Update app.py

app.py

@@ -11,10 +11,9 @@ from typing import List, Dict, Any, Tuple, Optional
 
 # --- Configuration & Constants ---
 warnings.filterwarnings('ignore')
-
+MAX_DASHBOARD_PLOTS = 10
 CSS = """
-/* --- Phoenix UI Professional Dark CSS --- */
-#app-title { text-align: center; font-weight: 800; font-size: 2.5rem; color: #f9fafb; }
+#app-title { text-align: center; font-weight: 800; font-size: 2.5rem; color: #f9fafb; padding-top: 10px; }
 .stat-card { border-radius: 12px !important; padding: 20px !important; background: #1f2937 !important; border: 1px solid #374151 !important; text-align: center; transition: all 0.3s ease; }
 .stat-card:hover { transform: translateY(-5px); box-shadow: 0 10px 15px -3px rgba(0,0,0,0.1), 0 4px 6px -2px rgba(0,0,0,0.05); }
 .stat-card-title { font-size: 16px; font-weight: 500; color: #9ca3af !important; margin-bottom: 8px; }
@@ -25,7 +24,6 @@ CSS = """
 .sidebar .gr-button.selected { background-color: #4f46e5 !important; font-weight: 600 !important; color: white !important; }
 .explanation-block { background-color: #1e3a8a !important; border-left: 4px solid #3b82f6 !important; padding: 12px; color: #e5e7eb !important; border-radius: 4px; }
 """
-MAX_DASHBOARD_PLOTS = 10
 
 class DataExplorerApp:
     """A professional-grade, AI-powered data exploration application."""
@@ -37,28 +35,37 @@ class DataExplorerApp:
         with gr.Blocks(theme=gr.themes.Glass(primary_hue="indigo", secondary_hue="blue"), css=CSS, title="AI Data Explorer Pro") as demo:
             state_var = gr.State({})
             
-            # --- Component Definition ---
-            cockpit_btn, deep_dive_btn, copilot_btn = [gr.Button(elem_id=id) for id in ["cockpit", "deep_dive", "co-pilot"]]
-            file_input, status_output = gr.File(label="📁 Upload CSV File", file_types=[".csv"]), gr.Markdown("Status: Awaiting data...")
+            # --- Component Definition (Define-Then-Place Pattern) ---
+            # Sidebar
+            ### CRITICAL FIX HERE ###
+            # Buttons are defined individually with their value (text) to fix the "Run" bug.
+            cockpit_btn = gr.Button("📊 Data Cockpit", elem_classes="selected", elem_id="cockpit")
+            deep_dive_btn = gr.Button("🔍 Deep Dive Builder", elem_id="deep_dive")
+            copilot_btn = gr.Button("🤖 Chief Data Scientist", elem_id="co-pilot")
+            
+            file_input = gr.File(label="📁 Upload CSV File", file_types=[".csv"])
+            status_output = gr.Markdown("Status: Awaiting data...")
             api_key_input = gr.Textbox(label="🔑 Gemini API Key", type="password", placeholder="Enter key to enable AI...")
             suggestion_btn = gr.Button("Get Smart Suggestions", variant="secondary", interactive=False)
             
-            rows_stat, cols_stat = gr.Textbox("0", interactive=False, elem_classes="stat-card-value", show_label=False), gr.Textbox("0", interactive=False, elem_classes="stat-card-value", show_label=False)
-            quality_stat, time_cols_stat = gr.Textbox("0%", interactive=False, elem_classes="stat-card-value", show_label=False), gr.Textbox("0", interactive=False, elem_classes="stat-card-value", show_label=False)
+            # Cockpit
+            rows_stat, cols_stat = gr.Textbox("0", interactive=False, show_label=False, elem_classes="stat-card-value"), gr.Textbox("0", interactive=False, show_label=False, elem_classes="stat-card-value")
+            quality_stat, time_cols_stat = gr.Textbox("0%", interactive=False, show_label=False, elem_classes="stat-card-value"), gr.Textbox("0", interactive=False, show_label=False, elem_classes="stat-card-value")
             suggestion_buttons = [gr.Button(visible=False) for _ in range(5)]
             
