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Update app.py
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app.py
CHANGED
@@ -172,17 +172,10 @@ if st.session_state.df is not None:
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context=[analyze_data],
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)
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#
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agents=[sql_dev, data_analyst, report_writer],
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tasks=[extract_data, analyze_data, write_report],
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process=Process.sequential,
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verbose=True,
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)
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crew_conclusion = Crew(
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agents=[data_analyst, conclusion_writer],
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tasks=[write_conclusion],
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process=Process.sequential,
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verbose=True,
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)
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@@ -195,15 +188,15 @@ if st.session_state.df is not None:
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query = st.text_area("Enter Query:", value="Provide insights into the salary of a Principal Data Scientist.")
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if st.button("Submit Query"):
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with st.spinner("Processing query..."):
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report_result = crew_report.kickoff(inputs=report_inputs)
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#
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st.markdown("### Analysis Report:")
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# Step 3: Generate relevant visualizations
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visualizations = []
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@@ -223,17 +216,14 @@ if st.session_state.df is not None:
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title="Salary Distribution by Employment Type")
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visualizations.append(fig_employment)
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# Step 4:
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st.markdown(report_result)
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# Step 5: Insert Visual Insights
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st.markdown("## π Visual Insights")
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for fig in visualizations:
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st.plotly_chart(fig, use_container_width=True)
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# Step
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st.markdown("## Conclusion")
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st.markdown(
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# Tab 2: Full Data Visualization
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with tab2:
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@@ -257,7 +247,6 @@ if st.session_state.df is not None:
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else:
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st.info("Please load a dataset to proceed.")
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# Sidebar Reference
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with st.sidebar:
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st.header("π Reference:")
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context=[analyze_data],
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)
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# β
Optimized Single Crew for Report and Conclusion
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crew = Crew(
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agents=[sql_dev, data_analyst, report_writer, conclusion_writer],
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tasks=[extract_data, analyze_data, write_report, write_conclusion],
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process=Process.sequential,
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verbose=True,
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)
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query = st.text_area("Enter Query:", value="Provide insights into the salary of a Principal Data Scientist.")
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if st.button("Submit Query"):
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with st.spinner("Processing query..."):
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inputs = {"query": query}
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result = crew.kickoff(inputs=inputs)
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# Assuming result is structured as a dictionary:
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main_report = result.get('write_report', '')
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conclusion = result.get('write_conclusion', '')
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st.markdown("### Analysis Report:")
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st.markdown(main_report)
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# Step 3: Generate relevant visualizations
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visualizations = []
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title="Salary Distribution by Employment Type")
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visualizations.append(fig_employment)
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# Step 4: Insert Visual Insights
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st.markdown("## π Visual Insights")
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for fig in visualizations:
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st.plotly_chart(fig, use_container_width=True)
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# Step 5: Append the Conclusion
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st.markdown("## Conclusion")
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st.markdown(conclusion)
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# Tab 2: Full Data Visualization
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with tab2:
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else:
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st.info("Please load a dataset to proceed.")
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# Sidebar Reference
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with st.sidebar:
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st.header("π Reference:")
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