Update app.py

app.py

@@ -14,7 +14,7 @@ warnings.filterwarnings('ignore')
 
 CSS = """
 /* --- Phoenix UI Professional Dark CSS --- */
-body { --body-background-fill: #111827; }
+#app-title { text-align: center; font-weight: 800; font-size: 2.5rem; }
 .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; }
@@ -34,14 +34,10 @@ class DataExplorerApp:
         self.demo = self._build_ui()
 
     def _build_ui(self) -> gr.Blocks:
-        """
-        Defines all UI components, arranges them in the layout,
-        and registers all event handlers within the same Blocks context.
-        """
-        with gr.Blocks(theme=gr.themes.Glass(primary_hue="indigo", secondary_hue="blue"), css=CSS, title="Professional AI Data Explorer") as demo:
-            # --- State Management ---
+        """Defines, arranges, and connects all UI components and logic."""
+        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 ---
             # Sidebar
             cockpit_btn = gr.Button("📊 Data Cockpit", elem_classes="selected", elem_id="cockpit")
@@ -53,8 +49,8 @@ class DataExplorerApp:
             suggestion_btn = gr.Button("Get Smart Suggestions", variant="secondary", interactive=False)
             
             # Cockpit
-            rows_stat, cols_stat = gr.Textbox("0", interactive=False, elem_classes="stat-card-value"), gr.Textbox("0", interactive=False, elem_classes="stat-card-value")
-            quality_stat, time_cols_stat = gr.Textbox("0%", interactive=False, elem_classes="stat-card-value"), gr.Textbox("0", interactive=False, elem_classes="stat-card-value")
+            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)
             suggestion_buttons = [gr.Button(visible=False) for _ in range(5)]
             
             # Deep Dive
@@ -63,10 +59,10 @@ class DataExplorerApp:
             y_col_dd = gr.Dropdown([], label="Y-Axis (for Scatter/Box)", visible=False, interactive=False)
             add_plot_btn = gr.Button("Add to Dashboard", variant="primary", interactive=False)
             clear_plots_btn = gr.Button("Clear Dashboard")
-            dashboard_gallery = gr.Gallery(label="📊 Your Custom Dashboard", height="auto", columns=2, preview=True)
+            dashboard_gallery = gr.Gallery(label="📊 Your Custom Dashboard", height="auto", columns=[1, 2], preview=True)
 
             # Co-pilot
-            chatbot = gr.Chatbot(height=500, label="Conversation", show_copy_button=True)
+            chatbot = gr.Chatbot(height=500, label="Conversation", show_copy_button=True, avatar_images=("user.png", "bot.png"))
             copilot_explanation = gr.Markdown(visible=False, elem_classes="explanation-block")
             copilot_code = gr.Code(language="python", visible=False, label="Executed Code")
             copilot_plot = gr.Plot(visible=False, label="Generated Visualization")
@@ -77,13 +73,12 @@ class DataExplorerApp:
             # --- Layout Arrangement ---
             with gr.Row():
                 with gr.Column(scale=1, elem_classes="sidebar"):
-                    gr.Markdown("## 🚀 AI Explorer Pro"); cockpit_btn; deep_dive_btn; copilot_btn; gr.Markdown("---")
+                    gr.Markdown("## 🚀 AI Explorer Pro", elem_id="app-title"); cockpit_btn; deep_dive_btn; copilot_btn; gr.Markdown("---")
                     file_input; status_output; gr.Markdown("---"); api_key_input; suggestion_btn
                 with gr.Column(scale=4):
                     welcome_page = gr.Column(visible=True)
                     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.")
-                        gr.Image("workflow.png", show_label=False, show_download_button=False, container=False)
                     
                     cockpit_page = gr.Column(visible=False)
                     with cockpit_page:
@@ -108,35 +103,31 @@ class DataExplorerApp:
                         with gr.Accordion("AI's Detailed Response", open=True): copilot_explanation; copilot_code; copilot_plot; copilot_table
                         with gr.Row(): chat_input; chat_submit_btn
             
