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| """Verify AI-only mode (run_anomaly_detection=False, use_model=True): | |
| - detect_anomalies should run only the iforest, no rule detectors. | |
| - Every row in the response should carry has_anomaly=YES with a method | |
| starting "AI:". | |
| """ | |
| import sys | |
| from pathlib import Path | |
| sys.path.insert(0, str(Path(__file__).parent)) | |
| from telecom_anomaly.core.detector import TelecomAnomalyDetector | |
| from telecom_anomaly.core.models import TelecomConfig | |
| CSV = ( | |
| r"C:\my_project\work\GH_Police\main project\backend" | |
| r"\telecom_anomaly_detection\data\strictly_cleaned_data" | |
| r"\591296805 calls (1)_strictly_cleaned.csv" | |
| ) | |
| cfg = TelecomConfig() | |
| det = TelecomAnomalyDetector(cfg) | |
| det.load_data([CSV]) | |
| # AI-only mode | |
| det.detect_anomalies(use_model=True, run_rules=False) | |
| stats = det.get_statistics() | |
| print("=== AI-only mode (run_rules=False, use_model=True) ===") | |
| print(f"Total anomalies: {stats.total_anomalies_detected}") | |
| print(f"Rows with anomalies: {stats.rows_with_anomalies}") | |
| print(f"anomaly_types (should be AI: only): {stats.anomaly_types}") | |
| # Confirm no rule detector fired | |
| rule_method_seen = any( | |
| not m.startswith('AI:') | |
| for methods in det.row_anomaly_map.values() | |
| for m in methods | |
| ) | |
| print(f"Any non-AI method fired? {rule_method_seen}") | |
| # Show that 5 sample rows would land with has_anomaly=YES in the response | |
| print("\nSample of 5 flagged rows (these would have has_anomaly=YES):") | |
| shown = 0 | |
| for orig_idx, methods in det.row_anomaly_map.items(): | |
| if shown >= 5: | |
| break | |
| row = det.original_data[orig_idx] | |
| has_anomaly = "YES" if methods else "NO" | |
| print(f" row {orig_idx}: has_anomaly={has_anomaly} methods={methods}") | |
| shown += 1 | |