Update scripts/app.py

scripts/app.py

@@ -528,75 +528,59 @@ def get_recent_transactions():
 
 custom_css = """
 .metric-box { background-color: #1f2937; padding: 20px; border-radius: 12px; border: 1px solid #374151; text-align: center; }
-.metric-label { font-size: 1.1em; color: #9ca3af; margin-bottom: 5px; }
+.metric-label { font-size: 1.1em; color: #9ca3af; }
 .metric-value { font-size: 2.2em; font-weight: 700; color: #e5e7eb; }
-.disclaimer-box { background-color: #374151; padding: 15px; border-radius: 8px; border-left: 4px solid #f59e0b; color: #d1d5db; font-size: 0.9em; margin-bottom: 20px; }
 """
 
-with gr.Blocks(css=custom_css, title="Deep RL Portfolio Manager") as demo:
-    # JS to force dark mode
+with gr.Blocks(css=custom_css, title="Deep RL Manager") as demo:
     gr.HTML("""<script>function forceDark(){document.body.classList.add('dark');} forceDark(); setTimeout(forceDark, 500);</script>""")
-    
     gr.Markdown("# 🧠 Deep RL & LLM Portfolio Manager")
     
     with gr.Tabs():
-        with gr.TabItem("📊 Live Dashboard"):
-            nw_val, dc_val = get_dashboard_metrics()
+        with gr.TabItem("📊 Dashboard"):
+            nw, chg = get_dash_metrics()
             with gr.Row():
-                gr.HTML(f"<div class='metric-box'><div class='metric-label'>Current Net Worth</div><div class='metric-value'>{nw_val}</div></div>")
-                gr.HTML(f"<div class='metric-box'><div class='metric-label'>24h Change</div><div class='metric-value' style='color: #10b981;'>{dc_val}</div></div>")
+                gr.HTML(f"<div class='metric-box'><div class='metric-label'>Simulated Net Worth</div><div class='metric-value'>{nw}</div></div>")
+                gr.HTML(f"<div class='metric-box'><div class='metric-label'>24h Change</div><div class='metric-value'>{chg}</div></div>")
             with gr.Row():
-                with gr.Column(scale=3): history_chart = gr.Plot(value=get_portfolio_history_plot())
+                with gr.Column(scale=3): gr.Plot(value=get_hist_plot(), label="History")
             with gr.Row():
-                with gr.Column(scale=1): allocation_chart = gr.Plot(value=get_current_allocation_plot())
-                with gr.Column(scale=2): 
-                    gr.Markdown("### Recent Transactions")
-                    transactions_table = gr.Dataframe(value=get_recent_transactions(), interactive=False)
-
-        with gr.TabItem("🔮 Forecast & AI Analysis"):
-            gr.Markdown("### Generate Tomorrow's Strategy")
-            run_btn = gr.Button("🚀 Run Overnight Analysis", variant="primary", size="lg")
-            status_output = gr.Textbox(label="System Status", interactive=False, lines=1)
-            gr.Markdown("---")
+                with gr.Column(scale=1): gr.Plot(value=get_current_allocation_plot(), label="Allocation")
+                with gr.Column(scale=2): gr.Dataframe(value=get_trans(), label="Transactions")
+
+        with gr.TabItem("🔮 Forecast"):
+            run_btn = gr.Button("🚀 Run Analysis", variant="primary")
+            stat = gr.Textbox(label="Status", lines=1)
             with gr.Row():
                 with gr.Column(scale=2):
-                    gr.Markdown("### 📈 Suggested Position")
-                    allocation_output = gr.Dataframe(headers=["Asset", "Allocation"], interactive=False)
-                    gr.Markdown("### 🧠 XAI Feature Importance")
-                    xai_output_plot = gr.Plot(label="Influential Factors", show_label=False)
+                    alloc_out = gr.Dataframe(headers=["Asset", "Allocation"])
+                    xai_out = gr.Plot(label="XAI Factors")
                 with gr.Column(scale=3):
-                    analysis_report_html = gr.HTML(label="AI Report")
-            run_btn.click(fn=predict_and_analyze, inputs=None, outputs=[status_output, allocation_output, xai_output_plot, analysis_report_html])
+                    ai_out = gr.HTML(label="Report")
+            run_btn.click(predict_and_analyze, None, [stat, alloc_out, xai_out, ai_out])
 
