Update mylab/almost_blah.py

mylab/almost_blah.py

@@ -111,7 +111,7 @@ if st.session_state.df is not None:
         """Validate the SQL query syntax and structure before execution."""
         return QuerySQLCheckerTool(db=db, llm=llm).invoke({"query": sql_query})
 
-    # Agent for SQL data extraction
+    # Agents for SQL data extraction and analysis
     sql_dev = Agent(
         role="Senior Database Developer",
         goal="Extract data using optimized SQL queries.",
@@ -120,7 +120,6 @@ if st.session_state.df is not None:
         tools=[list_tables, tables_schema, execute_sql, check_sql],
     )
 
-    # Agent for data analysis
     data_analyst = Agent(
         role="Senior Data Analyst",
         goal="Analyze the data and produce insights.",
@@ -128,23 +127,21 @@ if st.session_state.df is not None:
         llm=llm,
     )
 
-    # Agent for generating the main report (without Conclusion)
     report_writer = Agent(
         role="Technical Report Writer",
-        goal="Summarize the analysis into a structured report with Introduction, Key Insights, and Analysis. DO NOT include any conclusion or summary.",
-        backstory="Markdown report excluding Conclusion and Summary.",
+        goal="Write a structured report with Key Insights and Analysis. DO NOT include Introduction or Conclusion.",
+        backstory="Specializes in detailed analytical reports without conclusions.",
         llm=llm,
     )
 
-    # New Agent for generating ONLY the Conclusion
     conclusion_writer = Agent(
         role="Conclusion Specialist",
-        goal="Summarize findings into a clear and concise Conclusion/Summary section.",
-        backstory="An expert in crafting well-structured and insightful conclusions.",
+        goal="Summarize findings into a clear and concise 3-5 line Conclusion highlighting only the most important insights.",
+        backstory="An expert in crafting impactful and clear conclusions.",
         llm=llm,
     )
 
-    # Tasks for each agent
+    # Define tasks for report and conclusion
     extract_data = Task(
         description="Extract data based on the query: {query}.",
         expected_output="Database results matching the query.",
@@ -153,57 +150,61 @@ if st.session_state.df is not None:
 
     analyze_data = Task(
         description="Analyze the extracted data for query: {query}.",
-        expected_output="Provide ONLY Key Insights and Analysis. Exclude Introduction and Conclusion.",
+        expected_output="Key Insights and Analysis without any Introduction or Conclusion.",
         agent=data_analyst,
         context=[extract_data],
     )
 
     write_report = Task(
-        description="Write the report with ONLY Key Insights and Analysis. DO NOT include Introduction or Conclusion.",
-        expected_output="Markdown report excluding Introduction and Conclusion.",
+        description="Write the analysis report with Key Insights. DO NOT include a Conclusion.",
+        expected_output="Markdown-formatted report excluding Conclusion.",
         agent=report_writer,
         context=[analyze_data],
     )
 
     write_conclusion = Task(
-        description="Summarize the findings into a concise Conclusion.",
-        expected_output="Markdown-formatted Conclusion section.",
+        description="Write a brief and impactful 3-5 line Conclusion summarizing only the most important insights.",
+        expected_output="Markdown-formatted concise Conclusion section.",
         agent=conclusion_writer,
         context=[analyze_data],
     )
 
-    # Crew setup
-    crew = Crew(
-        agents=[sql_dev, data_analyst, report_writer, conclusion_writer],
-        tasks=[extract_data, analyze_data, write_report, write_conclusion],
+    # Separate Crews for report and conclusion
+    crew_report = Crew(
+        agents=[sql_dev, data_analyst, report_writer],
+        tasks=[extract_data, analyze_data, write_report],
         process=Process.sequential,
         verbose=True,
     )
 
-    # Tabs for Query Results and General Insights
+    crew_conclusion = Crew(
+        agents=[data_analyst, conclusion_writer],
+        tasks=[write_conclusion],
+        process=Process.sequential,
+        verbose=True,
+    )
+
+    # Tabs for Query Results and Visualizations
     tab1, tab2 = st.tabs(["🔍 Query Insights + Viz", "📊 Full Data Viz"])
 
-    # Tab 1: Query-Insights + Visualization
+    # Query Insights + Visualization
     with tab1:
         query = st.text_area("Enter Query:", value="Provide insights into the salary of a Principal Data Scientist.")
         if st.button("Submit Query"):
             with st.spinner("Processing query..."):
-                # Step 1: Generate Report without Conclusion
-                report_inputs = {"query": query + " Provide a detailed analysis but DO NOT include a Conclusion."}
-                report_result = crew.kickoff(inputs=report_inputs)
-
-                # Step 2: Generate only the Conclusion
-                conclusion_inputs = {"query": query + " Now, provide only the Conclusion for this analysis."}
-                conclusion_result = crew.kickoff(inputs=conclusion_inputs)
+                # Step 1: Generate the analysis report
+                report_inputs = {"query": query + " Provide detailed analysis but DO NOT include Conclusion."}
+                report_result = crew_report.kickoff(inputs=report_inputs)
 
-                # Directly use the outputs 
-                main_report = report_result if report_result else "⚠️ No Report Generated."
-                conclusion = conclusion_result if conclusion_result else "⚠️ No Conclusion Generated."
+                # Step 2: Generate only the concise conclusion
+                conclusion_inputs = {"query": query + " Provide ONLY the most important insights in 3-5 concise lines."}
+                conclusion_result = crew_conclusion.kickoff(inputs=conclusion_inputs)
 
+                # Step 3: Display the report
                 st.markdown("### Analysis Report:")
-                st.markdown(main_report)
+                st.markdown(report_result if report_result else "⚠️ No Report Generated.")
 
-                # Step 3: Generate relevant visualizations
+                # Step 4: Generate Visualizations
                 visualizations = []
 
                 fig_salary = px.box(st.session_state.df, x="job_title", y="salary_in_usd",
@@ -221,16 +222,16 @@ if st.session_state.df is not None:
                                         title="Salary Distribution by Employment Type")
                 visualizations.append(fig_employment)
 
-                # Step 4: Insert Visual Insights
+                # Step 5: Insert Visual Insights
                 st.markdown("## 📊 Visual Insights")
                 for fig in visualizations:
                     st.plotly_chart(fig, use_container_width=True)
 
-                # Step 5: Append the Conclusion
+                # Step 6: Display Concise Conclusion
                 st.markdown("## Conclusion")
-                st.markdown(conclusion)
+                st.markdown(conclusion_result if conclusion_result else "⚠️ No Conclusion Generated.")
 
-    # Tab 2: Full Data Visualization
+    # Full Data Visualization Tab
     with tab2:
         st.subheader("📊 Comprehensive Data Visualizations")