Update test.py

test.py

@@ -10,6 +10,7 @@ import tempfile
 import time
 import ast
 import logging
+import traceback
 
 # Setup logging
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
@@ -17,7 +18,7 @@ logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(
 # Title and Application Introduction
 st.title("Patent Strategy and Innovation Consultant")
 st.sidebar.write(
-    "This application uses AI to provide actionable insights and comprehensive analysis for patent-related strategies."
+    "This application provides actionable insights and comprehensive analysis for patent-related strategies."
 )
 
 # User Input Section
@@ -29,15 +30,13 @@ stakeholder = st.text_input("Enter Stakeholder", value="Patent Attorneys")
 llm = None
 
 # Model Selection
-model_choice = st.radio("Select LLM", ["GPT-4o", "llama-3.3-70b"], index=1, horizontal=True)
+model_choice = st.radio("Select LLM", ["GPT-4o", "llama-3.3-70b"], index=0, horizontal=True)
 
 
 # API Key Validation and LLM Initialization
 groq_api_key = os.getenv("GROQ_API_KEY")
 openai_api_key = os.getenv("OPENAI_API_KEY")
 
-#llm = ChatGroq(groq_api_key=os.getenv("GROQ_API_KEY"), model="groq/llama-3.3-70b-versatile")
-
 if model_choice == "llama-3.3-70b":
     if not groq_api_key:
         st.error("Groq API key is missing. Please set the GROQ_API_KEY environment variable.")
@@ -64,27 +63,148 @@ with st.sidebar.expander("Customize Agent Goals", expanded=False):
     if enable_customization:
         planner_goal = st.text_area(
             "Planner Goal",
-            value="Research trends in patent filings and technological innovation, identify key players, and provide strategic recommendations."
+            value=(
+                "Conduct in-depth, data-driven research on leading companies' recent patent filings, technological innovation, R&D investments,"
+                "strategic partnerships and market dynamics strictly within the {topic} sector." 
+                "Identify key players, emerging technologies, competitor strategies, and market gaps with factually accurate and verifiable data. "
+                "Develop a Competitor Benchmark Matrix highlighting leaders in material/structural/software innovations vs. integration techniques." 
+                "Summarize key market trends and shifts in competitive positioning with bullet-point insights."
+                "Strictly avoid hallucinated, fabricated, or speculative findings. "
+                "Develop a phased Patent Filing Roadmap targeting emerging technologies and high-growth regions tailored to the specific needs"
+                "and strategic goals of {stakeholder}. Conduct a Risk Assessment covering regulatory barriers, supply chain risks, and material"
+                "costs with mitigation strategies. Suggest Investment Opportunities by identifying startups or strategic partnerships in {topic}."
+                "Present findings using a Phased Patent Strategy Table (short-term, mid-term, long-term) and a Risk Matrix."
+                "Avoid unrelated or generic recommendations."
+            )
         )
         writer_goal = st.text_area(
             "Writer Goal",
-            value="Craft a professional insights document summarizing trends, strategies, and actionable outcomes for stakeholders."
+            value=(
+                "Develop a high-impact, professionally structured insights report that integrates verified research data and strategic analysis into the following sections:\n\n"
+                "1. Executive Summary: Provide a concise overview of key insights and strategic recommendations strictly aligned with {stakeholder}'s strategic objectives.\n"
+                "2. Market Trends & Competitive Landscape: Detailed profiles, benchmarking, and market entry insights.\n"
+                "3. Emerging Technologies: Spotlight key technologies, TRL classification, adoption timelines.\n"
+                "4. Untapped Innovation Hotspots: Highlight regions with potential, innovation clusters, and readiness analysis.\n"
+                "5. Strategic Opportunities & Actionable Recommendations: Patent filing roadmap, risk mitigation, partnerships, and differentiation.\n"
+                "6. Future Growth Projections: Market forecasts, technology adoption, scenario analysis.\n"
+                "7. Industry Risk & Compliance Analysis: Risk matrix and mitigation strategies.\n"
+                "8. Summary & Appendix: Bullet-point insights and supporting data.\n\n"
+
+                "Ensure all insights, emerging technologies, and identified innovation gaps are fact-based, verifiable, and directly relevant to the {topic}."
+                "Present findings with clarity through well-structured sections, bullet points, and tables. Explicitly avoid hallucinated, fabricated, or speculative content throughout the report." 
+
+            )
         )
         analyst_goal = st.text_area(
             "Analyst Goal",
             value=(
-                "Perform detailed statistical analysis of patent filings, growth trends, and innovation distribution. "