-        with gr.TabItem("📅 Historical Data Analyst"):
-            gr.Markdown("### Analyze Past Market Performance")
+        with gr.TabItem("📅 Analyst"):
             with gr.Row():
                 with gr.Column(scale=1):
-                    all_tickers = ASSETS + list(FRED_IDS.values())
-                    avail_tickers = [t for t in all_tickers if DASHBOARD_DATA_DF is not None and t in DASHBOARD_DATA_DF.columns]
-                    asset_selector = gr.Dropdown(choices=avail_tickers, value=avail_tickers[:3] if avail_tickers else [], multiselect=True, label="Select Assets")
-                    period_selector = gr.Dropdown(choices=list(TIME_PERIODS.keys()), value="1 Year", label="Select Period")
-                    analyze_btn = gr.Button("🔎 Run Analysis", variant="primary")
-                with gr.Column(scale=3):
-                    historical_plot = gr.Plot(label="Performance Plot")
-            gr.Markdown("---")
-            historical_analysis_md = gr.Markdown("### 🤖 AI Analyst Report\n\n*Click 'Run Analysis' to generate.*")
-            analyze_btn.click(fn=run_historical_analysis, inputs=[asset_selector, period_selector], outputs=[historical_plot, historical_analysis_md])
-
-        with gr.TabItem("🔙 Historical Simulation"):
-            gr.Markdown("### Backtest Strategy")
-            gr.HTML(f"<div class='disclaimer-box'>⚠️ Model trained on {TRAIN_START_DATE} to {TRAIN_END_DATE}. Outside usage may be inaccurate.</div>")
+                    ticks = ASSETS + FRED_IDS.values() if DASHBOARD_DATA_DF is None else [c for c in ASSETS + list(FRED_IDS.values()) if c in DASHBOARD_DATA_DF.columns]
+                    sel = gr.Dropdown(choices=ticks, multiselect=True, label="Assets")
+                    per = gr.Dropdown(choices=list(TIME_PERIODS.keys()), value="1 Year", label="Period")
+                    btn = gr.Button("Analyze", variant="primary")
+                with gr.Column(scale=3): plot = gr.Plot()
+            rep = gr.Markdown()
+            btn.click(run_historical_analysis, [sel, per], [plot, rep])
+
+        with gr.TabItem("🔙 Simulation"):
+            gr.Markdown("### Backtest")
             with gr.Row():
-                with gr.Column(scale=1):
-                    start_date_input = gr.Textbox(label="Start Date", value=(datetime.now()-timedelta(days=365)).strftime('%Y-%m-%d'))
-                    end_date_input = gr.Textbox(label="End Date", value=(datetime.now()-timedelta(days=1)).strftime('%Y-%m-%d'))
-                    sim_btn = gr.Button("▶️ Run Simulation", variant="primary")
-                    sim_status = gr.Textbox(label="Status", interactive=False, lines=1)
-                with gr.Column(scale=3):
-                    sim_plot = gr.Plot(label="Performance")
-            gr.Markdown("---")
-            sim_metrics_df = gr.Dataframe(interactive=False, wrap=True, label="Professional Metrics")
-            sim_btn.click(fn=run_historical_simulation, inputs=[start_date_input, end_date_input], outputs=[sim_plot, sim_status, sim_metrics_df])
+                s_date = gr.Textbox(label="Start", value=(datetime.now()-timedelta(days=365)).strftime('%Y-%m-%d'))
+                e_date = gr.Textbox(label="End", value=(datetime.now()-timedelta(days=1)).strftime('%Y-%m-%d'))
+                s_btn = gr.Button("Run", variant="primary")
+                s_stat = gr.Textbox(label="Status")
+            s_plot = gr.Plot()
+            # FIX: Using Dataframe instead of Markdown for metrics table
+            s_metrics = gr.Dataframe(label="Professional Metrics")
+            s_btn.click(run_historical_simulation, [s_date, e_date], [s_plot, s_stat, s_metrics])
 
 if __name__ == "__main__":
     demo.queue().launch(server_name="0.0.0.0", server_port=7860, debug=True, share=True)