feat(ui): Auto-tune tab

app.py

@@ -405,6 +405,22 @@ def run_backtest(symbol, interval, start_date, end_date,
     out_table["hit_rate_running"] = (out_table["hit_rate_running"] * 100.0).round(2)
     return fig, summary, out_table
 
+def run_autotune_ui(symbol, interval, start_date, end_date,
+                    lookback, pred_len, stride, sample_count, max_anchors):
+    def _predict(**kwargs):
+        with PREDICT_LOCK:
+            return predictor.predict(**kwargs)
+    try:
+        return autotune.run_autotune(
+            predict_fn=_predict, fetch_fn=fetch_fmp, db_path=DB_PATH,
+            symbol=symbol, interval=interval,
+            start_date=start_date, end_date=end_date,
+            lookback=lookback, pred_len=pred_len, stride=stride,
+            sample_count=sample_count, max_anchors=max_anchors,
+        )
+    except (ValueError, RuntimeError) as e:
+        raise gr.Error(str(e))
+
 # ----- UI -----
 with gr.Blocks(title="Kronos Forecast Dashboard", theme=gr.themes.Soft()) as demo:
     gr.Markdown("# 📈 Kronos Financial Forecast Dashboard\nZero-shot OHLCV forecasting powered by [Kronos](https://github.com/shiyu-coder/Kronos) + FMP market data.")
@@ -540,6 +556,40 @@ with gr.Blocks(title="Kronos Forecast Dashboard", theme=gr.themes.Soft()) as dem
                 concurrency_id="predictor", concurrency_limit=1,
             )
 
+        # ---- Auto-tune tab ----
+        with gr.Tab("Auto-tune"):
+            gr.Markdown(
+                "Search Kronos sampling knobs (T, top_p) on a 3×3 grid, score each "
+                "cell with a walk-forward backtest, and persist the best "
+                "(T, top_p) per (symbol, interval). The Forecast tab can then "
+                "pre-fill those defaults via the 🎯 checkbox."
+            )
+            with gr.Row():
+                with gr.Column(scale=1):
+                    at_symbol   = gr.Textbox("SPY", label="Symbol")
+                    at_interval = gr.Dropdown(["1min","5min","15min","30min","1hour","4hour"],
+                                              value="5min", label="Interval")
+                    at_start    = gr.Textbox("", label="Start (YYYY-MM-DD HH:MM, blank=earliest)")
+                    at_end      = gr.Textbox("", label="End (YYYY-MM-DD HH:MM, blank=latest)")
+                    at_lookback = gr.Slider(100, 400, 200, step=1, label="Lookback bars")
+                    at_predlen  = gr.Slider(5, 120, 30, step=1, label="Forecast horizon (pred_len)")
+                    at_stride   = gr.Slider(1, 120, 30, step=1, label="Stride")
+                    at_samples  = gr.Slider(1, 5, 1, step=1, label="MC samples per step")
+                    at_max      = gr.Slider(3, 30, 5, step=1,
+                                            label="Max anchors per cell (caps work; 9 cells × this)")
+                    at_btn      = gr.Button("🎯 Run auto-tune", variant="primary")
+                with gr.Column(scale=3):
+                    at_chart   = gr.Plot(label="Heatmap: P&L % over (T, top_p)")
+                    at_summary = gr.Dataframe(label="Best parameters", interactive=False)
+                    at_table   = gr.Dataframe(label="Per-cell results", interactive=False)
+            at_btn.click(
+                run_autotune_ui,
+                inputs=[at_symbol, at_interval, at_start, at_end,
+                        at_lookback, at_predlen, at_stride, at_samples, at_max],
+                outputs=[at_chart, at_summary, at_table],
+                concurrency_id="predictor", concurrency_limit=1,
+            )
+
 
 demo.queue(default_concurrency_limit=10, max_size=32)