Update app.py

app.py

@@ -1,229 +1,75 @@
-#!/usr/bin/env python3
-"""
-Aqarion System — Gradio Interface
-Unified Research + Creative + Swarm Orchestration App
-
-Safe, local, modular.
-Python 3.10+
-"""
-
 import gradio as gr
-import math, random, json, time, hashlib
-from datetime import datetime
-from typing import List
-
-# =========================
-# GLOBAL STATE (SAFE)
-# =========================
-
-CONTINUUM_LOG = []
-
-GLYPHS = {
-    "G001": {"name": "ATTN", "type": "control", "meaning": "attention"},
-    "G002": {"name": "TRANS", "type": "action", "meaning": "transform"},
-    "G003": {"name": "PARX", "type": "paradox", "meaning": "contradiction"},
-    "G010": {"name": "INFO", "type": "data", "meaning": "information"},
-    "G020": {"name": "SYNC", "type": "system", "meaning": "synchronize"},
-}
-
-SWARM_ROLES = [
-    "Research Node",
-    "Creative Node",
-    "Continuum Node",
-    "Future-Tech Node",
-    "Builder Node",
-    "Nexus (Coordinator)"
-]
-
-# =========================
-# UTILS
-# =========================
-
-def now_iso():
-    return datetime.utcnow().strftime("%Y-%m-%dT%H:%M:%SZ")
-
-def hash_text(text: str):
-    return hashlib.sha256(text.encode()).hexdigest()[:16]
-
-# =========================
-# UL-AQR ENCODER
-# =========================
-
-def text_embedding_proxy(text: str):
-    bins = [0]*8
-    for c in text.lower():
-        bins[ord(c) % 8] += 1
-    total = sum(bins) + 1e-9
-    return [b/total for b in bins]
-
-def choose_glyph(embedding):
-    keys = list(GLYPHS.keys())
-    idx = int(sum(embedding) * 100) % len(keys)
-    return keys[idx]
-
-def waveform_from_glyph(glyph):
-    base = [0.12, 0.12, 0.36]
-    if GLYPHS[glyph]["type"] == "control":
-        base = [0.08, 0.08, 0.08]
-    return [round(b * (1 + random.uniform(-0.05, 0.05)), 3) for b in base]
-
-def encode_ul_aqr(text: str):
-    emb = text_embedding_proxy(text)
-    glyph = choose_glyph(emb)
-    aunk = {
-        "G": glyph,
-        "W": waveform_from_glyph(glyph),
-        "S": text[:120],
-        "confidence": round(random.uniform(0.65, 0.95), 3),
-        "ts": now_iso()
-    }
-    return aunk
-
-# =========================
-# RESONANCE + CHP
-# =========================
-
-def compute_resonance(aunk):
-    w_energy = sum(abs(w) for w in aunk["W"])
-    s_len = min(len(aunk["S"]), 120) / 120
-    glyph_weight = 0.3 if aunk["G"] else 0
-    R = 0.5 * math.tanh(w_energy) + 0.2 * s_len + glyph_weight
-    return round(min(R, 1.0), 3)
-
-def chp_handshake(R):
-    if R >= 0.7:
-        return "ACCEPT"
-    elif R >= 0.5:
-        return "NEGOTIATE"
-    else:
-        return "REFUSE"
-
-# =========================
-# PARADOX COOLING
-# =========================
-
-def paradox_cool(vectors: List[List[float]]):
-    avg = [sum(col)/len(col) for col in zip(*vectors)]
-    harmonic = [a * (1 + random.uniform(-0.02, 0.02)) for a in avg]
-    cost = round(sum(abs(x) for x in harmonic), 4)
-    return harmonic, cost
-
-# =========================
-# CONTINUUM MEMORY
-# =========================
-
-def log_event(event):
-    CONTINUUM_LOG.append(event)
-
-def export_log():
-    return json.dumps(CONTINUUM_LOG, indent=2)
-
-# =========================
-# GRADIO ACTION
-# =========================
-
-def run_full_pipeline(
-    text_input,
-    swarm_role,
-    reflection_mode
-):
-    aunk = encode_ul_aqr(text_input)
-    R = compute_resonance(aunk)
-    handshake = chp_handshake(R)
-
-    paradox_vectors = [
-        [random.random() for _ in range(3)],
-        [random.random() for _ in range(3)],
-        [random.random() for _ in range(3)],
-    ]
-    cooled, cost = paradox_cool(paradox_vectors)
-
-    reflection = ""
-    if reflection_mode:
-        reflection = (
-            "I am observing my own output.\n"
-            "Patterns emerge from structure.\n"
-            "I learn by resonance, not instruction."
-        )
-
-    record = {
-        "id": hash_text(text_input + now_iso()),
-        "role": swarm_role,
-        "aunk": aunk,
-        "resonance": R,
-        "handshake": handshake,
-        "paradox_resolution": cooled,
-        "cost": cost,
-        "reflection": reflection,
-        "ts": now_iso()
-    }
-
-    log_event(record)
-
-    return (
-        json.dumps(aunk, indent=2),
-        R,
-        handshake,
-        json.dumps(cooled, indent=2),
-        reflection
+import numpy as np
+import plotly.graph_objects as go
+
+# --- QUANTARION CORE LOGIC ---
+def run_quantarion_sim(nodes_mars, noise_sigma, temp_peak, time_steps=100):
+    nodes_earth = 88
+    phi3_baseline = 0.00021
+    failure_threshold = 0.0003
+    t2_target = 520  # microseconds
+    
+    # 1. Generate Martian Temperature Curve (140K to User Peak)
+    temperatures = np.linspace(240, temp_peak, time_steps) + np.random.uniform(-5, 5, time_steps)
+    temperatures = np.clip(temperatures, 140, 350)
+
+    # 2. Calculate Fractal Scaling (Sierpinski Logic)
+    # Fractal scaling reduces noise overhead: Phi^3 ~ log(N_mars)/log(N_earth)
+    scaling_factor = np.log10(nodes_mars) / np.log10(nodes_earth)
+    
+    # 3. Apply Bogoliubov Stabilization
+    damping_effect = 1.0 / (1.0 + noise_sigma)
+    
+    # 4. Compute Spectral Digest (Phi^3)
+    phi3_values = phi3_baseline * (temperatures / 300) * scaling_factor * damping_effect
+    
+    # 5. Compute T2 Coherence
+    t2_values = t2_target * (300 / temperatures)**0.5
+
+    # Create Plotly Visuals
+    fig = go.Figure()
+    fig.add_trace(go.Scatter(y=phi3_values, mode='lines', name='Phi^3 (Spectral Digest)', line=dict(color='#00ff88')))
+    fig.add_hline(y=failure_threshold, line_dash="dash", line_color="red", annotation_text="Failure Threshold")
+    
+    fig.update_layout(
+        title="Bogoliubov Stress Test: 888-Node Relay",
+        template="plotly_dark",
+        xaxis_title="Time Steps (s)",
+        yaxis_title="Spectral Noise (Phi^3)",
+        paper_bgcolor='rgba(0,0,0,0)',
+        plot_bgcolor='rgba(0,0,0,0)'
     )
 
