Update app.py

app.py

@@ -86,6 +86,71 @@ if st.session_state.df is not None and st.session_state.show_preview:
     st.subheader("📂 Dataset Preview")
     st.dataframe(st.session_state.df.head())
 
+# Ask GPT-4o for Visualization Suggestions
+def ask_gpt4o_for_visualization(query, df, llm):
+    columns = ', '.join(df.columns)
+    prompt = f"""
+    Analyze the query and suggest the best visualization.
+    Query: "{query}"
+    Available Columns: {columns}
+    Respond in this JSON format:
+    {{
+      "chart_type": "bar/box/line/scatter",
+      "x_axis": "column_name",
+      "y_axis": "column_name",
+      "group_by": "optional_column_name"
+    }}
+    """
+    response = llm.generate(prompt)
+    try:
+        return json.loads(response)
+    except json.JSONDecodeError:
+        st.error("⚠️ GPT-4o failed to generate a valid suggestion.")
+        return None
+
+# Dynamically generate Plotly visualizations based on GPT-4o suggestions
+def generate_visualization(suggestion, df):
+    chart_type = suggestion.get("chart_type", "bar").lower()
+    x_axis = suggestion.get("x_axis")
+    y_axis = suggestion.get("y_axis")
+    group_by = suggestion.get("group_by")
+
+    # Ensure required inputs are available
+    if not x_axis or not y_axis:
+        st.warning("⚠️ GPT-4o did not provide enough information for the visualization.")
+        return None
+
+    # Dynamically select the Plotly function
+    plotly_function = getattr(px, chart_type, None)
+
+    # Handle unsupported chart types gracefully
+    if not plotly_function:
+        st.warning(f"⚠️ Unsupported chart type '{chart_type}' suggested by GPT-4o.")
+        return None
+
+    # Prepare dynamic parameters for Plotly function
+    plot_args = {
+        "data_frame": df,
+        "x": x_axis,
+        "y": y_axis,
+    }
+    if group_by:
+        plot_args["color"] = group_by
+
+    try:
+        # Generate the dynamic visualization
+        fig = plotly_function(**plot_args)
+        fig.update_layout(
+            title=f"{chart_type.title()} Plot of {y_axis.replace('_', ' ').title()} by {x_axis.replace('_', ' ').title()}",
+            xaxis_title=x_axis.replace('_', ' ').title(),
+            yaxis_title=y_axis.replace('_', ' ').title(),
+        )
+        return fig
+
+    except Exception as e:
+        st.error(f"⚠️ Failed to generate visualization: {e}")
+        return None
+
 # Function to create TXT file
 def create_text_report_with_viz_temp(report, conclusion, visualizations):
     content = f"### Analysis Report\n\n{report}\n\n### Visualizations\n"
@@ -112,6 +177,59 @@ def create_text_report_with_viz_temp(report, conclusion, visualizations):
         return temp_txt.name
 
 
+def add_stats_to_figure(fig, df, y_axis, chart_type):
+    # Calculate statistics
+    min_val = df[y_axis].min()
+    max_val = df[y_axis].max()
+    avg_val = df[y_axis].mean()
+    median_val = df[y_axis].median()
+    std_dev_val = df[y_axis].std()
+
+    # Stats summary text
+    stats_text = (
+        f"📊 **Statistics**\n\n"
+        f"- **Min:** ${min_val:,.2f}\n"
+        f"- **Max:** ${max_val:,.2f}\n"
+        f"- **Average:** ${avg_val:,.2f}\n"
+        f"- **Median:** ${median_val:,.2f}\n"
+        f"- **Std Dev:** ${std_dev_val:,.2f}"
+    )
+
+    # Charts suitable for stats annotations
+    if chart_type in ["bar", "line", "scatter"]:
+        # Add annotation box
+        fig.add_annotation(
+            text=stats_text,
+            xref="paper", yref="paper",
+            x=1.05, y=1,
+            showarrow=False,
+            align="left",
+            font=dict(size=12, color="black"),
+            bordercolor="black",
+            borderwidth=1,
+            bgcolor="rgba(255, 255, 255, 0.8)"
+        )
+
+        # Add horizontal lines for min, median, avg, max
+        fig.add_hline(y=min_val, line_dash="dot", line_color="red", annotation_text="Min", annotation_position="bottom right")
+        fig.add_hline(y=median_val, line_dash="dash", line_color="orange", annotation_text="Median", annotation_position="top right")
+        fig.add_hline(y=avg_val, line_dash="dashdot", line_color="green", annotation_text="Avg", annotation_position="top right")
+        fig.add_hline(y=max_val, line_dash="dot", line_color="blue", annotation_text="Max", annotation_position="top right")
+
+    elif chart_type == "box":
+        # Box plots already show distribution (no extra stats needed)
+        pass
+
+    elif chart_type == "pie":
+        # Pie charts don't need statistical overlays
+        st.info("📊 Pie charts focus on proportions. No additional stats displayed.")
+    
+    else:
+        st.warning(f"⚠️ No stats added for unsupported chart type: {chart_type}")
+
+    return fig
+
+
 # Function to create PDF with report text and visualizations
 def create_pdf_report_with_viz(report, conclusion, visualizations):
     pdf = FPDF()
@@ -301,27 +419,11 @@ if st.session_state.df is not None:
                 st.markdown(report_result if report_result else "⚠️ No Report Generated.")
 
                 # Step 4: Generate Visualizations
-                visualizations = []
 
-                fig_salary = px.box(st.session_state.df, x="job_title", y="salary_in_usd",
-                                    title="Salary Distribution by Job Title")
-                visualizations.append(fig_salary)
-
-                fig_experience = 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"
-                )
-                visualizations.append(fig_experience)
-
-                fig_employment = px.box(st.session_state.df, x="employment_type", y="salary_in_usd",
-                                        title="Salary Distribution by Employment Type")
-                visualizations.append(fig_employment)
 
                 # Step 5: Insert Visual Insights
                 st.markdown("### Visual Insights")
-                for fig in visualizations:
-                    st.plotly_chart(fig, use_container_width=True)
+
 
                 # Step 6: Display Concise Conclusion
                 #st.markdown("#### Conclusion")
@@ -355,5 +457,4 @@ else:
 # Sidebar Reference
 with st.sidebar:
     st.header("📚 Reference:")
-    st.markdown("[SQL Agents w CrewAI & Llama 3 - Plaban Nayak](https://github.com/plaban1981/Agents/blob/main/SQL_Agents_with_CrewAI_and_Llama_3.ipynb)")
-
+    st.markdown("[SQL Agents w CrewAI & Llama 3 - Plaban Nayak](https://github.com/plaban1981/Agents/blob/main/SQL_Agents_with_CrewAI_and_Llama_3.ipynb)")