Update app.py

app.py

@@ -1,11 +1,9 @@
-# app.py
 import os
 import time
 import json
 import re
 import streamlit as st
 import plotly.graph_objects as go
-import plotly.express as px
 from dotenv import load_dotenv
 from crewai import Agent, Crew, Process, Task
 
@@ -203,199 +201,6 @@ def update_progress(container, progress, message=""):
     """
     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"""
-    try:
-        # Handle CrewOutput object
-        if hasattr(raw_output, 'raw_output'):
-            raw_text = str(raw_output.raw_output)
-        else:
-            raw_text = str(raw_output)
-
-        # Try to find and parse JSON structure
-        json_pattern = r"\{[\s\S]*\}"
-        match = re.search(json_pattern, raw_text)
-        if match:
-            try:
-                return json.loads(match.group())
-            except:
-                pass
-
-        # If no JSON found, create structured format
-        return {
-            "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),
-            "metrics": {
-                "market_size_data": [],
-                "growth_rates": [],
-                "market_shares": []
-            }
-        }
-    except Exception as e:
-        st.error(f"Error formatting output: {str(e)}")
-        return {
-            "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": [],
-            "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|$)"
-    match = re.search(pattern, text, re.DOTALL | re.IGNORECASE)
-    return match.group(1).strip() if match else ""
-
-def extract_sources(text):
-    """Extract sources from the text"""
-    sources = []
-    source_pattern = r"Source:.*?(?:\n|$)|\[.*?\]|\(https?://.*?\)"
-    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:
@@ -422,27 +227,14 @@ def run_market_research(topic: str, progress_container, chat_container):
         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()
-        
-        # Format and process the result
-        report_data = format_json_output(result)
-        
-        # Add visualizations
-        charts = generate_visualizations(report_data)
-        report_data['charts'] = charts
+        time.sleep(1)
         
         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 during research: {str(e)}")
-        return None
 
 def main():
     st.title("🤖 AI Market Research Generator")
@@ -478,97 +270,12 @@ def main():
                         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.")
+                            run_market_research(topic, progress_container, chat_container)
+                            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 AI Disclaimer
-            st.markdown("""
-                <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>
-            """, unsafe_allow_html=True)
-            
-            # Executive Summary Section
-            st.subheader("Executive Summary")
-            st.markdown("""
-                <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['exec_summary']['summary'],
-                report['exec_summary']['market_size'],
-                report['exec_summary']['growth_rate'],
-                report['exec_summary']['key_players']
-            ), unsafe_allow_html=True)
-            
-            # 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>
-            """, 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}_detailed_report.md",
-                    mime="text/markdown"
-                )
 
 if __name__ == "__main__":
-    main()
+    main()