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| #!/usr/bin/env python3 | |
| """ | |
| K1RL QUANT - Accuracy Tracking API | |
| HuggingFace Spaces Edition | |
| Standalone module to track training accuracy | |
| """ | |
| import re | |
| import json | |
| import time | |
| import os | |
| from datetime import datetime | |
| from collections import deque | |
| from pathlib import Path | |
| import threading | |
| # ✅ FIXED: Container-safe storage paths | |
| BASE_DIR = Path('/home/user/app') | |
| DATA_DIR = BASE_DIR / 'data' | |
| LOG_DIR = BASE_DIR / 'logs' | |
| # Ensure directories exist | |
| DATA_DIR.mkdir(parents=True, exist_ok=True) | |
| LOG_DIR.mkdir(parents=True, exist_ok=True) | |
| # ✅ FIXED: HuggingFace Spaces compatible paths | |
| accuracy_history = deque(maxlen=1000) | |
| accuracy_file = DATA_DIR / 'accuracy_data.json' | |
| # Load existing data | |
| if accuracy_file.exists(): | |
| try: | |
| with open(accuracy_file, 'r') as f: | |
| data = json.load(f) | |
| accuracy_history.extend(data) | |
| print(f"✅ Loaded {len(accuracy_history)} accuracy readings") | |
| except Exception as e: | |
| print(f"⚠️ Could not load accuracy data: {e}") | |
| def parse_accuracy_from_logs(): | |
| """Parse accuracy from quasar logs (HF Spaces compatible)""" | |
| # ✅ FIXED: HuggingFace Spaces log path | |
| log_file = LOG_DIR / 'quasar_engine.log' | |
| last_position = 0 | |
| print(f"🔍 Starting accuracy parser on {log_file}") | |
| while True: | |
| try: | |
| # Check if log file exists | |
| if not log_file.exists(): | |
| print(f"⚠️ Log file not found: {log_file}") | |
| time.sleep(10) | |
| continue | |
| with open(log_file, 'r') as f: | |
| f.seek(last_position) | |
| new_lines = f.readlines() | |
| last_position = f.tell() | |
| for line in new_lines: | |
| # Multiple patterns for accuracy detection | |
| patterns = [ | |
| r'🎯 Avg Accuracy: ([\d.]+)%', | |
| r'AVN Accuracy: ([\d.]+)%?', | |
| r'Avg Accuracy: ([\d.]+)%?', | |
| r'accuracy[:\s]+([\d.]+)%?', | |
| r'acc[:\s]+([\d.]+)%?' | |
| ] | |
| for pattern in patterns: | |
| match = re.search(pattern, line, re.IGNORECASE) | |
| if match: | |
| accuracy = float(match.group(1)) | |
| # Sanity check - accuracy should be 0-100 | |
| if 0 <= accuracy <= 100: | |
| timestamp = datetime.now().isoformat() | |
| data_point = { | |
| 'timestamp': timestamp, | |
| 'accuracy': accuracy, | |
| 'iteration': len(accuracy_history) + 1 | |
| } | |
| accuracy_history.append(data_point) | |
| print(f"📈 Accuracy: {accuracy:.1f}% (iteration {data_point['iteration']})") | |
| # Save periodically | |
| if len(accuracy_history) % 10 == 0: | |
| save_accuracy_data() | |
| break # Only take first match per line | |
| time.sleep(5) | |
| except Exception as e: | |
| print(f"⚠️ Error parsing logs: {e}") | |
| time.sleep(10) | |
| def save_accuracy_data(): | |
| """Save accuracy data to file""" | |
| try: | |
| with open(accuracy_file, 'w') as f: | |
| json.dump(list(accuracy_history), f, indent=2) | |
| except Exception as e: | |
| print(f"⚠️ Could not save accuracy data: {e}") | |
| def get_current_accuracy(): | |
| """Get current accuracy""" | |
| if accuracy_history: | |
| return accuracy_history[-1] | |
| return {'accuracy': 0, 'timestamp': None, 'iteration': 0} | |
| def get_accuracy_history(): | |
| """Get all history""" | |
| return list(accuracy_history) | |
| def get_accuracy_stats(): | |