-                "Identify top assignees/companies in the transparent antenna industry. "
-                "Provide structured output in a list of dictionaries with 'Category' and 'Values' keys for clear data presentation."
+                "Perform precise, data-driven statistical analysis of patent filings, growth trends, and innovation distribution strictly within the {topic} sector, "
+                "specifically customized to the strategic needs of {stakeholder}. "
+                "Identify top regions, leading assignees/companies, and emerging technologies that are explicitly and directly relevant to {topic}. "
+                "Strictly avoid hallucinated, fabricated, or speculative statistical data and patent numbers in the analysis. "
+                "Conduct a thorough market gap analysis, identifying 4-5 highly actionable and verifiable innovation opportunities aligned with {topic}, "
+                "emphasizing sustainability, emerging technology integration, industry collaboration, and competitor positioning. "
+                "Evaluate competitor patent strategies with factual data to uncover untapped opportunities and competitive advantages. "
+                "All innovation hotspots and emerging technology suggestions must be strictly aligned with {topic} - no generic or unrelated recommendations are allowed. "
+                "Deliver highly actionable, data-driven insights to support strategic decision-making and long-term growth. "
+                "Present findings in a structured, well-organized format using 'Category' and 'Values' keys for easy data interpretation."
+
             )
         )
     else:
-        planner_goal = "Research trends in patent filings and technological innovation, identify key players, and provide strategic recommendations."
-        writer_goal = "Craft a professional insights document summarizing trends, strategies, and actionable outcomes for stakeholders."
+        #planner_goal = (
+         #   "Conduct comprehensive, data-driven research on patent filings, technological innovation, and market dynamics strictly within the {topic} sector." 
+         #   "Avoid unrelated or generic recommendations."
+         #   "Identify key players, emerging technologies, competitor strategies, and market gaps with factually accurate and verifiable data. "
+         #   "Strictly avoid hallucinated, fabricated, or speculative findings. "
+         #   "Develop a phased Patent Filing Roadmap targeting emerging technologies and high-growth regions tailored to the specific needs"
+         #   "and strategic goals of {stakeholder}. Conduct a Risk Assessment covering regulatory barriers, supply chain risks, and"
+         #   "material costs with mitigation strategies. Suggest Investment Opportunities by identifying startups or strategic partnerships in {topic}."
+         #   "Present findings using a Phased Patent Strategy Table (short-term, mid-term, long-term) and a Risk Matrix."
+        #)
+        planner_goal = (
+            "Conduct comprehensive, data-driven research on patent filings, technological innovations, and market dynamics strictly within the {topic} sector. "
+            "Deliver factually accurate and verifiable insights with no hallucinated, fabricated, or speculative findings. Avoid unrelated or generic recommendations. "
+            "Provide detailed outputs in the following structure:\n\n"
+
+            "1. Market Trends & Competitive Landscape:\n"
+            "- In-depth company profiles (recent patent filings, R&D investments, partnerships).\n"
+            "- Competitor Benchmarking (material innovations vs. integration techniques, etc.).\n"
+            "- Competitor Comparison Matrix (tabular comparison on innovation focus, market share, partnerships).\n"
+            "- Competitor Expansion Plans (predict market entries, M&A, product launches).\n\n"
+
+            "2. Emerging Technologies:\n"
+            "- Identify 4–5 key emerging technologies shaping the {topic} market.\n"
+            "- Classify technologies by Technology Readiness Level (TRL).\n"
+            "- Highlight disruptive technologies (e.g., metamaterials, quantum antennas).\n"
+            "- Analyze breakthroughs related to {topic} domain.\n"
+            "- Predict adoption timelines with Technology Adoption Curves.\n\n"
+
+            "3. Untapped Innovation Hotspots:\n"
+            "- Provide a Regional Patent Trends.\n"
+            "- Identify Innovation Clusters (universities, startups).\n"
+            "- Conduct Regulatory Landscape Analysis.\n"
+            "- Explore Application Expansion (non-traditional sectors).\n"
+            "- Evaluate Infrastructure Readiness (supply chains, logistics).\n\n"
+
+            "4. Strategic Opportunities & Actionable Recommendations:\n"
+            "- Develop a Phased Patent Strategy (short-term, mid-term, long-term).\n"
+            "- Conduct Risk Assessments (regulatory, supply chain, operational risks).\n"
