Update app.py

app.py

@@ -1,14 +1,13 @@
-
+# app.py
 import os
 import time
 import json
-import random
 import re
-
-import plotly.graph_objects as go
 import streamlit as st
-from crewai import Agent, Crew, Process, Task
+import plotly.graph_objects as go
+import plotly.express as px
 from dotenv import load_dotenv
+from crewai import Agent, Crew, Process, Task
 
 # Load environment variables
 load_dotenv()
@@ -21,100 +20,76 @@ st.set_page_config(
     initial_sidebar_state="expanded"
 )
 
-# Enhanced CSS with more animations
+# Add all CSS styles
 st.markdown("""
     <style>
-        /* Animated background */
-        .stApp {
-            background: linear-gradient(135deg, #f5f7fa 0%, #e4e7eb 100%);
-        }
-        
-        /* Agent Chat Containers */
-        .chat-window {
-            height: 400px;
-            overflow-y: auto;
+        /* Agent Team Section */
+        .agent-team {
+            display: flex;
+            justify-content: space-around;
+            margin-bottom: 20px;
             padding: 20px;
             background: rgba(255, 255, 255, 0.9);
             border-radius: 15px;
-            box-shadow: 0 8px 32px rgba(31, 38, 135, 0.15);
-            margin: 20px 0;
-            border: 1px solid rgba(255, 255, 255, 0.18);
+            box-shadow: 0 4px 15px rgba(0, 0, 0, 0.1);
         }
         
-        .agent-message {
-            display: flex;
-            align-items: flex-start;
-            margin: 15px 0;
-            animation: messageSlide 0.5s ease forwards;
-            opacity: 0;
-            transform: translateX(-20px);
+        .agent-card {
+            text-align: center;
+            padding: 15px;
+            border-radius: 10px;
+            transition: all 0.3s ease;
         }
         
-        @keyframes messageSlide {
-            to {
-                opacity: 1;
-                transform: translateX(0);
-            }
+        .agent-card.active {
+            transform: scale(1.05);
+            box-shadow: 0 4px 20px rgba(0, 0, 0, 0.15);
         }
         
         .agent-avatar {
-            width: 45px;
-            height: 45px;
+            width: 60px;
+            height: 60px;
             border-radius: 50%;
+            margin: 0 auto 10px;
             display: flex;
             align-items: center;
             justify-content: center;
-            font-size: 24px;
-            margin-right: 15px;
-            box-shadow: 0 4px 12px rgba(0, 0, 0, 0.1);
-            animation: avatarPop 0.3s ease forwards;
-        }
-        
-        @keyframes avatarPop {
-            0% { transform: scale(0); }
-            50% { transform: scale(1.2); }
-            100% { transform: scale(1); }
-        }
-        
-        .message-bubble {
+            font-size: 30px;
             background: white;
-            padding: 12px 20px;
-            border-radius: 18px;
-            box-shadow: 0 2px 8px rgba(0, 0, 0, 0.08);
-            max-width: 80%;
-            position: relative;
-            animation: bubbleFade 0.3s ease forwards;
+            box-shadow: 0 4px 12px rgba(0, 0, 0, 0.1);
         }
         
-        @keyframes bubbleFade {
-            from { opacity: 0; transform: scale(0.9); }
-            to { opacity: 1; transform: scale(1); }
+        /* Chat Messages */
+        .chat-container {
+            height: 400px;
+            overflow-y: auto;
+            padding: 20px;
+            background: rgba(255, 255, 255, 0.9);
+            border-radius: 15px;
+            margin: 20px 0;
         }
         
-        /* Thinking animation */
-        .thinking-dots {
-            display: inline-flex;
-            gap: 4px;
-            margin-left: 8px;
+        .chat-message {
+            display: flex;
+            margin: 15px 0;
+            opacity: 0;
+            animation: fadeIn 0.5s forwards;
         }
         
