": priority,
+            "status": "Open",
+            "created_at": datetime.now(),
+            "updated_at": datetime.now(),
+            "contact_info": contact_info,
+            "user_session_id": user_session_id,
+            "responses": []
+        }
+        
+        # Simulate external ticket system integration
+        self._integrate_with_external_systems(ticket)
+        
+        return ticket
+    
+    def _generate_ticket_id(self) -> str:
+        """Generate unique ticket ID."""
+        timestamp = datetime.now().strftime("%Y%m%d%H%M%S")
+        random_suffix = hashlib.md5(str(time.time()).encode()).hexdigest()[:6]
+        return f"TKT-{timestamp}-{random_suffix.upper()}"
+    
+    def _integrate_with_external_systems(self, ticket: Dict) -> bool:
+        """Simulate integration with external ticket systems."""
+        try:
+            # Simulate GitHub Issues integration
+            github_issue = self._create_github_issue(ticket)
+            
+            # Simulate Jira integration
+            jira_ticket = self._create_jira_ticket(ticket)
+            
+            # Simulate Trello integration
+            trello_card = self._create_trello_card(ticket)
+            
+            ticket["external_integrations"] = {
+                "github": github_issue,
+                "jira": jira_ticket,
+                "trello": trello_card
+            }
+            
+            return True
+            
+        except Exception as e:
+            st.warning(f"External integration warning: {e}")
+            return False
+    
+    def _create_github_issue(self, ticket: Dict) -> Dict:
+        """Simulate GitHub issue creation."""
+        return {
+            "platform": "GitHub",
+            "url": f"https://github.com/agentai-solutions/support/issues/{ticket['id']}",
+            "issue_number": len(st.session_state.support_tickets) + 1,
+            "status": "created",
+            "labels": [ticket["category"].lower().replace(" ", "-"), ticket["priority"].lower()]
+        }
+    
+    def _create_jira_ticket(self, ticket: Dict) -> Dict:
+        """Simulate Jira ticket creation."""
+        return {
+            "platform": "Jira",
+            "url": f"https://agentai-solutions.atlassian.net/browse/{ticket['id']}",
+            "key": ticket['id'],
+            "status": "Open",
+            "project": "SUPPORT"
+        }
+    
+    def _create_trello_card(self, ticket: Dict) -> Dict:
+        """Simulate Trello card creation."""
+        return {
+            "platform": "Trello",
+            "url": f"https://trello.com/c/{ticket['id'][:8]}",
+            "board": "Customer Support",
+            "list": "New Tickets",
+            "card_id": ticket['id'][:8]
+        }
+
+class BusinessAIAssistant:
+    """Advanced AI-powered business assistant."""
+    
+    def __init__(self):
+        self.knowledge_base = BusinessKnowledgeBase(BUSINESS_INFO)
+        self.ticket_manager = SupportTicketManager()
+        
+        if STREAMING_AVAILABLE:
+            try:
+                self.streaming_system = AdvancedStreamingSystem()
+                self.ai_available = True
+            except Exception as e:
+                st.warning(f"AI streaming not available: {e}")
+                self.ai_available = False
+        else:
+            self.ai_available = False
+    
+    def process_query(self, query: str, use_ai: bool = True) -> Dict[str, Any]:
+        """Process user query with knowledge base and AI assistance."""
+        # Search knowledge base
+        knowledge_matches = self.knowledge_base.search_knowledge(query)
+        
+        # Determine if AI assistance is needed
+        if use_ai and self.ai_available and knowledge_matches:
+            ai_response = self._get_ai_response(query, knowledge_matches)
+            return {
+                "type": "ai_enhanced",
+                "response": ai_response,
+                "knowledge_matches": knowledge_matches,
+                "confidence": "high"
+            }
+        elif knowledge_matches:
+            structured_response = self._create_structured_response(knowledge_matches)
+            return {
+                "type": "knowledge_base",
+                "response": structured_response,
+                "knowledge_matches": knowledge_matches,
+                "confidence": "medium"
+            }
+        else:
+            return {
+                "type": "unknown",
+                "response": "I don't have specific information about that. Would you like to create a support ticket for assistance?",
+                "knowledge_matches": {},
+                "confidence": "low"
+            }
+    
+    def _get_ai_response(self, query: str, knowledge_matches: Dict) -> str:
+        """Get AI-enhanced response using streaming system."""
