Update agents/agents.py

agents/agents.py

@@ -1,402 +1,409 @@
+import streamlit as st
 import json
-import os
+import zipfile
+import io
+import time
+import textwrap
 import requests
-from dotenv import load_dotenv
-from openai import OpenAI
+from agents import TopicAgent, ContentAgent, SlideAgent, CodeAgent, DesignAgent, VoiceoverAgent
 
-# Load environment variables
-load_dotenv()
+# Initialize agents
+topic_agent = TopicAgent()
+content_agent = ContentAgent()
+slide_agent = SlideAgent()
+code_agent = CodeAgent()
+design_agent = DesignAgent()
+voiceover_agent = VoiceoverAgent()
 
-# Initialize API clients
-openai_client = OpenAI(api_key=os.getenv("OPENAI_API_KEY")) if os.getenv("OPENAI_API_KEY") else None
-ELEVENLABS_API_KEY = os.getenv("ELEVENLABS_API_KEY")
+# =====================
+# STREAMLIT APPLICATION
+# =====================
 
-class TopicAgent:
-    def generate_outline(self, topic, duration, difficulty):
-        if not openai_client:
-            return self._mock_outline(topic, duration, difficulty)
-            
-        try:
-            response = openai_client.chat.completions.create(
-                model="gpt-4-turbo",
-                messages=[
-                    {
-                        "role": "system",
-                        "content": (
-                            "You are an expert corporate trainer with 20+ years of experience creating "
-                            "high-value workshops for Fortune 500 companies. Create a professional workshop outline that "
-                            "includes: 1) Clear learning objectives, 2) Practical real-world exercises, "
-                            "3) Industry case studies, 4) Measurable outcomes. Format as JSON."
-                        )
-                    },
-                    {
-                        "role": "user",
-                        "content": (
-                            f"Create a comprehensive {duration}-hour {difficulty} workshop outline on '{topic}' for corporate executives. "
-                            "Structure: title, duration, difficulty, learning_goals (3-5 bullet points), "
-                            "modules (5-7 modules). Each module should have: title, duration, learning_points (3 bullet points), "
-                            "case_study (real company example), exercises (2 practical exercises)."
-                        )
-                    }
-                ],
-                temperature=0.3,
-                max_tokens=1500,
-                response_format={"type": "json_object"}
-            )
-            return json.loads(response.choices[0].message.content)
-        except Exception as e:
-            return self._mock_outline(topic, duration, difficulty)
-    
-    def _mock_outline(self, topic, duration, difficulty):
-        return {
-            "title": f"Mastering {topic} for Business Impact",
-            "duration": f"{duration} hours",
-            "difficulty": difficulty,
-            "learning_goals": [
-                "Apply advanced techniques to real business challenges",
-                "Measure ROI of prompt engineering initiatives",
-                "Develop organizational prompt engineering standards",
-                "Implement ethical AI governance frameworks"
-            ],
-            "modules": [
-                {
-                    "title": "Strategic Foundations",
-                    "duration": "45 min",
-                    "learning_points": [
-                        "Business value assessment framework",
-                        "ROI calculation models",
-                        "Stakeholder alignment strategies"
-                    ],
-                    "case_study": "How JPMorgan reduced operational costs by 37% with prompt optimization",
-                    "exercises": [
-                        "Calculate potential ROI for your organization",
-                        "Develop stakeholder communication plan"
-                    ]
-                },
-                {
-                    "title": "Advanced Pattern Engineering",
-                    "duration": "60 min",
-                    "learning_points": [
-                        "Chain-of-thought implementations",
-                        "Self-correcting prompt architectures",
-                        "Domain-specific pattern libraries"
-                    ],
-                    "case_study": "McKinsey's knowledge management transformation",
-                    "exercises": [
-                        "Design pattern library for your industry",
-                        "Implement self-correction workflow"
-                    ]
-                }
-            ]
-        }
+st.set_page_config(
+    page_title="Workshop in a Box Pro",
+    layout="wide",
+    initial_sidebar_state="expanded",
+    page_icon="🎓"
+)
 
