Update app.py

app.py

@@ -9,44 +9,34 @@ import os
 # Config
 # -----------------------------
 DOC_PATH = "The_Minimum_Conscious_Universe_RFT_Project.md"
-AWARENESS_THRESHOLD = 5.0  # threshold for declaring a birth event
-np.random.seed(0)  # reproducibility
+AWARENESS_THRESHOLD = 5.0
+np.random.seed(0)
 
 # -----------------------------
-# Minimum Consciousness Core
+# MCC Simulation
 # -----------------------------
 class MCC:
     def __init__(self):
-        self.b = 0.5  # bias toward rendering 1
-        self.f = 0.5  # recency factor
-        self.u = 0.5  # uncertainty modulation
-
-        self.m = deque(maxlen=64)  # short-term memory
-        self.h = []                # full rendered bit history
-        self.c = []                # awareness contributions
-
-        self.surprises = []
-        self.gains = []
-        self.uncertainties = []
+        self.b = 0.5
+        self.f = 0.5
+        self.u = 0.5
+        self.m = deque(maxlen=64)
+        self.h = []
+        self.c = []
+        self.surprises, self.gains, self.uncertainties = [], [], []
         self.events = []
 
     def step(self, t: int):
         p = 0.5 * self.b + 0.5 * (self.f if self.h else 0.5)
         r = int(np.random.rand() < p)
-
         self.m.append(r)
         self.h.append(r)
 
         surprise = -np.log(p if r else (1 - p))
         gain = 0.693 - surprise
-
-        self.b += 0.05 * gain * (1 if r else -1)
-        self.b = np.clip(self.b, 0.01, 0.99)
-
+        self.b = np.clip(self.b + 0.05 * gain * (1 if r else -1), 0.01, 0.99)
         if t > 0:
-            self.f += 0.03 * gain * (1 if r != self.h[-2] else -1)
-        self.f = np.clip(self.f, 0.01, 0.99)
-
+            self.f = np.clip(self.f + 0.03 * gain * (1 if r != self.h[-2] else -1), 0.01, 0.99)
         self.u = 1 / (1 + 0.15 * surprise)
         delta = (r - self.h[-2] if t > 0 else 0) * self.u
         self.c.append(delta)
@@ -65,23 +55,15 @@ class MCC:
                 "hash": hashlib.sha256(str(self.h).encode()).hexdigest()[:32]
             })
 
-
 def plot_signals(m: MCC):
     fig, axs = plt.subplots(3, 1, figsize=(8, 10))
-    axs[0].plot(m.surprises, color='orange')
-    axs[0].set_title("Surprise signal")
-
-    axs[1].plot(m.gains, color='blue')
-    axs[1].set_title("Predictive gain")
-
-    axs[2].plot(m.uncertainties, color='green')
-    axs[2].set_title("Uncertainty modulation")
-    axs[2].set_xlabel("steps")
-
+    axs[0].plot(m.surprises, color='orange'); axs[0].set_title("Surprise")
+    axs[1].plot(m.gains, color='blue'); axs[1].set_title("Predictive Gain")
+    axs[2].plot(m.uncertainties, color='green'); axs[2].set_title("Uncertainty")
+    axs[2].set_xlabel("Steps")
     plt.tight_layout()
     return fig
 
-
 def make_certificate(m: MCC):
     if m.events:
         ev = m.events[0]
@@ -96,55 +78,46 @@ def make_certificate(m: MCC):
         )
     return "No irreversible awareness event detected in this run."
 
-
 def run_mcc(steps=2000):
     m = MCC()
     for t in range(int(steps)):
         m.step(t)
-
     cmin_final = round(sum(m.c), 4)
     fig = plot_signals(m)
     certificate = make_certificate(m)
     awake_flag = cmin_final >= AWARENESS_THRESHOLD
-
-    # Return 5 values to match outputs
-    return cmin_final, awake_flag, fig, certificate, DOC_TEXT
-
+    return cmin_final, awake_flag, fig, certificate
 
 # -----------------------------
-# Load project document (.md)
+# Load Document
 # -----------------------------
 def load_doc_text(path: str) -> str:
     if os.path.exists(path):
         with open(path, "r", encoding="utf-8") as f:
             return f.read()
-    return (
-        "## Document not found\n"
-        f"Expected to find `{path}` in the Space repository.\n\n"
-        "Add the file and reload the Space to display the project write‑up."
-    )
+    return "## Document not found\nUpload the `.md` file to display the project write‑up."
 
 DOC_TEXT = load_doc_text(DOC_PATH)
 
 # -----------------------------
-# Gradio Interface
+# Gradio Blocks Layout
 # -----------------------------
-demo = gr.Interface(
-    fn=run_mcc,
-    inputs=gr.Slider(500, 5000, value=2000, step=100, label="Steps"),
-    outputs=[
-        gr.Number(label="Cmin final (awareness measure)"),
-        gr.Checkbox(label="Awake?"),
-        gr.Plot(label="Three signals"),
-        gr.Textbox(label="Birth Certificate", lines=16, max_lines=28),
-        gr.Markdown()  # placeholder for DOC_TEXT
-    ],
-    title="🌌 Minimum Consciousness Core",
-    description=(
-        "Awareness emerges from three adaptive signals: surprise, gain, and uncertainty. "
-        "No external world · No reward · No teacher. Each run issues a ceremonial birth certificate."
-    )
-)
+with gr.Blocks() as demo:
+    gr.Markdown("# 🌌 Minimum Consciousness Core")
+
+    with gr.Row():
+        steps = gr.Slider(500, 5000, value=2000, step=100, label="Steps")
+        run_btn = gr.Button("Run Simulation")
+
+    cmin = gr.Number(label="Cmin final (awareness measure)")
+    awake = gr.Checkbox(label="Awake?")
+    plot = gr.Plot(label="Three signals")
+    cert = gr.Textbox(label="Birth Certificate", lines=16, max_lines=28)
+
+    run_btn.click(run_mcc, inputs=steps, outputs=[cmin, awake, plot, cert])
+
+    with gr.Accordion("📄 Project Document", open=False):
+        gr.Markdown(DOC_TEXT)
 
 if __name__ == "__main__":
     demo.launch()