-        .dot {
-            width: 8px;
-            height: 8px;
-            background: #4CAF50;
-            border-radius: 50%;
-            animation: dotPulse 1.5s infinite;
+        @keyframes fadeIn {
+            to { opacity: 1; }
         }
         
-        .dot:nth-child(2) { animation-delay: 0.2s; }
-        .dot:nth-child(3) { animation-delay: 0.4s; }
-        
-        @keyframes dotPulse {
-            0%, 100% { transform: scale(0.7); opacity: 0.5; }
-            50% { transform: scale(1); opacity: 1; }
+        .message-content {
+            background: white;
+            padding: 15px;
+            border-radius: 15px;
+            margin-left: 15px;
+            box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
+            max-width: 80%;
         }
         
-        /* Progress bar animation */
+        /* Progress Bar */
         .progress-container {
             width: 100%;
             height: 8px;
@@ -128,65 +103,193 @@ st.markdown("""
             height: 100%;
             background: linear-gradient(90deg, #4CAF50, #81C784);
             transition: width 0.5s ease;
-            position: relative;
-            overflow: hidden;
-        }
-        
-        .progress-bar::after {
-            content: '';
-            position: absolute;
-            top: 0;
-            left: 0;
-            width: 100%;
-            height: 100%;
-            background: linear-gradient(
-                90deg,
-                transparent,
-                rgba(255, 255, 255,   
- 0.4),
-                transparent   
-
-            );
-            animation: shimmer 2s infinite;
         }
         
-        @keyframes shimmer {
-            0% { transform: translateX(-100%); }
-            100% { transform: translateX(100%); }
+        /* Report Sections */
+        .report-header {
+            background: #f8f9fa;
+            padding: 15px;
+            border-radius: 10px;
+            margin-bottom: 20px;
+            border-left: 4px solid #ff4444;
         }
         
-        /* Status badges */
-        .status-badge {
-            display: inline-flex;
-            align-items: center;
-            padding: 6px 12px;
-            border-radius: 12px;
-            font-size: 14px;
-            font-weight: 500;
-            margin: 4px;
-            animation: badgeFade 0.3s ease forwards;
-        }
-        
-        @keyframes badgeFade {
-            from { opacity: 0; transform: translateY(-10px); }
-            to { opacity: 1; transform: translateY(0); }
+        .exec-summary {
+            background: white;
+            padding: 25px;
+            border-radius: 15px;
+            margin-bottom: 30px;
+            box-shadow: 0 4px 15px rgba(0, 0, 0, 0.1);
         }
         
-        /* Agent-specific styles */
-        .researcher {
-            background: linear-gradient(135deg, #E3F2FD 0%, #BBDEFB 100%);
+        .key-findings {
+            display: grid;
+            grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));
+            gap: 20px;
+            margin: 20px 0;
         }
         
-        .analyst {
-            background: linear-gradient(135deg, #F3E5F5 0%, #E1BEE7 100%);
+        .finding-card {
+            background: white;
+            padding: 20px;
+            border-radius: 10px;
+            box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
         }
         
-        .writer {
-            background: linear-gradient(135deg, #E8F5E9 0%, #C8E6C9 100%);
+        .detailed-section {
+            background: white;
+            padding: 30px;
+            border-radius: 15px;
+            margin: 20px 0;
+            box-shadow: 0 4px 15px rgba(0, 0, 0, 0.1);
         }
     </style>
 """, unsafe_allow_html=True)
 