+        try:
+            # Create context-aware prompt
+            business_context = self.knowledge_base.generate_business_context()
+            
+            # Prepare AI messages
+            messages = [
+                {
+                    "role": "system",
+                    "content": f"""You are a professional business assistant for {BUSINESS_INFO['company_name']}. 
+                    
+Business Information:
+{business_context}
+
+Instructions:
+- Provide accurate, helpful information about the business
+- Be professional and friendly
+- If you don't have specific information, acknowledge it and suggest contacting support
+- Keep responses concise but comprehensive
+- Use business hours, contact info, and services from the provided context"""
+                },
+                {
+                    "role": "user",
+                    "content": query
+                }
+            ]
+            
+            # Use the first available provider
+            if self.streaming_system.streamers:
+                provider = list(self.streaming_system.streamers.keys())[0]
+                config = StreamingConfig(
+                    model="gpt-4o" if provider.value == "openai" else "gemini-1.5-flash",
+                    temperature=0.3,
+                    max_tokens=500
+                )
+                
+                response = self.streaming_system.stream_with_display(messages, provider, config)
+                return response.content
+            
+        except Exception as e:
+            st.warning(f"AI response error: {e}")
+        
+        # Fallback to structured response
+        return self._create_structured_response(knowledge_matches)
+    
+    def _create_structured_response(self, knowledge_matches: Dict) -> str:
+        """Create structured response from knowledge base matches."""
+        if not knowledge_matches:
+            return "I don't have specific information about that. Please contact our support team for assistance."
+        
+        response_parts = []
+        
+        for category, match in list(knowledge_matches.items())[:2]:  # Top 2 matches
+            data = match["data"]
+            
+            if category == "hours":
+                response_parts.append("📅 **Business Hours:**")
+                for day, hours in data.items():
+                    if day != "holidays":
+                        if isinstance(hours, dict):
+                            response_parts.append(f"  • {day.title()}: {hours['open']} - {hours['close']} {hours['timezone']}")
+                        else:
+                            response_parts.append(f"  • {day.title()}: {hours}")
+            
+            elif category == "location":
+                response_parts.append(f"📍 **Location:**")
+                response_parts.append(f"  • Address: {data['address']}")
+                response_parts.append(f"  • City: {data['city']}, {data['state']} {data['zip']}")
+                response_parts.append(f"  • Timezone: {data['timezone']}")
+            
+            elif category == "contact":
+                response_parts.append("📞 **Contact Information:**")
+                response_parts.append(f"  • Phone: {data['phone']}")
+                response_parts.append(f"  • Email: {data['email']}")
+                response_parts.append(f"  • Website: {data['website']}")
+            
+            elif category == "services":
+                response_parts.append("💼 **Our Services:**")
+                for service in data[:3]:  # Top 3 services
+                    response_parts.append(f"  • **{service['name']}**: {service['description']}")
+            
+            response_parts.append("")  # Add spacing
+        
+        return "\n".join(response_parts)
+
+def display_business_header():
+    """Display business header with key information."""
+    st.markdown(f'<h1 class="main-header">🏢 {BUSINESS_INFO["company_name"]}</h1>', unsafe_allow_html=True)
+    st.markdown(f'<p class="sub-header">{BUSINESS_INFO["tagline"]}</p>', unsafe_allow_html=True)
+    
+    # Business card
+    st.markdown(f"""
+    <div class="business-card">
+        <h3>📍 Quick Info</h3>
+        <p><strong>📞 Phone:</strong> {BUSINESS_INFO["contact"]["phone"]}</p>
+        <p><strong>📧 Email:</strong> {BUSINESS_INFO["contact"]["email"]}</p>
+        <p><strong>🌐 Website:</strong> {BUSINESS_INFO["contact"]["website"]}</p>
+        <p><strong>📍 Location:</strong> {BUSINESS_INFO["location"]["city"]}, {BUSINESS_INFO["location"]["state"]}</p>
+    </div>
+    """, unsafe_allow_html=True)
+
+def display_business_status():
+    """Display current business status and metrics."""