| """Get comprehensive statistics""" | |
| if not accuracy_history: | |
| return { | |
| 'current': 0, | |
| 'average': 0, | |
| 'min': 0, | |
| 'max': 0, | |
| 'count': 0, | |
| 'last_10_avg': 0, | |
| 'trend': 'unknown' | |
| } | |
| accuracies = [d['accuracy'] for d in accuracy_history] | |
| # Calculate trend | |
| trend = 'stable' | |
| if len(accuracies) >= 20: | |
| recent_avg = sum(accuracies[-10:]) / 10 | |
| older_avg = sum(accuracies[-20:-10]) / 10 | |
| if recent_avg > older_avg * 1.02: # 2% improvement | |
| trend = 'up' | |
| elif recent_avg < older_avg * 0.98: # 2% decline | |
| trend = 'down' | |
| return { | |
| 'current': accuracies[-1], | |
| 'average': sum(accuracies) / len(accuracies), | |
| 'min': min(accuracies), | |
| 'max': max(accuracies), | |
| 'count': len(accuracies), | |
| 'last_10_avg': sum(accuracies[-10:]) / min(10, len(accuracies)), | |
| 'trend': trend, | |
| 'std_dev': (sum((x - sum(accuracies)/len(accuracies))**2 for x in accuracies) / len(accuracies))**0.5, | |
| 'latest_timestamp': accuracy_history[-1]['timestamp'] if accuracy_history else None | |
| } | |
| def get_accuracy_by_timerange(hours=24): | |
| """Get accuracy data for specific time range""" | |
| if not accuracy_history: | |
| return [] | |
| # Filter by timestamp (last N hours) | |
| cutoff_time = datetime.now().timestamp() - (hours * 3600) | |
| filtered = [] | |
| for entry in accuracy_history: | |
| try: | |
| entry_time = datetime.fromisoformat(entry['timestamp']).timestamp() | |
| if entry_time >= cutoff_time: | |
| filtered.append(entry) | |
| except: | |
| # Include entries with invalid timestamps | |
| filtered.append(entry) | |
| return filtered | |
| # ✅ ADDED: HuggingFace Spaces health check | |
| def get_parser_status(): | |
| """Get parser health status""" | |
| log_file = LOG_DIR / 'quasar_engine.log' | |
| status = { | |
| 'running': parser_thread.is_alive() if 'parser_thread' in globals() else False, | |
| 'log_file_exists': log_file.exists(), | |
| 'log_file_path': str(log_file), | |
| 'total_readings': len(accuracy_history), | |
| 'last_reading': accuracy_history[-1] if accuracy_history else None, | |
| 'data_file_exists': accuracy_file.exists(), | |
| 'data_file_path': str(accuracy_file) | |
| } | |
| return status | |
| # Start parser thread | |
| print("🚀 Starting accuracy parser thread...") | |
| parser_thread = threading.Thread(target=parse_accuracy_from_logs, daemon=True) | |
| parser_thread.start() | |
| # ✅ ADDED: Graceful shutdown handler | |
| import atexit | |
| def cleanup(): | |
| """Save data on shutdown""" | |
| print("💾 Saving accuracy data on shutdown...") | |
| save_accuracy_data() | |
| atexit.register(cleanup) | |
| if __name__ == "__main__": | |
| print("=" * 60) | |
| print("K1RL QUANT - Accuracy Tracker") | |
| print("HuggingFace Spaces Edition 🤗") | |
| print("=" * 60) | |
| print(f"📁 Data directory: {DATA_DIR}") | |
| print(f"📁 Log directory: {LOG_DIR}") | |
| print(f"📊 Loaded {len(accuracy_history)} existing readings") | |
| print("🔄 Parser running in background...") | |
| print("=" * 60) | |
| # Keep alive | |
| try: | |
| while True: | |
| time.sleep(60) | |
| if len(accuracy_history) > 0: | |
| latest = accuracy_history[-1] | |
| print(f"📈 Latest accuracy: {latest['accuracy']:.1f}% ({latest['timestamp']})") | |
| except KeyboardInterrupt: | |
| print("🛑 Shutting down accuracy tracker...") | |
| cleanup() | |