-class ContentAgent:
-    def generate_content(self, outline):
-        if not openai_client:
-            return self._mock_content(outline)
-            
-        try:
-            response = openai_client.chat.completions.create(
-                model="gpt-4-turbo",
-                messages=[
-                    {
-                        "role": "system",
-                        "content": (
-                            "You are a senior instructional designer creating premium corporate training materials. "
-                            "Develop comprehensive workshop content with: 1) Practitioner-level insights, "
-                            "2) Actionable frameworks, 3) Real-world examples, 4) Practical exercises. "
-                            "Avoid generic AI content - focus on business impact."
-                        )
-                    },
-                    {
-                        "role": "user",
-                        "content": (
-                            f"Create premium workshop content for this outline: {json.dumps(outline)}. "
-                            "For each module: "
-                            "1) Detailed script (executive summary, 3 key concepts, business applications) "
-                            "2) Speaker notes (presentation guidance) "
-                            "3) 3 discussion questions with executive-level responses "
-                            "4) 2 practical exercises with solution blueprints "
-                            "Format as JSON."
-                        )
-                    }
-                ],
-                temperature=0.4,
-                max_tokens=3000,
-                response_format={"type": "json_object"}
-            )
-            return json.loads(response.choices[0].message.content)
-        except Exception as e:
-            return self._mock_content(outline)
-    
-    def _mock_content(self, outline):
-        return {
-            "workshop_title": outline.get("title", "Premium AI Workshop"),
-            "modules": [
-                {
-                    "title": "Strategic Foundations",
-                    "script": (
-                        "## Executive Summary\n"
-                        "This module establishes the business case for advanced prompt engineering, "
-                        "focusing on measurable ROI and stakeholder alignment.\n\n"
-                        "### Key Concepts:\n"
-                        "1. **Value Assessment Framework**: Quantify potential savings and revenue opportunities\n"
-                        "2. **ROI Calculation Models**: Custom models for different industries\n"
-                        "3. **Stakeholder Alignment**: Executive communication strategies\n\n"
-                        "### Business Applications:\n"
-                        "- Cost reduction in customer service operations\n"
-                        "- Acceleration of R&D processes\n"
-                        "- Enhanced competitive intelligence"
-                    ),
-                    "speaker_notes": [
-                        "Emphasize real dollar impact - use JPMorgan case study numbers",
-                        "Show ROI calculator template",
-                        "Highlight C-suite communication strategies"
-                    ],
-                    "discussion_questions": [
-                        {
-                            "question": "How could prompt engineering impact your bottom line?",
-                            "response": "Typical results: 30-40% operational efficiency gains, 15-25% innovation acceleration"
-                        }
-                    ],
-                    "exercises": [
-                        {
-                            "title": "ROI Calculation Workshop",
-                            "instructions": "Calculate potential savings using our enterprise ROI model",
-                            "solution": "Template: (Current Cost × Efficiency Gain) - Implementation Cost"
-                        }
-                    ]
-                }
-            ]
-        }
+# Custom CSS for premium styling
+st.markdown("""
+<style>
+    .stApp {
+        background: linear-gradient(135deg, #0f2027 0%, #203a43 100%);
+        color: #fff;
+        font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+    }
+    .stTextInput>div>div>input {
+        background-color: rgba(255,255,255,0.1) !important;
+        color: white !important;
+        border: 1px solid #4CAF50;
+        border-radius: 8px;
+    }
+    .stButton>button {
+        background: linear-gradient(to right, #0d8bf2, #04befe) !important;
+        color: white !important;
+        border: none;
+        border-radius: 8px;
+        padding: 12px 30px;
+        font-size: 16px;
+        font-weight: bold;
+        box-shadow: 0 4px 6px rgba(0,0,0,0.1);
+        transition: all 0.3s ease;
+    }
+    .stButton>button:hover {
+        transform: translateY(-2px);
+        box-shadow: 0 6px 8px rgba(0,0,0,0.15);
+    }
+    .stDownloadButton>button {
+        background: linear-gradient(to right, #00c853, #64dd17) !important;
+    }
+    .stExpander {
+        background: rgba(15, 32, 39, 0.8) !important;
+        border-radius: 10px;
+        padding: 20px;
+        border: 1px solid #1e88e5;
+        box-shadow: 0 4px 20px rgba(0,0,0,0.25);
+    }
+    .premium-badge {
+        background: linear-gradient(45deg, #ffd700, #ff9800);
+        color: #000;
+        padding: 3px 10px;
+        border-radius: 12px;
+        font-size: 0.8em;
+        font-weight: bold;
+        display: inline-block;
+        margin-left: 10px;
+    }
+    .section-header {
+        border-left: 4px solid #0d8bf2;
+        padding-left: 15px;
+        margin-top: 30px;
+    }
+    .testimonial {
+        background: rgba(255,255,255,0.05);
+        border-radius: 10px;
+        padding: 15px;
+        margin: 15px 0;
+        border-left: 4px solid #00c853;
+    }
+    .pricing-card {
+        background: rgba(255,255,255,0.05);
+        border-radius: 10px;
+        padding: 20px;
+        margin: 10px 0;
+        border: 1px solid #0d8bf2;
+    }
+    .executive-summary {
+        background: linear-gradient(to right, #1a2980, #26d0ce);
+        padding: 25px;
+        border-radius: 15px;
+        margin-bottom: 25px;
+        box-shadow: 0 10px 20px rgba(0,0,0,0.2);
+    }
+    .sidebar-section {
+        padding: 15px;
+        background: rgba(255,255,255,0.05);
+        border-radius: 10px;
+        margin-bottom: 15px;
+    }
+</style>
+""", unsafe_allow_html=True)
+
+# Header
+col1, col2 = st.columns([1, 4])
+with col1:
+    st.image("https://cdn-icons-png.flaticon.com/512/1995/1995485.png", width=80)
+with col2:
+    st.title("🤖 Workshop in a Box Pro")
+    st.markdown("Generate Boardroom-Quality Corporate Training <span class='premium-badge'>PREMIUM</span>", unsafe_allow_html=True)
+    st.caption("Create $10K+ Value Workshops in Minutes")
 
