utils.py

from typing import Optional, Dict
import pandas as pd
import matplotlib.pyplot as plt
from data_manager import data_manager

def filter_leaderboard(
    family: Optional[str] = None,
    quantization_level: Optional[str] = None
) -> pd.DataFrame:
    """Filter leaderboard data based on criteria."""
    df = data_manager.leaderboard_data.copy()
    
    if family:
        df = df[df["family"] == family]
    if quantization_level:
        df = df[df["quantization_level"] == quantization_level]
    
    return df.sort_values("score", ascending=False)

def search_responses(query: str, model: str) -> pd.DataFrame:
    """Search model responses based on query."""
    if not query or not model:
        return pd.DataFrame()
    
    filtered = data_manager.responses_data[
        data_manager.responses_data["bolum"].str.contains(query, case=False, na=False)
    ]
    
    selected_columns = ["bolum", "soru", "cevap", f"{model}_cevap"]
    return filtered[selected_columns].dropna()

def plot_section_results() -> plt.Figure:
    """Generate section results plot."""
    fig, ax = plt.subplots(figsize=(12, 6))
    avg_scores = data_manager.section_results_data.mean(numeric_only=True)
    
    bars = avg_scores.plot(kind="bar", ax=ax)
    
    # Customize plot
    ax.set_title("Average Section-Wise Performance", pad=20)
    ax.set_ylabel("Accuracy (%)")
    ax.set_xlabel("Sections")
    plt.xticks(rotation=45, ha='right')
    plt.tight_layout()
    
    # Add value labels
    for i, v in enumerate(avg_scores):
        ax.text(i, v, f'{v:.1f}%', ha='center', va='bottom')
    
    return fig

def validate_model_submission(
    model_name: str,
    base_model: str,
    revision: str,
    precision: str,
    weight_type: str,
    model_type: str
) -> tuple[bool, str]:
    """Validate model submission parameters."""
    if not all([model_name, base_model]):
        return False, "Model name and base model are required."
    
    if model_name in data_manager.leaderboard_data["model"].values:
        return False, "Model name already exists."
    
    return True, "Validation successful"