1

app.py

@@ -11,7 +11,7 @@ import threading
 # 配置参数
 MAX_LENGTH = 512
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
-SAVE_DIR = "./cate1"  # 模型路径
+SAVE_DIR = "cate1"  # 模型路径
 LABEL_ENCODER_PATH = "cate1/label_encoder.pkl"  # 标签映射器路径
 
 app = Flask(__name__)
@@ -124,7 +124,7 @@ def health_check():
 
 
 if __name__ == '__main__':
-    app.run(host='0.0.0.0', port=5000, threaded=True)
+    app.run(host='0.0.0.0', port=5002, threaded=True)
 else:
     application = app  # 兼容 WSGI 标准（如 Gunicorn）
 

bert_train.py

@@ -18,6 +18,7 @@ import joblib
 # 1. 参数配置（集中管理）
 class Config:
     MODEL_NAME = "bert-base-chinese"
+    Train_CSV = "order_address.csv"
     MAX_LENGTH = 64
     BATCH_SIZE = 32
     NUM_EPOCHS = 5
@@ -157,7 +158,7 @@ def batch_predict(texts, model, tokenizer, label_map, top_k=1, batch_size=16):
 # 主流程
 if __name__ == "__main__":
     # 1. 加载数据
-    df = load_data("goods_cate.csv")
+    df = load_data(Config.Train_CSV)
 
     # 2. 数据清洗 - 只保留中文
     print("🧼 开始清洗文本数据...")