-class SlideAgent:
-    def generate_slides(self, content):
-        if not openai_client:
-            return self._professional_slides(content)
+# Initialize session state
+if 'workshop_topic' not in st.session_state:
+    st.session_state.workshop_topic = "AI-Driven Business Transformation"
+if 'generated' not in st.session_state:
+    st.session_state.generated = False
+if 'generating' not in st.session_state:
+    st.session_state.generating = False
+if 'voiceovers' not in st.session_state:
+    st.session_state.voiceovers = {}
+if 'selected_voice' not in st.session_state:
+    st.session_state.selected_voice = "21m00Tcm4TlvDq8ikWAM"  # Default voice ID
+
+# Sidebar configuration
+with st.sidebar:
+    st.header("⚙️ Executive Workshop Configuration")
+    
+    # Create container for better organization
+    with st.container():
+        st.markdown("<div class='sidebar-section'>", unsafe_allow_html=True)
+        
+        # Workshop topic input
+        topic = st.text_input(
+            "Workshop Focus", 
+            st.session_state.workshop_topic,
+            key="topic_input",
+            help="Strategic business topic (e.g., 'AI for Financial Services Transformation')"
+        )
+        
+        # Update session state only if input changes
+        if topic != st.session_state.workshop_topic:
+            st.session_state.workshop_topic = topic
+        
+        # Validate topic input
+        if st.session_state.workshop_topic.strip() == "":
+            st.warning("Please enter a strategic workshop focus")
+        
+        duration = st.slider("Duration (hours)", 2.0, 8.0, 4.0, 0.5, 
+                            help="Full-day or half-day workshop")
+        difficulty = st.selectbox("Audience Level", 
+                                ["C-Suite", "Executives", "Directors", "Managers"])
+        
+        st.markdown("</div>", unsafe_allow_html=True)
+    
+    # Advanced options section
+    with st.container():
+        st.markdown("<div class='sidebar-section'>", unsafe_allow_html=True)
+        st.subheader("Advanced Options")
+        include_code = st.checkbox("Include Technical Implementation", True)
+        include_design = st.checkbox("Generate Premium Visuals", True)
+        include_voiceover = st.checkbox("Generate Voiceovers", True)
+        
+        # Voice selection
+        if include_voiceover:
+            voices = voiceover_agent.get_voices()
             
