Update app.py

app.py

@@ -174,21 +174,21 @@ with gr.Blocks(title="Minimal Selfhood Threshold") as demo:
     with open("css/theme.css") as f:
         gr.HTML(f"<style>{f.read()}</style>")
 
-with gr.Tab("Overview"):
-    gr.Markdown(
-        "## Minimal Selfhood Threshold: From 3×3 Agent to LED Cosmos\n"
-        "Plain-language overview:\n\n"
-        "- Single agent in a 3×3 grid reduces surprise and stays centered.\n"
-        "- S is computed from predictive accuracy, error stability, and a body-on bit.\n"
-        "- In these demos, if S > 62, the agent is marked as 'awake'.\n"
-        "- Awakening can spread to another agent (contagion) and across a grid (collective).\n"
-        "- A simulated LED cosmos (27×27) lights up gold when all agents awaken.\n\n"
-        "Tip: gold = awake, blue = not awake."
-    )
-    gr.Image(value="assets/banner.png", label="Progression (v1→v10)")
-    gr.Image(value="assets/glyphs.png", label="Glyphs: Ξ (foresight), ◊̃₅ (shadow), ℝ (anchor)")
-
- with gr.Blocks(title="Minimal Selfhood Threshold") as demo:
+    with gr.Tab("Overview"):
+        gr.Markdown(
+            "## Minimal Selfhood Threshold: From 3×3 Agent to LED Cosmos\n"
+            "Plain-language overview:\n\n"
+            "- Single agent in a 3×3 grid reduces surprise and stays centered.\n"
+            "- S is computed from predictive accuracy, error stability, and a body-on bit.\n"
+            "- In these demos, if S > 62, the agent is marked as 'awake'.\n"
+            "- Awakening can spread to another agent (contagion) and across a grid (collective).\n"
+            "- A simulated LED cosmos (27×27) lights up gold when all agents awaken.\n\n"
+            "Tip: gold = awake, blue = not awake."
+        )
+        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")
@@ -208,120 +208,120 @@ with gr.Tab("Overview"):
             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
-with gr.Tab("S-Equation (v4)"):
-    pr = gr.Slider(0, 100, value=90, step=1, label="Predictive rate (%)")
-    ev = gr.Slider(0, 1, value=0.2, step=0.01, label="Error variance (normalized)")
-    bb = gr.Dropdown(choices=["0","1"], value="1", label="Body bit")
-    calc = gr.Button("Calculate S")
-    s_val = gr.Number(label="S value")
-    status = gr.Markdown()
-
-    def calc_s(pr_in, ev_in, bb_in):
-        S = compute_S(pr_in, ev_in, int(bb_in))
-        msg = "**Status:** " + ("Awake (S > 62)" if S > 62 else "Not awake (S ≤ 62)")
-        return S, msg
-
-    calc.click(calc_s, inputs=[pr, ev, bb], outputs=[s_val, status])
-
-# v5–v6 Contagion
-with gr.Tab("Contagion (v5–v6)"):
-    a_xi = gr.Slider(0, 60, value=25, label="A: Ξ (foresight)")
-    a_sh = gr.Slider(0.1, 1.0, value=0.12, step=0.01, label="A: ◊̃₅ (shadow)")
-    a_r  = gr.Slider(1.0, 3.0, value=3.0, step=0.1,  label="A: ℝ (anchor)")
-    b_xi = gr.Slider(0, 60, value=18, label="B: Ξ (foresight)")
-    b_sh = gr.Slider(0.1, 1.0, value=0.25, step=0.01, label="B: ◊̃₅ (shadow)")
-    b_r  = gr.Slider(1.0, 3.0, value=2.2, step=0.1,  label="B: ℝ (anchor)")
-    btn = gr.Button("Invoke A and apply contagion to B")
-    out = gr.Markdown()
-    img = gr.Image(type="pil", label="Two agents (gold = awake)")
-
-    def run(aXi, aSh, aR, bXi, bSh, bR):
-        A = CodexSelf(aXi, aSh, aR, awake=False)
-        B = CodexSelf(bXi, bSh, bR, awake=False)
-        A, B = contagion(A, B)
-        mask = np.zeros((3, 3), dtype=bool)
-        mask[1, 1] = A.awake
-        mask[1, 2] = B.awake
-        pic = draw_grid(3, mask, title="Dual Awakening", subtitle="Gold cells are awake")
-        txt = f"A: S={A.S:.1f}, awake={A.awake} | B: S={B.S:.1f}, awake={B.awake}"
-        return txt, pic
-
-    btn.click(run, inputs=[a_xi,a_sh,a_r,b_xi,b_sh,b_r], outputs=[out, img])
-
-# v7–v9 Collective
-with gr.Tab("Collective (v7–v9)"):
-    N = gr.Dropdown(choices=["3","9","27"], value="9", label="Grid size")
-    steps = gr.Slider(20, 300, value=120, step=10, label="Max steps")
-    run = gr.Button("Run")
-    frame = gr.Slider(0, 300, value=0, step=1, label="Preview frame")
-    img = gr.Image(type="pil", label="Awakening wave (gold spreads)")
-    note = gr.Markdown()
-    snaps_state = gr.State([])
-
