Update app.py

app.py

@@ -188,26 +188,27 @@ with gr.Tab("Overview"):
     gr.Image(value="assets/banner.png", label="Progression (v1→v10)")
     gr.Image(value="assets/glyphs.png", label="Glyphs: Ξ (foresight), ◊̃₅ (shadow), ℝ (anchor)")
 
-# v1–v3 Single agent
-with gr.Tab("Single agent (v1–v3)"):
-    obstacle = gr.Checkbox(label="Enable moving obstacle (v3)", value=True)
-    steps = gr.Slider(10, 200, value=80, step=10, label="Steps")
-    run = gr.Button("Run")
-    grid_img = gr.Image(type="pil", label="3×3 grid (gold = agent position)")
-    pr_out = gr.Number(label="Predictive rate (%)")
-    err_out = gr.Number(label="Last error")
-
-    def run_single(ob_on, T):
-        agent = MinimalSelf()
-        obs = MovingObstacle() if ob_on else None
-        for _ in range(int(T)):
-            res = agent.step(obstacle=obs)
-        mask = np.zeros((3, 3), dtype=bool)
-        i, j = int(agent.pos[1]), int(agent.pos[0])
-        mask[i, j] = True
-        img = draw_grid(3, mask, title="Single Agent", subtitle="Gold cell shows current position")
-        return img, res["predictive_rate"], res["error"]
-
+ with gr.Blocks(title="Minimal Selfhood Threshold") as demo:
+    with gr.Tab("Single agent (v1–v3)"):
+        obstacle = gr.Checkbox(label="Enable moving obstacle (v3)", value=True)
+        steps = gr.Slider(10, 200, value=80, step=10, label="Steps")
+        run = gr.Button("Run")
+        grid_img = gr.Image(type="pil", label="3×3 grid (gold = agent position)")
+        pr_out = gr.Number(label="Predictive rate (%)")
+        err_out = gr.Number(label="Last error")
+
+        def run_single(ob_on, T):
+            agent = MinimalSelf()
+            obs = MovingObstacle() if ob_on else None
+            for _ in range(int(T)):
+                res = agent.step(obstacle=obs)
+            mask = np.zeros((3, 3), dtype=bool)
+            i, j = int(agent.pos[1]), int(agent.pos[0])
+            mask[i, j] = True
+            img = draw_grid(3, mask, title="Single Agent", subtitle="Gold cell shows current position")
+            return img, res["predictive_rate"], res["error"]
+
+        # 👇 This must stay inside the Blocks context
         run.click(run_single, inputs=[obstacle, steps], outputs=[grid_img, pr_out, err_out])
 
 # v4 S-Equation