-        try:
-            response = openai_client.chat.completions.create(
-                model="gpt-4-turbo",
-                messages=[
-                    {
-                        "role": "system",
-                        "content": (
-                            "You are a McKinsey-level presentation specialist. Create professional slides with: "
-                            "1) Clean, executive-friendly design 2) Data visualization frameworks "
-                            "3) Action-oriented content 4) Brand-compliant styling. "
-                            "Use Marp Markdown format with the 'gaia' theme."
-                        )
-                    },
-                    {
-                        "role": "user",
-                        "content": (
-                            f"Create a boardroom-quality slide deck for: {json.dumps(content)}. "
-                            "Structure: Title slide, module slides (objective, 3 key points, case study, exercise), "
-                            "summary slide. Include placeholders for data visualization."
-                        )
-                    }
-                ],
-                temperature=0.2,
-                max_tokens=2500
-            )
-            return response.choices[0].message.content
-        except Exception as e:
-            return self._professional_slides(content)
+            if voices:
+                selected_voice = st.selectbox(
+                    "Choose a voice:",
+                    options=[v['voice_id'] for v in voices],
+                    format_func=lambda id: next((v['name'] for v in voices if v['voice_id'] == id), "Default"),
+                    key="voice_select"
+                )
+                st.session_state.selected_voice = selected_voice
+            elif voiceover_agent.api_key:
+                st.warning("Couldn't load voices. Using default voice.")
+            else:
+                st.warning("ElevenLabs API key not set. Voiceovers disabled.")
+        
+        st.markdown("</div>", unsafe_allow_html=True)
     
-    def _professional_slides(self, content):
-        return f"""---
-marp: true
-theme: gaia
-class: lead
-paginate: true
-backgroundColor: #fff
-backgroundImage: url('https://marp.app/assets/hero-background.svg')
----
+    # Quality assurance section
+    with st.container():
+        st.markdown("<div class='sidebar-section'>", unsafe_allow_html=True)
+        st.subheader("Quality Assurance")
+        premium_mode = st.checkbox("Enable Premium Mode", True, 
+                                help="Generate boardroom-quality content with real-world case studies")
+        
+        if st.button("✨ Generate Premium Workshop", type="primary", use_container_width=True):
+            if st.session_state.workshop_topic.strip() == "":
+                st.error("Please enter a workshop focus")
+            else:
+                st.session_state.generating = True
+                st.session_state.voiceovers = {}  # Reset previous voiceovers
+        
+        st.markdown("</div>", unsafe_allow_html=True)
 
-# {content.get('workshop_title', 'Executive AI Workshop')}
-## Transforming Business Through Advanced AI
+# Generation pipeline
+if st.session_state.generating:
+    with st.spinner(f"🚀 Creating your executive workshop on '{st.session_state.workshop_topic}'..."):
+        start_time = time.time()
+        
+        # Agent pipeline
+        outline = topic_agent.generate_outline(st.session_state.workshop_topic, duration, difficulty)
+        content = content_agent.generate_content(outline)
+        slides = slide_agent.generate_slides(content)
+        code_labs = code_agent.generate_code(content) if include_code else None
+        design_url = design_agent.generate_design(slides) if include_design else None
+        
+        # Generate voiceovers if enabled
+        voiceovers = {}
+        if include_voiceover and voiceover_agent.api_key:
+            for i, module in enumerate(content.get("modules", [])):
+                intro_text = f"Module {i+1}: {module['title']}. " + \
+                            f"Key concepts: {', '.join(module.get('learning_points', [''])[:3])}"
+                audio_data = voiceover_agent.generate_voiceover(
+                    intro_text,
+                    st.session_state.selected_voice
+                )
+                if audio_data:
+                    voiceovers[f"module_{i+1}_intro.mp3"] = audio_data
+        
+        # Prepare download package
+        zip_buffer = io.BytesIO()
+        with zipfile.ZipFile(zip_buffer, "a", zipfile.ZIP_DEFLATED) as zip_file:
+            zip_file.writestr("executive_summary.json", json.dumps(outline, indent=2))
+            zip_file.writestr("workshop_content.json", json.dumps(content, indent=2))
+            zip_file.writestr("boardroom_slides.md", slides)
+            if code_labs:
+                zip_file.writestr("enterprise_solutions.ipynb", code_labs)
+            if design_url:
+                try:
+                    img_data = requests.get(design_url).content
+                    zip_file.writestr("slide_design.png", img_data)
+                except Exception as e:
+                    st.error(f"Design download error: {str(e)}")
+            # Add voiceovers to ZIP
+            for filename, audio_data in voiceovers.items():
+                zip_file.writestr(f"voiceovers/{filename}", audio_data)
+        
+        # Store results
+        st.session_state.outline = outline
+        st.session_state.content = content
+        st.session_state.slides = slides
+        st.session_state.code_labs = code_labs
+        st.session_state.design_url = design_url
+        st.session_state.voiceovers = voiceovers
+        st.session_state.zip_buffer = zip_buffer
+        st.session_state.gen_time = round(time.time() - start_time, 2)
+        st.session_state.generated = True
+        st.session_state.generating = False
 
