import pandas as pd
import numpy as np

class MockCropModel:
    def __init__(self):
        self.knowledge_base = {
            ('loamy', 'tropical'): ['Cassava', 'Banana', 'Rice'],
            ('clay', 'temperate'): ['Wheat', 'Potatoes', 'Barley'],
            ('sandy', 'arid'): ['Sorghum', 'Millet', 'Dates'],
            ('default', 'default'): ['Maize', 'Beans', 'Soybeans']
        }
    
    def predict(self, soil_type, climate):
        soil = soil_type.lower()
        climate = climate.lower()
        
        for key in self.knowledge_base:
            if soil in key[0] and climate in key[1]:
                crops = self.knowledge_base[key]
                break
        else:
            crops = self.knowledge_base[('default', 'default')]
        
        confidences = np.linspace(0.9, 0.7, num=len(crops))
        return pd.DataFrame({
            'Crop': crops,
            'Confidence': confidences,
            'Soil Type': soil_type,
            'Climate Zone': climate
        })