Update app.py

app.py

@@ -3,7 +3,7 @@
 # Author: Liam Grinstead | RFT Systems | All Rights Reserved
 # ============================================================
 
-import json, hashlib, random
+import json, random
 from datetime import datetime
 import numpy as np
 import gradio as gr
@@ -18,13 +18,14 @@ LEGAL_NOTICE = (
 
 # ------------------ System Profiles -------------------------
 PROFILES = {
-    "AI / Neural": {"base": (0.86, 0.80), "w": (0.65, 0.35)},
-    "SpaceX / Aerospace": {"base": (0.84, 0.79), "w": (0.60, 0.40)},
-    "Energy / RHES": {"base": (0.83, 0.78), "w": (0.55, 0.45)},
+    "AI / Neural":          {"base": (0.86, 0.80), "w": (0.65, 0.35)},
+    "SpaceX / Aerospace":   {"base": (0.84, 0.79), "w": (0.60, 0.40)},
+    "Energy / RHES":        {"base": (0.83, 0.78), "w": (0.55, 0.45)},
     "Extreme Perturbation": {"base": (0.82, 0.77), "w": (0.50, 0.50)},
 }
 
-def _rng(seed:int): 
+# ------------------ Simulation Core -------------------------
+def _rng(seed: int):
     return np.random.RandomState(seed)
 
 def simulate_step(rng, profile, sigma, dist):
@@ -32,19 +33,22 @@ def simulate_step(rng, profile, sigma, dist):
     wq, wz = PROFILES[profile]["w"]
     if dist == "uniform":
         qn = rng.uniform(-sigma, sigma)
-        zn = rng.uniform(-sigma*0.8, sigma*0.8)
+        zn = rng.uniform(-sigma * 0.8, sigma * 0.8)
     else:
         qn = rng.normal(0, sigma)
-        zn = rng.normal(0, sigma*0.8)
-    q = float(np.clip(base_q + wq*qn, 0.0, 0.99))
-    z = float(np.clip(base_z + wz*zn, 0.0, 0.99))
+        zn = rng.normal(0, sigma * 0.8)
+
+    q = float(np.clip(base_q + wq * qn, 0.0, 0.99))
+    z = float(np.clip(base_z + wz * zn, 0.0, 0.99))
     variance = abs(qn) + abs(zn)
+
     if variance > 0.15:
         status = "critical"
     elif variance > 0.07:
         status = "perturbed"
     else:
         status = "nominal"
+
     return {"σ": round(sigma, 6), "QΩ": q, "ζ_sync": z, "status": status}
 
 # ------------------ Simulation Runner -----------------------
@@ -53,8 +57,11 @@ def run(profile, dist, sigma, seed, samples):
     results = [simulate_step(rng, profile, sigma, dist) for _ in range(samples)]
     q_mean = np.mean([r["QΩ"] for r in results])
     z_mean = np.mean([r["ζ_sync"] for r in results])
-    majority = max(["nominal","perturbed","critical"],
-                   key=lambda s: sum(1 for r in results if r["status"]==s))
+    majority = max(
+        ["nominal", "perturbed", "critical"],
+        key=lambda s: sum(1 for r in results if r["status"] == s),
+    )
+
     return {
         "profile": profile,
         "noise_scale": sigma,
@@ -63,17 +70,21 @@ def run(profile, dist, sigma, seed, samples):
         "ζ_sync_mean": round(float(z_mean), 6),
         "status_majority": majority,
         "timestamp_utc": datetime.utcnow().isoformat() + "Z",
-        "rft_notice": LEGAL_NOTICE
+        "rft_notice": LEGAL_NOTICE,
     }
 
 # ------------------ Gradio Interface ------------------------
 with gr.Blocks(title="RFT-Ω Total-Proof Kernel") as demo:
-    gr.Markdown(f"### RFT-Ω Total-Proof Kernel ({RFT_VERSION})  \n"
-                f"DOI: [{RFT_DOI}]({RFT_DOI})  \n{LEGAL_NOTICE}")
+    gr.Markdown(
+        f"### RFT-Ω Total-Proof Kernel ({RFT_VERSION}) \n"
+        f"DOI: [{RFT_DOI}]({RFT_DOI}) \n{LEGAL_NOTICE}"
+    )
 
     with gr.Row():
-        profile = gr.Dropdown(list(PROFILES.keys()), label="System Profile", value="AI / Neural")
-        dist = gr.Radio(["gauss","uniform"], label="Noise Distribution", value="gauss")
+        profile = gr.Dropdown(
+            list(PROFILES.keys()), label="System Profile", value="AI / Neural"
+        )
+        dist = gr.Radio(["gauss", "uniform"], label="Noise Distribution", value="gauss")
 
     with gr.Row():
         sigma = gr.Slider(0.0, 0.3, value=0.05, step=0.01, label="Noise Scale (σ)")
@@ -87,4 +98,5 @@ with gr.Blocks(title="RFT-Ω Total-Proof Kernel") as demo:
 
 # ------------------ Launch -------------------------------
 if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7860)
+    # Disable SSR for Hugging Face Spaces compatibility
+    demo.launch(server_name="0.0.0.0", share=False, ssr_mode=False)