import sys
import os
from sheet_manager.sheet_crud.sheet_crud import SheetManager
from sheet_manager.sheet_monitor.sheet_sync import SheetMonitor, MainLoop
import time
from pia_bench.pipe_line.piepline import BenchmarkPipeline, PipelineConfig
from sheet_manager.sheet_convert.json2sheet import update_benchmark_json
import os
import shutil
import json

def calculate_total_accuracy(metrics: dict) -> float:
    """
    Calculate the average accuracy across all categories excluding 'micro_avg'.

    Args:
        metrics (dict): Metrics dictionary containing accuracy values.

    Returns:
        float: The average accuracy across categories.
    """
    total_accuracy = 0
    total_count = 0

    for category, values in metrics.items():
        if category == "micro_avg":
            continue  # Skip 'micro_avg'

        if "accuracy" in values:
            total_accuracy += values["accuracy"]
            total_count += 1

    if total_count == 0:
        raise ValueError("No accuracy values found in the provided metrics dictionary.")

    return total_accuracy / total_count

def my_custom_function(huggingface_id, benchmark_name, prompt_cfg_name):
    model_name = huggingface_id.split("/")[-1]
    config = PipelineConfig(
        model_name=model_name,
        benchmark_name=benchmark_name,
        cfg_target_path=f"/mnt/nas_192tb/videos/huggingface_benchmarks_dataset/Leaderboard_bench/{benchmark_name}/CFG/{prompt_cfg_name}.json",
        base_path="/mnt/nas_192tb/videos/huggingface_benchmarks_dataset/Leaderboard_bench"
)
    pipeline = BenchmarkPipeline(config)
    pipeline.run()
    result = pipeline.bench_result_dict
    value = calculate_total_accuracy(result)
    print("---"*50)
    sheet = SheetManager()
    sheet.change_worksheet("model")
    sheet.update_cell_by_condition(condition_column="Model name",
                                    condition_value=model_name ,
                                    target_column=benchmark_name,
                                    target_value=value)
    
    update_benchmark_json(
    model_name = model_name, 
    benchmark_data = result, 
    target_column = benchmark_name  # 타겟 칼럼 파라미터 추가
)
    
    print(f"\n파이프라인 실행 결과:")

sheet_manager = SheetManager()
monitor = SheetMonitor(sheet_manager, check_interval=60.0)
main_loop = MainLoop(sheet_manager, monitor, callback_function=my_custom_function)

try:
    main_loop.start()
    while True:
        time.sleep(5)
except KeyboardInterrupt:
    main_loop.stop()