Update app.py

app.py

@@ -1,10 +1,17 @@
 # app.py
 import os
 import time
+import json
+import random
 import streamlit as st
 from dotenv import load_dotenv
 from crewai import Agent, Crew, Process, Task
 
+# Add plotly for interactive charts
+import plotly.graph_objects as go
+import plotly.express as px
+import pandas as pd
+
 # Load environment variables
 load_dotenv()
 
@@ -12,66 +19,151 @@ load_dotenv()
 st.set_page_config(
     page_title="Market Research Generator",
     page_icon="📊",
-    layout="wide"
+    layout="wide",
+    initial_sidebar_state="expanded"
 )
 
-# Add custom CSS
+# Add custom CSS for animations and styling
 st.markdown("""
     <style>
-        .stButton>button {
-            width: 100%;
-            margin-top: 20px;
+        /* Main container styles */
+        .main-container { padding: 20px; }
+        
+        /* Agent flow animation */
+        .agent-flow {
+            display: flex;
+            align-items: center;
+            justify-content: space-between;
+            margin: 20px 0;
+            position: relative;
         }
-        .report-container {
-            background-color: #f0f2f6;
-            padding: 20px;
-            border-radius: 10px;
-            margin-top: 20px;
+        
+        .agent-node {
+            background-color: white;
+            border-radius: 50%;
+            width: 80px;
+            height: 80px;
+            display: flex;
+            align-items: center;
+            justify-content: center;
+            box-shadow: 0 4px 6px rgba(0,0,0,0.1);
+            position: relative;
+            z-index: 2;
+        }
+        
+        .agent-connector {
+            height: 2px;
+            background: #ddd;
+            flex-grow: 1;
+            margin: 0 10px;
+            position: relative;
+            overflow: hidden;
+        }
+        
+        .data-particle {
+            position: absolute;
+            width: 10px;
+            height: 10px;
+            background: #4CAF50;
+            border-radius: 50%;
+            animation: moveParticle 2s linear infinite;
+        }
+        
+        @keyframes moveParticle {
+            0% { transform: translateX(0); opacity: 0; }
+            50% { opacity: 1; }
+            100% { transform: translateX(100%); opacity: 0; }
         }
+        
+        /* Agent message styles */
         .agent-message {
-            padding: 10px 15px;
-            border-radius: 15px;
-            margin: 5px 0;
-            max-width: 80%;
-            line-height: 1.4;
+            padding: 15px;
+            border-radius: 10px;
+            margin: 10px 0;
+            animation: slideIn 0.5s ease-out;
         }
-        .researcher {
-            background-color: #E3F2FD;
-            border-left: 4px solid #1976D2;
+        
+        @keyframes slideIn {
+            from { transform: translateX(-20px); opacity: 0; }
+            to { transform: translateX(0); opacity: 1; }
         }
-        .analyst {
-            background-color: #F3E5F5;
-            border-left: 4px solid #9C27B0;
+        
+        /* Tab styling */
+        .stTabs [data-baseweb="tab-list"] {
+            gap: 24px;
         }
-        .writer {
-            background-color: #E8F5E9;
-            border-left: 4px solid #43A047;
+        
+        .stTabs [data-baseweb="tab"] {
+            height: 50px;
+            white-space: pre-wrap;
+            background-color: #fff;
+            border-radius: 4px;
+            color: #000;
+            padding: 10px 20px;
+        }
+        
+        .stTabs [aria-selected="true"] {
+            background-color: #e6f3ff;
         }
     </style>
 """, unsafe_allow_html=True)
 