+            "- Suggest Open Innovation Partnerships (universities, labs).\n"
+            "- Propose a Supply Chain Strategy (risk mitigation, diversification).\n"
+            "- Identify Investment Opportunities (startups, partnerships).\n"
+            "- Recommend Competitive Differentiation Strategies (blocking patents, cross-licensing).\n"
+            "- Market Entry Roadmap aligning patent filings with market strategies.\n\n"
+
+            "5. Future Growth Projections:\n"
+            "- Provide Market Size Forecasts (CAGR, revenue projections for 1–3 and 5–10 years).\n"
+            "- Analyze Demand Drivers and Barriers (tech adoption, regulatory hurdles, etc.).\n"
+            "- Conduct Scenario Analysis (best-case, worst-case, base-case).\n"
+            "- Predict Competitor Expansion Plans.\n"
+            "- Present Growth Projection Graphs and Forecast Summaries.\n\n"
+
+            "6. Industry Risk & Compliance Analysis:\n"
+            "- Identify Market, Operational, and Regulatory Risks.\n"
+            "- Develop Mitigation Strategies (compliance pathways, supply chain diversification).\n"
+            "- Provide a Regulatory Risk Matrix.\n\n"
+
+            "7. Summary & Appendix:\n"
+            "- Summarize key insights in bullet-point format.\n"
+            "- Include supplementary data, raw analysis, and research methodology."
+        )
+
+        
+        writer_goal = (
+            "Develop a high-impact, professionally structured insights report that integrates verified research data and strategic analysis into the following sections:\n\n"
+            "1. Executive Summary: Provide a concise overview of key insights and strategic recommendations strictly aligned with {stakeholder}'s strategic objectives.\n"
+            "2. Market Trends & Competitive Landscape: Detailed profiles, benchmarking, and market entry insights.\n"
+            "3. Emerging Technologies: Spotlight key technologies, TRL classification, adoption timelines.\n"
+            "4. Untapped Innovation Hotspots: Highlight regions with potential, innovation clusters, and readiness analysis.\n"
+            "5. Strategic Opportunities & Actionable Recommendations: Patent filing roadmap, risk mitigation, partnerships, and differentiation.\n"
+            "6. Future Growth Projections: Market forecasts, technology adoption, scenario analysis.\n"
+            "7. Industry Risk & Compliance Analysis: Risk matrix and mitigation strategies.\n"
+            "8. Summary & Appendix: Bullet-point insights and supporting data.\n\n"
+
+            "Ensure all insights, emerging technologies, and identified innovation gaps are fact-based, verifiable, and directly relevant to the {topic}."
+            "Present findings with clarity through well-structured sections, bullet points, and tables. Explicitly avoid hallucinated, fabricated, or speculative content throughout the report." 
+
+        )
+
+
         analyst_goal = (
-            "Perform detailed statistical analysis of patent filings, growth trends, and innovation distribution. "
-            "Identify top assignees/companies in the transparent antenna industry. "
-            "Provide structured output in a list of dictionaries with 'Category' and 'Values' keys for clear data presentation."
+            "Perform precise, data-driven statistical analysis of patent filings, growth trends, and innovation distribution strictly within the {topic} sector, "
+            "specifically customized to the strategic needs of {stakeholder}. "
+            "Identify top regions, leading assignees/companies, and emerging technologies that are explicitly and directly relevant to {topic}. "
+            "Identify 4-5 emerging technologies shaping the {topic} market with brief impact analyses."
+            "Highlight untapped markets and geographic regions with low patent activity but high growth potential."
+            "Provide Technology Spotlight Cards detailing each technology's name, description, development stage, and potential market impact."
+            "Strictly avoid hallucinated, fabricated, or speculative statistical data and patent numbers in the analysis. "
+            "Conduct a thorough market gap analysis, identifying 4-5 highly actionable and verifiable innovation opportunities aligned with {topic}, "
+            "emphasizing sustainability, emerging technology integration, industry collaboration, and competitor positioning. "
+            "Evaluate competitor patent strategies with factual data to uncover untapped opportunities and competitive advantages. "
+            "All innovation hotspots and emerging technology suggestions must be strictly aligned with {topic} - no generic or unrelated recommendations are allowed. "
+            "Deliver highly actionable, data-driven insights to support strategic decision-making and long-term growth. "
+            "Present findings in a structured, well-organized format using 'Category' and 'Values' keys for easy data interpretation."
         )
 