+def display_agent_team(container, active_agent=None):
+    """Display the team of agents with active state"""
+    agents = [
+        {"role": "Research Analyst", "icon": "🔍", "color": "#E3F2FD"},
+        {"role": "Data Analyst", "icon": "📊", "color": "#F3E5F5"},
+        {"role": "Report Writer", "icon": "✍️", "color": "#E8F5E9"}
+    ]
+    
+    html = '<div class="agent-team">'
+    for agent in agents:
+        active_class = "active" if agent["role"] == active_agent else ""
+        html += f"""
+            <div class="agent-card {active_class}" style="background: {agent['color']}">
+                <div class="agent-avatar">{agent['icon']}</div>
+                <div class="agent-role">{agent['role']}</div>
+                <div class="agent-status">
+                    {"Working..." if agent["role"] == active_agent else "Standby"}
+                </div>
+            </div>
+        """
+    html += '</div>'
+    
+    container.markdown(html, unsafe_allow_html=True)
+
+def display_agent_message(container, agent_type: str, message: str):
+    """Display an agent message with improved styling"""
+    icons = {"researcher": "🔍", "analyst": "📊", "writer": "✍️"}
+    colors = {
+        "researcher": "#E3F2FD",
+        "analyst": "#F3E5F5",
+        "writer": "#E8F5E9"
+    }
+    
+    html = f"""
+        <div class="chat-message">
+            <div class="agent-avatar" style="background: {colors.get(agent_type, '#fff')}">
+                {icons.get(agent_type, "👤")}
+            </div>
+            <div class="message-content">
+                <div>{message}</div>
+            </div>
+        </div>
+    """
+    container.markdown(html, unsafe_allow_html=True)
+
+def update_progress(container, progress, message=""):
+    """Update progress bar with animation"""
+    progress_html = f"""
+        <div class="progress-container">
+            <div class="progress-bar" style="width: {progress}%"></div>
+        </div>
+        <div style="text-align: center; color: #666;">
+            {message}
+        </div>
+    """
+    container.markdown(progress_html, unsafe_allow_html=True)
+
+def create_research_crew(topic: str):
+    """Create the research crew with enhanced prompts"""
+    researcher = Agent(
+        role='Research Analyst',
+        goal=f'Conduct comprehensive market research about {topic} with detailed metrics and verifiable sources',
+        backstory="You are an experienced market research analyst who focuses on gathering concrete data points and always verifies sources.",
+        verbose=True
+    )
+    
+    analyst = Agent(
+        role='Data Analyst',
+        goal='Transform research data into actionable insights with visualization-ready metrics',
+        backstory="You are a skilled data analyst who excels at interpreting market research and creating data-driven insights.",
+        verbose=True
+    )
+    
+    writer = Agent(
+        role='Report Writer',
+        goal='Create professional market research reports with executive summary and detailed analysis',
+        backstory="You are an expert business writer who specializes in creating clear, comprehensive market research reports.",
+        verbose=True
+    )
+
+    research_task = Task(
+        description=f"""
+        Conduct extensive market research on {topic} with:
+        1. Market Overview (market size, growth rates, projections)
+        2. Competitive Analysis (market shares, positioning)
+        3. Market Dynamics (drivers, challenges, trends)
+        
+        Provide specific numerical values and sources.
+        Format data for visualization.
+        """,
+        agent=researcher,
+        expected_output="Comprehensive research data with specific metrics and sources"
+    )
+
+    analysis_task = Task(
+        description=f"""
+        Analyze the findings and provide:
+        1. Growth projections and trends (5 years)
+        2. Market share analysis
+        3. Competitive landscape
+        4. Strategic recommendations
+        
+        Include specific numbers and percentages.
+        """,
+        agent=analyst,
+        expected_output="Detailed analysis with visualization-ready metrics",
+        context=[research_task]
+    )
+
+    report_task = Task(
+        description=f"""
+        Create a professional report with:
+        1. Executive Summary (2-3 pages)
+        2. Detailed Report (10+ pages)
+        3. Sources and Citations
+        
+        Format as JSON:
+        {{
+            "exec_summary": {{
+                "summary": "text",
+                "market_size": "data",
+                "growth_rate": "data",
+                "key_players": "data"
+            }},
+            "detailed_report": "text",
+            "sources": ["source1", "source2"],
+            "metrics": {{
+                "market_size_data": [],
+                "growth_rates": [],
+                "market_shares": []
+            }}
+        }}
+        """,
+        agent=writer,
+        expected_output="JSON containing executive summary and detailed report",
+        context=[research_task, analysis_task]
+    )
+
+    return Crew(
+        agents=[researcher, analyst, writer],
+        tasks=[research_task, analysis_task, report_task],
+        verbose=True,
+        process=Process.sequential
+    )
 