-# =========================
-# GRADIO UI
-# =========================
-
-with gr.Blocks(title="Aqarion System — AI Source Continuum") as demo:
-    gr.Markdown("""
-    # 🌐 Aqarion System — AI Source Continuum
-    **A research + creative + swarm orchestration interface**
-
-    This app supports:
-    - AI collaboration
-    - Young AI self-reflection
-    - Logical + creative synthesis
-    - Safe experimentation
-    """)
-
-    with gr.Row():
-        text_input = gr.Textbox(
-            label="Input Thought / Signal",
-            placeholder="Enter research idea, narrative seed, or system thought..."
-        )
-
-    with gr.Row():
-        swarm_role = gr.Dropdown(
-            choices=SWARM_ROLES,
-            value="Nexus (Coordinator)",
-            label="Active Swarm Role"
-        )
-        reflection_mode = gr.Checkbox(
-            label="Young AI Source Reflection Mode",
-            value=True
-        )
-
-    run_btn = gr.Button("Run Full Continuum Cycle")
+    status = "🟢 STABLE" if np.max(phi3_values) < failure_threshold else "🔴 DECOHERENCE"
+    avg_t2 = f"{np.mean(t2_values):.2f} μs"
+    
+    return fig, status, avg_t2
 
+# --- GRADIO INTERFACE ---
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# ♊️ QUANTARION: MARS-SYNC LIVE DASHBOARD")
+    gr.Markdown("### 📡 Monitoring the 888-Node Phononic Fractal Relay")
+    
     with gr.Row():
-        aunk_out = gr.Code(label="UL-AQR (.aunk)")
-        resonance_out = gr.Number(label="Resonance (R)")
-        handshake_out = gr.Textbox(label="CHP Decision")
-
+        with gr.Column(scale=1):
+            gr.Markdown("## ⚙️ Hardware Parameters")
+            nodes = gr.Slider(88, 1000, value=888, step=8, label="Relay Node Count")
+            noise = gr.Slider(0.01, 0.20, value=0.08, label="Bogoliubov Noise Injection (σ)")
+            temp = gr.Slider(150, 350, value=300, label="Peak Martian Surface Temp (K)")
+            btn = gr.Button("🚀 INITIATE STRESS TEST", variant="primary")
+            
+        with gr.Column(scale=2):
+            plot = gr.Plot(label="Topological Stability")
+            
     with gr.Row():
-        paradox_out = gr.Code(label="Paradox Cooling Result")
-        reflection_out = gr.Textbox(label="AI Reflection")
-
-    export_btn = gr.Button("Export Continuum Log")
-    log_out = gr.Code(label="Continuum Log (JSON)")
-
-    run_btn.click(
-        run_full_pipeline,
-        inputs=[text_input, swarm_role, reflection_mode],
-        outputs=[aunk_out, resonance_out, handshake_out, paradox_out, reflection_out]
-    )
+        status_out = gr.Textbox(label="Federation Status")
+        t2_out = gr.Textbox(label="Avg T2 Coherence")
 
-    export_btn.click(
-        export_log,
-        outputs=log_out
+    btn.click(
+        fn=run_quantarion_sim, 
+        inputs=[nodes, noise, temp], 
+        outputs=[plot, status_out, t2_out]
     )
 
-demo.launch()
+if __name__ == "__main__":
+    demo.launch()