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>
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admin
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lib/kg_review_marker.py
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240
lib/kg_review_marker.py
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#!/usr/bin/env python3
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"""
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Knowledge Graph Review Marker
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Marks incomplete research sessions for manual review without auto-fixing.
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Creates review queue entries and annotations in the KG database.
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"""
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import json
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import time
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from datetime import datetime
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from pathlib import Path
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from typing import List, Dict
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class IncompleteResearchReviewMarker:
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"""Mark incomplete research for manual review."""
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REVIEW_QUEUE_DIR = Path('/home/admin/conductor/review')
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REVIEW_TAG = 'needs_human_review'
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def __init__(self):
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"""Initialize the review marker."""
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self.REVIEW_QUEUE_DIR.mkdir(parents=True, exist_ok=True)
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def mark_for_review(self, entity_id: str, entity_name: str, reason: str,
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severity: str = 'medium', pattern: str = 'unknown') -> Dict:
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"""
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Mark a single KG entity for review.
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Args:
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entity_id: KG entity ID
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entity_name: Human-readable entity name
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reason: Why this needs review (pattern type)
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severity: 'high' | 'medium' | 'low'
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pattern: Pattern type that triggered marking
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Returns:
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Dict with review_id, file_path, status
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"""
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review_id = f"{entity_id}_review_{int(time.time())}"
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review_file = self.REVIEW_QUEUE_DIR / f"{review_id}.json"
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review_data = {
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'review_id': review_id,
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'entity_id': entity_id,
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'entity_name': entity_name,
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'pattern': pattern,
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'severity': severity,
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'reason': reason,
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'marked_at': datetime.now().isoformat(),
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'marked_by': 'kg_health_checker',
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'status': 'pending_review',
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'action_required': self._get_action_for_pattern(pattern),
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'notes': ''
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}
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review_file.write_text(json.dumps(review_data, indent=2))
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return {
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'review_id': review_id,
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'entity_id': entity_id,
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'file_path': str(review_file),
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'status': 'marked'
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}
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def mark_findings_batch(self, findings: List[Dict]) -> Dict:
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"""
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Mark multiple findings for review.
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Args:
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findings: List of finding dicts from KGPatternDetector
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Returns:
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Dict with:
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- 'marked_count': Number of sessions marked
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- 'review_files': List of created files
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- 'summary': Breakdown by severity
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"""
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marked = []
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review_files = []
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summary = {'high': 0, 'medium': 0, 'low': 0}
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for finding in findings:
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# Only mark KG database findings (not files)
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if finding['source'] != 'kg_database':
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continue
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result = self.mark_for_review(
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entity_id=finding['id'],
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entity_name=finding.get('name', 'unknown'),
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reason=f"Pattern: {finding['pattern']}",
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severity=finding.get('severity', 'medium'),
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pattern=finding['pattern']
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)
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marked.append(result)
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review_files.append(result['file_path'])
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summary[finding.get('severity', 'medium')] += 1
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return {
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'marked_count': len(marked),
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'review_files': review_files,
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'summary': summary,
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'review_queue_path': str(self.REVIEW_QUEUE_DIR),
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'timestamp': time.time()
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}
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def create_review_queue(self, findings: List[Dict]) -> Dict:
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"""
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Create review queue from findings (alias for mark_findings_batch).
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Args:
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findings: List of findings to create review queue for
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Returns:
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Review queue creation result
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"""
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return self.mark_findings_batch(findings)
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def get_pending_reviews(self) -> List[Dict]:
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"""Get list of all pending review items."""
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reviews = []
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if not self.REVIEW_QUEUE_DIR.exists():
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return reviews
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for review_file in self.REVIEW_QUEUE_DIR.glob('*_review_*.json'):
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try:
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data = json.loads(review_file.read_text())
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if data.get('status') == 'pending_review':
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reviews.append(data)
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except Exception:
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pass
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return sorted(reviews, key=lambda x: x.get('severity') == 'high', reverse=True)
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def mark_review_complete(self, review_id: str, resolution: str = '') -> Dict:
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"""
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Mark a review as complete.
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Args:
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review_id: The review ID to complete
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resolution: What was done to resolve the issue
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Returns:
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Updated review data
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"""
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review_file = self.REVIEW_QUEUE_DIR / f"{review_id}.json"
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if not review_file.exists():
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return {'status': 'error', 'message': f'Review {review_id} not found'}
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data = json.loads(review_file.read_text())
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data['status'] = 'completed'
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data['completed_at'] = datetime.now().isoformat()
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data['resolution'] = resolution
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review_file.write_text(json.dumps(data, indent=2))
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return {
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'status': 'completed',
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'review_id': review_id,
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'resolution': resolution
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}
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def get_review_stats(self) -> Dict:
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"""Get statistics about review queue."""
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reviews = []
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if not self.REVIEW_QUEUE_DIR.exists():
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return {
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'pending': 0,
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'completed': 0,
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'by_severity': {},
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'by_pattern': {}
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}
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pending = 0
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completed = 0
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by_severity = {}
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by_pattern = {}
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for review_file in self.REVIEW_QUEUE_DIR.glob('*_review_*.json'):
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try:
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data = json.loads(review_file.read_text())
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severity = data.get('severity', 'unknown')
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pattern = data.get('pattern', 'unknown')
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if data.get('status') == 'pending_review':
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pending += 1
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elif data.get('status') == 'completed':
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completed += 1
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by_severity[severity] = by_severity.get(severity, 0) + 1
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by_pattern[pattern] = by_pattern.get(pattern, 0) + 1
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except Exception:
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pass
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return {
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'pending': pending,
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'completed': completed,
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'total': pending + completed,
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'by_severity': by_severity,
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'by_pattern': by_pattern,
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'review_queue_path': str(self.REVIEW_QUEUE_DIR)
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}
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def _get_action_for_pattern(self, pattern: str) -> str:
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"""Get recommended action for a pattern."""
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actions = {
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'unresolved_question': 'Resume research session with user feedback; complete final analysis',
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'incomplete_duration': 'Investigate why session ended early; may need deeper research',
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'claude_no_conclusion': 'Add missing conclusion/summary section to analysis',
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'unknown': 'Review and complete research session'
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}
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return actions.get(pattern, actions['unknown'])
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if __name__ == '__main__':
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marker = IncompleteResearchReviewMarker()
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# Test: create sample review
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result = marker.mark_for_review(
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entity_id='research_12345',
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entity_name='Structured Repositories & Trusted Data Sources for AI Agents',
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reason='Session ended with unresolved user question',
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severity='high',
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pattern='unresolved_question'
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)
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print(f"Created review: {result['review_id']}")
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print(f"Review file: {result['file_path']}")
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# Show stats
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stats = marker.get_review_stats()
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print(f"\nReview queue stats:")
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print(f" Pending: {stats['pending']}")
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print(f" Completed: {stats['completed']}")
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print(f" By severity: {stats['by_severity']}")
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