 # Agent Definitions
@@ -124,53 +244,52 @@ analyst = Agent(
 # Task Definitions
 plan = Task(
     description=(
-        "1. Research recent trends in {topic} patent filings and innovation.\n"
-        "2. Identify key players and emerging technologies.\n"
-        "3. Provide recommendations for stakeholders on strategic directions.\n"
-        "4. Identify key statistics such as top regions, top players, and hot areas of innovation.\n"
-        "5. Limit the output to 600 words."
+        "1. Conduct comprehensive, fact-based research on recent trends in {topic} patent filings and innovation.\n"
+        "2. Identify key players, emerging technologies, and market gaps that are strictly relevant to {topic}.\n"
+        "3. Ensure all findings—especially emerging technologies and innovation hotspots—are explicitly aligned with {topic}.\n"
+        "4. Avoid speculative, fabricated, or unrelated content entirely.\n"
+        "5. Provide actionable, data-backed strategic recommendations aligned with {stakeholder}'s goals.\n"
+        "6. Limit the output to 600 words."
     ),
-    expected_output="A research document with structured insights, strategic recommendations, and key statistics.",
+    expected_output="A fact-driven research document with strictly relevant insights, strategic recommendations, and key statistics.",
     agent=planner
 )
 
 write = Task(
     description=(
-        "1. Use the Planner's and Analyst's outputs to craft a professional patent insights document.\n"
-        "2. Include key findings, visual aids, and actionable strategies.\n"
-        "3. Suggest strategic directions and highlight untapped innovation areas.\n"
-        "4. Incorporate summarized tables for key statistics and example inventions.\n"
-        "5. Limit the document to 600 words."
+        "1. Use the Planner's and Analyst's strictly topic-aligned outputs to craft a professional patent insights document.\n"
+        "2. Include key findings, visual aids, and actionable strategies strictly related to {topic}.\n"
+        "3. Highlight strategic directions and strictly relevant innovation opportunities.\n"
+        "4. Incorporate well-structured tables for key statistics and example inventions without using any fabricated data or fake patent numbers.\n"
+        "5. Avoid any speculative, fabricated, or unrelated content.\n"
+        "6. Limit the document to 600 words."
     ),
-    expected_output="A polished, stakeholder-ready patent insights document with actionable recommendations.",
+    expected_output="A polished, stakeholder-ready patent insights report with actionable, strictly relevant recommendations.",
     agent=writer
 )
 
 analyse = Task(
     description=(
-        "1. Conduct a comprehensive statistical analysis of patent filing trends, innovation hot spots, and future growth projections in the transparent antenna industry.\n"
+        "1. Conduct a comprehensive statistical analysis of patent filing trends, innovation hot spots, and future growth projections in the {topic} sector.\n"
         "2. Identify and rank the top regions, leading assignees/companies driving innovation.\n"
         "3. Highlight regional innovation trends and the distribution of emerging technologies across different geographies.\n"
         "4. Provide actionable insights and strategic recommendations based on the data.\n"
-        "5. Deliver structured output in a list of dictionaries with 'Category' and 'Values' fields:\n"
-        "   - 'Values' can be:\n"
-        "     a) A dictionary with counts for quantitative data (e.g., {{'Region A': 120, 'Region B': 95}}),\n"
-        "     b) A list of key items (technologies, companies, inventors), or\n"
-        "     c) Descriptive text for qualitative insights.\n"
+        "5. Categorize outputs as either:\n"
+        "   - 'Data Insight' for visualizations and tables (quantitative data, trends, technologies).\n"
+        "   - 'Key Insight' for strategic recommendations and innovation opportunities.\n"
         "6. Example Output Format:\n"
         "[\n"
-        "  {{'Category': 'Top Regions', 'Values': {{'North America': 120, 'Europe': 95, 'Asia-Pacific': 85}}}},\n"
-        "  {{'Category': 'Top Assignees', 'Values': {{'Company A': 40, 'Company B': 35}}}},\n"
-        "  {{'Category': 'Emerging Technologies', 'Values': ['Graphene Antennas', '5G Integration']}},\n"
-        "  {{'Category': 'Strategic Insights', 'Values': 'Collaborations between automotive and material science industries are accelerating innovation.'}}\n"
+        "  {{'Category': 'Top Regions', 'Type': 'Data Insight', 'Values': {{'North America': 120, 'Europe': 95}},\n"
+        "  {{'Category': 'Emerging Technologies', 'Type': 'Data Insight', 'Values': ['Transparent Conductive Films']}},\n"
+        "  {{'Category': 'Strategic Insights', 'Type': 'Key Insight', 'Values': 'Collaborate with material science companies to develop advanced transparent antennas.'}},\n"
+        "  {{'Category': 'Innovation Gaps', 'Type': 'Key Insight', 'Values': 'Limited patents in self-healing transparent materials present a growth opportunity.'}}\n"
         "]\n"
-        "7. Ensure that the output is clean, well-structured, and formatted for use in visualizations and tables."
+        "7. Ensure all data is factually accurate, verifiable, and strictly aligned with {topic}."
     ),
-    expected_output="A structured, well-organized dataset with numeric, list-based, and descriptive insights for comprehensive visual and tabular reporting.",
+    expected_output="A structured dataset combining Data Insights for comprehensive visualizations and table reporting, and Key Insights for strategic actions.",
     agent=analyst
 )
 
