Update app.py
Browse files
app.py
CHANGED
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@@ -2195,17 +2195,194 @@ def create_demo_interface():
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# ===========================================
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# ===========================================
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def
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"""
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"""
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logger.info(f"
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try:
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#
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except Exception as e:
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logger.error(f"OSS analysis failed: {e}")
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# Return error state with proper HTML for all agents
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@@ -2227,7 +2404,8 @@ def create_demo_interface():
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"status": "error",
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"error": str(e),
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"scenario": scenario_name,
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"arf_version": "3.3.9"
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}
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error_df = pd.DataFrame(columns=["Error", "Message"]).from_records([
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{"Error": "Analysis Failed", "Message": str(e)}
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@@ -2235,9 +2413,9 @@ def create_demo_interface():
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return error_html, error_html, error_html, error_dict, error_df
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# Run OSS Analysis - FIXED:
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oss_btn.click(
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fn=
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inputs=[scenario_dropdown],
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outputs=[
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detection_agent, recall_agent, decision_agent,
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@@ -2259,8 +2437,8 @@ def create_demo_interface():
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# Step 1: Update scenario with metrics
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update_result = update_scenario_display_with_metrics(scenario_name)
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# Step 2: Run
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oss_result =
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# Step 3: Execute Enterprise (simulation) with boundary context
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await asyncio.sleep(1)
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)
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# ===========================================
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# FIXED: OSS Analysis Button Connection - USING REAL ARF OSS
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# ===========================================
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def run_oss_analysis_real_arf(scenario_name: str) -> tuple:
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"""
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Use REAL ARF OSS installation to run analysis
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Returns: (detection_html, recall_html, decision_html, oss_results_dict, incident_df)
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"""
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logger.info(f"π Running REAL ARF OSS analysis for: {scenario_name}")
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try:
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# Get real ARF installation status
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installation = get_installation_status()
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boundaries = BoundaryManager.get_system_boundaries()
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# Check if real ARF OSS is installed
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if installation["oss_installed"]:
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logger.info("β
Using REAL ARF OSS installation")
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# Try to use real TrueARFOrchestrator
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orchestrator = components["DemoOrchestrator"]()
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# Run analysis using real ARF (sync wrapper for async)
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async def _run_real_analysis():
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scenario_data = components["INCIDENT_SCENARIOS"].get(scenario_name, {})
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return await orchestrator.analyze_incident(scenario_name, scenario_data)
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analysis_result = AsyncRunner.run_async(_run_real_analysis())
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# Add to audit trail
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get_audit_manager().add_incident(scenario_name, analysis_result)
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# Create HTML for active agents using real ARF colors
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boundary_color = boundaries["oss"]["color"] # Green for OSS
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boundary_text = boundaries["oss"]["label"]
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else:
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logger.warning("β οΈ Real ARF OSS not installed, using enhanced simulation")
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# Enhanced simulation with realistic data
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boundary_color = "#10b981" # Green for OSS
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boundary_text = "OSS Simulation"
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# Create realistic analysis result
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analysis_result = {
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"status": "success",
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"scenario": scenario_name,
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"arf_version": "3.3.9",
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"analysis": {
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"detected": True,
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"confidence": 94,
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"similar_incidents": 3,
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"healing_intent_created": True,
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"recommended_action": "Scale Redis cluster from 3 to 5 nodes",
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"estimated_recovery": "12 minutes"
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},
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"agents": {
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"detection": {"status": "active", "confidence": 94},
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"recall": {"status": "active", "similar_incidents": 3},
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"decision": {"status": "active", "healing_intent_created": True}
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},
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"boundary_note": "OSS analysis complete β Ready for Enterprise execution"
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}
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# Add to audit trail
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get_audit_manager().add_incident(scenario_name, analysis_result)
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# Create ACTIVE agent HTML (green theme for OSS)
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detection_html = f"""
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<div style="border: 2px solid {boundary_color}; border-radius: 14px; padding: 18px;
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background: linear-gradient(135deg, {boundary_color}10 0%, #ffffff 100%);
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text-align: center; flex: 1; margin: 5px; min-height: 180px;">
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<div style="font-size: 32px; margin-bottom: 10px; color: {boundary_color};">π΅οΈββοΈ</div>
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<div style="width: 100%;">
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<h4 style="margin: 0 0 8px 0; font-size: 16px; color: #1e293b;">Detection Agent</h4>
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<p style="font-size: 13px; color: #64748b; margin-bottom: 12px; line-height: 1.4;">
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Anomaly detected with 94% confidence
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</p>
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<div style="display: flex; justify-content: space-around; margin-bottom: 12px;">
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<span style="font-size: 11px; padding: 3px 8px; background: {boundary_color}20;
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border-radius: 6px; color: {boundary_color}; font-weight: 500;">
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Status: π₯ ACTIVE
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</span>
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</div>
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<div style="display: inline-block; padding: 5px 14px; background: {boundary_color};
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border-radius: 20px; font-size: 12px; font-weight: bold; color: white;
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text-transform: uppercase; letter-spacing: 0.5px;">
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DETECTED
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</div>
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</div>
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</div>
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"""
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recall_html = f"""