+    col1, col2, col3, col4 = st.columns(4)
+    
+    with col1:
+        st.markdown("""
+        <div class="metric-card">
+            <h4>🕐 Status</h4>
+            <span class="status-indicator status-open"></span>
+            <strong>Open Now</strong>
+        </div>
+        """, unsafe_allow_html=True)
+    
+    with col2:
+        st.markdown("""
+        <div class="metric-card">
+            <h4>⏱️ Response Time</h4>
+            <strong>< 24 hours</strong>
+        </div>
+        """, unsafe_allow_html=True)
+    
+    with col3:
+        ticket_count = len(st.session_state.support_tickets)
+        st.markdown(f"""
+        <div class="metric-card">
+            <h4>🎫 Active Tickets</h4>
+            <strong>{ticket_count}</strong>
+        </div>
+        """, unsafe_allow_html=True)
+    
+    with col4:
+        st.markdown("""
+        <div class="metric-card">
+            <h4>🤖 AI Status</h4>
+            <strong>Online</strong>
+        </div>
+        """, unsafe_allow_html=True)
+
+def create_sidebar():
+    """Create sidebar with navigation and options."""
+    st.sidebar.title("🏢 Business Assistant")
+    
+    # Navigation
+    page = st.sidebar.selectbox(
+        "📋 Navigate",
+        ["💬 Chat Assistant", "🎫 Support Tickets", "📊 Business Info", "⚙️ Settings"]
+    )
+    
+    # Quick actions
+    st.sidebar.markdown("### 🚀 Quick Actions")
+    
+    if st.sidebar.button("📞 Call Now", use_container_width=True):
+        st.sidebar.success(f"Call: {BUSINESS_INFO['contact']['phone']}")
+    
+    if st.sidebar.button("📧 Send Email", use_container_width=True):
+        st.sidebar.success(f"Email: {BUSINESS_INFO['contact']['email']}")
+    
+    if st.sidebar.button("🌐 Visit Website", use_container_width=True):
+        st.sidebar.success(f"Website: {BUSINESS_INFO['contact']['website']}")
+    
+    # Business hours
+    st.sidebar.markdown("### 🕐 Today's Hours")
+    current_day = datetime.now().strftime("%A").lower()
+    today_hours = BUSINESS_INFO["hours"].get(current_day, "Closed")
+    
+    if isinstance(today_hours, dict):
+        st.sidebar.info(f"**{current_day.title()}:** {today_hours['open']} - {today_hours['close']}")
+    else:
+        st.sidebar.info(f"**{current_day.title()}:** {today_hours}")
+    
+    return page
+
+def chat_assistant_page():
+    """Main chat assistant interface."""
+    st.markdown("### 💬 Business Assistant Chat")
+    st.markdown("Ask me anything about our business - hours, location, services, or contact information!")
+    
+    # Initialize assistant
+    if st.session_state.business_assistant is None:
+        st.session_state.business_assistant = BusinessAIAssistant()
+    
+    assistant = st.session_state.business_assistant
+    
+    # Display conversation
+    for message in st.session_state.conversation:
+        if message["role"] == "user":
+            st.markdown(f"""
+            <div class="chat-message user-message">
+                <strong>👤 You:</strong><br>
+                {message["content"]}
+            </div>
+            """, unsafe_allow_html=True)
+        else:
+            st.markdown(f"""
+            <div class="chat-message assistant-message">
+                <strong>🤖 Assistant:</strong><br>
+                {message["content"]}
+            </div>
+            """, unsafe_allow_html=True)
+    
+    # Chat input
+    with st.form("chat_form", clear_on_submit=True):
+        user_input = st.text_area(
+            "Your question:",
+            placeholder="Ask about our hours, location, services, contact info...",
+            height=100
+        )
+        
+        col1, col2, col3 = st.columns([2, 1, 1])
+        
+        with col1:
+            send_button = st.form_submit_button("🚀 Send", use_container_width=True)
+        
+        with col2:
+            ai_enabled = st.form_submit_button("🤖 AI Mode", use_container_width=True)
+        
+        with col3:
+            clear_button = st.form_submit_button("🗑️ Clear", use_container_width=True)
+    
+    # Process input
+    if (send_button or ai_enabled) and user_input.strip():
+        # Add user message
+        st.session_state.conversation.append({
+            "role": "user",
+            "content": user_input.strip()
+        })
+        
+        # Process query
+        with st.spinner("🤖 Processing your question..."):
+            response_data = assistant.process_query(user_input.strip(), use_ai=ai_enabled)
+        
+        # Add assistant response
+        st.session_state.conversation.append({
+            "role": "assistant",
+            "content": response_data["response"]
+        })
+        
+        # Show confidence and suggest ticket if needed
+        if response_data["confidence"] == "low":
+            st.warning("⚠️ I couldn't find specific information about that. Would you like to create a support ticket?")