-            # --- Event Handlers Registration (inside the 'with' block) ---
-            pages = [cockpit_page, deep_dive_page, copilot_page]
+            # --- Event Handlers Registration ---
+            pages = [welcome_page, cockpit_page, deep_dive_page, copilot_page]
             nav_buttons = [cockpit_btn, deep_dive_btn, copilot_btn]
             
             for i, btn in enumerate(nav_buttons):
-                btn.click(
-                    lambda id=btn.elem_id: self._switch_page(id), outputs=pages
-                ).then(
-                    lambda i=i: [gr.update(elem_classes="selected" if j==i else "") for j in range(len(nav_buttons))], outputs=nav_buttons
-                )
+                btn.click(lambda id=btn.elem_id: self._switch_page(id, pages), outputs=pages).then(
+                    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,
                 x_col_dd, y_col_dd, add_plot_btn
-            ]).then(lambda: self._switch_page("cockpit"), outputs=pages) \
-            .then(lambda: [gr.update(elem_classes="selected"), gr.update(elem_classes=""), gr.update(elem_classes="")], outputs=nav_buttons)
+            ]).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])
-
             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_gallery])
             clear_plots_btn.click(self.clear_dashboard, inputs=[state_var], outputs=[state_var, dashboard_gallery])
-
             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=[cockpit_page, deep_dive_page, copilot_page, chat_input]) \
-                .then(lambda: self._switch_page("co-pilot"), outputs=pages) \
-                .then(lambda: (gr.update(elem_classes=""), gr.update(elem_classes=""), gr.update(elem_classes="selected")), outputs=nav_buttons)
+                btn.click(self.handle_suggestion_click, inputs=[btn], outputs=[welcome_page, cockpit_page, deep_dive_page, copilot_page, chat_input]) \
+                   .then(lambda: self._switch_page("co-pilot", pages), outputs=pages) \
+                   .then(lambda: (gr.update(elem_classes=""), gr.update(elem_classes=""), gr.update(elem_classes="selected")), outputs=nav_buttons)
             
             chat_submit_btn.click(self.respond_to_chat, [state_var, api_key_input, chat_input, chatbot], [chatbot, copilot_explanation, copilot_code, copilot_plot, copilot_table]).then(lambda: "", outputs=[chat_input])
             chat_input.submit(self.respond_to_chat, [state_var, api_key_input, chat_input, chatbot], [chatbot, copilot_explanation, copilot_code, copilot_plot, copilot_table]).then(lambda: "", outputs=[chat_input])
@@ -144,12 +135,14 @@ class DataExplorerApp:
         return demo
 
     def launch(self):
-        """Launches the Gradio application."""
         self.demo.launch(debug=True)
 
-    # --- Backend Logic Methods ---
-    def _switch_page(self, page_id: str) -> Tuple[gr.update, ...]:
-        return gr.update(visible=page_id=="cockpit"), gr.update(visible=page_id=="deep_dive"), gr.update(visible=page_id=="co-pilot")
+    def _switch_page(self, page_id: str, all_pages: List) -> List[gr.update]:
+        visibility_updates = [gr.update(visible=False)] * len(all_pages)
+        if page_id == "cockpit": visibility_updates[1] = gr.update(visible=True)
+        elif page_id == "deep_dive": visibility_updates[2] = gr.update(visible=True)
+        elif page_id == "co-pilot": visibility_updates[3] = gr.update(visible=True)
+        return visibility_updates
     
