changed gradio interface to block

app.py

@@ -30,14 +30,23 @@
 # Last update: 02 Apr 2025
 #+--------------------------------------------------------------------------------------------+
 
+import os
+
+# MUST come before importing yfinance
+os.environ["YFINANCE_NO_CACHE"] = "1"   # disable cache
+os.environ["XDG_CACHE_HOME"] = "/tmp/xfake_cache"
+if not os.path.exists("/tmp/xfake_cache"):
+    os.makedirs("/tmp/xfake_cache", exist_ok=True)
+
+import yfinance as yf
 import gradio as gr
 import numpy as np
 import pandas as pd
-import yfinance as yf
+
 from datetime import datetime
 from pandas.tseries.offsets import BDay
 from tabulate import tabulate
-import os
+
 
 from tensorflow.keras.models import load_model
 from sklearn.preprocessing import MinMaxScaler
@@ -49,7 +58,7 @@ import shutil
 from pytz import timezone
 from pandas.tseries.offsets import BDay
 import hashlib
-
+import yfinance as yf
 import time
 import gc
 
@@ -69,11 +78,6 @@ NN_model.predict(np.zeros((1, 5)))  # warm-up dummy prediction
 scaler_X = joblib.load(os.path.join(model_dir, "scaler_X.pkl"))
 scaler_y = joblib.load(os.path.join(model_dir, "scaler_y.pkl"))
 
-os.environ["YFINANCE_NO_CACHE"] = "1"   # <-- 🔥 disables SQLite caching
-os.environ["XDG_CACHE_HOME"] = "/tmp/xfake_cache"
-if not os.path.exists("/tmp/xfake_cache"):
-    os.makedirs("/tmp/xfake_cache", exist_ok=True)
-
 def safe_download(*args, retries=3, delay=1, **kwargs):
     for i in range(retries):
         try: