Refactor cockpit to use DockerTmuxController pattern
Based on claude-code-tools TmuxCLIController, this refactor: - Added DockerTmuxController class for robust tmux session management - Implements send_keys() with configurable delay_enter - Implements capture_pane() for output retrieval - Implements wait_for_prompt() for pattern-based completion detection - Implements wait_for_idle() for content-hash-based idle detection - Implements wait_for_shell_prompt() for shell prompt detection Also includes workflow improvements: - Pre-task git snapshot before agent execution - Post-task commit protocol in agent guidelines Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
admin
313
lib/health_report_generator.py
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313
lib/health_report_generator.py
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#!/usr/bin/env python3
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"""
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Health Report Generator
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Generates formatted health reports with:
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- 0-100 overall scores
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- Component breakdown
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- Specific issue examples
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- Actionable recommendations
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"""
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import json
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from datetime import datetime
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from typing import List, Dict
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from pathlib import Path
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class HealthReportGenerator:
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"""Generate formatted health reports."""
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def __init__(self):
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"""Initialize report generator."""
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pass
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def generate_dashboard_report(self, health_data: Dict) -> str:
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"""
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Generate formatted dashboard report.
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Args:
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health_data: Health data from system orchestrator
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Returns:
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Formatted dashboard string
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"""
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overall = health_data['overall_score']
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status = health_data['status'].upper()
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timestamp = datetime.fromtimestamp(health_data['timestamp']).strftime('%Y-%m-%d %H:%M UTC')
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report = f"""
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╔════════════════════════════════════════════════════════════════════╗
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║ LUZIA SYSTEM HEALTH REPORT ║
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║ {timestamp:42} ║
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╚════════════════════════════════════════════════════════════════════╝
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OVERALL HEALTH SCORE: {overall:3.1f}/100 [{self._status_emoji(status)} {status}]
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━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
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COMPONENT BREAKDOWN:
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"""
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components = health_data.get('component_scores', {})
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for name, score in components.items():
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emoji = self._score_emoji(score)
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status_str = 'healthy' if score >= 80 else 'degraded' if score >= 60 else 'critical'
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report += f" {name:15} {score:6.1f}/100 {emoji} {status_str}\n"
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report += "\n" + "━" * 70 + "\n\n"
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return report
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def generate_component_report(self, component_name: str, component_data: Dict) -> str:
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"""
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Generate detailed component report.
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Args:
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component_name: Name of component (kg, conductor, etc)
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component_data: Component health data
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Returns:
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Formatted component report
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"""
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report = f"\n{'=' * 70}\n"
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report += f"{component_name.upper()} COMPONENT REPORT\n"
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report += f"{'=' * 70}\n\n"
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# Score
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score = component_data.get('health_score') or component_data.get('overall_score', 0)
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status = component_data.get('status', 'unknown').upper()
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report += f"Score: {score:3.1f}/100 [{status}]\n\n"
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# Issues
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issues = component_data.get('issues', [])
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if issues:
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report += f"ISSUES FOUND ({len(issues)}):\n\n"
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for i, issue in enumerate(issues[:10], 1):
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if isinstance(issue, dict):
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report += f" [{i}] {issue.get('severity', 'UNKNOWN').upper()}\n"
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report += f" {issue.get('pattern', 'Unknown pattern')}\n"
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if 'example' in issue:
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example = issue['example']
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if len(example) > 80:
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example = example[:80] + "..."
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report += f" Example: {example}\n\n"
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else:
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report += f" [{i}] {issue}\n\n"
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# Recommendations
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recommendations = component_data.get('recommendations', [])
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if recommendations:
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report += f"RECOMMENDATIONS:\n\n"
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for i, rec in enumerate(recommendations, 1):
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report += f" {i}. {rec}\n"
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report += "\n"
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return report
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def generate_summary_report(self, health_data: Dict) -> str:
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"""
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Generate executive summary report.
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Args:
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health_data: Health data from system orchestrator
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Returns:
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Summary report string
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"""
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overall = health_data['overall_score']
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timestamp = datetime.fromtimestamp(health_data['timestamp']).strftime('%Y-%m-%d %H:%M UTC')
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report = f"""
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╔════════════════════════════════════════════════════════════════════╗
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║ SYSTEM HEALTH SUMMARY ║
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║ {timestamp:42} ║
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╚════════════════════════════════════════════════════════════════════╝
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OVERALL SCORE: {overall:3.1f}/100
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COMPONENT STATUS:
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"""
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components = health_data.get('component_scores', {})
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for name, score in components.items():
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emoji = self._score_emoji(score)
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report += f" ├─ {name:20} {score:6.1f}/100 {emoji}\n"
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report += """
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NEXT STEPS:
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"""
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# Provide actionable next steps based on score
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if overall >= 80:
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report += """
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✓ System is healthy - continue normal operations
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- Run weekly full audits for proactive monitoring
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- Review error patterns for systemic improvements
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"""
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elif overall >= 60:
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report += f"""
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⚠ System is degraded - {int(100 - overall)} points below healthy threshold
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- Address component issues in order of severity
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- Run luzia health --full for detailed analysis
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- Implement recommended fixes for each component
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"""
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else:
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report += """
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✗ System is critical - immediate action required
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- Run luzia health --full immediately
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- Address URGENT issues first
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- Contact administrator if problems persist
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"""
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report += f"\nFor detailed analysis:\n luzia health --full\n\n"
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return report
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def generate_full_report(self, all_health_data: Dict) -> str:
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"""
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Generate comprehensive full system report.
