my-gradio-app / scripts /fine_tune_agent.py
Nguyen Trong Lap
Recreate history without binary blobs
eeb0f9c
"""
Fine-tune Agent Script
Usage: python scripts/fine_tune_agent.py --agent nutrition --min-rating 4.0
"""
import argparse
from fine_tuning import get_data_collector, fine_tune_agent
def main():
parser = argparse.ArgumentParser(description='Fine-tune a healthcare agent')
parser.add_argument('--agent', required=True,
choices=['nutrition', 'exercise', 'symptom', 'mental_health', 'general_health'],
help='Agent to fine-tune')
parser.add_argument('--min-rating', type=float, default=None,
help='Minimum quality rating (1-5) to include conversations')
parser.add_argument('--model', default='gpt-4o-mini-2024-07-18',
help='Base model to fine-tune')
parser.add_argument('--suffix', default=None,
help='Suffix for fine-tuned model name')
parser.add_argument('--no-wait', action='store_true',
help='Don\'t wait for fine-tuning to complete')
args = parser.parse_args()
# Get data collector
collector = get_data_collector()
# Check conversation count
counts = collector.get_conversation_count(f"{args.agent}_agent")
agent_key = args.agent
if agent_key not in counts or counts[agent_key] == 0:
print(f"❌ No conversations found for {args.agent} agent")
print(f" Start using the chatbot to collect training data")
return
print(f"πŸ“Š Found {counts[agent_key]} conversations for {args.agent} agent")
# Export training data
print(f"\nπŸ“€ Exporting training data...")
training_file = collector.export_for_openai_finetuning(
agent_name=f"{args.agent}_agent",
min_quality_rating=args.min_rating
)
# Start fine-tuning
print(f"\nπŸš€ Starting fine-tuning job...")
result = fine_tune_agent(
agent_name=args.agent,
training_file=training_file,
model=args.model,
suffix=args.suffix,
wait_for_completion=not args.no_wait
)
if args.no_wait:
print(f"\nβœ… Fine-tuning job started: {result}")
print(f" Check status with: python scripts/check_finetuning_status.py --job-id {result}")
else:
print(f"\nβœ… Fine-tuning completed!")
print(f" Model ID: {result}")
print(f"\nπŸ’‘ To use this model, update your agent configuration:")
print(f" MODEL = '{result}'")
if __name__ == '__main__':
main()