Update app.py

app.py

@@ -1,6 +1,6 @@
 # ============================================================
-# RFT-Ω FRAMEWORK — TOTAL-PROOF API (Sprint 1, stable UI)
-# Author: Liam Grinstead (RFT Systems) | All Rights Reserved
+# RENDERED FRAME THEORY-Ω FRAMEWORK — API (Sprint 1, Stable Build)
+# Author: Liam Grinstead (RFT Systems)  |  All Rights Reserved
 # ============================================================
 """
 Deterministic, signed validation harness for the
@@ -10,7 +10,6 @@ Rendered Frame Theory (RFT-Ω) harmonic stability kernel.
 import os, io, json, time, math, hashlib, zipfile, random
 from datetime import datetime
 from typing import Dict, Any, List, Tuple
-
 import numpy as np
 import gradio as gr
 
@@ -42,7 +41,7 @@ ABOUT_BLOCK = {
     "legal": LEGAL_NOTICE,
 }
 
-# ------------------ Rate limit ------------------------------
+# ------------------ Rate-limit -------------------------------
 RUN_HISTORY_TS: List[float] = []
 MAX_RUNS_PER_MINUTE = 60
 
@@ -63,49 +62,41 @@ PROFILES = {
     "Extreme Perturbation":{"base": (0.82, 0.77), "w": (0.50, 0.50)},
 }
 
-def _rng(seed: int) -> np.random.RandomState:
-    return np.random.RandomState(seed)
+def _rng(seed:int)->np.random.RandomState: return np.random.RandomState(seed)
 
-def simulate_step(rng: np.random.RandomState, profile: str, sigma: float, noise_dist: str) -> Dict[str, Any]:
+def simulate_step(rng:np.random.RandomState, profile:str, sigma:float, noise_dist:str)->Dict[str,Any]:
     base_q, base_z = PROFILES[profile]["base"]
     wq, wz = PROFILES[profile]["w"]
     if noise_dist == "uniform":
         q_noise = rng.uniform(-sigma, sigma)
-        z_noise = rng.uniform(-sigma * 0.8, sigma * 0.8)
+        z_noise = rng.uniform(-sigma*0.8, sigma*0.8)
     else:
         q_noise = rng.normal(0, sigma)
-        z_noise = rng.normal(0, sigma * 0.8)
+        z_noise = rng.normal(0, sigma*0.8)
     q = float(np.clip(base_q + wq*q_noise, 0.0, 0.99))
     z = float(np.clip(base_z + wz*z_noise, 0.0, 0.99))
-    variance = abs(q_noise) + abs(z_noise)
-    if variance > 0.15:
-        status = "critical"
-    elif variance > 0.07:
-        status = "perturbed"
-    else:
-        status = "nominal"
-    return {"sigma": float(round(sigma,6)), "QΩ": q, "ζ_sync": z, "status": status}
+    variance = abs(q_noise)+abs(z_noise)
+    if variance > 0.15: status="critical"
+    elif variance > 0.07: status="perturbed"
+    else: status="nominal"
+    return {"sigma": round(sigma,6),"QΩ":q,"ζ_sync":z,"status":status}
 
 # ------------------ Schedules -------------------------------
-def build_sigma_series(schedule_type: str, params: Dict[str, Any]) -> List[float]:
-    if schedule_type == "single":
-        return [float(params.get("sigma", 0.05))]
-    elif schedule_type == "ramp":
-        return list(np.linspace(float(params.get("start",0.0)),
-                                float(params.get("stop",0.3)),
-                                int(params.get("steps",10))))
-    elif schedule_type == "random":
+def build_sigma_series(schedule_type:str, params:Dict[str,Any])->List[float]:
+    if schedule_type=="single":
+        return [float(params.get("sigma",0.05))]
+    elif schedule_type=="ramp":
+        return list(np.linspace(float(params.get("start",0.0)), float(params.get("stop",0.3)), int(params.get("steps",10))))
+    elif schedule_type=="random":
         r = random.Random(int(params.get("seed",0)))
-        return [r.uniform(float(params.get("min",0.0)),
-                          float(params.get("max",0.3)))
-                for _ in range(int(params.get("steps",10)))]
-    elif schedule_type == "impulse":
-        base, spike, at, steps = float(params.get("base",0.05)), float(params.get("spike",0.25)), int(params.get("at",5)), int(params.get("steps",10))
+        return [r.uniform(float(params.get("min",0.0)), float(params.get("max",0.3))) for _ in range(int(params.get("steps",10)))]
+    elif schedule_type=="impulse":
+        base,spike,at,steps = float(params.get("base",0.05)), float(params.get("spike",0.25)), int(params.get("at",5)), int(params.get("steps",10))
         s=[base]*steps
         if 0<=at<len(s): s[at]=spike
         return s
-    elif schedule_type == "step":
-        before, after, at, steps = float(params.get("before",0.05)), float(params.get("after",0.2)), int(params.get("at",5)), int(params.get("steps",10))
+    elif schedule_type=="step":
+        before,after,at,steps = float(params.get("before",0.05)), float(params.get("after",0.2)), int(params.get("at",5)), int(params.get("steps",10))
         s=[before]*steps
         for i in range(steps):
             if i>=at: s[i]=after
@@ -119,8 +110,7 @@ def make_run_id(seed:int,profile:str)->str:
 
 def write_bundle(run_dir:str,config:Dict[str,Any],results:Dict[str,Any])->Tuple[str,str]:
     os.makedirs(run_dir,exist_ok=True)
-    run_json=os.path.join(run_dir,"run.json")
-    with open(run_json,"w") as f: json.dump({"config":config,"results":results},f,indent=2)
+    with open(os.path.join(run_dir,"run.json"),"w") as f: json.dump({"config":config,"results":results},f,indent=2)
     canonical=json.dumps({"config":config,"results":results},sort_keys=True)
     digest=sha512_hex(canonical)
     with open(os.path.join(run_dir,"run.sha512"),"w") as f: f.write(digest+"\n")
@@ -225,7 +215,9 @@ else:
 
 # ------------------ Launch (stable queue) -------------------
 if __name__=="__main__":
-    demo.queue(concurrency_count=1,max_size=5).launch(server_name="0.0.0.0",
-                                                      server_port=7860,
-                                                      show_error=True,
-                                                      debug=False)
+    demo.queue(concurrency_limit=1, max_size=5).launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        show_error=True,
+        debug=False
+    )