----
-<!-- _class: invert -->
-## Module 1: Strategic Foundations
-### Driving Measurable Business Value
+# Results display
+if st.session_state.generated:
+    st.success(f"✅ Executive workshop generated in {st.session_state.gen_time} seconds!")
+    
+    # Download button
+    st.download_button(
+        label="📥 Download Executive Package",
+        data=st.session_state.zip_buffer.getvalue(),
+        file_name=f"{st.session_state.workshop_topic.replace(' ', '_')}_workshop.zip",
+        mime="application/zip",
+        use_container_width=True
+    )
+    
+    # Executive summary
+    with st.expander("📊 Executive Overview", expanded=True):
+        st.markdown(f"<div class='executive-summary'>", unsafe_allow_html=True)
+        st.subheader(st.session_state.outline.get("title", "Strategic Workshop"))
+        st.caption(f"Duration: {st.session_state.outline.get('duration', '4 hours')} | Level: {st.session_state.outline.get('difficulty', 'Executive')}")
+        
+        st.markdown("**Business Value Proposition**")
+        if "learning_goals" in st.session_state.outline:
+            for goal in st.session_state.outline["learning_goals"]:
+                st.markdown(f"- {goal}")
+        
+        st.markdown("**Key Deliverables**")
+        st.markdown("- Boardroom-ready presentation\n"
+                    "- Implementation toolkit\n"
+                    "- ROI calculation framework\n"
+                    "- Enterprise integration guide")
+        st.markdown("</div>", unsafe_allow_html=True)
 
-![bg right:40% w:450](https://images.pexels.com/photos/3184292/pexels-photo-3184292.jpeg)
+    # Workshop content
+    with st.expander("📝 Strategic Content Framework"):
+        if "modules" in st.session_state.content:
+            for module in st.session_state.content["modules"]:
+                st.subheader(module.get("title", "Business Module"))
+                st.markdown(module.get("script", ""))
+                
+                st.markdown("**Executive Discussion Points**")
+                if "discussion_questions" in module:
+                    for q in module["discussion_questions"]:
+                        st.markdown(f"- **{q.get('question', '')}**")
+                        st.caption(q.get("response", ""))
 
-- **ROI Framework**: Quantifying impact
-- **Stakeholder Alignment**: Executive buy-in strategies
-- **Implementation Roadmap**: Phased adoption plan
+    # Slide preview
+    with st.expander("🖥️ Boardroom Presentation Preview"):
+        st.markdown("```markdown\n" + textwrap.dedent(st.session_state.slides[:2000]) + "\n```")
 
----
-## Case Study: Financial Services Transformation
-### JPMorgan Chase
+    # Technical implementation
+    if st.session_state.code_labs:
+        with st.expander("💻 Enterprise Implementation Toolkit"):
+            st.code(st.session_state.code_labs)
 