 def format_json_output(raw_output):
     """Format CrewOutput or raw string into proper JSON structure"""
@@ -203,199 +306,143 @@ def format_json_output(raw_output):
         if match:
             try:
                 return json.loads(match.group())
-            except json.JSONDecodeError:
-                pass  # Or handle the error as needed
+            except:
+                pass
 
         # If no JSON found, create structured format
         return {
-            "exec_summary": extract_section(raw_text, "Executive Summary"),
+            "exec_summary": {
+                "summary": extract_section(raw_text, "Executive Summary"),
+                "market_size": extract_section(raw_text, "Market Size"),
+                "growth_rate": extract_section(raw_text, "Growth Rate"),
+                "key_players": extract_section(raw_text, "Key Players")
+            },
             "detailed_report": raw_text,
-            "sources": extract_sources(raw_text)
+            "sources": extract_sources(raw_text),
+            "metrics": {
+                "market_size_data": [],
+                "growth_rates": [],
+                "market_shares": []
+            }
         }
-
     except Exception as e:
         st.error(f"Error formatting output: {str(e)}")
         return {
-            "exec_summary": "Error formatting report",
+            "exec_summary": {
+                "summary": "Error formatting report",
+                "market_size": "N/A",
+                "growth_rate": "N/A",
+                "key_players": "N/A"
+            },
             "detailed_report": raw_text if 'raw_text' in locals() else str(raw_output),
-            "sources": []
+            "sources": [],
+            "metrics": {
+                "market_size_data": [],
+                "growth_rates": [],
+                "market_shares": []
+            }
         }
 
+def extract_section(text, section_name):
+    """Extract a section from the text"""
+    pattern = f"{section_name}.*?\n(.*?)(?=\n\n|$)"
+    match = re.search(pattern, text, re.DOTALL | re.IGNORECASE)
+    return match.group(1).strip() if match else ""
 
-def display_thinking_animation():
-    """Display thinking animation dots"""
-    return """
-        <div class="thinking-dots">
-            <div class="dot"></div>
-            <div class="dot"></div>
-            <div class="dot"></div>
-        </div>
-    """
-
-
-def display_agent_message(container, agent_type: str, message: str, thinking: bool = False):
-    """Display an animated agent message"""
-    icons = {
-        "researcher": "🔍",
-        "analyst": "📊",
-        "writer": "✍️"
-    }
-
-    message_html = f"""
-        <div class="agent-message">
-            <div class="agent-avatar {agent_type}">
-                {icons.get(agent_type, "👤")}
-            </div>
-            <div class="message-bubble">
-                {message}
-                {display_thinking_animation() if thinking else ""}
-            </div>
-        </div>
-    """
-    container.markdown(message_html, unsafe_allow_html=True)
-
-
-def update_progress(container, progress, message=""):
-    """Update progress bar with animation"""
-    progress_html = f"""
-        <div class="progress-container">
-            <div class="progress-bar" style="width: {progress}%"></div>
-        </div>
-        <div class="status-badge">
-            {message}
-        </div>
-    """
-    container.markdown(progress_html, unsafe_allow_html=True)
+def extract_sources(text):
+    """Extract sources from the text"""
+    sources = []
+    source_pattern = r"Source:.*?(?:\n|$)|\[.*?\]|\(https?://.*?\)"
+    matches = re.finditer(source_pattern, text, re.MULTILINE)
+    return [match.group().strip() for match in matches]
 