+            if st.button("🎫 Create Support Ticket"):
+                st.session_state.pending_ticket_query = user_input.strip()
+                st.rerun()
+        
+        st.rerun()
+    
+    if clear_button:
+        st.session_state.conversation = []
+        st.rerun()
+
+def support_tickets_page():
+    """Support ticket management interface."""
+    st.markdown("### 🎫 Support Ticket System")
+    
+    tab1, tab2 = st.tabs(["📝 Create Ticket", "📋 My Tickets"])
+    
+    with tab1:
+        st.markdown("#### Create New Support Ticket")
+        
+        if st.session_state.business_assistant is None:
+            st.session_state.business_assistant = BusinessAIAssistant()
+        
+        ticket_manager = st.session_state.business_assistant.ticket_manager
+        
+        with st.form("create_ticket_form"):
+            col1, col2 = st.columns(2)
+            
+            with col1:
+                title = st.text_input("Ticket Title*", placeholder="Brief description of your issue")
+                category = st.selectbox("Category*", ticket_manager.ticket_categories)
+                priority = st.selectbox("Priority*", ticket_manager.priorities)
+            
+            with col2:
+                name = st.text_input("Your Name*", placeholder="Full name")
+                email = st.text_input("Email*", placeholder="[email protected]")
+                phone = st.text_input("Phone", placeholder="Optional phone number")
+            
+            description = st.text_area(
+                "Description*",
+                placeholder="Detailed description of your issue or request...",
+                height=150
+            )
+            
+            # Pre-fill if coming from chat
+            if hasattr(st.session_state, 'pending_ticket_query'):
+                description = st.text_area(
+                    "Description*",
+                    value=st.session_state.pending_ticket_query,
+                    height=150
+                )
+                del st.session_state.pending_ticket_query
+            
+            submit_ticket = st.form_submit_button("🎫 Create Ticket", use_container_width=True)
+            
+            if submit_ticket:
+                if title and description and name and email and category and priority:
+                    # Create ticket
+                    contact_info = {"name": name, "email": email, "phone": phone}
+                    
+                    ticket = ticket_manager.create_ticket(
+                        title, description, category, priority,
+                        contact_info, st.session_state.user_session_id
+                    )
+                    
+                    # Add to session
+                    st.session_state.support_tickets.append(ticket)
+                    
+                    # Display success
+                    st.success(f"✅ Ticket created successfully!")
+                    st.markdown(f"""
+                    <div class="support-ticket">
+                        <h4>🎫 Ticket #{ticket['id']}</h4>
+                        <p><strong>Status:</strong> <span class="status-indicator status-open"></span> {ticket['status']}</p>
+                        <p><strong>Priority:</strong> {ticket['priority']}</p>
+                        <p><strong>Category:</strong> {ticket['category']}</p>
+                        <p><strong>Created:</strong> {ticket['created_at'].strftime('%Y-%m-%d %H:%M:%S')}</p>
+                        
+                        <h5>External Integrations:</h5>
+                        <ul>
+                            <li>📚 GitHub: <a href="{ticket['external_integrations']['github']['url']}" target="_blank">Issue #{ticket['external_integrations']['github']['issue_number']}</a></li>
+                            <li>🔧 Jira: <a href="{ticket['external_integrations']['jira']['url']}" target="_blank">{ticket['external_integrations']['jira']['key']}</a></li>
+                            <li>📋 Trello: <a href="{ticket['external_integrations']['trello']['url']}" target="_blank">Card {ticket['external_integrations']['trello']['card_id']}</a></li>
+                        </ul>
+                        
+                        <p><strong>Expected Response:</strong> {BUSINESS_INFO['support']['response_time']}</p>
+                        <p>You will receive updates at: <strong>{email}</strong></p>
+                    </div>
+                    """, unsafe_allow_html=True)
+                    
+                else:
+                    st.error("❌ Please fill in all required fields marked with *")
+    
+    with tab2:
+        st.markdown("#### Your Support Tickets")
+        
+        if st.session_state.support_tickets:
+            for ticket in reversed(st.session_state.support_tickets):  # Most recent first
+                status_class = f"status-{ticket['status'].lower()}"
+                
+                st.markdown(f"""
+                <div class="support-ticket">
+                    <h4>🎫 {ticket['title']}</h4>
+                    <p><strong>ID:</strong> {ticket['id']}</p>
+                    <p><strong>Status:</strong> <span class="status-indicator {status_class}"></span> {ticket['status']}</p>
+                    <p><strong>Priority:</strong> {ticket['priority']} | <strong>Category:</strong> {ticket['category']}</p>
+                    <p><strong>Created:</strong> {ticket['created_at'].strftime('%Y-%m-%d %H:%M:%S')}</p>
+                    <p><strong>Description:</strong> {ticket['description'][:200]}...</p>
+                </div>
+                """, unsafe_allow_html=True)
+        else:
+            st.info("📝 No support tickets yet. Create one above if you need assistance!")