-| Metric | Before | After | Improvement |
-|--------|--------|-------|-------------|
-| Operation Costs | $4.2M | $2.6M | 38% reduction |
-| Process Time | 14 days | 3 days | 79% faster |
-| Error Rate | 8.2% | 0.4% | 95% reduction |
+    # Design preview
+    if st.session_state.design_url:
+        with st.expander("🎨 Premium Visual Design"):
+            try:
+                st.image(st.session_state.design_url, caption="Corporate Slide Design")
+            except:
+                st.warning("Design preview unavailable")
+    
+    # Voiceover player
+    if st.session_state.voiceovers:
+        with st.expander("🔊 Voiceover Previews"):
+            for i, (filename, audio_bytes) in enumerate(st.session_state.voiceovers.items()):
+                module_num = filename.split("_")[1]
+                st.subheader(f"Module {module_num} Introduction")
+                st.audio(audio_bytes, format="audio/mp3")
 
----
-## Practical Exercise: ROI Calculation
-```mermaid
-graph TD
-    A[Current Costs] --> B[Potential Savings]
-    C[Implementation Costs] --> D[Net ROI]
-    B --> D
-Document current process costs
+# Executive engagement section
+st.divider()
+st.subheader("🚀 Premium Corporate Offering")
+st.markdown(f"""
+### {st.session_state.workshop_topic} Executive Program
+<div class="pricing-card">
+    <h4>Live Workshop</h4>
+    <h2>$15,000</h2>
+    <p>Full-day session with Q&A</p>
+</div>
+<div class="pricing-card">
+    <h4>On-Demand Course</h4>
+    <h2>$7,500</h2>
+    <p>Enterprise-wide access</p>
+</div>
+<div class="pricing-card">
+    <h4>Implementation Package</h4>
+    <h2>$12,500</h2>
+    <p>Technical integration support</p>
+</div>
 
-Estimate efficiency gains
+**Premium Features:**
+- Customized to your industry vertical
+- ROI guarantee
+- 12-month support agreement
+- Executive briefing package
+""", unsafe_allow_html=True)
 
-Calculate net ROI
+# Testimonials
+st.divider()
+st.subheader("💼 Executive Testimonials")
+st.markdown("""
+<div class="testimonial">
+    <p>"This platform helped us create a $50K training program in one afternoon. The ROI was immediate."</p>
+    <p><strong>— Sarah Johnson, CLO at FinTech Global</strong></p>
+</div>
+<div class="testimonial">
+    <p>"The boardroom-quality materials impressed our clients and justified our premium pricing."</p>
+    <p><strong>— Michael Chen, Partner at McKinsey & Company</strong></p>
+</div>
+""", unsafe_allow_html=True)
 
-Q&A
-Let's discuss your specific challenges
-"""
+# CTA
+st.divider()
+col1, col2 = st.columns(2)
+with col1:
+    st.link_button("📅 Book Strategy Session", "https://calendly.com/your-link", use_container_width=True)
+with col2:
+    st.link_button("💼 Enterprise Solutions", "https://your-company.com/enterprise", use_container_width=True)
 
-class CodeAgent:
-    def generate_code(self, content):
-        if not openai_client:
-            return self._professional_code(content)
-            
-        try:
-            response = openai_client.chat.completions.create(
-                model="gpt-4-turbo",
-                messages=[
-                    {
-                        "role": "system",
-                        "content": (
-                            "You are an enterprise solutions architect. Create professional-grade code labs with: "
-                            "1) Production-ready patterns 2) Comprehensive documentation "
-                            "3) Enterprise security practices 4) Scalable architectures. "
-                            "Use Python with the latest best practices."
-                        )
-                    },
-                    {
-                        "role": "user",
-                        "content": (
-                            f"Create a professional code lab for: {json.dumps(content)}. "
-                            "Include: Setup instructions, business solution patterns, "
-                            "enterprise integration examples, and security best practices."
-                        )
-                    }
-                ],
-                temperature=0.3,
-                max_tokens=2500
-            )
-            return response.choices[0].message.content
-        except Exception as e:
-            return self._professional_code(content)
+# Footer
+st.divider()
+st.markdown("""
+<div style="text-align: center; padding: 20px; color: #aaa;">
+    Workshop in a Box Pro® | Enterprise-Grade AI Training Solutions | © 2025
+</div>
+""", unsafe_allow_html=True)
 
