init.py

import requests
from pathlib import Path
import pandas as pd
from typing import Tuple, List

# Mock data for demonstration - in a real implementation, this would load from a dataset hub
def is_model_on_hub(model_name: str) -> Tuple[bool, str]:
    """
    Check if a model exists on Hugging Face Hub.
    Returns (is_on_hub, error_message)
    """
    try:
        # For demo purposes, we'll accept any model name that contains a slash
        if "/" not in model_name:
            return False, "Model name must be in format 'username/model_name'"
        
        # In a real implementation, you would check the Hugging Face API
        # response = requests.get(f"https://huggingface.co/api/models/{model_name}")
        # return response.status_code == 200, ""
        
        return True, ""
    except Exception as e:
        return False, f"Error checking model: {str(e)}"

def upload_file(filename: str, filepath: Path) -> None:
    """
    Upload a file to the dataset hub.
    In a real implementation, this would upload to Hugging Face Hub.
    """
    # For demo purposes, we'll just print the upload
    print(f"Uploading {filename} from {filepath}")
    # In a real implementation, you would use the Hugging Face Hub API
    pass

def load_all_info_from_dataset_hub() -> Tuple[Path, List[str], Path, None]:
    """
    Load evaluation queue, requested models, and results from dataset hub.
    Returns (eval_queue_repo, requested_models, jsonl_results, multilingual_jsonl_path)
    """
    # Create mock data for demonstration
    eval_queue_repo = Path("evaluation_queue")
    requested_models = []
    
    # Create a sample JSONL with ImageNet-1k results
    jsonl_results = Path("imagenet_results.jsonl")
    
    return eval_queue_repo, requested_models, jsonl_results, None