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Args:
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all_health_data: Complete health data dict
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Returns:
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Full report string
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"""
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report = self.generate_dashboard_report(all_health_data)
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# Add capacity section
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capacity = all_health_data.get('capacity', {})
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report += f"""
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SYSTEM CAPACITY:
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Disk Usage: {capacity['disk']['usage_pct']:5.1f}% ({capacity['disk']['status']})
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Memory Usage: {capacity['memory']['usage_pct']:5.1f}% ({capacity['memory']['status']})
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CPU Load: {capacity['cpu']['load_pct']:5.1f}% ({capacity['cpu']['status']})
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Concurrency: {capacity['concurrency']['active_agents']}/{capacity['concurrency']['max_concurrent']} agents
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"""
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# Configuration status
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config = all_health_data.get('configuration', {})
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report += f"""
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CONFIGURATION STATUS:
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Config File: {'✓' if config['config_file_valid'] else '✗'}
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Permissions: {'✓' if config['permissions_valid'] else '✗'}
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Databases: {'✓' if config['databases_accessible'] else '✗'}
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MCP Servers: {'✓' if config['mcp_servers_configured'] else '✗'}
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"""
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# Integration tests
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integration = all_health_data.get('integration', {})
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report += f"""
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INTEGRATION TESTS:
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KG Query: {'✓' if integration['kg_query'] else '✗'}
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Conductor R/W: {'✓' if integration['conductor_rw'] else '✗'}
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Context Retrieval: {'✓' if integration['context_retrieval'] else '✗'}
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Bash Execution: {'✓' if integration['bash_execution'] else '✗'}
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"""
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# Issues summary
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all_issues = []
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all_issues.extend(capacity.get('issues', []))
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all_issues.extend(config.get('issues', []))
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all_issues.extend(integration.get('issues', []))
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if all_issues:
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report += f"""
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ISSUES FOUND ({len(all_issues)}):
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"""
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for issue in all_issues[:20]:
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report += f" • {issue}\n"
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if len(all_issues) > 20:
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report += f"\n ... and {len(all_issues) - 20} more issues\n"
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report += f"\n{'━' * 70}\n"
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return report
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def save_report(self, filename: str, content: str) -> Path:
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"""
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Save report to file.
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Args:
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filename: Filename to save
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content: Report content
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Returns:
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Path to saved file
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"""
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output_path = Path('/home/admin') / filename
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output_path.write_text(content)
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return output_path
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def _status_emoji(self, status: str) -> str:
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"""Get emoji for status."""
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emojis = {
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'HEALTHY': '✅',
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'DEGRADED': '⚠️',
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'CRITICAL': '❌',
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'UNKNOWN': '❓'
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}
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return emojis.get(status, '❓')
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def _score_emoji(self, score: float) -> str:
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"""Get emoji for score."""
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if score >= 80:
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return '✅'
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elif score >= 60:
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return '⚠️'
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else:
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return '❌'
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if __name__ == '__main__':
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generator = HealthReportGenerator()
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# Example health data
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sample_data = {
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'overall_score': 87,
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'status': 'healthy',
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'timestamp': 1704729600,
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'component_scores': {
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'kg': 92,
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'conductor': 84,
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'context': 89,
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'scripts': 95,
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'routines': 88,
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'capacity': 81,
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'configuration': 98,
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'integration': 100
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},
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'capacity': {
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'disk': {'usage_pct': 82, 'status': 'warning'},
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'memory': {'usage_pct': 65, 'status': 'healthy'},
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'cpu': {'load_pct': 45, 'status': 'healthy'},
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'concurrency': {'active_agents': 2, 'max_concurrent': 4},
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'issues': []
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},
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'configuration': {
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'config_file_valid': True,
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'permissions_valid': True,
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'databases_accessible': True,
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'mcp_servers_configured': True,
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'issues': []
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},
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'integration': {
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'kg_query': True,
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'conductor_rw': True,
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'context_retrieval': True,
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'bash_execution': True,
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'issues': []
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}
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}
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print(generator.generate_dashboard_report(sample_data))
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print(generator.generate_summary_report(sample_data))
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