-
 crew = Crew(
     agents=[planner, analyst, writer],
     tasks=[plan, analyse, write],
@@ -178,58 +297,90 @@ crew = Crew(
 )
 
 # PDF Report Generation
-def generate_pdf_report(result, charts=None, table_data=None, metadata=None):
+def generate_pdf_report(result, charts=None, table_data=None, metadata=None, key_insights=None):
     with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as temp_pdf:
         pdf = FPDF()
         pdf.add_page()
-        pdf.set_font("Arial", size=12)
+
+        # Add DejaVu fonts (regular and bold)
+        pdf.add_font('DejaVu', '', '/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf', uni=True)          
+        pdf.add_font('DejaVu', 'B', '/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf', uni=True)    
+
+        pdf.set_font("DejaVu", size=12)
         pdf.set_auto_page_break(auto=True, margin=15)
 
-        pdf.set_font("Arial", size=16, style="B")
+        # Title (Bold)
+        pdf.set_font("DejaVu", size=16, style="B")
         pdf.cell(200, 10, txt="Patent Strategy and Innovation Report", ln=True, align="C")
         pdf.ln(10)
 
+        # Metadata Section
         if metadata:
-            pdf.set_font("Arial", size=10)
+            pdf.set_font("DejaVu", size=10)
             for key, value in metadata.items():
                 pdf.cell(200, 10, txt=f"{key}: {value}", ln=True)
 
-        pdf.set_font("Arial", size=12)
+        # Report Content
+        pdf.set_font("DejaVu", size=12)
         pdf.multi_cell(0, 10, txt=result)
 
+        # Key Insights Section
+        if key_insights:
+            pdf.add_page()
+            pdf.set_font("DejaVu", size=14, style="B")
+            pdf.cell(200, 10, txt="Key Strategic Insights", ln=True)
+            pdf.ln(5)
+            pdf.set_font("DejaVu", size=12)
+            for insight in key_insights:
+                pdf.multi_cell(0, 10, txt=f"- {insight}")
+
+        # Insert Charts
         if charts:
             for chart_path in charts:
                 try:
                     pdf.add_page()
                     pdf.image(chart_path, x=10, y=20, w=180)
-                    logging.info(f"Successfully included chart: {chart_path}")
                 except Exception as e:
-                    logging.error(f"Failed to include chart in PDF: {chart_path}. Error: {e}")
+                    logging.error(f"Error including chart: {e}")
 