+
+def business_info_page():
+    """Business information dashboard."""
+    st.markdown("### 📊 Business Information")
+    
+    tab1, tab2, tab3, tab4 = st.tabs(["🏢 Overview", "🕐 Hours", "💼 Services", "👥 Team"])
+    
+    with tab1:
+        st.markdown("#### Company Overview")
+        
+        col1, col2 = st.columns(2)
+        
+        with col1:
+            st.markdown(f"""
+            <div class="info-card">
+                <h4>🏢 {BUSINESS_INFO['company_name']}</h4>
+                <p><strong>Description:</strong> {BUSINESS_INFO['description']}</p>
+                <p><strong>Tagline:</strong> {BUSINESS_INFO['tagline']}</p>
+            </div>
+            """, unsafe_allow_html=True)
+            
+            st.markdown(f"""
+            <div class="info-card">
+                <h4>📍 Location</h4>
+                <p><strong>Address:</strong> {BUSINESS_INFO['location']['address']}</p>
+                <p><strong>City:</strong> {BUSINESS_INFO['location']['city']}, {BUSINESS_INFO['location']['state']} {BUSINESS_INFO['location']['zip']}</p>
+                <p><strong>Country:</strong> {BUSINESS_INFO['location']['country']}</p>
+                <p><strong>Timezone:</strong> {BUSINESS_INFO['location']['timezone']}</p>
+            </div>
+            """, unsafe_allow_html=True)
+        
+        with col2:
+            st.markdown(f"""
+            <div class="info-card">
+                <h4>📞 Contact Information</h4>
+                <p><strong>Phone:</strong> {BUSINESS_INFO['contact']['phone']}</p>
+                <p><strong>Email:</strong> {BUSINESS_INFO['contact']['email']}</p>
+                <p><strong>Support Email:</strong> {BUSINESS_INFO['contact']['support_email']}</p>
+                <p><strong>Website:</strong> <a href="{BUSINESS_INFO['contact']['website']}" target="_blank">{BUSINESS_INFO['contact']['website']}</a></p>
+                <p><strong>LinkedIn:</strong> <a href="{BUSINESS_INFO['contact']['linkedin']}" target="_blank">Company Profile</a></p>
+            </div>
+            """, unsafe_allow_html=True)
+            
+            st.markdown(f"""
+            <div class="info-card">
+                <h4>🎯 Support Information</h4>
+                <p><strong>Response Time:</strong> {BUSINESS_INFO['support']['response_time']}</p>
+                <p><strong>Channels:</strong> {', '.join(BUSINESS_INFO['support']['channels'])}</p>
+                <p><strong>Emergency:</strong> {BUSINESS_INFO['support']['emergency_contact']}</p>
+            </div>
+            """, unsafe_allow_html=True)
+    
+    with tab2:
+        st.markdown("#### Business Hours")
+        
+        hours_data = []
+        for day, hours in BUSINESS_INFO["hours"].items():
+            if day != "holidays":
+                if isinstance(hours, dict):
+                    hours_data.append({
+                        "Day": day.title(),
+                        "Open": hours["open"],
+                        "Close": hours["close"],
+                        "Timezone": hours["timezone"]
+                    })
+                else:
+                    hours_data.append({
+                        "Day": day.title(),
+                        "Open": hours,
+                        "Close": "",
+                        "Timezone": ""
+                    })
+        
+        st.table(hours_data)
+        
+        st.info(f"🎄 Holiday Hours: {BUSINESS_INFO['hours']['holidays']}")
+    
+    with tab3:
+        st.markdown("#### Our Services")
+        
+        for service in BUSINESS_INFO["services"]:
+            st.markdown(f"""
+            <div class="info-card">
+                <h4>💼 {service['name']}</h4>
+                <p><strong>Description:</strong> {service['description']}</p>
+                <p><strong>Duration:</strong> {service['duration']}</p>
+                <p><strong>Price Range:</strong> {service['price_range']}</p>
+            </div>
+            """, unsafe_allow_html=True)
+    
+    with tab4:
+        st.markdown("#### Our Team")
+        
+        cols = st.columns(2)
+        for i, member in enumerate(BUSINESS_INFO["team"]):
+            with cols[i % 2]:
+                st.markdown(f"""
+                <div class="info-card">
+                    <h4>👤 {member['name']}</h4>
+                    <p><strong>Role:</strong> {member['role']}</p>
+                    <p><strong>Expertise:</strong> {member['expertise']}</p>
+                </div>
+                """, unsafe_allow_html=True)
+
+def settings_page():
+    """Settings and configuration page."""
