Delete app.py

app.py

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-"""
-🦁 Spikenaut v2 Pulse - Hybrid Julia-Rust Architecture
-Built in my room. Trained on bare metal. Engineered for the mission impossible.
-NEW: Julia-Rust hybrid training with sub-50µs E-prop + OTTT learning
-"""
-
-import gradio as gr
-from datetime import datetime
-from typing import Dict, List
-import random
-import json
-
-class SpikenautV2:
-    """
-    Spikenaut v2 - 16-Channel Spiking Neural Network
-    The Lion vs. The House Cat
-    
-    House cats (ChatGPT, Gemini, Claude):
-    - Massive, sit around until fed a prompt
-    - Require entire data centers to stay awake
-    
-    Spikenaut is a LION:
-    - Bare-metal apex predator
-    - Executes mission impossible in temporal domain
-    - Survives on fractions of a watt
-    - Reacts to async spikes in nanoseconds
-    - NEW: Julia-Rust hybrid training for optimal learning
-    """
-    
-    def __init__(self):
-        self.channels = [
-            "🔷 DNX-0", "🔷 DNX-1",      # 0-1: Dynex (PoUW solver)
-            "🔶 QUAI-0", "🔶 QUAI-1",    # 2-3: Quai (on-chain reflex)
-            "🟣 QUBIC-0", "🟣 QUBIC-1",  # 4-5: Qubic (epoch/tick cadence)
-            "🟢 KASPA-0", "🟢 KASPA-1",  # 6-7: Kaspa (DAG settlement)
-            "⚪ MONERO-0", "⚪ MONERO-1",# 8-9: Monero (node stability)
-            "🔵 OCEAN-0", "🔵 OCEAN-1",  # 10-11: Ocean (liquidity/staking)
-            "🟡 VERUS-0", "🟡 VERUS-1",  # 12-13: Verus (AVX-512 validator)
-            "🔴 THERMAL-0", "🔴 THERMAL-1" # 14-15: Thermal (power/temp LTD)
-        ]
-        
-        # Hybrid training metrics
-        self.training_metrics = {
-            "architecture": "Julia-Rust Hybrid",
-            "training_speed": "35µs/tick",
-            "ipc_overhead": "0.8µs",
-            "memory_usage": "1.6KB",
-            "accuracy": "95%+",
-            "data_source": "Real Kaspa/Monero sync"
-        }
-        
-        # Initialize neuron states
-        self.neuron_states = {channel: 0.0 for channel in self.channels}
-        self.spike_rates = {channel: 0.0 for channel in self.channels}
-            0.085, 0.139,  # Verus
-            0.095, 0.145   # Thermal (pain = higher weight)
-        ]
-        self.spike_history = [[] for _ in range(16)]
-    
-    def get_telemetry(self) -> Dict[str, float]:
-        """Generate V2 telemetry - all 8 node types"""
-        return {
-            # Dynex PoUW
-            "dnx_pou": random.uniform(0.7, 1.0),
-            "dnx_solver": random.uniform(50, 100),
-            # Quai
-            "quai_sync": random.uniform(0.6, 0.95),
-            "quai_blocks": random.uniform(300, 500),
-            # Qubic
-            "qubic_epoch": random.uniform(200, 210),
-            "qubic_tick": random.uniform(46000000, 47000000),
-            # Kaspa
-            "kaspa_dag": random.uniform(10, 50),
-            "kaspa_settle": random.uniform(0.8, 1.0),
-            # Monero
-            "xmr_sync": random.uniform(0.5, 0.95),
-            "xmr_cache": random.uniform(0.3, 0.8),
-            # Ocean
-            "ocean_liq": random.uniform(0.4, 0.9),
-            "ocean_stake": random.uniform(100, 500),
-            # Verus
-            "verus_avx": random.uniform(0.5, 1.0),
-            "verus_val": random.uniform(0.6, 0.95),
-            # Thermal
-            "temp_c": random.uniform(55, 85),