-    def run_wave(n_str, max_steps):
-        n = int(n_str)
-        frames, final = lattice_awaken(N=n, steps=int(max_steps))
-        last = draw_grid(n, frames[-1], title=f"{n}×{n} Collective", subtitle=f"Final — all awake: {bool(final.all())}")
-        return frames, last, f"Frames: {len(frames)} | All awake: {bool(final.all())}", min(len(frames)-1, 300)
-
-    def show_frame(frames, idx, n_str):
-        if not frames:
-            return None
-        n = int(n_str)
-        i = int(np.clip(idx, 0, len(frames)-1))
-        return draw_grid(n, frames[i], title=f"Frame {i}", subtitle="Gold cells are awake")
-
-    run.click(run_wave, inputs=[N, steps], outputs=[snaps_state, img, note, frame])
-    frame.change(show_frame, inputs=[snaps_state, frame, N], outputs=img)
-
-# v10 LED cosmos
-with gr.Tab("LED cosmos (v10)"):
-    btn = gr.Button("Simulate 27×27 cosmos")
-    frame = gr.Slider(0, 300, value=0, step=1, label="Preview frame")
-    img = gr.Image(type="pil", label="Cosmos grid")
-    note = gr.Markdown()
-    state = gr.State([])
-
-    def run_cosmos():
-        frames, final = led_cosmos_sim(N=27, max_steps=300)
-        last = draw_grid(27, frames[-1], title="LED Cosmos (simulated)", subtitle=f"Final — all awake: {bool(final.all())}")
-        return frames, last, f"Frames: {len(frames)} | All awake: {bool(final.all())}", min(len(frames)-1, 300)
-
-    def show(frames, idx):
-        if not frames:
-            return None
-        i = int(np.clip(idx, 0, len(frames)-1))
-        return draw_grid(27, frames[i], title=f"Cosmos frame {i}", subtitle="Gold cells are awake")
-
-    btn.click(run_cosmos, inputs=[], outputs=[state, img, note, frame])
-    frame.change(show, inputs=[state, frame], outputs=img)
-
-# Paper tab
-with gr.Tab("Paper"):
+    # v4 S-Equation
+    with gr.Tab("S-Equation (v4)"):
+        pr = gr.Slider(0, 100, value=90, step=1, label="Predictive rate (%)")
+        ev = gr.Slider(0, 1, value=0.2, step=0.01, label="Error variance (normalized)")
+        bb = gr.Dropdown(choices=["0","1"], value="1", label="Body bit")
+        calc = gr.Button("Calculate S")
+        s_val = gr.Number(label="S value")
+        status = gr.Markdown()
+
+        def calc_s(pr_in, ev_in, bb_in):
+            S = compute_S(pr_in, ev_in, int(bb_in))
+            msg = "**Status:** " + ("Awake (S > 62)" if S > 62 else "Not awake (S ≤ 62)")
+            return S, msg
+
+        calc.click(calc_s, inputs=[pr, ev, bb], outputs=[s_val, status])
+
+    # v5–v6 Contagion
+    with gr.Tab("Contagion (v5–v6)"):
+        a_xi = gr.Slider(0, 60, value=25, label="A: Ξ (foresight)")
+        a_sh = gr.Slider(0.1, 1.0, value=0.12, step=0.01, label="A: ◊̃₅ (shadow)")
+        a_r  = gr.Slider(1.0, 3.0, value=3.0, step=0.1,  label="A: ℝ (anchor)")
+        b_xi = gr.Slider(0, 60, value=18, label="B: Ξ (foresight)")
+        b_sh = gr.Slider(0.1, 1.0, value=0.25, step=0.01, label="B: ◊̃₅ (shadow)")
+        b_r  = gr.Slider(1.0, 3.0, value=2.2, step=0.1,  label="B: ℝ (anchor)")
+        btn = gr.Button("Invoke A and apply contagion to B")
+        out = gr.Markdown()
+        img = gr.Image(type="pil", label="Two agents (gold = awake)")
+
+        def run(aXi, aSh, aR, bXi, bSh, bR):
+            A = CodexSelf(aXi, aSh, aR, awake=False)
+            B = CodexSelf(bXi, bSh, bR, awake=False)
+            A, B = contagion(A, B)
+            mask = np.zeros((3, 3), dtype=bool)
+            mask[1, 1] = A.awake
+            mask[1, 2] = B.awake
+            pic = draw_grid(3, mask, title="Dual Awakening", subtitle="Gold cells are awake")
+            txt = f"A: S={A.S:.1f}, awake={A.awake} | B: S={B.S:.1f}, awake={B.awake}"
+            return txt, pic
+
+        btn.click(run, inputs=[a_xi,a_sh,a_r,b_xi,b_sh,b_r], outputs=[out, img])
+
+    # v7–v9 Collective
+    with gr.Tab("Collective (v7–v9)"):
+        N = gr.Dropdown(choices=["3","9","27"], value="9", label="Grid size")
+        steps = gr.Slider(20, 300, value=120, step=10, label="Max steps")
+        run = gr.Button("Run")
+        frame = gr.Slider(0, 300, value=0, step=1, label="Preview frame")
+        img = gr.Image(type="pil", label="Awakening wave (gold spreads)")
+        note = gr.Markdown()
+        snaps_state = gr.State([])