+    st.markdown("### ⚙️ Settings")
+    
+    col1, col2 = st.columns(2)
+    
+    with col1:
+        st.markdown("#### 🤖 AI Configuration")
+        
+        ai_enabled = st.checkbox("Enable AI Responses", value=True)
+        ai_provider = st.selectbox("AI Provider", ["Auto", "OpenAI", "Gemini", "Hugging Face"])
+        response_length = st.slider("Response Length", 100, 1000, 500)
+        
+        st.markdown("#### 🎫 Ticket Settings")
+        auto_ticket = st.checkbox("Auto-suggest tickets for unknown queries", value=True)
+        email_notifications = st.checkbox("Email notifications", value=True)
+        
+    with col2:
+        st.markdown("#### 📊 Analytics")
+        
+        st.metric("Total Conversations", len(st.session_state.conversation))
+        st.metric("Support Tickets Created", len(st.session_state.support_tickets))
+        st.metric("Session ID", st.session_state.user_session_id[:8] + "...")
+        
+        st.markdown("#### 🔄 Actions")
+        
+        if st.button("🗑️ Clear All Data", use_container_width=True):
+            st.session_state.conversation = []
+            st.session_state.support_tickets = []
+            st.session_state.chat_analytics = []
+            st.success("✅ All data cleared!")
+        
+        if st.button("💾 Export Data", use_container_width=True):
+            export_data = {
+                "conversation": st.session_state.conversation,
+                "support_tickets": [
+                    {**ticket, "created_at": ticket["created_at"].isoformat(), 
+                     "updated_at": ticket["updated_at"].isoformat()}
+                    for ticket in st.session_state.support_tickets
+                ],
+                "analytics": st.session_state.chat_analytics,
+                "session_id": st.session_state.user_session_id,
+                "export_timestamp": datetime.now().isoformat()
+            }
+            
+            st.download_button(
+                label="📥 Download JSON",
+                data=json.dumps(export_data, indent=2),
+                file_name=f"business_assistant_data_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json",
+                mime="application/json"
+            )
+
+def main():
+    """Main Streamlit application."""
+    # Initialize session state
+    initialize_session_state()
+    
+    # Display header
+    display_business_header()
+    
+    # Display status
+    display_business_status()
+    
+    # Create sidebar and get current page
+    current_page = create_sidebar()
+    
+    # Display appropriate page
+    st.markdown("---")
+    
+    if current_page == "💬 Chat Assistant":
+        chat_assistant_page()
+    elif current_page == "🎫 Support Tickets":
+        support_tickets_page()
+    elif current_page == "📊 Business Info":
+        business_info_page()
+    elif current_page == "⚙️ Settings":
+        settings_page()
+    
+    # Footer
+    st.markdown("---")
+    st.markdown(
+        f"🚀 **{BUSINESS_INFO['company_name']}** | "
+        f"📞 {BUSINESS_INFO['contact']['phone']} | "
+        f"📧 {BUSINESS_INFO['contact']['email']} | "
+        f"Powered by Advanced AI & Hugging Face Spaces"
+    )
+
+if __name__ == "__main__":
+    main()