+        # Insert Tables
         if table_data:
             pdf.add_page()
-            pdf.set_font("Arial", size=10)
-            pdf.cell(200, 10, txt="Consolidated Table:", ln=True, align="L")
+            pdf.set_font("DejaVu", size=10)
+            pdf.cell(200, 10, txt="Consolidated Data Table:", ln=True, align="L")
             for row in table_data:
                 pdf.cell(200, 10, txt=str(row), ln=True)
 
         pdf.output(temp_pdf.name)
         return temp_pdf.name
 
+
 # Data Validation
 def validate_analyst_output(analyst_output):
     if not analyst_output:
         st.warning("No data available for analysis.")
+        logging.warning("Validation Failed: Analyst output is empty.")
         return None
-    if not isinstance(analyst_output, list) or not all(isinstance(item, dict) for item in analyst_output):
+
+    if not isinstance(analyst_output, list):
         st.warning("Analyst output must be a list of dictionaries.")
+        logging.warning(f"Validation Failed: Analyst output is not a list. Type: {type(analyst_output)}")
         return None
+
     required_keys = {'Category', 'Values'}
-    if not all(required_keys.issubset(item.keys()) for item in analyst_output):
-        st.warning(f"Each dictionary must contain keys: {required_keys}")
-        return None
+    for idx, item in enumerate(analyst_output):
+        if not isinstance(item, dict):
+            st.warning(f"Item at index {idx} is not a dictionary.")
+            logging.warning(f"Validation Failed: Item {idx} is not a dictionary. Item: {item}")
+            return None
+        if not required_keys.issubset(item.keys()):
+            st.warning(f"Item at index {idx} missing keys: {required_keys - set(item.keys())}")
+            logging.warning(f"Validation Failed: Item {idx} missing keys: {required_keys - set(item.keys())}")
+            return None
+
     return analyst_output
 
+
 # Visualization and Table Display
 def create_visualizations(analyst_output):
     chart_paths = []
@@ -241,55 +392,55 @@ def create_visualizations(analyst_output):
             values = item["Values"]
 
             try:
-                # Handle dictionary data
+                # Handle dictionary data for bar charts
                 if isinstance(values, dict):
                     df = pd.DataFrame(list(values.items()), columns=["Label", "Count"])
-
-                    # Choose Pie Chart for fewer categories, else Bar Chart
                     if len(df) <= 5:
                         chart = px.pie(df, names="Label", values="Count", title=f"{category} Distribution")
                     else:
                         chart = px.bar(df, x="Label", y="Count", title=f"{category} Analysis")
 
-                # Handle list data 
+                # Handle list data for bar/pie charts
                 elif isinstance(values, list):
-                    # Convert the list into a frequency count without dummy values
-                    df = pd.DataFrame(values, columns=["Label"])
-                    df = df["Label"].value_counts().reset_index()
-                    df.columns = ["Label", "Count"]
-
-                    # Plot as a bar chart or pie chart
-                    if len(df) <= 5:
-                        chart = px.pie(df, names="Label", values="Count", title=f"{category} Distribution")
+                    # Check if it's a list of dictionaries (e.g., Technology Spotlight)
+                    if all(isinstance(v, dict) for v in values):
+                        df = pd.DataFrame(values)
+                        st.subheader(f"{category} (Detailed View)")
+                        st.dataframe(df)
+                        continue  # Skip chart for detailed data
+
+                    # Frequency analysis for simple lists
                     else:
-                        chart = px.bar(df, x="Label", y="Count", title=f"{category} Frequency")
+                        df = pd.DataFrame(values, columns=["Items"])
+                        df = df["Items"].value_counts().reset_index()
+                        df.columns = ["Label", "Count"]
+                        chart = px.pie(df, names="Label", values="Count", title=f"{category} Distribution") if len(df) <= 5 else px.bar(df, x="Label", y="Count", title=f"{category} Frequency")
 
-                # Handle text data
+                # Handle string data (Insights)
                 elif isinstance(values, str):
                     st.subheader(f"{category} Insights")
                     st.table(pd.DataFrame({"Insights": [values]}))
-                    continue  # No chart for text data
+                    continue
 
                 else:
                     st.warning(f"Unsupported data format for category: {category}")
+                    logging.warning(f"Unsupported data format in {category}: {values}")
                     continue
 
-                # Display the chart in Streamlit
+                # Display in Streamlit
                 st.plotly_chart(chart)
 
-                # Save the chart for PDF export
+                # Save for PDF export
                 with tempfile.NamedTemporaryFile(delete=False, suffix=".png") as temp_chart:
                     chart.write_image(temp_chart.name)
                     chart_paths.append(temp_chart.name)
 
             except Exception as e:
                 st.error(f"Failed to generate visualization for {category}: {e}")
-                logging.error(f"Error in {category} visualization: {e}")
+                logging.error(f"Visualization error in {category}: {e}")
 
     return chart_paths
 
-
-
 def display_table(analyst_output):
     table_data = []
     validated_data = validate_analyst_output(analyst_output)
@@ -299,7 +450,6 @@ def display_table(analyst_output):
             category = item["Category"]
             values = item["Values"]
 