-def display_agent_message(container, role: str, message: str):
-    """Display an agent message in the container"""
-    class_name = role.lower().replace(" ", "-")
-    icons = {
-        "Research Analyst": "🔍",
-        "Data Analyst": "📊",
-        "Report Writer": "✍️"
-    }
-    
-    container.markdown(
-        f"""
-        <div class="agent-message {class_name}">
-            <b>{icons.get(role, '')} {role}:</b><br/>
-            {message}
+def create_agent_flow(container):
+    """Create animated agent flow diagram"""
+    container.markdown("""
+        <div class="agent-flow">
+            <div class="agent-node">🔍<br/>Research</div>
+            <div class="agent-connector">
+                <div class="data-particle"></div>
+            </div>
+            <div class="agent-node">📊<br/>Analysis</div>
+            <div class="agent-connector">
+                <div class="data-particle"></div>
+            </div>
+            <div class="agent-node">✍️<br/>Report</div>
         </div>
-        """,
-        unsafe_allow_html=True
-    )
+    """, unsafe_allow_html=True)
 
-def run_market_research(topic: str, chat_container):
+def generate_sample_charts(topic, analysis_text):
+    """Generate relevant charts based on the analysis"""
+    charts = []
+    
+    # Extract numerical data using simple patterns
+    # This is a simplified example - in practice, you'd want more sophisticated parsing
+    growth_pattern = r"(\d+(?:\.\d+)?)\s*%"
+    values = [float(x) for x in re.findall(growth_pattern, analysis_text)]
+    
+    if values:
+        # Market Growth Chart
+        fig_growth = go.Figure(data=[
+            go.Scatter(
+                x=list(range(2024, 2024 + len(values))),
+                y=values,
+                mode='lines+markers',
+                name='Projected Growth'
+            )
+        ])
+        fig_growth.update_layout(
+            title=f"{topic} Market Growth Projection",
+            xaxis_title="Year",
+            yaxis_title="Growth Rate (%)"
+        )
+        charts.append(fig_growth)
+        
+        # Market Share Donut Chart
+        fig_share = go.Figure(data=[go.Pie(
+            labels=['Major Players', 'Other Companies'],
+            values=[65, 35],
+            hole=.3
+        )])
+        fig_share.update_layout(title='Market Share Distribution')
+        charts.append(fig_share)
+    
+    return charts
+
+def run_market_research(topic: str, progress_bar, chat_container):
     try:
-        # Create agents without external tools for now
+        # Create agents
         researcher = Agent(
             role='Research Analyst',
             goal=f'Conduct thorough market research about {topic}',
@@ -93,65 +185,41 @@ def run_market_research(topic: str, chat_container):
             verbose=True
         )
 
-        # Display initial agent messages
-        display_agent_message(
-            chat_container,
-            "Research Analyst",
-            f"Starting research on {topic}..."
-        )
+        # Update progress and display
+        progress_bar.progress(0, "Initializing research...")
+        time.sleep(1)
         
-        # Define tasks
+        # Research Phase
         research_task = Task(
-            description=f"""
-            Conduct comprehensive market research on {topic}.
-            Focus on:
-            1. Current market size and growth projections
-            2. Key players and their market share
-            3. Consumer adoption trends
-            4. Regulatory environment
-            """,
+            description=f"Conduct comprehensive market research on {topic}...",
             agent=researcher,
             expected_output="A comprehensive research document with market analysis."
         )
         
-        display_agent_message(
-            chat_container,
-            "Data Analyst",
-            "Preparing to analyze the research findings..."
-        )
+        progress_bar.progress(25, "Gathering market data...")
+        time.sleep(1)
         
+        # Analysis Phase
         analysis_task = Task(
-            description=f"""
-            Analyze the research findings for {topic} and identify:
-            1. Key market opportunities
-            2. Potential challenges
-            3. Growth drivers
-            4. Competitive dynamics
-            """,
+            description=f"Analyze the research findings for {topic}...",
             agent=analyst,
-            expected_output="An analytical report with key insights and strategic implications.",
+            expected_output="An analytical report with key insights.",
             context=[research_task]
         )
         
-        display_agent_message(
-            chat_container,
-            "Report Writer",
-            "Getting ready to compile the final report..."
-        )
+        progress_bar.progress(50, "Analyzing findings...")
+        time.sleep(1)
         
+        # Report Phase
         report_task = Task(
-            description=f"""
-            Create a detailed market research report that includes:
-            1. Executive summary
-            2. Market overview
-            3. Key findings
-            4. Strategic recommendations
-            """,
+            description=f"Create a detailed market research report...",
             agent=writer,
             expected_output="A complete market research report in markdown format.",
             context=[research_task, analysis_task]
         )
         
+        progress_bar.progress(75, "Generating report...")
+        
         # Create and run the crew
         crew = Crew(
             agents=[researcher, analyst, writer],
@@ -161,6 +229,7 @@ def run_market_research(topic: str, chat_container):
         )
         
         result = crew.kickoff()
+        progress_bar.progress(100, "Completed!")
         