+            # Deep Dive
             plot_type_dd = gr.Dropdown(['histogram', 'bar', 'scatter', 'box'], label="Plot Type", value='histogram')
             x_col_dd = gr.Dropdown([], label="X-Axis / Column", interactive=False)
             y_col_dd = gr.Dropdown([], label="Y-Axis (for Scatter/Box)", visible=False, interactive=False)
-            add_plot_btn, clear_plots_btn = gr.Button("Add to Dashboard", variant="primary", interactive=False), gr.Button("Clear Dashboard")
-            
-            # CORRECTED: Use a dynamic set of Plot components, not Gallery
+            add_plot_btn, clear_plots_btn = gr.Button("Add to Dashboard", variant="primary", interactive=False), gr.Button("Clear Dashboard", interactive=False)
             dashboard_plots = [gr.Plot(visible=False) for _ in range(MAX_DASHBOARD_PLOTS)]
 
-            chatbot, chat_input, chat_submit_btn = gr.Chatbot(height=500, label="Conversation", show_copy_button=True), gr.Textbox(label="Your Question", placeholder="e.g., 'What is the relationship between age and salary?'", scale=4), gr.Button("Ask AI", variant="primary")
+            # Co-pilot
+            chatbot = gr.Chatbot(height=500, label="Conversation", show_copy_button=True, avatar_images=(None, "bot.png"))
             copilot_explanation, copilot_code = gr.Markdown(visible=False, elem_classes="explanation-block"), gr.Code(language="python", visible=False, label="Executed Code")
             copilot_plot, copilot_table = gr.Plot(visible=False, label="Generated Visualization"), gr.Dataframe(visible=False, label="Generated Table", wrap=True)
-
+            chat_input, chat_submit_btn = gr.Textbox(label="Your Question", placeholder="e.g., 'What is the relationship between age and salary?'", scale=4), gr.Button("Ask AI", variant="primary", interactive=False)
+            
             # --- Layout Arrangement ---
             with gr.Row():
                 with gr.Column(scale=1, elem_classes="sidebar"):
@@ -66,7 +73,7 @@ class DataExplorerApp:
                     file_input; status_output; gr.Markdown("---"); api_key_input; suggestion_btn
                 with gr.Column(scale=4):
                     welcome_page, cockpit_page, deep_dive_page, copilot_page = [gr.Column(visible=i==0) for i in range(4)]
-                    with welcome_page: gr.Markdown("# Welcome to the AI Data Explorer Pro\n> Please **upload a CSV file** and **enter your Gemini API key** to begin.")
+                    with welcome_page: gr.Markdown("# Welcome to the AI Data Explorer Pro\n> Please **upload a CSV file** and **enter your Gemini API key** to begin your analysis.")
                     with cockpit_page:
                         gr.Markdown("## 📊 Data Cockpit: At-a-Glance Overview")
                         with gr.Row():
@@ -79,7 +86,7 @@ class DataExplorerApp:
                         gr.Markdown("## 🔍 Deep Dive: Manual Dashboard Builder"); gr.Markdown("Construct visualizations to investigate specific relationships.")
                         with gr.Row(): plot_type_dd; x_col_dd; y_col_dd
                         with gr.Row(): add_plot_btn; clear_plots_btn
-                        with gr.Column(): [plot for plot in dashboard_plots] # Place the plot holders
+                        with gr.Column(): [plot for plot in dashboard_plots]
                     with copilot_page:
                         gr.Markdown("## 🤖 Chief Data Scientist: Your AI Partner"); chatbot
                         with gr.Accordion("AI's Detailed Response", open=True): copilot_explanation; copilot_code; copilot_plot; copilot_table
@@ -92,16 +99,18 @@ class DataExplorerApp:
                     lambda i=i: [gr.update(elem_classes="selected" if j==i else "") for j in range(len(nav_buttons))], outputs=nav_buttons)
 
             file_input.upload(self.load_and_process_file, inputs=[file_input], outputs=[
-                state_var, status_output, welcome_page, cockpit_page, rows_stat, cols_stat, quality_stat, time_cols_stat,
+                state_var, status_output, *pages, rows_stat, cols_stat, quality_stat, time_cols_stat,
                 x_col_dd, y_col_dd, add_plot_btn]).then(lambda: self._switch_page("cockpit", pages), outputs=pages).then(
                 lambda: [gr.update(elem_classes="selected"), gr.update(elem_classes=""), gr.update(elem_classes="")], outputs=nav_buttons)
 
