#!/usr/bin/env python3
"""
Script sederhana untuk menjalankan fine-tuning Novita AI
"""

import os
import sys
from pathlib import Path

# Import NovitaAIClient dari script yang sudah ada
sys.path.append('scripts')
from novita_ai_setup_v2 import NovitaAIClient, create_sample_dataset

def main():
    print("🚀 Novita AI Fine-tuning - Auto Run")
    print("=" * 50)
    
    # Check environment variables
    api_key = os.getenv('NOVITA_API_KEY')
    if not api_key:
        print("❌ NOVITA_API_KEY tidak ditemukan")
        print("Silakan set: export NOVITA_API_KEY='your_key'")
        return
    
    base_url = os.getenv('NOVITA_BASE_URL', 'https://api.novita.ai/openai')
    print(f"🔑 API Key: {api_key[:10]}...{api_key[-10:]}")
    print(f"🌐 Base URL: {base_url}")
    
    # Create client
    client = NovitaAIClient(api_key)
    client.base_url = base_url
    
    # Test connection
    print("\n1️⃣ Testing connection...")
    if not client.test_connection():
        print("❌ Koneksi gagal")
        return
    
    # Get available models
    print("\n2️⃣ Getting available models...")
    models = client.get_available_models()
    
    if not models:
        print("❌ Tidak bisa mendapatkan daftar model")
        return
    
    # Select model automatically (Llama 3.2 1B Instruct if available)
    selected_model = None
    preferred_models = [
        "meta-llama/llama-3.2-1b-instruct",
        "meta-llama/llama-3.2-3b-instruct",
        "qwen/qwen3-4b-fp8",
        "qwen/qwen3-8b-fp8"
    ]
    
    print("\n🎯 Selecting model...")
    for preferred in preferred_models:
        if isinstance(models, dict) and 'data' in models:
            for model in models['data']:
                if model.get('id') == preferred:
                    selected_model = preferred
                    print(f"✅ Selected: {preferred}")
                    break
        elif isinstance(models, list):
            for model in models:
                if model.get('id') == preferred:
                    selected_model = preferred
                    print(f"✅ Selected: {preferred}")
                    break
        
        if selected_model:
            break
    
    if not selected_model:
        # Fallback to first available model
        if isinstance(models, dict) and 'data' in models and models['data']:
            selected_model = models['data'][0].get('id')
        elif isinstance(models, list) and models:
            selected_model = models[0].get('id')
        
        if selected_model:
            print(f"⚠️  Fallback to: {selected_model}")
        else:
            print("❌ Tidak ada model yang tersedia")
            return
    
    # Create dataset
    print("\n3️⃣ Preparing dataset...")
    training_file = create_sample_dataset()
    
    # Create fine-tuning job
    print(f"\n4️⃣ Creating fine-tuning job...")
    print(f"   Model: {selected_model}")
    print(f"   Training file: {training_file}")
    
    job = client.create_fine_tuning_job(selected_model, training_file)
    
    if job:
        print(f"\n✅ Fine-tuning job created successfully!")
        print(f"   Job ID: {job.get('id')}")
        print(f"   Status: {job.get('status', 'unknown')}")
        print(f"   Model: {job.get('model', 'unknown')}")
        
        print(f"\n📋 Next steps:")
        print(f"1. Monitor job status")
        print(f"2. Check logs for progress")
        print(f"3. Download fine-tuned model when complete")
        
    else:
        print("\n❌ Failed to create fine-tuning job")
        print("💡 Check the error messages above")

if __name__ == "__main__":
    main()