# Base costs mapping: {"category": {"water": L, "energy": kWh}}
BASE_COSTS = {
    "simple factual question": {"water": 0.5, "energy": 0.01},
    "mathematical calculation": {"water": 0.3, "energy": 0.005},
    "creative content generation": {"water": 5.0, "energy": 0.5},
    "complex research query": {"water": 10.0, "energy": 1.0}
}

def get_confidence_multiplier(confidence_score):
    if confidence_score > 0.8:
        return 1.0
    elif 0.5 <= confidence_score <= 0.8:
        return 1.2  # Add 20% uncertainty buffer
    else:
        return 1.5  # Add 50% buffer

def get_length_factor(query_text):
    word_count = len(query_text.split())
    if word_count < 20:
        return 1.0
    elif 20 <= word_count <= 50:
        return 1.3
    else:
        return 1.5

def calculate_impact(category, confidence_score, query_text):
    base_cost = BASE_COSTS.get(category, {"water": 0, "energy": 0})
    conf_mult = get_confidence_multiplier(confidence_score)
    len_factor = get_length_factor(query_text)

    water_impact = base_cost["water"] * conf_mult * len_factor
    energy_impact = base_cost["energy"] * conf_mult * len_factor

    return {"water": round(water_impact, 2), "energy": round(energy_impact, 3)}