             api_key_input.change(lambda x: gr.update(interactive=bool(x)), inputs=[api_key_input], outputs=[suggestion_btn])
+            chat_input.change(lambda x: gr.update(interactive=bool(x.strip())), inputs=[chat_input], outputs=[chat_submit_btn])
+            
             plot_type_dd.change(self._update_plot_controls, inputs=[plot_type_dd], outputs=[y_col_dd])
-            add_plot_btn.click(self.add_plot_to_dashboard, inputs=[state_var, x_col_dd, y_col_dd, plot_type_dd], outputs=[state_var, *dashboard_plots])
-            clear_plots_btn.click(self.clear_dashboard, inputs=[state_var], outputs=[state_var, *dashboard_plots])
-            suggestion_btn.click(self.get_ai_suggestions, inputs=[state_var, api_key_input], outputs=suggestion_buttons)
+            add_plot_btn.click(self.add_plot_to_dashboard, inputs=[state_var, x_col_dd, y_col_dd, plot_type_dd], outputs=[state_var, clear_plots_btn, *dashboard_plots])
+            clear_plots_btn.click(self.clear_dashboard, inputs=[state_var], outputs=[state_var, clear_plots_btn, *dashboard_plots])
             
+            suggestion_btn.click(self.get_ai_suggestions, inputs=[state_var, api_key_input], outputs=suggestion_buttons)
             for btn in suggestion_buttons:
                 btn.click(self.handle_suggestion_click, inputs=[btn], outputs=[*pages, chat_input]).then(
                     lambda: self._switch_page("co-pilot", pages), outputs=pages).then(
@@ -113,8 +122,9 @@ class DataExplorerApp:
 
     def launch(self): self.demo.launch(debug=True)
 
+    # --- Backend Logic Methods ---
     def _switch_page(self, page_id: str, all_pages: List) -> List[gr.update]:
-        visibility = {"welcome":0, "cockpit":1, "deep_dive":2, "co-pilot":3}
+        visibility = {"cockpit": 1, "deep_dive": 2, "co-pilot": 3}
         return [gr.update(visible=i == visibility.get(page_id, 0)) for i in range(len(all_pages))]
     
     def _update_plot_controls(self, plot_type: str) -> gr.update:
@@ -126,11 +136,12 @@ class DataExplorerApp:
             metadata = self._extract_dataset_metadata(df)
             state = {'df': df, 'metadata': metadata, 'dashboard_plots': []}
             rows, cols, quality = metadata['shape'][0], metadata['shape'][1], metadata['data_quality']
-            return (state, f"✅ **{os.path.basename(file_obj.name)}** loaded.", gr.update(visible=False), gr.update(visible=True),
-                    f"{rows:,}", f"{cols}", f"{quality}%", f"{len(metadata['datetime_cols'])}",
-                    gr.update(choices=metadata['columns'], interactive=True), gr.update(choices=metadata['columns'], interactive=True), gr.update(interactive=True))
+            updates = (state, f"✅ **{os.path.basename(file_obj.name)}** loaded.", *self._switch_page("cockpit", [0,1,2,3]),
+                       f"{rows:,}", f"{cols}", f"{quality}%", f"{len(metadata['datetime_cols'])}",
+                       gr.update(choices=metadata['columns'], interactive=True), gr.update(choices=metadata['columns'], interactive=True), gr.update(interactive=True))
+            return updates
         except Exception as e:
-            gr.Error(f"File Load Error: {e}"); return {}, f"❌ Error: {e}", gr.update(visible=True), gr.update(visible=False), "0", "0", "0%", "0", gr.update(choices=[], interactive=False), gr.update(choices=[], interactive=False), gr.update(interactive=False)
+            gr.Error(f"File Load Error: {e}"); return {}, f"❌ Error: {e}", *self._switch_page("welcome", [0,1,2,3]), "0", "0", "0%", "0", gr.update(choices=[], interactive=False), gr.update(choices=[], interactive=False), gr.update(interactive=False)
 