+def generate_visualizations(data):
+    """Generate visualizations based on the report data"""
+    charts = []
+    
+    # Market Size Chart
+    if data['metrics']['market_size_data']:
+        fig = go.Figure(data=[
+            go.Bar(
+                x=['Current', 'Projected'],
+                y=data['metrics']['market_size_data'],
+                text=data['metrics']['market_size_data'],
+                textposition='auto',
+            )
+        ])
+        fig.update_layout(title='Market Size Projection')
+        charts.append(fig)
+    
+    # Growth Rate Chart
+    if data['metrics']['growth_rates']:
+        fig = go.Figure(data=[
+            go.Line(
+                x=list(range(len(data['metrics']['growth_rates']))),
+                y=data['metrics']['growth_rates'],
+                mode='lines+markers'
+            )
+        ])
+        fig.update_layout(title='Growth Rate Trends')
+        charts.append(fig)
+    
+    # Market Share Chart
+    if data['metrics']['market_shares']:
+        fig = go.Figure(data=[go.Pie(
+            labels=list(data['metrics']['market_shares'].keys()),
+            values=list(data['metrics']['market_shares'].values())
+        )])
+        fig.update_layout(title='Market Share Distribution')
+        charts.append(fig)
+    
+    return charts
 
 def run_market_research(topic: str, progress_container, chat_container):
+    """Run the market research process"""
     try:
-        researcher = Agent(
-            role='Research Analyst',
-            goal=f'Conduct thorough market research about {topic} with verifiable sources',
-            backstory='You are an experienced market research analyst with expertise in data analysis and trend identification.',
-            verbose=True
-        )
-
-        analyst = Agent(
-            role='Data Analyst',
-            goal='Create data-driven insights with specific metrics',
-            backstory='You are a skilled data analyst who specializes in turning research into actionable insights.',
-            verbose=True
-        )
-
-        writer = Agent(
-            role='Report Writer',
-            goal='Create both executive summary and detailed reports with citations',
-            backstory='You are a professional writer who creates clear, structured reports.',
-            verbose=True
-        )
-
+        # Initialize with team display
+        display_agent_team(progress_container, None)
+        update_progress(progress_container, 0, "Initializing research team...")
+        
         # Research Phase
-        display_agent_message(chat_container, "researcher",
-                              f"👋 Hello! I'll be researching the {topic} market thoroughly.", False)
+        display_agent_team(progress_container, "Research Analyst")
+        display_agent_message(chat_container, "researcher", 
+            f"Starting comprehensive research on {topic}...")
+        update_progress(progress_container, 25, "Gathering market data...")
         time.sleep(1)
-
-        update_progress(progress_container, 20, "🔍 Gathering market data...")
-        display_agent_message(chat_container, "researcher", "Processing market information...", True)
-        time.sleep(1)
-
-        research_task = Task(
-            description=f"""
-            Research {topic} with focus on:
-            1. Market size and growth projections (with specific numbers)
-            2. Key players and market share percentages
-            3. Competitive analysis
-            4. Future trends
-            5. Include verifiable sources
-
-            Format the output as clear sections with numerical data points.
-            """,
-            agent=researcher,
-            expected_output="Detailed market research with data points and sources"
-        )
-
+        
         # Analysis Phase
-        update_progress(progress_container, 40, "📊 Analyzing findings...")
-        display_agent_message(chat_container, "analyst",
-                              "I've received the research data. Beginning analysis...", False)
+        display_agent_team(progress_container, "Data Analyst")
+        display_agent_message(chat_container, "analyst", 
+            "Processing research data and identifying key insights...")
+        update_progress(progress_container, 50, "Analyzing findings...")
         time.sleep(1)
-
-        analysis_task = Task(
-            description=f"""
-            Analyze the research findings and provide:
-            1. Growth projections and trends
-            2. Market share analysis
-            3. Competitive landscape
-            4. Key opportunities and challenges
-
-            Include specific metrics and percentages.
-            """,
-            agent=analyst,
-            expected_output="Market analysis with specific metrics",
-            context=[research_task]
-        )
-
+        
         # Report Phase
-        update_progress(progress_container, 70, "✍️ Generating report...")
-        display_agent_message(chat_container, "writer",
-                              "Converting analysis into comprehensive report...", False)
-        time.sleep(1)
-
-        report_task = Task(
-            description=f"""
-            Create a market research report with:
-            1. Executive Summary (2-3 paragraphs)
-            2. Detailed Report (full analysis)
-            3. Sources and Citations
-
-            Format as a JSON with:
-            {{
-                "exec_summary": "summary text",
-                "detailed_report": "detailed text",
-                "sources": ["source1", "source2"]
-            }}
-            """,
-            agent=writer,
-            expected_output="JSON formatted report with summary and details",
-            context=[research_task, analysis_task]
-        )
-
-        crew = Crew(
-            agents=[researcher, analyst, writer],
-            tasks=[research_task, analysis_task, report_task],
-            verbose=True,
-            process=Process.sequential
-        )
-
+        display_agent_team(progress_container, "Report Writer")
+        display_agent_message(chat_container, "writer", 
+            "Compiling final report with executive summary and detailed analysis...")
+        update_progress(progress_container, 75, "Generating report...")
+        
+        # Create and run the crew
+        crew = create_research_crew(topic)
         result = crew.kickoff()
-
-        # Update final progress
-        update_progress(progress_container, 100, "✨ Report completed!")
-        display_agent_message(chat_container, "writer",
-                              "Report generation completed! You can now view the full report.", False)
-
-        return format_json_output(result)
+        
+        # Format and process the result
+        report_data = format_json_output(result)
+        
+        # Add visualizations
+        charts = generate_visualizations(report_data)
+        report_data['charts'] = charts
+        
+        update_progress(progress_container, 100, "Report completed!")
+        display_agent_message(chat_container, "writer", 
+            "✨ Report generation completed! You can now view the full report.")
+        
+        return report_data
 
