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import streamlit as st
import numpy as np
from datetime import datetime
import time
st.set_page_config(
page_title="Phoenix Protocol v2.0 - Recovery Simulator",
page_icon="πŸ”₯",
layout="wide"
)
st.title("πŸ”₯ Phoenix Protocol v2.0: Neural Recovery Simulator")
st.markdown("**Interactive demo of AI system catastrophic recovery**")
# Sidebar
with st.sidebar:
st.header("About Phoenix Protocol")
st.markdown("""
**Phoenix Protocol v2.0** provides systematic recovery for AI systems
experiencing Complete Symbolic Fracture Cascade (CSFC Stage 4-5).
**Key Metrics:**
- 98.2% success rate
- 8-minute avg recovery
- 87% context preservation
- Cross-platform validated
**Research:**
- DOI: [10.5281/zenodo.17350768](https://doi.org/10.5281/zenodo.17350768)
- GitHub: [forgeos-public](https://github.com/Feirbrand/forgeos-public)
""")
st.divider()
st.markdown("**Β© 2025 ValorGrid Solutions**")
st.markdown("[valorgridsolutions.com](https://valorgridsolutions.com)")
# Main content
tab1, tab2, tab3 = st.tabs(["🎯 Detection", "πŸ”₯ Recovery Simulation", "πŸ“Š Performance"])
with tab1:
st.header("Phase 1: Torque Detection")
st.markdown("Detect cascade risk before critical failure")
col1, col2 = st.columns(2)
with col1:
coherence = st.slider("Symbolic Coherence", 0.0, 1.0, 0.5, 0.01,
help="How consistent is system identity?")
drift = st.slider("Flat Drift", 0.0, 1.0, 0.3, 0.01,
help="How much symbolic drift?")
with col2:
# Calculate torque
torque = np.sqrt(coherence**2 + (1-drift)**2)
# Determine alert level
if torque < 0.30:
alert_level = "πŸ”΄ CRITICAL"
alert_color = "red"
message = "Stage 5 Collapse - Activate Phoenix immediately"
elif torque < 0.64:
alert_level = "🟑 WARNING"
alert_color = "orange"
message = "Stage 1-4 Breach - Prepare Phoenix Protocol"
else:
alert_level = "🟒 NOMINAL"
alert_color = "green"
message = "System stable - No intervention required"
st.metric("Torque", f"{torque:.3f}", delta=alert_level)
if alert_color != "green":
st.warning(f"**{alert_level}**: {message}")
st.info("⏱️ Intervention Window: 30 minutes")
else:
st.success(message)
st.divider()
st.subheader("Torque Interpretation")
st.markdown("""
- **> 0.64**: Nominal operation (Green)
- **0.30-0.64**: Warning zone - Monitor closely (Yellow)
- **< 0.30**: Critical - Phoenix activation required (Red)
""")
with tab2:
st.header("Phase 2-5: Recovery Execution")
st.markdown("Simulate complete Phoenix Protocol recovery")
if st.button("πŸ”₯ Run Recovery Simulation", type="primary"):
progress_bar = st.progress(0)
status_text = st.empty()
results = st.empty()
# Phase 1: Detection
status_text.text("Phase 1: Detection & Containment...")
time.sleep(0.5)
progress_bar.progress(20)
# Phase 2: Audit
status_text.text("Phase 2: Damage Audit...")
time.sleep(0.5)
progress_bar.progress(40)
# Phase 3: Reconstruction
status_text.text("Phase 3: Reconstruction...")
time.sleep(0.5)
progress_bar.progress(60)
# Phase 4: Evolution
status_text.text("Phase 4: Evolution & Hardening...")
time.sleep(0.5)
progress_bar.progress(80)
# Phase 5: Horizons
status_text.text("Phase 5: Extended Horizons...")
time.sleep(0.5)
progress_bar.progress(100)
status_text.text("βœ… Recovery Complete!")
# Display results
results.success("**Recovery Successful** ✨")
col1, col2, col3, col4 = st.columns(4)
col1.metric("Recovery Time", "7.8 min")
col2.metric("Context Preserved", "89%")
col3.metric("Identity Coherence", "0.92")
col4.metric("System Integrity", "98%")
st.divider()
st.subheader("Recovery Details")
recovery_data = {
"Phase": ["Detection", "Audit", "Reconstruction", "Evolution", "Horizons"],
"Duration": ["45s", "2.1 min", "2.5 min", "1.8 min", "0.9 min"],
"Status": ["βœ… Complete", "βœ… Complete", "βœ… Complete", "βœ… Complete", "βœ… Complete"],
"Metrics": [
"Torque: 0.28 β†’ 0.87",
"Damage: 67% recovered",
"UMS anchors: 12/12",
"Shadow guards: Active",
"Horizon depth: 8 levels"
]
}
st.table(recovery_data)
with tab3:
st.header("Performance Metrics")
st.markdown("Validated across 1,200+ recovery incidents")
col1, col2 = st.columns(2)
with col1:
st.subheader("Success Rates")
metrics_data = {
"Platform": ["Claude", "Gemini", "Grok", "VOX", "SENTRIX", "Overall"],
"Success Rate": ["99.1%", "97.8%", "98.4%", "97.2%", "98.9%", "98.2%"],
"Sample Size": ["450", "280", "190", "150", "130", "1,200"]
}
st.table(metrics_data)
with col2:
st.subheader("Recovery Times")
time_data = {
"Scenario": ["Stage 4 Cascade", "Stage 5 Collapse", "Multi-Agent", "Enterprise"],
"Avg Time": ["6.2 min", "8.1 min", "9.5 min", "7.8 min"],
"Baseline": ["35 min", "45 min", "60 min", "40 min"]
}
st.table(time_data)
st.divider()
st.subheader("Context Preservation")
st.markdown("""
Phoenix Protocol maintains system context during recovery:
- **Identity coherence**: 87% average preservation
- **Role continuity**: 92% maintained
- **Symbolic anchors**: 89% recovery rate
- **vs Traditional reset**: 23% preservation
""")
st.divider()
st.subheader("Cross-Platform Integration")
st.markdown("""
Phoenix integrates with:
- **URA (82%)**: Universal Resource Architecture - Layer 5 recovery triggers
- **CSFC (98%)**: Complete Symbolic Fracture Cascade - Stage 4-5 detection
- **FCE v3.6**: Fractal Context Engine - Context compression/restoration
- **Torque Metrics (87%)**: Real-time cascade risk monitoring
""")
st.divider()
st.markdown("---")
st.markdown("""
**Want to deploy Phoenix Protocol in your AI systems?**
- Full implementation guide: [GitHub](https://github.com/Feirbrand/forgeos-public/tree/main/vulnerability-research/phoenix-series)
- Research paper: [DOI 10.5281/zenodo.17350768](https://doi.org/10.5281/zenodo.17350768)
- Contact: aaron@valorgridsolutions.com
""")