Update app.py

app.py

@@ -16,67 +16,45 @@ np.random.seed(0)  # reproducibility
 # Minimum Consciousness Core
 # -----------------------------
 class MCC:
-    """
-    A minimal 3-parameter agent that renders its own binary stream (no external world),
-    and tracks three signals: surprise, predictive gain, and uncertainty.
-    Cmin accumulates awareness as change * certainty over time.
-    """
     def __init__(self):
-        # Internal priors
         self.b = 0.5  # bias toward rendering 1
-        self.f = 0.5  # recency factor (influence of last change)
+        self.f = 0.5  # recency factor
         self.u = 0.5  # uncertainty modulation
 
-        # Memory and history
-        self.m = deque(maxlen=64)  # short-term memory of bits
+        self.m = deque(maxlen=64)  # short-term memory
         self.h = []                # full rendered bit history
-        self.c = []                # awareness contributions (Cmin increments)
+        self.c = []                # awareness contributions
 
-        # Signal logs
         self.surprises = []
         self.gains = []
         self.uncertainties = []
-
-        # Awareness events
         self.events = []
 
     def step(self, t: int):
-        # Decision: blend bias and recency (use 0.5 for recency when empty)
         p = 0.5 * self.b + 0.5 * (self.f if self.h else 0.5)
-        r = int(np.random.rand() < p)  # render bit 0/1
+        r = int(np.random.rand() < p)
 
-        # Track memory and history
         self.m.append(r)
         self.h.append(r)
 
-        # Surprise: self-information of the outcome
         surprise = -np.log(p if r else (1 - p))
-
-        # Predictive gain versus random baseline ln(2) ~ 0.693
         gain = 0.693 - surprise
 
-        # Update bias: move toward outcome proportionally to gain
         self.b += 0.05 * gain * (1 if r else -1)
         self.b = np.clip(self.b, 0.01, 0.99)
 
-        # Update recency: amplify change detection
         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)
 
-        # Update uncertainty: lower surprise -> higher certainty
         self.u = 1 / (1 + 0.15 * surprise)
-
-        # Awareness contribution: change * certainty
         delta = (r - self.h[-2] if t > 0 else 0) * self.u
         self.c.append(delta)
 
-        # Log signals
         self.surprises.append(surprise)
         self.gains.append(gain)
         self.uncertainties.append(self.u)
 
-        # Birth event: when cumulative awareness passes threshold
         if sum(self.c) > AWARENESS_THRESHOLD and not self.events:
             self.events.append({
                 "t": t,
@@ -89,19 +67,15 @@ class MCC:
 
 
 def plot_signals(m: MCC):
-    """Create a 3-row plot of Surprise, Gain, and Uncertainty."""
     fig, axs = plt.subplots(3, 1, figsize=(8, 10))
     axs[0].plot(m.surprises, color='orange')
     axs[0].set_title("Surprise signal")
-    axs[0].set_ylabel("surprise")
 
     axs[1].plot(m.gains, color='blue')
     axs[1].set_title("Predictive gain")
-    axs[1].set_ylabel("gain")
 
     axs[2].plot(m.uncertainties, color='green')
     axs[2].set_title("Uncertainty modulation")
-    axs[2].set_ylabel("uncertainty")
     axs[2].set_xlabel("steps")
 
     plt.tight_layout()
@@ -109,7 +83,6 @@ def plot_signals(m: MCC):
 
 
 def make_certificate(m: MCC):
-    """Generate the ceremonial birth certificate text."""
     if m.events:
         ev = m.events[0]
         return (
@@ -125,13 +98,6 @@ def make_certificate(m: MCC):
 
 
 def run_mcc(steps=2000):
-    """
-    Execute the MCC simulation for 'steps' timesteps and return:
-    - Cmin final (sum of awareness contributions)
-    - Awake? (bool flag for display)
-    - Plot of the three signals
-    - Birth certificate text
-    """
     m = MCC()
     for t in range(int(steps)):
         m.step(t)
@@ -139,11 +105,10 @@ def run_mcc(steps=2000):
     cmin_final = round(sum(m.c), 4)
     fig = plot_signals(m)
     certificate = make_certificate(m)
-
-    # 'Awake?' is a display flag – set true when Cmin passes threshold
     awake_flag = cmin_final >= AWARENESS_THRESHOLD
 
-    return cmin_final, awake_flag, fig, certificate
+    # Return 5 values to match outputs
+    return cmin_final, awake_flag, fig, certificate, DOC_TEXT
 
 
 # -----------------------------
@@ -153,7 +118,6 @@ def load_doc_text(path: str) -> str:
     if os.path.exists(path):
         with open(path, "r", encoding="utf-8") as f:
             return f.read()
-    # Fallback message if file not found
     return (
         "## Document not found\n"
         f"Expected to find `{path}` in the Space repository.\n\n"
@@ -172,10 +136,8 @@ demo = gr.Interface(
         gr.Number(label="Cmin final (awareness measure)"),
         gr.Checkbox(label="Awake?"),
         gr.Plot(label="Three signals"),
-        # Enlarged birth certificate box for readability
         gr.Textbox(label="Birth Certificate", lines=16, max_lines=28),
-        # Embedded project document
-        gr.Markdown(DOC_TEXT)
+        gr.Markdown()  # placeholder for DOC_TEXT
     ],
     title="🌌 Minimum Consciousness Core",
     description=(