import pickle import pandas as pd # 加载模型 def load_model(): with open('model_optimize/pkl/RF_filt.pkl', 'rb') as f: return pickle.load(f) # 初始化模型 model = load_model() # 模型会在model.py被导入时加载一次 # 预测函数 def predict(input_data: pd.DataFrame): # 假设输入数据已经准备好 predictions = model.predict(input_data) return predictions.tolist() if __name__ == '__main__': # 测试 predict 函数 x = pd.DataFrame([{ "organic_matter": 5.2, "chloride": 3.1, "cec": 25.6, "h_concentration": 0.5, "hn": 12.4, "al_concentration": 0.8, "free_alumina": 1.2, "free_iron": 0.9, "delta_ph": -0.2 }]) print(predict(x)) # 预测结果