import pandas as pd
from benchmark_runner import BenchmarkRunner
import sys
import os
sys.path.append(os.path.join(os.path.dirname(__file__), '..', '..'))
from backend.core.orchestrator import Orchestrator

# Load datasets
datasets = {
    "titanic": (pd.read_csv(os.path.join(os.path.dirname(__file__), '..', '..', 'datasets', 'real_world', 'titanic.csv')), "Survived"),
    "credit_default": (pd.read_csv(os.path.join(os.path.dirname(__file__), '..', '..', 'datasets', 'real_world', 'credit_default.csv')), "default.payment.next.month"),
    "house_prices": (pd.read_csv(os.path.join(os.path.dirname(__file__), '..', '..', 'datasets', 'real_world', 'house_prices.csv')), "Price"),
    "telecom_churn": (pd.read_csv(os.path.join(os.path.dirname(__file__), '..', '..', 'datasets', 'real_world', 'telecom_churn.csv')), "Churn"),
    "news_classification": (pd.read_csv(os.path.join(os.path.dirname(__file__), '..', '..', 'datasets', 'real_world', 'news_classification.csv')), "label"),
}

orchestrator = Orchestrator()
runner = BenchmarkRunner()
results = runner.run(orchestrator, datasets)

print("Benchmark Results:")
for result in results:
    print(result)

# Save results to file
with open("experiments/benchmark_results.json", "w") as f:
    import json
    json.dump(results, f, indent=4)