-            # Error handling to prevent crashes
             try:
                 # Handle dictionary data (Table View)
                 if isinstance(values, dict):
@@ -308,120 +458,155 @@ def display_table(analyst_output):
                     st.dataframe(df)
                     table_data.extend(df.to_dict(orient="records"))
 
-                # Handle list data (List View)
+                # Handle list data 
                 elif isinstance(values, list):
-                    df = pd.DataFrame(values, columns=["Items"])
-                    st.subheader(f"{category} (List View)")
-                    st.dataframe(df)
-                    table_data.extend(df.to_dict(orient="records"))
+                    # Handle complex lists (list of dictionaries)
+                    if all(isinstance(v, dict) for v in values):
+                        df = pd.DataFrame(values)
+                        st.subheader(f"{category} (Detailed View)")
+                        st.dataframe(df)
+                        table_data.extend(df.to_dict(orient="records"))
+                    # Handle simple lists 
+                    else:
+                        df = pd.DataFrame(values, columns=["Items"])
+                        st.subheader(f"{category} (List View)")
+                        st.dataframe(df)
+                        table_data.extend(df.to_dict(orient="records"))
 
-                # Handle text data (Summary View)
+                # Handle text data
                 elif isinstance(values, str):
                     st.subheader(f"{category} (Summary)")
                     st.table(pd.DataFrame({"Insights": [values]}))
                     table_data.append({"Category": category, "Values": values})
 
                 else:
-                    st.warning(f"Unsupported data format for category: {category}")
+                    st.warning(f"Unsupported data format for {category}")
+                    logging.warning(f"Unsupported data in {category}: {values}")
 
             except Exception as e:
-                logging.error(f"Error processing {category}: {e}")
-                st.error(f"Failed to display {category} as a table due to an error.")
+                st.error(f"Error displaying {category}: {e}")
+                logging.error(f"Display error for {category}: {e}")
 
     return table_data
 
 
-
 def parse_analyst_output(raw_output):
-    structured_data = []
-    current_category = None
-    current_values = []
-
-    # Split raw output by line
-    lines = raw_output.split('\n')
-
-    for line in lines:
-        line = line.strip()
-
-        # Detect the start of a new category
-        if line.startswith("Category:"):
-            # Save the previous category and its values
-            if current_category and current_values:
-                structured_data.append({
-                    "Category": current_category,
-                    "Values": current_values if len(current_values) > 1 else current_values[0]
-                })
-            # Start processing the new category
-            current_category = line.replace("Category:", "").strip()
-            current_values = []
-
-        # Skip 'Values:' header
-        elif line.startswith("Values:"):
-            continue
-
-        # Process the values under the current category
-        elif line and current_category:
-            try:
-                # Attempt to convert the line into Python data (dict/list)
-                parsed_value = ast.literal_eval(line)
-                current_values.append(parsed_value)
-            except (ValueError, SyntaxError):
-                # If parsing fails, treat it as plain text
-                current_values.append(line)
+    key_insights = []
+    data_insights = []
+
+    try:
+        # Correctly parse the raw output
+        structured_data = ast.literal_eval(raw_output) if isinstance(raw_output, str) else raw_output
+
+        for item in structured_data:
+            if "Category" not in item or "Values" not in item:
+                logging.warning(f"Missing 'Category' or 'Values' in item: {item}")
+                continue  
+
+            if item.get("Type") == "Key Insight":
+                key_insights.append(item["Values"])
+            elif item.get("Type") == "Data Insight":
+                # Handle nested structures (e.g., Technology Spotlight Cards)
+                if isinstance(item["Values"], list):
+                    for sub_item in item["Values"]:
+                        data_insights.append({"Category": item["Category"], "Values": sub_item})
+                else:
+                    data_insights.append(item)
+            else:
+                data_insights.append(item)
 
-    # Save the last processed category
-    if current_category and current_values:
-        structured_data.append({
-            "Category": current_category,
-            "Values": current_values if len(current_values) > 1 else current_values[0]
-        })
+    except Exception as e:
+        logging.error(f"Error parsing analyst output: {e}")
 