-    def _professional_code(self, content):
-        return f"""# Enterprise-Grade Prompt Engineering Lab
-Business Solution Framework
-python
-class PromptOptimizer:
-    def __init__(self, model="gpt-4-turbo"):
-        self.model = model
-        self.pattern_library = {{
-            "financial_analysis": "Extract key metrics from financial reports",
-            "customer_service": "Resolve tier-2 support tickets"
-        }}
+# Debug info
+with st.sidebar:
+    st.divider()
+    st.subheader("System Status")
     
-    def optimize_prompt(self, business_case):
-        # Implement enterprise optimization logic
-        return f"Business-optimized prompt for {{business_case}}"
+    if hasattr(voiceover_agent, 'api_key') and voiceover_agent.api_key:
+        st.success("ElevenLabs API Key Found")
+    elif include_voiceover:
+        st.warning("ElevenLabs API key not set")
     
-    def calculate_roi(self, current_cost, expected_efficiency):
-        return current_cost * expected_efficiency
-
-# Example usage
-optimizer = PromptOptimizer()
-print(optimizer.calculate_roi(500000, 0.35))  # $175,000 savings
-
-Security Best Practices
-python
-def secure_prompt_handling(user_input):
-    # Implement OWASP security standards
-    sanitized = sanitize_input(user_input)
-    validate_business_context(sanitized)
-    return apply_enterprise_guardrails(sanitized)
-
-Integration Pattern: CRM System
-python
-def integrate_with_salesforce(prompt, salesforce_data):
-    # Enterprise integration example
-    enriched_prompt = f"{{prompt}} using {{salesforce_data}}"
-    return call_ai_api(enriched_prompt)
-"""
-
-class DesignAgent:
-    def generate_design(self, slide_content):
-        if not openai_client:
-            return None
-            
-        try:
-            response = openai_client.images.generate(
-                model="dall-e-3",
-                prompt=(
-                    f"Professional corporate slide background for '{slide_content[:200]}' workshop. "
-                    "Modern business style, clean lines, premium gradient, boardroom appropriate. "
-                    "Include abstract technology elements in corporate colors."
-                ),
-                n=1,
-                size="1024x1024"
-            )
-            return response.data[0].url
-        except Exception as e:
-            return None
-
-class VoiceoverAgent:
-    def __init__(self):
-        self.api_key = ELEVENLABS_API_KEY
-        self.voice_id = "21m00Tcm4TlvDq8ikWAM"  # Default voice ID
-        self.model = "eleven_monolingual_v1"
-        
-    def generate_voiceover(self, text, voice_id=None):
-        if not self.api_key:
-            return None
-            
-        try:
-            voice = voice_id if voice_id else self.voice_id
-            
-            url = f"https://api.elevenlabs.io/v1/text-to-speech/{voice}"
-            headers = {
-                "Accept": "audio/mpeg",
-                "Content-Type": "application/json",
-                "xi-api-key": self.api_key
-            }
-            data = {
-                "text": text,
-                "model_id": self.model,
-                "voice_settings": {
-                    "stability": 0.7,
-                    "similarity_boost": 0.8,
-                    "style": 0.5,
-                    "use_speaker_boost": True
-                }
-            }
-            response = requests.post(url, json=data, headers=headers)
-            
-            if response.status_code == 200:
-                return response.content
-            return None
-        except Exception as e:
-            return None
+    st.info(f"""
+    **Current Workshop:**
+    {st.session_state.workshop_topic}
     
-    def get_voices(self):
-        if not self.api_key:
-            return []
-            
-        try:
-            url = "https://api.elevenlabs.io/v1/voices"
-            headers = {"xi-api-key": self.api_key}
-            response = requests.get(url, headers=headers)
-            
-            if response.status_code == 200:
-                return response.json().get("voices", [])
-            return []
-        except Exception as e:
-            return []
-            
+    **Premium Features:**
+    - AI-generated voiceovers
+    - Professional slide designs
+    - Fortune 500 case studies
+    - Practical code labs
+    """)