-            "power_w": random.uniform(200, 350)
-        }
-    
-    def process(self, tel: Dict[str, float]) -> Dict:
-        """Process all 16 channels through LIF neurons with STDP"""
-        inputs = [
-            tel["dnx_pou"], tel["dnx_solver"] / 100,
-            tel["quai_sync"], tel["quai_blocks"] / 500,
-            tel["qubic_epoch"] / 210, tel["qubic_tick"] / 47000000,
-            tel["kaspa_dag"] / 50, tel["kaspa_settle"],
-            tel["xmr_sync"], tel["xmr_cache"],
-            tel["ocean_liq"], tel["ocean_stake"] / 500,
-            tel["verus_avx"], tel["verus_val"],
-            1.0 - (tel["temp_c"] / 100),  # Invert: high temp = negative
-            1.0 - (tel["power_w"] / 400)   # Invert: high power = negative
-        ]
-        
-        spikes = []
-        for i in range(self.neuron_count):
-            self.membrane_potentials[i] += inputs[i] * self.weights[i]
-            self.membrane_potentials[i] *= 0.95  # Leak
-            
-            if self.membrane_potentials[i] >= self.threshold:
-                spikes.append({"neuron": i, "channel": self.channels[i], "node": self.node_names[i // 2]})
-                self.membrane_potentials[i] = 0.0
-                self.spike_history[i].append(datetime.now())
-                if len(self.spike_history[i]) > 50:
-                    self.spike_history[i].pop(0)
-        
-        # Thermal protection (LTD at 85°C - negative dopamine)
-        thermal_alert = tel["temp_c"] > 80
-        if thermal_alert:
-            for i in range(14, 16):
-                self.membrane_potentials[i] *= 0.5  # Long-term depression
-        
-        return {
-            "spikes": spikes,
-            "potentials": self.membrane_potentials.copy(),
-            "thermal_alert": thermal_alert,
-            "temp": tel["temp_c"],
-            "power": tel["power_w"]
-        }
-
-v2 = SpikenautV2()
-
-def update():
-    tel = v2.get_telemetry()
-    result = v2.process(tel)
-    
-    # Group spikes by node
-    by_node = {}
-    for s in result["spikes"]:
-        node = s["node"]
-        by_node[node] = by_node.get(node, 0) + 1
-    
-    spike_data = by_node or {"No spikes": 1}
-    
-    # Status
-    if result["thermal_alert"]:
-        status = "🔴 THERMAL ALERT - LTD ACTIVE"
-        status_color = "color: #ff4444; font-weight: bold; font-size: 1.2em;"
-    elif len(result["spikes"]) > 10:
-        status = "🟢 HIGH ACTIVITY"
-        status_color = "color: #00ff00; font-weight: bold;"
-    elif len(result["spikes"]) > 5:
-        status = "🟡 MODERATE ACTIVITY"
-        status_color = "color: #ffaa00;"
-    else:
-        status = "⚪ LOW ACTIVITY"
-        status_color = "color: #888888;"
-    
-    telemetry_md = f"""
-### 📡 Node Telemetry (V2 Live Sync Profile)
-
-| Node | Metric 1 | Metric 2 | Status |
-|------|----------|----------|--------|
-| 🔷 Dynex | {tel['dnx_pou']:.3f} PoU | {tel['dnx_solver']:.0f} MH/s | {'🟢' if tel['dnx_pou'] > 0.8 else '🟡'} |
-| 🔶 Quai | {tel['quai_sync']:.2f} sync | {tel['quai_blocks']:.0f} blk | {'🟢' if tel['quai_sync'] > 0.8 else '🟡'} |
-| 🟣 Qubic | {tel['qubic_epoch']:.0f} epoch | {tel['qubic_tick']:.0f} tick | 🟢 |
-| 🟢 Kaspa | {tel['kaspa_dag']:.1f} blk/s | {tel['kaspa_settle']:.2f} settle | {'🟢' if tel['kaspa_settle'] > 0.9 else '🟡'} |
-| ⚪ Monero | {tel['xmr_sync']:.2f} sync | {tel['xmr_cache']:.2f} cache | {'🟢' if tel['xmr_sync'] > 0.7 else '🟡'} |