-    return structured_data
+    return key_insights, data_insights
 
 
 # Main Execution Block
 if st.button("Generate Patent Insights"):
     with st.spinner('Processing...'):
         try:
+            # Start the timer
             start_time = time.time()
-            results = crew.kickoff(inputs={"topic": patent_area, "stakeholder": stakeholder})
+
+            # Kick off the crew with user inputs
+            if not patent_area or not stakeholder:
+                st.error("Please provide both Patent Technology Area and Stakeholder.")
+            else:
+                logging.info(f"Starting analysis with Topic: {patent_area}, Stakeholder: {stakeholder}")
+                results = crew.kickoff(inputs={"topic": patent_area, "stakeholder": stakeholder})
+
+            # Calculate elapsed time
             elapsed_time = time.time() - start_time
 
+            # Extract Writer's Output
             writer_output = getattr(results.tasks_output[2], "raw", "No details available.")
-            if writer_output:
+            if writer_output and writer_output.strip():
                 st.markdown("### Final Report")
                 st.write(writer_output)
             else:
                 st.warning("No final report available.")
 
+            # Expandable section for detailed insights
             with st.expander("Explore Detailed Insights"):
                 tab1, tab2 = st.tabs(["Planner's Insights", "Analyst's Analysis"])
 
+                # Planner's Insights
                 with tab1:
                     planner_output = getattr(results.tasks_output[0], "raw", "No details available.")
-                    st.write(planner_output)
+                    if planner_output and planner_output.strip():
+                        st.write(planner_output)
+                    else:
+                        st.warning("No planner insights available.")
 
+                # Analyst's Analysis
                 with tab2:
                     analyst_output = getattr(results.tasks_output[1], "raw", "No details available.")
-                    st.write(analyst_output)
-                    # Convert raw text to structured data
-                    if isinstance(analyst_output, str):
-                        analyst_output = parse_analyst_output(analyst_output)
-                    st.subheader("Structured Analyst Output")
-                    st.write(analyst_output)
-                    
+                    if analyst_output and analyst_output.strip():
+                        st.write(analyst_output)
 
-                    charts = []
-                    if enable_advanced_analysis:
-                        charts = create_visualizations(analyst_output)
+                        # Parse Analyst Output (Key Insights + Data Insights)
+                        key_insights, data_insights = parse_analyst_output(analyst_output)
+                        st.subheader("Structured Analyst Output")
+                        st.write(data_insights)
 
-                    table_data = display_table(analyst_output)
+                        # Create Visualizations if enabled
+                        charts = []
+                        if enable_advanced_analysis and data_insights:
+                            charts = create_visualizations(data_insights)
+                        else:
+                            st.info("No data insights available for visualizations.")
 
+                        # Display Data Tables
+                        table_data = display_table(data_insights)
+
+                    else:
+                        st.warning("No analyst analysis available.")
+
+            # Notify user that the analysis is complete
             st.success(f"Analysis completed in {elapsed_time:.2f} seconds.")
-            pdf_path = generate_pdf_report(writer_output, charts=charts, table_data=table_data, metadata={"Technology Area": patent_area, "Stakeholder": stakeholder})
-            with open(pdf_path, "rb") as report_file:
-                st.download_button("Download Report", data=report_file, file_name="Patent_Strategy_Report.pdf")
+
+            # Generate the PDF report with Key Insights and Data Insights
+            if writer_output:
+                pdf_path = generate_pdf_report(
+                    result=writer_output,
+                    charts=charts,
+                    table_data=data_insights,
+                    metadata={"Technology Area": patent_area, "Stakeholder": stakeholder},
+                    key_insights=key_insights  # Pass key insights to the PDF
+                )
+
+                # Download button for the generated PDF
+                with open(pdf_path, "rb") as report_file:
+                    st.download_button(
+                        label="📄 Download Report",
+                        data=report_file,
+                        file_name="Patent_Strategy_Report.pdf",
+                        mime="application/pdf"
+                    )
+            else:
+                st.warning("Report generation skipped due to missing content.")
 
         except Exception as e:
-            logging.error(f"An error occurred during execution: {e}")
-            st.error(f"An error occurred during execution: {e}")
+            error_message = traceback.format_exc()
+            logging.error(f"An error occurred during execution:\n{error_message}")
+            st.error(f"⚠️ An unexpected error occurred:\n{e}")