     except Exception as e:
-        st.error(f"Error generating report: {str(e)}")
-        return {
-            "exec_summary": "Error generating report",
-            "detailed_report": "",
-            "sources": []
-        }
-
-def extract_section(text, section_name):
-    """Extract a section from the text"""
-    pattern = rf"{section_name}.*?\n(.*?)(?=\n\n|<span class=\"math-inline\">)"
-    match = re.search(pattern, text, re.DOTALL | re.IGNORECASE)
-    return match.group(1).strip() if match else ""
-
-def extract_sources(text):
-    """Extract sources from the text"""
-    source_pattern = r"Source:.*?(?:\n|<span class=\"math-inline\">)|\[.*?\]|\(https?://.*?\)"
-    matches = re.finditer(source_pattern, text, re.MULTILINE)
-    return [match.group().strip() for match in matches]
+        st.error(f"Error during research: {str(e)}")
+        return None
 
 def main():
     st.title("🤖 AI Market Research Generator")
@@ -425,67 +472,101 @@ def main():
                         st.error("Please enter a research topic")
                     else:
                         st.session_state.generating = True
-                        st.rerun()
-        
-        # Only show chat window if generating
-        if st.session_state.generating:
-            with col2:
-                st.markdown('<div class="chat-window">', unsafe_allow_html=True)
-                chat_container = st.empty()
-                st.markdown('</div>', unsafe_allow_html=True)
-                
-                progress_container = st.container()
-                
-                try:
-                    result = run_market_research(topic, progress_container, chat_container)
-                    
-                    if result:
-                        st.session_state.current_report = result
-                        st.success("Report generated successfully! View it in the Reports tab.")
-                except Exception as e:
-                    st.error(f"Error generating report: {str(e)}")
-                finally:
-                    st.session_state.generating = False
-                    st.rerun()
+                        
+                        # Create containers for progress and chat
+                        progress_container = st.container()
+                        chat_container = st.container()
+                        
+                        try:
+                            result = run_market_research(topic, progress_container, chat_container)
+                            
+                            if result:
+                                st.session_state.current_report = result
+                                st.session_state.current_topic = topic
+                                st.success("Report generated successfully! View it in the Reports tab.")
+                        except Exception as e:
+                            st.error(f"Error generating report: {str(e)}")
+                        finally:
+                            st.session_state.generating = False
     
     with tab2:
         if hasattr(st.session_state, 'current_report'):
             report = st.session_state.current_report
+            topic = st.session_state.current_topic
             
