changed gradio interface to block

app.py

@@ -50,6 +50,10 @@ from pytz import timezone
 from pandas.tseries.offsets import BDay
 import hashlib
 
+
+import time
+import gc
+
 import threading
 lock = threading.Lock()
 # This forces all inference requests to run one at a time, which avoids file 
@@ -69,12 +73,34 @@ 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:
+            df = yf.download(*args, **kwargs)
+            if not df.empty:
+                return df
+        except Exception as e:
+            print(f"[Attempt {i+1}] yfinance error: {e}")
+        time.sleep(delay)
+    raise RuntimeError("yfinance download failed after retries.")
+
+lock = threading.Lock() 
 
 # --- Inference Function --- #
 def predict_stock():
+    
     # lightweight log print near the top of predict_stock() to verify it's hitting the cache config:
     print("YFINANCE_NO_CACHE =", os.getenv("YFINANCE_NO_CACHE"))
-  
+
+    # Check for time zone
+    now_est = datetime.now(timezone("US/Eastern"))
+    print("Current Eastern Time:", now_est)
+    print("Trying to fetch data up to:", now_est.strftime('%Y-%m-%d'))
+
     # --- Clear yfinance cache to get latest volume and price data --- #
     cache_path = os.path.expanduser("~/.cache/py-yfinance")
     if os.path.exists(cache_path):
@@ -84,22 +110,28 @@ def predict_stock():
     Stock = "NVDA"
     start_date = "2020-01-01"
     train_end_date = "2024-12-31"
-    today = datetime.today().strftime('%Y-%m-%d')
+    #today = datetime.today().strftime('%Y-%m-%d')
+    # Use EST for consistently for today
+    today = now_est.strftime('%Y-%m-%d')
 
     # Download the full dataset (might contain stale final row)
+    # solves any error with empty dataframes
     try:
-        full_data = yf.download(
-        tickers=Stock,
-        start=start_date,
-        end=today,
-        interval="1d",
-        auto_adjust=False,
-        actions=False,
-        progress=False,
-        threads=True        #<-- for parallel downloads, use True
+        full_data = safe_download(
+            tickers=Stock,
+            start=start_date,
+            end=today,
+            interval="1d",
+            auto_adjust=False,
+            actions=False,
+            progress=False,
+            threads=True        #<-- for parallel downloads, use True
         )
+
         if full_data.empty:
-            raise RuntimeError("Download failed or returned no data.")
+            print("yfinance returned empty data for:", today)
+            return "Error: Stock data not available at this time. Please try again shortly.", pd.DataFrame()
+
     except Exception as e:
         print("yfinance error:", e)
         return "Error: Could not fetch stock data. Please try again later.", pd.DataFrame()