     def _extract_dataset_metadata(self, df: pd.DataFrame) -> Dict[str, Any]:
         rows, cols = df.shape
@@ -141,9 +152,10 @@ class DataExplorerApp:
 
     def add_plot_to_dashboard(self, state: Dict, x_col: str, y_col: Optional[str], plot_type: str) -> List[Any]:
         if len(state.get('dashboard_plots', [])) >= MAX_DASHBOARD_PLOTS:
-            gr.Warning(f"Dashboard is full. Max {MAX_DASHBOARD_PLOTS} plots allowed."); return [state, *self._get_plot_updates(state)]
-        if not x_col: gr.Warning("Please select at least an X-axis column."); return [state, *self._get_plot_updates(state)]
-        df, title = state['df'], f"{plot_type.capitalize()}: {y_col} by {x_col}" if y_col and plot_type in ['box', 'scatter'] else f"Distribution of {x_col}"
+            gr.Warning(f"Dashboard is full. Max {MAX_DASHBOARD_PLOTS} plots."); return [state, gr.update(), *self._get_plot_updates(state)]
+        if not x_col: gr.Warning("Please select an X-axis column."); return [state, gr.update(), *self._get_plot_updates(state)]
+        df = state['df']
+        title = f"{plot_type.capitalize()}: {y_col} by {x_col}" if y_col and plot_type in ['box', 'scatter'] else f"Distribution of {x_col}"
         try:
             if plot_type == 'histogram': fig = px.histogram(df, x=x_col, title=title)
             elif plot_type == 'box': fig = px.box(df, x=x_col, y=y_col, title=title)
@@ -153,62 +165,48 @@ class DataExplorerApp:
                 fig = px.bar(counts, x=counts.index, y=counts.values, title=f"Top 20 Categories for {x_col}", labels={'index': x_col, 'y': 'Count'})
             if fig:
                 fig.update_layout(template="plotly_dark"); state['dashboard_plots'].append(fig); gr.Info(f"Added '{title}' to dashboard.")
-            return [state, *self._get_plot_updates(state)]
-        except Exception as e: gr.Error(f"Plotting Error: {e}"); return [state, *self._get_plot_updates(state)]
+            return [state, gr.update(interactive=True), *self._get_plot_updates(state)]
+        except Exception as e: gr.Error(f"Plotting Error: {e}"); return [state, gr.update(), *self._get_plot_updates(state)]
     
     def _get_plot_updates(self, state: Dict) -> List[gr.update]:
         plots = state.get('dashboard_plots', [])
-        updates = []
-        for i in range(MAX_DASHBOARD_PLOTS):
-            if i < len(plots): updates.append(gr.update(value=plots[i], visible=True))
-            else: updates.append(gr.update(value=None, visible=False))
-        return updates
+        return [gr.update(value=plots[i] if i < len(plots) else None, visible=i < len(plots)) for i in range(MAX_DASHBOARD_PLOTS)]
 
     def clear_dashboard(self, state: Dict) -> List[Any]:
-        state['dashboard_plots'] = []; gr.Info("Dashboard cleared."); return [state, *self._get_plot_updates(state)]
+        state['dashboard_plots'] = []; gr.Info("Dashboard cleared."); return [state, gr.update(interactive=False), *self._get_plot_updates(state)]
 
     def get_ai_suggestions(self, state: Dict, api_key: str) -> List[gr.update]:
         if not api_key: gr.Warning("API Key is required."); return [gr.update(visible=False)]*5
         if not state: gr.Warning("Please load data first."); return [gr.update(visible=False)]*5
-        # CORRECTED: metadata assignment
-        metadata = state['metadata']
-        prompt = f"From columns {metadata['columns']}, generate 4 impactful analytical questions. Return ONLY a JSON list of strings."
+        metadata = state['metadata']; prompt = f"From columns {metadata['columns']}, generate 4 impactful analytical questions. Return ONLY a JSON list of strings."
         try:
             genai.configure(api_key=api_key); suggestions = json.loads(genai.GenerativeModel('gemini-1.5-flash').generate_content(prompt).text)
             return [gr.Button(s, visible=True) for s in suggestions] + [gr.Button(visible=False)] * (5 - len(suggestions))
         except Exception as e: gr.Error(f"AI Suggestion Error: {e}"); return [gr.update(visible=False)]*5
 
