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5f91e0b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 | #!/usr/bin/env python
"""
Train initial models from Kaggle datasets.
"""
import asyncio
import sys
import os
import logging
# Add backend and app to path
sys.path.append(os.path.join(os.getcwd(), "backend"))
sys.path.append(os.path.join(os.getcwd(), "backend", "app"))
from app.services.model_training_scheduler import ModelTrainingScheduler
logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s — %(message)s")
logger = logging.getLogger("TRAIN")
async def main():
logger.info("Starting initial model training...")
# Ensure data dirs exist
from app.config import ensure_data_dirs
ensure_data_dirs()
scheduler = ModelTrainingScheduler()
domains = ["finance", "tech", "healthcare"]
results = await scheduler.train_all_domains(domains)
print("\n" + "="*50)
print("TRAINING RESULTS")
print("="*50)
for domain, meta in results.items():
if "error" in meta:
print(f"✗ {domain}: FAILED - {meta['error']}")
else:
print(f"✓ {domain}: SUCCESS - {meta.get('selected_pairs', 0)} pairs, {meta.get('size_kb', 0):.1f} KB")
print("="*50)
if __name__ == "__main__":
asyncio.run(main())
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