Update app.py

app.py

@@ -1,5 +1,5 @@
 # ============================================================
-# RFT-Ω FRAMEWORK — TOTAL-PROOF KERNEL (Gradio Stable Build)
+# Rendered Frame Theory — Stabilising System Verification Panel
 # Author: Liam Grinstead | RFT Systems | All Rights Reserved
 # ============================================================
 
@@ -9,7 +9,7 @@ import numpy as np
 import gradio as gr
 
 # ------------------ About / Legal ---------------------------
-RFT_VERSION = "v4.0-total-proof-stable"
+RFT_VERSION = "v4.0-verification-panel"
 RFT_DOI = "https://doi.org/10.5281/zenodo.17466722"
 LEGAL_NOTICE = (
     "All Rights Reserved — RFT-IPURL v1.0 (UK / Berne). "
@@ -62,7 +62,7 @@ def run(profile, dist, sigma, seed, samples):
         key=lambda s: sum(1 for r in results if r["status"] == s),
     )
 
-    return {
+    summary = {
         "profile": profile,
         "noise_scale": sigma,
         "distribution": dist,
@@ -72,37 +72,48 @@ def run(profile, dist, sigma, seed, samples):
         "timestamp_utc": datetime.utcnow().isoformat() + "Z",
         "rft_notice": LEGAL_NOTICE,
     }
+    return summary, json.dumps(summary, indent=2)
+
+# ------------------ File Saver -------------------------------
+def save_run_log(run_json_str):
+    try:
+        data = json.loads(run_json_str)
+        filename = f"RFT_Omega_Run_{datetime.utcnow().strftime('%Y-%m-%dT%H-%M-%SZ')}.json"
+        with open(filename, "w") as f:
+            json.dump(data, f, indent=2)
+        return filename
+    except Exception as e:
+        return None
 
 # ------------------ Gradio Interface ------------------------
-with gr.Blocks(title="RFT-Ω Total-Proof Kernel") as demo:
+with gr.Blocks(title="Rendered Frame Theory — Stabilising System Verification Panel") as demo:
     gr.Markdown(
-        f"### 🧠 RFT-Ω Total-Proof Kernel ({RFT_VERSION}) \n"
-        f"DOI: [{RFT_DOI}]({RFT_DOI})  \n"
+        f"## 🧠 Rendered Frame Theory — Stabilising System Verification Panel  \n"
+        f"**Version:** {RFT_VERSION}  \n"
+        f"**DOI:** [{RFT_DOI}]({RFT_DOI})  \n"
         f"{LEGAL_NOTICE}"
     )
 
-    # ---- New Instruction Panel ----
     gr.Markdown(
         """
-        🧩 **How to Use:**  
+        ### 🧩 How to Use  
         1️⃣ Select a **System Profile** (AI / Neural, SpaceX / Aerospace, Energy / RHES, Extreme Perturbation).  
         2️⃣ Choose a **Noise Distribution** (gauss or uniform).  
-        3️⃣ Adjust **Noise Scale (σ)** to simulate increasing perturbations.  
-        4️⃣ Press **Run Simulation** — results display mean QΩ (stability) and ζ_sync (coherence) over several sample runs.  
-        
-        ⚙️ **Interpretation:**  
+        3️⃣ Adjust **Noise Scale (σ)** to simulate environmental perturbations.  
+        4️⃣ Press **Run Simulation** — results will show mean QΩ (stability) and ζ_sync (coherence) across samples.  
+        5️⃣ Use **Save Run Log** to download your test record as a JSON file with timestamp.  
+
+        **Interpretation:**  
         - `Nominal` → Stable harmonic equilibrium  
         - `Perturbed` → Transitional / adaptive state  
         - `Critical` → Instability threshold reached  
-        
-        🔬 Each run demonstrates Rendered Frame Theory’s capacity for self-stabilisation under synthetic noise.  
+
+        Each output is time-stamped, reproducible, and protected under RFT-IPURL v1.0.  
         """
     )
 
     with gr.Row():
-        profile = gr.Dropdown(
-            list(PROFILES.keys()), label="System Profile", value="AI / Neural"
-        )
+        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():
@@ -112,8 +123,12 @@ with gr.Blocks(title="RFT-Ω Total-Proof Kernel") as demo:
 
     run_btn = gr.Button("Run Simulation")
     output = gr.JSON(label="Simulation Results")
+    hidden_json = gr.Textbox(visible=False)
+    save_btn = gr.Button("💾 Save Run Log")
+    download_file = gr.File(label="Download Saved Log")
 
-    run_btn.click(run, inputs=[profile, dist, sigma, seed, samples], outputs=[output])
+    run_btn.click(run, inputs=[profile, dist, sigma, seed, samples], outputs=[output, hidden_json])
+    save_btn.click(save_run_log, inputs=[hidden_json], outputs=[download_file])
 
 # ------------------ Launch -------------------------------
 if __name__ == "__main__":