     def _update_plot_controls(self, plot_type: str) -> gr.update:
         return gr.update(visible=plot_type in ['scatter', 'box'])
@@ -157,16 +150,10 @@ class DataExplorerApp:
     def load_and_process_file(self, file_obj: Any) -> Tuple[Any, ...]:
         try:
             df = pd.read_csv(file_obj.name, low_memory=False)
-            for col in df.select_dtypes(include=['object']).columns:
-                try: df[col] = pd.to_datetime(df[col], errors='raise')
-                except (ValueError, TypeError): continue
-            
             metadata = self._extract_dataset_metadata(df)
             state = {'df': df, 'metadata': metadata, 'dashboard_plots': []}
-            status_msg = f"✅ **{os.path.basename(file_obj.name)}** loaded."
             rows, cols, quality = metadata['shape'][0], metadata['shape'][1], metadata['data_quality']
-            
-            return (state, status_msg, gr.update(visible=False), gr.update(visible=True),
+            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))
         except Exception as e:
@@ -179,11 +166,11 @@ class DataExplorerApp:
                 'numeric_cols': df.select_dtypes(include=np.number).columns.tolist(),
                 'categorical_cols': df.select_dtypes(include=['object', 'category']).columns.tolist(),
                 'datetime_cols': df.select_dtypes(include=['datetime64', 'datetime64[ns]']).columns.tolist(),
-                'dtypes_head': df.head().to_string()}
+                'dtypes_head': df.head(3).to_string(),
+                'data_quality': quality} # <--- CRITICAL FIX: KEY ADDED HERE
 
     def add_plot_to_dashboard(self, state: Dict, x_col: str, y_col: Optional[str], plot_type: str) -> Tuple[Dict, List]:
-        if not x_col:
-            gr.Warning("Please select at least an X-axis column."); return state, state.get('dashboard_plots', [])
+        if not x_col: gr.Warning("Please select at least an X-axis column."); return state, state.get('dashboard_plots', [])
         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:
@@ -196,17 +183,15 @@ class DataExplorerApp:
             if fig:
                 fig.update_layout(template="plotly_dark"); state['dashboard_plots'].append(fig); gr.Info(f"Added '{title}' to the dashboard.")
             return state, state['dashboard_plots']
-        except Exception as e:
-            gr.Error(f"Plotting Error: {e}"); return state, state.get('dashboard_plots', [])
+        except Exception as e: gr.Error(f"Plotting Error: {e}"); return state, state.get('dashboard_plots', [])
 
     def clear_dashboard(self, state: Dict) -> Tuple[Dict, List]:
         state['dashboard_plots'] = []; gr.Info("Dashboard cleared."); return state, []
 
     def get_ai_suggestions(self, state: Dict, api_key: str) -> List[gr.update]:
-        if not api_key: gr.Warning("API Key is required for suggestions."); return [gr.update(visible=False)]*5
+        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
-        metadata = state['metadata']
-        prompt = f"""Based on this metadata (columns: {metadata['columns']}), generate 4 impactful analytical questions. Return ONLY a JSON list of strings."""
+        metadata, prompt = state['metadata'], 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)
@@ -214,22 +199,22 @@ class DataExplorerApp:
         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=True), question
+        return gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(visible=True), 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 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...
+        metadata, prompt = state['metadata'], f"""You are 'Chief Data Scientist', an expert AI analyst. Your goal is to answer a user's question about a pandas DataFrame (`df`) by writing and executing Python code.
         **Instructions:**
-        1. **Analyze:** Understand the user's intent.
-        2. **Method:** Choose the best method (table, value, or plot). Infer the best plot type.
-        3. **Plan:** Briefly explain your plan.
-        4. **Code:** Write Python code. Use `fig` for plots (with `template='plotly_dark'`) and `result_df` for tables.
-        5. **Insight:** Provide a one-sentence business insight.
-        6. **Respond ONLY with a single JSON object with keys: "plan", "code", "insight".**
+        1. **Analyze:** Understand the user's intent. Infer the best plot type if not specified.
+        2. **Plan:** Briefly explain your plan of attack.
+        3. **Code:** Write Python code. Use `fig` for plots (with `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}"
         """