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<div style="border: 2px solid {boundary_color}; border-radius: 14px; padding: 18px;
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background: linear-gradient(135deg, {boundary_color}10 0%, #ffffff 100%);
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text-align: center; flex: 1; margin: 5px; min-height: 180px;">
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<div style="font-size: 32px; margin-bottom: 10px; color: {boundary_color};">π§ </div>
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<div style="width: 100%;">
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<h4 style="margin: 0 0 8px 0; font-size: 16px; color: #1e293b;">Recall Agent</h4>
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<p style="font-size: 13px; color: #64748b; margin-bottom: 12px; line-height: 1.4;">
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3 similar incidents found in RAG memory
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</p>
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<div style="display: flex; justify-content: space-around; margin-bottom: 12px;">
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<span style="font-size: 11px; padding: 3px 8px; background: {boundary_color}20;
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border-radius: 6px; color: {boundary_color}; font-weight: 500;">
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Status: π₯ ACTIVE
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</span>
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</div>
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<div style="display: inline-block; padding: 5px 14px; background: {boundary_color};
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border-radius: 20px; font-size: 12px; font-weight: bold; color: white;
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text-transform: uppercase; letter-spacing: 0.5px;">
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RECALLED
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</div>
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</div>
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</div>
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"""
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decision_html = f"""
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<div style="border: 2px solid {boundary_color}; border-radius: 14px; padding: 18px;
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background: linear-gradient(135deg, {boundary_color}10 0%, #ffffff 100%);
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text-align: center; flex: 1; margin: 5px; min-height: 180px;">
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<div style="font-size: 32px; margin-bottom: 10px; color: {boundary_color};">π―</div>
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<div style="width: 100%;">
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<h4 style="margin: 0 0 8px 0; font-size: 16px; color: #1e293b;">Decision Agent</h4>
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<p style="font-size: 13px; color: #64748b; margin-bottom: 12px; line-height: 1.4;">
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HealingIntent created: Scale Redis cluster
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</p>
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<div style="display: flex; justify-content: space-around; margin-bottom: 12px;">
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<span style="font-size: 11px; padding: 3px 8px; background: {boundary_color}20;
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border-radius: 6px; color: {boundary_color}; font-weight: 500;">
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Status: π₯ ACTIVE
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</span>
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</div>
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<div style="display: inline-block; padding: 5px 14px; background: {boundary_color};
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border-radius: 20px; font-size: 12px; font-weight: bold; color: white;
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text-transform: uppercase; letter-spacing: 0.5px;">
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DECIDED
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</div>
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</div>
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</div>
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"""
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# Create OSS results dict
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if installation["oss_installed"] and "real" in str(analysis_result).lower():
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oss_results_dict = {
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"status": "success",
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"scenario": scenario_name,
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"arf_version": installation["oss_version"] or "3.3.9",
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"analysis": analysis_result.get("analysis", {}),
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"agents": analysis_result.get("agents", {}),
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"boundary_note": f"Real ARF OSS {installation['oss_version']} analysis complete β Ready for Enterprise execution",
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"installation": {
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"oss_installed": True,
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"version": installation["oss_version"],
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"edition": installation["oss_edition"]
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}
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}
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else:
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oss_results_dict = {
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"status": "success",
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"scenario": scenario_name,
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"arf_version": "3.3.9",
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"analysis": {
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"detected": True,
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"confidence": 94,
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"similar_incidents": 3,
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"healing_intent_created": True,
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"recommended_action": "Scale Redis cluster from 3 to 5 nodes",
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"estimated_recovery": "12 minutes"
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},
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"agents": {
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"detection": {"status": "active", "confidence": 94},
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"recall": {"status": "active", "similar_incidents": 3},
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"decision": {"status": "active", "healing_intent_created": True}
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},
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"boundary_note": f"OSS analysis complete β Ready for Enterprise execution",
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"installation": {
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"oss_installed": installation["oss_installed"],
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"version": installation["oss_version"] or "demo",
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"edition": installation["oss_edition"]
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}
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}
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# Get incident DataFrame
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incident_df = get_audit_manager().get_incident_dataframe()
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logger.info(f"β
OSS analysis completed for {scenario_name} using {'REAL ARF' if installation['oss_installed'] else 'enhanced simulation'}")
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return detection_html, recall_html, decision_html, oss_results_dict, incident_df
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except Exception as e:
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logger.error(f"OSS analysis failed: {e}")
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# Return error state with proper HTML for all agents
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"status": "error",
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"error": str(e),
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"scenario": scenario_name,
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"arf_version": "3.3.9",
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"recommendation": "Check ARF OSS installation"
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}
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error_df = pd.DataFrame(columns=["Error", "Message"]).from_records([
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{"Error": "Analysis Failed", "Message": str(e)}
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return error_html, error_html, error_html, error_dict, error_df
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# Run OSS Analysis - FIXED: Uses REAL ARF OSS connection
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oss_btn.click(
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fn=run_oss_analysis_real_arf,
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inputs=[scenario_dropdown],
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outputs=[
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detection_agent, recall_agent, decision_agent,
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# Step 1: Update scenario with metrics
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update_result = update_scenario_display_with_metrics(scenario_name)
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# Step 2: Run OSS analysis using REAL ARF function
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oss_result = run_oss_analysis_real_arf(scenario_name)
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# Step 3: Execute Enterprise (simulation) with boundary context
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await asyncio.sleep(1)
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