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utils/seed_data.py

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+"""
+Seeds the incident log CSV and ChromaDB with sample data for testing.
+Run once: python -m utils.seed_data
+"""
+
+import sys, os
+sys.path.insert(0, os.path.dirname(os.path.dirname(__file__)))
+
+from utils.incident_logger import log_incident
+from rag_module.vector_store import rebuild_from_csv
+
+SAMPLE_INCIDENTS = [
+    ("KA05MN1234", "car",   "Gate_A",      "normal",       ""),
+    ("MH12AB5678", "truck", "VIP_LOT",      "unauthorized", "Heavy vehicle in VIP zone"),
+    ("KA01XY9999", "car",   "Gate_B",      "flagged",      "Reported stolen vehicle"),
+    ("DL4CAF0001", "bus",   "Gate_A",      "normal",       ""),
+    ("TN09CD2222", "car",   "COMPACT_ONLY","normal",       ""),
+    ("UNKNOWN",    "car",   "Gate_C",      "flagged",      "Plate unreadable"),
+    ("KA05MN1234", "car",   "Gate_A",      "anomaly",      "Same plate seen 6x in 10 min"),
+    ("AP28PQ3344", "motorcycle", "Gate_B", "normal",       ""),
+    ("KA01XY9999", "car",   "Gate_A",      "unauthorized", "Blacklisted vehicle re-entry"),
+    ("GJ05BK7777", "car",   "Gate_A",      "normal",       ""),
+]
+
+print("Seeding incidents...")
+for plate, cls, zone, status, notes in SAMPLE_INCIDENTS:
+    row = log_incident(plate, cls, zone, status, notes)
+    print(f"  Logged: {row['id']} | {plate} | {status}")
+
+print("\nRebuilding ChromaDB from CSV...")
+rebuild_from_csv()
+print("Done! You can now query the RAG pipeline.")