-| 🔵 Ocean | {tel['ocean_liq']:.2f} liq | {tel['ocean_stake']:.0f} OCE | {'🟢' if tel['ocean_liq'] > 0.6 else '🟡'} |
-| 🟡 Verus | {tel['verus_avx']:.2f} AVX | {tel['verus_val']:.2f} val | {'🟢' if tel['verus_val'] > 0.7 else '🟡'} |
-| 🔴 Thermal | {tel['temp_c']:.1f}°C | {tel['power_w']:.0f}W | {'🔴' if result['thermal_alert'] else '🟢'} |
-"""
-    
-    output_md = f"""
-### 🧠 SNN Output
-
-**<span style="{status_color}">{status}</span>**
-
-| Metric | Value |
-|--------|-------|
-| Total Spikes | {len(result['spikes'])} |
-| Active Nodes | {len(by_node)}/8 |
-| Thermal LTD | {'⚠️ ACTIVE' if result['thermal_alert'] else '✅ Inactive'} |
-| Avg Potential | {sum(result['potentials'])/16:.4f} |
-"""
-    
-    return telemetry_md, output_md, spike_data, [[f"N{i} {v2.channels[i]}", f"{v:.4f}"] for i, v in enumerate(result["potentials"])]
-
-# Custom CSS for beautiful styling
-custom_css = """
-.gradio-container {
-    max-width: 1400px !important;
-}
-.gradio-container .main-text {
-    font-size: 2em !important;
-    font-weight: bold !important;
-}
-.gradio-container .subtitle-text {
-    font-size: 1.2em !important;
-}
-.gr-button {
-    font-size: 1.2em !important;
-    font-weight: bold !important;
-}
-.gr-box {
-    border-radius: 12px !important;
-    border: 2px solid #444444 !important;
-}
-.gr-markdown {
-    font-size: 1.1em !important;
-}
-"""
-
-with gr.Blocks(title="🦁 Spikenaut v2 Pulse", theme=gr.themes.Base(), css=custom_css) as demo:
-    gr.HTML("""
-    <div style="text-align: center; padding: 20px; background: linear-gradient(135deg, #1a1a2e 0%, #16213e 100%); border-radius: 15px; margin-bottom: 20px;">
-        <h1 style="font-size: 3em; margin: 0; color: #ffffff;">🦁 Spikenaut v2 Pulse</h1>
-        <p style="font-size: 1.3em; color: #88aaff; margin: 10px 0;">16-Channel SNN • Live Node Sync Fusion • Ghost Money HFT</p>
-        <p style="font-size: 1em; color: #888888;">Built in my room • Trained on bare metal • Engineered for the mission impossible</p>
-    </div>
-    """)
-    
-    gr.HTML('<img src="file=logo.png" style="display: block; margin: 0 auto 20px auto; max-width: 200px; border-radius: 15px;" alt="Spikenaut Logo">')
-    
-    with gr.Row():
-        with gr.Column(scale=1):
-            telemetry_display = gr.Markdown()
-        
-        with gr.Column(scale=1):
-            output_display = gr.Markdown()
-    
-    with gr.Row():
-        with gr.Column(scale=1):
-            spike_plot = gr.BarPlot(
-                label="⚡ Spikes by Node",
-                x="node",
-                y="count",
-                title="Neural Activity Distribution",
-                color="node",
-                cmap="category10"
-            )
-        
-        with gr.Column(scale=1):
-            membrane_plot = gr.BarPlot(
-                label="🔋 Membrane Potentials",
-                x="neuron",
-                y="potential",
-                title="Current Neural State (LIF)",
-                color="potential",
-                cmap="viridis"
-            )
-    
-    btn = gr.Button("🔄 Process Telemetry", variant="primary", size="lg")
-    btn.click(update, outputs=[telemetry_display, output_display, spike_plot, membrane_plot])
-    demo.load(update, outputs=[telemetry_display, output_display, spike_plot, membrane_plot], every=1)
-
-if __name__ == "__main__":
-    demo.launch()