Update app.py - Voice Streaming & AI Coaching Features

app.py

@@ -26,6 +26,9 @@ from document_templates import DocumentTemplateGenerator  # Document template ge
 from financial_data_integration import FinancialDataIntegrator  # Real-time financial data
 from document_intelligence import DocumentIntelligenceEngine  # AI document intelligence
 from advanced_analytics import AdvancedAnalyticsDashboard  # Advanced analytics
+from voice_streaming import VoiceStreamingManager, VoiceUIManager  # OpenAI voice streaming
+from startup_coach_personas import StartupCoachPersonas, PersonaUIManager  # AI coaching personas
+from market_intelligence_dashboard import MarketIntelligenceDashboard  # Market intelligence
 print("DEBUG: Importing chainlit", flush=True)
 import chainlit as cl  # Chainlit framework for building conversational AI interfaces
 print("DEBUG: Chainlit imported", flush=True)
@@ -8439,7 +8442,133 @@ Look for startups with larger radar areas and balanced performance across dimens
         return
 
     # =============================
-    # ROUTE 13: AI-POWERED Q&A WITH MEMORY & PERSONA (DEFAULT)
+    # ROUTE 14: VOICE STREAMING & CONVERSATION
+    # =============================
+    if any(keyword in user_input for keyword in ["voice chat", "start voice", "voice streaming", "talk to", "voice conversation"]):
+        # Initialize voice streaming interface
+        voice_ui = VoiceUIManager()
+        voice_interface = await voice_ui.create_voice_interface()
+
+        await cl.Message(
+            content="🎤 **Voice Conversation Mode**\n\n"
+                   "Choose your AI coaching persona and start a voice conversation!\n\n"
+                   "**Available Features:**\n"
+                   "• Real-time voice conversation with OpenAI\n"
+                   "• Multiple specialized coaching personas\n"
+                   "• Audio visualization and recording\n"
+                   "• Conversation summaries\n\n"
+                   "Click the microphone button below to start:",
+            elements=[cl.Html(content=voice_interface)]
+        ).send()
+        return
+
+    # Handle voice-related messages from JavaScript interface
+    if hasattr(message, 'type') and message.type in ['voice_audio', 'switch_persona', 'get_summary']:
+        voice_ui = VoiceUIManager()
+        response = await voice_ui.handle_voice_message(message.type, message.content)
+
+        if response.get('status') == 'success':
+            await cl.Message(content=f"✅ {response.get('message', 'Voice command processed')}").send()
+        else:
+            await cl.Message(content=f"❌ {response.get('message', 'Voice command failed')}").send()
+        return
+
+    # =============================
+    # ROUTE 15: AI STARTUP COACHING PERSONAS
+    # =============================
+    if any(keyword in user_input for keyword in ["coaching", "advisor", "persona", "coach", "startup coach", "choose coach"]):
+        # Initialize persona manager
+        persona_ui = PersonaUIManager()
+        coach_personas = StartupCoachPersonas()
+
+        if "switch" in user_input or "change" in user_input:
+            # Handle persona switching
+            personas = coach_personas.get_available_personas()
+            persona_list = "\n".join([f"• **{p['name']}** - {', '.join(p['expertise'][:2])}"
+                                    for p in personas.values()])
+
+            await cl.Message(
+                content=f"🎯 **Available Startup Coaches:**\n\n{persona_list}\n\n"
+                       "Which coach would you like to work with? Just mention their name or expertise area."
+            ).send()
+            return
+
+        # Show persona selector interface
+        persona_interface = persona_ui.create_persona_selector()
+
+        await cl.Message(
+            content="🎯 **AI-Powered Startup Coaching**\n\n"
+                   "Choose from our specialized AI coaches, each with deep expertise in different areas of startup development:",
+            elements=[cl.Html(content=persona_interface)]
+        ).send()
+        return
+
+    # Handle persona selection from interface
+    if hasattr(message, 'type') and message.type == 'select_persona':
+        coach_personas = StartupCoachPersonas()
+        persona_id = message.content.get('persona_id')
+        startup_context = message.content.get('startup_context', {})
+
+        session_result = await coach_personas.initialize_coaching_session(persona_id, startup_context)
+
+        if session_result.get('status') == 'success':
+            persona = session_result['persona']
+            welcome = session_result['welcome_message']
+
+            # Store session in Chainlit user session
+            cl.user_session.set("coaching_session", session_result['session_id'])
+            cl.user_session.set("current_persona", persona_id)
+
+            await cl.Message(
+                content=f"✅ **{persona['avatar']} {persona['name']} is now your coach!**\n\n"
+                       f"{welcome}\n\n"
+                       f"**Expertise:** {', '.join(persona['expertise'])}\n\n"
+                       "Ask me anything about your startup - I'm here to help!"
+            ).send()
+        else:
+            await cl.Message(content=f"❌ Error initializing coaching session: {session_result.get('message')}").send()
+        return
+
+    # =============================
+    # ROUTE 16: MARKET INTELLIGENCE DASHBOARD
+    # =============================
+    if any(keyword in user_input for keyword in ["market intelligence", "market dashboard", "competitive analysis",
+                                                  "market trends", "sector analysis", "market data"]):
+        # Initialize market intelligence dashboard
+        market_dashboard = MarketIntelligenceDashboard()
+        dashboard_interface = await market_dashboard.create_dashboard_interface()
+
+        await cl.Message(
+            content="📊 **Market Intelligence Dashboard**\n\n"
+                   "Access real-time market data, competitive intelligence, and trend analysis:\n\n"
+                   "**Features:**\n"
+                   "• Sector performance analysis\n"
+                   "• Competitive landscape mapping\n"
+                   "• Market trend identification\n"
+                   "• Investment theme analysis\n"
+                   "• Real-time data visualization\n\n"
+                   "Use the controls below to analyze your market:",
+            elements=[cl.Html(content=dashboard_interface)]
+        ).send()
+        return
+
+    # Handle dashboard requests from interface
+    if hasattr(message, 'type') and message.type == 'dashboard_request':
+        market_dashboard = MarketIntelligenceDashboard()
+        request_type = message.content.get('request_type')
+        data = message.content.get('data', {})
+
+        response = await market_dashboard.handle_dashboard_request(request_type, data)
+
+        if response.get('status') == 'success':
+            # Send the response back to the dashboard
+            await cl.Message(content="📊 Dashboard updated with latest data.").send()
+        else:
+            await cl.Message(content=f"❌ Dashboard error: {response.get('message')}").send()
+        return
+
+    # =============================
+    # ROUTE 17: AI-POWERED Q&A WITH MEMORY & PERSONA (DEFAULT)
     # =============================
     # If no specific pattern matched, use GPT-4 for natural language response