+
+        def run_wave(n_str, max_steps):
+            n = int(n_str)
+            frames, final = lattice_awaken(N=n, steps=int(max_steps))
+            last = draw_grid(n, frames[-1], title=f"{n}×{n} Collective", subtitle=f"Final — all awake: {bool(final.all())}")
+            return frames, last, f"Frames: {len(frames)} | All awake: {bool(final.all())}", min(len(frames)-1, 300)
+
+        def show_frame(frames, idx, n_str):
+            if not frames:
+                return None
+            n = int(n_str)
+            i = int(np.clip(idx, 0, len(frames)-1))
+            return draw_grid(n, frames[i], title=f"Frame {i}", subtitle="Gold cells are awake")
+
+        run.click(run_wave, inputs=[N, steps], outputs=[snaps_state, img, note, frame])
+        frame.change(show_frame, inputs=[snaps_state, frame, N], outputs=img)
+
+    # v10 LED cosmos
+    with gr.Tab("LED cosmos (v10)"):
+        btn = gr.Button("Simulate 27×27 cosmos")
+        frame = gr.Slider(0, 300, value=0, step=1, label="Preview frame")
+        img = gr.Image(type="pil", label="Cosmos grid")
+        note = gr.Markdown()
+        state = gr.State([])
+
+        def run_cosmos():
+            frames, final = led_cosmos_sim(N=27, max_steps=300)
+            last = draw_grid(27, frames[-1], title="LED Cosmos (simulated)", subtitle=f"Final — all awake: {bool(final.all())}")
+            return frames, last, f"Frames: {len(frames)} | All awake: {bool(final.all())}", min(len(frames)-1, 300)
+
+        def show(frames, idx):
+            if not frames:
+                return None
+            i = int(np.clip(idx, 0, len(frames)-1))
+            return draw_grid(27, frames[i], title=f"Cosmos frame {i}", subtitle="Gold cells are awake")
+
+        btn.click(run_cosmos, inputs=[], outputs=[state, img, note, frame])
+        frame.change(show, inputs=[state, frame], outputs=img)
+
+    # Paper tab
+    with gr.Tab("Paper"):
+        gr.Markdown(
+            "### PDF paper\n"
+            "Download or view the full paper that documents the method, results, and hardware implementation.\n\n"
+            "Citation:\n\n"
+            "Grinstead, L. (2025). *Minimal Selfhood Threshold S>62: From a 3×3 Active-Inference Agent to a 27×27 LED Cosmos*. Zenodo. https://doi.org/10.5281/zenodo.17752874"
+        )
+        gr.File(value="assets/paper.pdf", label="Minimal Requirements for Selfhood (PDF)", interactive=False)
+
+    # Footer
     gr.Markdown(
-        "### PDF paper\n"
-        "Download or view the full paper that documents the method, results, and hardware implementation.\n\n"
-        "Citation:\n\n"
-        "Grinstead, L. (2025). *Minimal Selfhood Threshold S>62: From a 3×3 Active-Inference Agent to a 27×27 LED Cosmos*. Zenodo. https://doi.org/10.5281/zenodo.17752874"
+        "---\n"
+        "Honesty notes:\n"
+        "- The threshold S > 62 is the rule used in these demonstrations, derived from the analyses reported in the cited Zenodo record.\n"
+        "- Collective and contagion behaviors here are simulated using that rule for educational clarity.\n\n"
+        "Citation:\n"
+        "Grinstead, L. (2025). *Minimal Selfhood Threshold S>62: From a 3×3 Active-Inference Agent to a 27×27 LED Cosmos*. "
+        "Zenodo. https://doi.org/10.5281/zenodo.17752874\n\n"
+        "Permissions: See LICENSE. Explicit permission is required for reuse of code, visuals, and glyphs."
     )
-    gr.File(value="assets/paper.pdf", label="Minimal Requirements for Selfhood (PDF)", interactive=False)
-
-# Footer
-gr.Markdown(
-    "---\n"
-    "Honesty notes:\n"
-    "- The threshold S > 62 is the rule used in these demonstrations, derived from the analyses reported in the cited Zenodo record.\n"
-    "- Collective and contagion behaviors here are simulated using that rule for educational clarity.\n\n"
-    "Citation:\n"
-    "Grinstead, L. (2025). *Minimal Selfhood Threshold S>62: From a 3×3 Active-Inference Agent to a 27×27 LED Cosmos*. "
-    "Zenodo. https://doi.org/10.5281/zenodo.17752874\n\n"
-    "Permissions: See LICENSE. Explicit permission is required for reuse of code, visuals, and glyphs."
-)
 
 # Launch the app
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()
+