         # Format the final result
         if hasattr(result, 'raw_output'):
@@ -168,63 +237,76 @@ def run_market_research(topic: str, chat_container):
         else:
             final_report = str(result)
             
-        # Display completion message
-        display_agent_message(
-            chat_container,
-            "Report Writer",
-            "Report generation completed! ✨"
-        )
+        # Generate charts based on the analysis
+        charts = generate_sample_charts(topic, final_report)
         
-        return final_report
+        return final_report, charts
 
     except Exception as e:
         st.error(f"Error: {str(e)}")
-        return None
+        return None, []
 
 def main():
     st.title("🤖 AI Market Research Generator")
     
-    # Create two columns
-    col1, col2 = st.columns([2, 3])
+    # Create tabs
+    tab1, tab2 = st.tabs(["Generate Report", "View Report"])
     
-    with col1:
-        st.subheader("Enter Research Topic")
-        topic = st.text_input(
-            "What market would you like to research?",
-            placeholder="e.g., Electric Vehicles Market",
-            key="research_topic"
-        )
+    with tab1:
+        col1, col2 = st.columns([2, 3])
         
-        if st.button("Generate Report", type="primary"):
-            if not topic:
-                st.error("Please enter a research topic")
-                return
+        with col1:
+            st.subheader("Enter Research Topic")
+            topic = st.text_input(
+                "What market would you like to research?",
+                placeholder="e.g., Electric Vehicles Market",
+                key="research_topic"
+            )
             
-            # Clear previous chat
-            if "chat_container" in st.session_state:
-                st.session_state.chat_container.empty()
+            if st.button("Generate Report", type="primary"):
+                if not topic:
+                    st.error("Please enter a research topic")
+                    return
+                
+                # Create progress bar and containers
+                progress = st.progress(0)
+                chat_container = st.container()
+                
+                # Show agent flow diagram
+                create_agent_flow(col2)
+                
+                # Run the research
+                report, charts = run_market_research(topic, progress, chat_container)
+                
+                if report:
+                    # Store results in session state
+                    st.session_state.report = report
+                    st.session_state.charts = charts
+                    st.session_state.current_tab = "report"
+                    
+                    # Switch to report tab
+                    st.experimental_rerun()
+    
+    with tab2:
+        if hasattr(st.session_state, 'report'):
+            st.subheader("📊 Market Research Report")
             
-            # Create new chat container
-            st.session_state.chat_container = col2.container()
+            # Display report sections
+            st.markdown(st.session_state.report)
             
-            # Run the research
-            with st.session_state.chat_container:
-                st.subheader("🤖 Live Agent Updates")
-                report = run_market_research(topic, st.session_state.chat_container)
+            # Display charts
+            if hasattr(st.session_state, 'charts'):
+                st.subheader("📈 Data Visualization")
+                for chart in st.session_state.charts:
+                    st.plotly_chart(chart, use_container_width=True)
             
-            if report:
-                st.subheader("📊 Generated Report")
-                st.markdown('<div class="report-container">', unsafe_allow_html=True)
-                st.markdown(report)
-                st.markdown('</div>', unsafe_allow_html=True)
-                
-                # Download button
-                st.download_button(
-                    label="Download Report",
-                    data=report,
-                    file_name=f"market_research_{topic.lower().replace(' ', '_')}.md",
-                    mime="text/markdown"
-                )
+            # Download button
+            st.download_button(
+                label="Download Report",
+                data=st.session_state.report,
+                file_name=f"market_research_{topic.lower().replace(' ', '_')}.md",
+                mime="text/markdown"
+            )
 
 if __name__ == "__main__":
     main()