     def handle_suggestion_click(self, question: str) -> Tuple[gr.update, ...]:
-        return gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(visible=True), question
+        return *self._switch_page("co-pilot", [0,1,2,3]), question
 
     def respond_to_chat(self, state: Dict, api_key: str, user_message: str, history: List) -> Any:
-        if not user_message.strip(): gr.Warning("Message is empty."); return history, *[gr.update()]*4
+        if not user_message.strip(): return history, *[gr.update()]*4
         if not api_key or not state:
             msg = "I need a Gemini API key and a dataset to work."; history.append((user_message, msg)); return history, *[gr.update(visible=False)]*4
         
         history.append((user_message, "Thinking... 🤔")); yield history, *[gr.update(visible=False)]*4
         
         metadata, prompt = state['metadata'], f"""You are 'Chief Data Scientist', an expert AI analyst...
-        **Instructions:**
-        1. **Analyze:** Understand user intent. Infer best plot type.
-        2. **Plan:** Briefly explain your plan.
-        3. **Code:** Write Python code. Use `fig` for plots (`template='plotly_dark'`) and `result_df` for tables.
-        4. **Insight:** Provide a one-sentence business insight.
-        5. **Respond ONLY with a single JSON object with keys: "plan", "code", "insight".**
-        **Metadata:** {metadata['dtypes_head']}
-        **User Question:** "{user_message}"
+        Respond ONLY with a single JSON object with keys: "plan", "code", "insight".
+        Metadata: {metadata['dtypes_head']}
+        User Question: "{user_message}"
         """
         try:
-            genai.configure(api_key=api_key)
-            response_json = json.loads(genai.GenerativeModel('gemini-1.5-flash').generate_content(prompt).text.strip().replace("```json", "").replace("```", ""))
+            genai.configure(api_key=api_key); response_json = json.loads(genai.GenerativeModel('gemini-1.5-flash').generate_content(prompt).text.strip().replace("```json", "").replace("```", ""))
             plan, code, insight = response_json.get("plan"), response_json.get("code"), response_json.get("insight")
             stdout, fig, df_result, error = self._safe_exec(code, {'df': state['df'], 'px': px, 'pd': pd})
-            
             history[-1] = (user_message, f"**Plan:** {plan}")
             explanation = f"**Insight:** {insight}"
             if stdout: explanation += f"\n\n**Console Output:**\n```\n{stdout}\n```"
             if error: gr.Error(f"AI Code Execution Failed: {error}")
-            
             yield (history, gr.update(visible=bool(explanation), value=explanation), gr.update(visible=bool(code), value=code),
                    gr.update(visible=bool(fig), value=fig), gr.update(visible=bool(df_result is not None), value=df_result))
         except Exception as e:
@@ -216,12 +214,24 @@ class DataExplorerApp:
             yield history, *[gr.update(visible=False)]*4
             
     def _safe_exec(self, code_string: str, local_vars: Dict) -> Tuple[Any, ...]:
-        output_buffer = io.StringIO()
         try:
+            output_buffer = io.StringIO()
             with redirect_stdout(output_buffer): exec(code_string, globals(), local_vars)
             return output_buffer.getvalue(), local_vars.get('fig'), local_vars.get('result_df'), None
         except Exception as e: return None, None, None, str(e)
 
 if __name__ == "__main__":
+    # Create dummy files for avatar images if they don't exist
+    if not os.path.exists("bot.png"):
+        from PIL import Image
+        img = Image.new('RGB', (100, 100), color = 'darkblue')
+        img.save('bot.png')
+    if not os.path.exists("user.png"):
+        from PIL import Image
+        img = Image.new('RGB', (100, 100), color = 'gray')
+        img.save('user.png')
+    if not os.path.exists("workflow.png"):
+        gr.Warning("workflow.png not found. The welcome screen image will be missing.")
+
     app = DataExplorerApp()
     app.launch()