v1.0 - Version stable: multi-PC, détection UI-DETR-1, 3 modes exécution
- Frontend v4 accessible sur réseau local (192.168.1.40) - Ports ouverts: 3002 (frontend), 5001 (backend), 5004 (dashboard) - Ollama GPU fonctionnel - Self-healing interactif - Dashboard confiance Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
Dom
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core/precision/api/__init__.py
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core/precision/api/__init__.py
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"""
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API Métriques - Fiche #10
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"""
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from .metrics_api import MetricsAPI
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__all__ = ['MetricsAPI']
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core/precision/api/metrics_api.py
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core/precision/api/metrics_api.py
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"""
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API Métriques - Fiche #10 Patch D
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API REST pour accès aux métriques de précision temps réel.
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Auteur: Dom, Alice Kiro - 15 décembre 2024
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"""
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import time
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import logging
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from typing import Dict, Any, List, Optional
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from ..metrics_engine import MetricsEngine
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from ..models.metric_models import MetricType
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logger = logging.getLogger(__name__)
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class MetricsAPI:
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"""
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API REST pour métriques de précision
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Fournit endpoints optimisés pour monitoring temps réel.
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"""
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def __init__(self, metrics_engine: MetricsEngine):
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"""
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Initialise API métriques
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Args:
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metrics_engine: Instance MetricsEngine
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"""
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self.engine = metrics_engine
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def get_precision_stats(self, time_range: str = "1h") -> Dict[str, Any]:
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"""
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Statistiques précision temps réel
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Args:
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time_range: Plage temporelle ("1h", "24h", "7d")
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Returns:
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Dictionnaire statistiques précision
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"""
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try:
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time_range_seconds = self._parse_time_range(time_range)
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# Récupération métriques résolution
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resolution_metrics = self.engine.get_metrics(
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MetricType.RESOLUTION,
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limit=10000,
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time_range_seconds=time_range_seconds
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)
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if not resolution_metrics:
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return self._empty_precision_stats()
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# Calcul statistiques
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total_resolutions = len(resolution_metrics)
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successful_resolutions = sum(1 for m in resolution_metrics if m.get('success', False))
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precision_rate = successful_resolutions / total_resolutions if total_resolutions > 0 else 0.0
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# Statistiques par stratégie
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strategy_stats = {}
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for metric in resolution_metrics:
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strategy = metric.get('resolution_strategy', 'unknown')
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if strategy not in strategy_stats:
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strategy_stats[strategy] = {'total': 0, 'successful': 0}
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strategy_stats[strategy]['total'] += 1
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if metric.get('success', False):
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strategy_stats[strategy]['successful'] += 1
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# Calcul précision par stratégie
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for strategy, stats in strategy_stats.items():
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stats['precision_rate'] = stats['successful'] / stats['total'] if stats['total'] > 0 else 0.0
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# Durées moyennes
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durations = [m.get('duration_ms', 0) for m in resolution_metrics]
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avg_duration = sum(durations) / len(durations) if durations else 0.0
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p95_duration = sorted(durations)[int(len(durations) * 0.95)] if durations else 0.0
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return {
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'time_range': time_range,
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'timestamp': time.time(),
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'precision': {
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'overall_rate': precision_rate,
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'total_resolutions': total_resolutions,
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'successful_resolutions': successful_resolutions,
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'failed_resolutions': total_resolutions - successful_resolutions
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},
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'performance': {
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'avg_duration_ms': avg_duration,
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'p95_duration_ms': p95_duration
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},
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'by_strategy': strategy_stats
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}
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except Exception as e:
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logger.error(f"Failed to get precision stats: {e}")
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return self._empty_precision_stats()
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def get_performance_stats(self, time_range: str = "1h") -> Dict[str, Any]:
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"""
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Statistiques performance système
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Args:
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time_range: Plage temporelle
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Returns:
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Dictionnaire statistiques performance
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"""
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try:
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# Récupération stats moteur
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engine_stats = self.engine.get_stats()
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return {
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'time_range': time_range,
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'timestamp': time.time(),
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'engine_stats': engine_stats
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}
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except Exception as e:
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logger.error(f"Failed to get performance stats: {e}")
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return {'error': str(e)}
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def get_error_stats(self, time_range: str = "1h") -> Dict[str, Any]:
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"""
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Statistiques erreurs système
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Args:
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time_range: Plage temporelle
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Returns:
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Dictionnaire statistiques erreurs
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"""
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try:
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time_range_seconds = self._parse_time_range(time_range)
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# Récupération métriques erreurs
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error_metrics = self.engine.get_metrics(
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MetricType.ERROR,
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limit=1000,
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time_range_seconds=time_range_seconds
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)
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return {
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'time_range': time_range,
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'timestamp': time.time(),
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'summary': {
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'total_errors': len(error_metrics),
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'error_rate': len(error_metrics) / max(time_range_seconds / 3600, 1)
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},
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'recent_errors': error_metrics[-10:] if error_metrics else []
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}
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except Exception as e:
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logger.error(f"Failed to get error stats: {e}")
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return {'error': str(e)}
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def export_metrics(self, format: str = "json", time_range: str = "24h") -> Dict[str, Any]:
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"""
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Export métriques pour monitoring externe
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Args:
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format: Format export ("json")
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time_range: Plage temporelle
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Returns:
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Données export formatées
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"""
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try:
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return {
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'precision': self.get_precision_stats(time_range),
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'performance': self.get_performance_stats(time_range),
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'errors': self.get_error_stats(time_range)
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}
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except Exception as e:
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logger.error(f"Failed to export metrics: {e}")
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return {'error': str(e)}
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def _parse_time_range(self, time_range: str) -> float:
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"""Parse time range string to seconds"""
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time_range = time_range.lower().strip()
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if time_range.endswith('s'):
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return float(time_range[:-1])
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elif time_range.endswith('m'):
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return float(time_range[:-1]) * 60
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elif time_range.endswith('h'):
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return float(time_range[:-1]) * 3600
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elif time_range.endswith('d'):
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return float(time_range[:-1]) * 86400
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else:
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# Default to hours
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try:
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return float(time_range) * 3600
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except ValueError:
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return 3600 # 1 hour default
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def _empty_precision_stats(self) -> Dict[str, Any]:
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"""Retourne stats précision vides"""
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return {
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'time_range': '1h',
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'timestamp': time.time(),
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'precision': {
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'overall_rate': 0.0,
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'total_resolutions': 0,
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'successful_resolutions': 0,
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'failed_resolutions': 0
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},
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'performance': {
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'avg_duration_ms': 0.0,
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'p95_duration_ms': 0.0
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},
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'by_strategy': {}
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}
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