Update app.py

app.py

@@ -149,17 +149,73 @@ if st.session_state.df is not None:
         verbose=True,
     )
 
-    query = st.text_area("Enter Query:", placeholder="e.g., 'What is the average salary for senior employees?'")
-    if st.button("Submit Query"):
-        with st.spinner("Processing query..."):
-            inputs = {"query": query}
-            result = crew.kickoff(inputs=inputs)
-            st.markdown("### Analysis Report:")
-            st.markdown(result)
+# SQL-RAG Analysis
+if st.session_state.df is not None:
+    temp_dir = tempfile.TemporaryDirectory()
+    db_path = os.path.join(temp_dir.name, "data.db")
+    connection = sqlite3.connect(db_path)
+    st.session_state.df.to_sql("salaries", connection, if_exists="replace", index=False)
+    db = SQLDatabase.from_uri(f"sqlite:///{db_path}")
+
+    @tool("execute_sql")
+    def execute_sql(sql_query: str) -> str:
+        return QuerySQLDataBaseTool(db=db).invoke(sql_query)
+
+    sql_dev = Agent("SQL Developer", "Optimize SQL queries for data extraction.", llm, tools=[execute_sql])
+    data_analyst = Agent("Data Analyst", "Analyze data and generate insights.", llm)
+    report_writer = Agent("Report Writer", "Summarize analysis into reports.", llm)
+
+    extract_data = Task("Extract data for: {query}.", "Query results.", sql_dev)
+    analyze_data = Task("Analyze extracted data for: {query}.", "Insights.", data_analyst, context=[extract_data])
+    write_report = Task("Generate a report for: {query}.", "Summary report.", report_writer, context=[analyze_data])
+
+    crew = Crew([sql_dev, data_analyst, report_writer], [extract_data, analyze_data, write_report], Process.sequential)
+
+    # Tabs for UI
+    tab1, tab2 = st.tabs(["🔍 Query Specific Insights + Viz", "📊 Full Data Insights"])
+
+    #  Tab 1: Query-Specific Analysis + viz
+    with tab1:
+        query = st.text_area("Enter Query:", placeholder="e.g., 'What is the average salary for senior employees?'")
+        if st.button("Submit Query"):
+            with st.spinner("Processing query..."):
+                result = crew.kickoff(inputs={"query": query})
+                st.subheader("📝 Analysis Report")
+                st.markdown(result)
+
+                # Query-Specific Visualization
+                if "salary" in query.lower():
+                    fig = px.box(st.session_state.df, x="job_title", y="salary_in_usd", title="Salary by Job Title")
+                    st.plotly_chart(fig)
+
+    # Tab 2: Full Insights
+    with tab2:
+        st.subheader("📊 Comprehensive Data Visualizations")
+
+        # Salary by Job Title
+        fig1 = px.box(st.session_state.df, x="job_title", y="salary_in_usd", title="Salary Distribution by Job Title")
+        st.plotly_chart(fig1)
+
+        # Average Salary by Experience Level
+        fig2 = px.bar(st.session_state.df.groupby("experience_level")["salary_in_usd"].mean().reset_index(),
+                      x="experience_level", y="salary_in_usd", title="Average Salary by Experience Level")
+        st.plotly_chart(fig2)
+
+        # Average Salary by Company Size
+        fig3 = px.bar(st.session_state.df.groupby("company_size")["salary_in_usd"].mean().reset_index(),
+                      x="company_size", y="salary_in_usd", title="Average Salary by Company Size")
+        st.plotly_chart(fig3)
+
+        # Download CSV Report
+        if st.button("📥 Download CSV Summary"):
+            summary = st.session_state.df.groupby("job_title")["salary_in_usd"].mean().reset_index()
+            summary.to_csv("summary.csv", index=False)
+            with open("summary.csv", "rb") as file:
+                st.download_button("Download CSV", file, "summary.csv", "text/csv")
 
     temp_dir.cleanup()
 else:
-    st.info("Please load a dataset to proceed.")
+    st.info("Upload a dataset to continue.")
 
 with st.sidebar:
     # st.markdown("---")