session-stats-history

#!/usr/bin/env python3
"""
Muestra el historial acumulado de todas las sesiones de OpenCode.
Uso: session-stats-history

Lee session_history.json y muestra:
- Total de sesiones
- Total de requests
- Total de tokens input/output
- Costo total acumulado
- Desglose por modelo
"""

import json
from pathlib import Path

def format_number(n):
    """Formatea números grandes con separadores."""
    if n >= 1000000:
        return f"{n/1000000:.1f}M"
    elif n >= 1000:
        return f"{n/1000:.1f}K"
    return str(n)

def format_cost(cost):
    """Formatea costo en dólares."""
    if cost >= 1:
        return f"${cost:.2f}"
    elif cost >= 0.01:
        return f"${cost:.4f}"
    return f"${cost:.6f}"

def main():
    history_file = Path(__file__).parent / "session_history.json"
    
    if not history_file.exists():
        print("No hay historial de sesiones disponible")
        return
    
    try:
        with open(history_file, 'r') as f:
            data = json.load(f)
    except json.JSONDecodeError:
        print("Error leyendo el historial de sesiones")
        return
    
    if not data:
        print("El historial está vacío")
        return
    
    # Sumar todos los valores
    total_requests = sum(item.get("requests", 0) for item in data.values())
    total_input = sum(item.get("input", 0) for item in data.values())
    total_output = sum(item.get("output", 0) for item in data.values())
    total_cost = sum(item.get("cost", 0) for item in data.values())
    total_sessions = len(data)
    
    # Agrupar por modelo de todas las sesiones
    models_totals = {}
    for session in data.values():
        by_model = session.get("by_model", {})
        for model, model_data in by_model.items():
            if model not in models_totals:
                models_totals[model] = {"requests": 0, "input": 0, "output": 0, "cost": 0}
            models_totals[model]["requests"] += model_data.get("requests", 0)
            models_totals[model]["input"] += model_data.get("input", 0)
            models_totals[model]["output"] += model_data.get("output", 0)
            models_totals[model]["cost"] += model_data.get("cost", 0)
    
    # Mostrar resumen
    print(f"📊 HISTORIAL ACUMULADO ({total_sessions} sesiones)")
    print(f"   Requests: {total_requests}")
    print(f"   Input:    {format_number(total_input)} tokens")
    print(f"   Output:   {format_number(total_output)} tokens")
    
    # Mostrar desglose por modelo
    if models_totals:
        print(f"\n📈 DESGLOSE POR MODELO:")
        # Ordenar por costo descendente
        sorted_models = sorted(models_totals.items(), key=lambda x: x[1]["cost"], reverse=True)
        for model, mdata in sorted_models:
            short_model = model.replace("antigravity-", "").replace("-thinking-high", "").replace("claude-opus-4-5", "claude-opus-4.5")
            print(f"   └─ {short_model}: {mdata['requests']} req, in:{format_number(mdata['input'])}, out:{format_number(mdata['output'])}, costo:{format_cost(mdata['cost'])}")
    
    print(f"\n💰 Costo Total Acumulado: {format_cost(total_cost)}")

if __name__ == "__main__":
    main()