-            # Display Executive Summary in a card
+            # Display AI Disclaimer
             st.markdown("""
-                <div style='background-color: white; padding: 20px; border-radius: 10px; margin: 10px 0;'>
-                    <h3>Executive Summary</h3>
-                    <p>{}</p>
+                <div class="report-header">
+                    <strong>⚠️ AI-Generated Report Disclaimer</strong>
+                    <p>This report was generated using AI agents for market research and analysis. 
+                    While we strive for accuracy, please review all content and verify critical information 
+                    independently. The analysis and recommendations provided should be used as a 
+                    supplementary resource rather than the sole basis for decision-making.</p>
                 </div>
-            """.format(report['exec_summary']), unsafe_allow_html=True)
+            """, unsafe_allow_html=True)
             
-            # Display Detailed Report in a card
+            # Executive Summary Section
+            st.subheader("Executive Summary")
             st.markdown("""
-                <div style='background-color: white; padding: 20px; border-radius: 10px; margin: 10px 0;'>
-                    <h3>Detailed Report</h3>
-                    <p>{}</p>
+                <div class="exec-summary">
+                    {}
+                    
+                    <div class="key-findings">
+                        <div class="finding-card">
+                            <h4>Market Size</h4>
+                            {}
+                        </div>
+                        <div class="finding-card">
+                            <h4>Growth Rate</h4>
+                            {}
+                        </div>
+                        <div class="finding-card">
+                            <h4>Key Players</h4>
+                            {}
+                        </div>
+                    </div>
                 </div>
-            """.format(report['detailed_report']), unsafe_allow_html=True)
+            """.format(
+                report['exec_summary']['summary'],
+                report['exec_summary']['market_size'],
+                report['exec_summary']['growth_rate'],
+                report['exec_summary']['key_players']
+            ), unsafe_allow_html=True)
             
-            # Display Sources in a card
-            st.markdown("""
-                <div style='background-color: white; padding: 20px; border-radius: 10px; margin: 10px 0;'>
-                    <h3>Sources</h3>
-                    <ul>
-                        {}
-                    </ul>
+            # Visualizations
+            if 'charts' in report and report['charts']:
+                st.subheader("Market Analysis Visualizations")
+                for chart in report['charts']:
+                    st.plotly_chart(chart, use_container_width=True)
+            
+            # Detailed Report Section
+            st.subheader("Detailed Report")
+            st.markdown(f"""
+                <div class="detailed-section">
+                    {report['detailed_report']}
                 </div>
-            """.format('\n'.join([f"<li>{source}</li>" for source in report['sources']])), 
-            unsafe_allow_html=True)
+            """, unsafe_allow_html=True)
+            
+            # Sources Section
+            if report['sources']:
+                st.subheader("Sources")
+                for source in report['sources']:
+                    st.markdown(f"- {source}")
             
             # Download buttons
             col1, col2 = st.columns(2)
             with col1:
+                st.download_button(
+                    "Download Executive Summary",
+                    data=report['exec_summary']['summary'],
+                    file_name=f"{topic}_executive_summary.md",
+                    mime="text/markdown"
+                )
+            with col2:
                 st.download_button(
                     "Download Full Report",
                     data=report['detailed_report'],
-                    file_name=f"{topic}_report.md",
+                    file_name=f"{topic}_detailed_report.md",
                     mime="text/markdown"
                 )