update

app.py

@@ -33,7 +33,7 @@ except Exception:
 # ----------------------------
 # Load data & artifacts
 # ----------------------------
-DATA_PATH = "data/AAPL_stock_2015_2025.csv"
+DATA_PATH = "AAPL_stock_2015_2025.csv"
 df = pd.read_csv(DATA_PATH)
 df["Date"] = pd.to_datetime(df["Date"])
 df = df.sort_values("Date").set_index("Date")
@@ -67,8 +67,10 @@ if PROPHET_AVAILABLE and os.path.exists(PROPHET_PATH):
         prophet_model = None
 
 if TENSORFLOW_AVAILABLE and os.path.exists(LSTM_PATH):
+    print("✅ TensorFlow imported successfully")
     try:
         lstm_model = load_model(LSTM_PATH, compile=False)
+        print("✅ LSTM model loaded:", LSTM_PATH)
     except Exception:
         lstm_model = None
 
@@ -307,7 +309,7 @@ def do_backtest(test_days, arima, prophet, lstm):
 
 
 with gr.Blocks(title="DataSynthis_ML_JobTask") as demo:
-    gr.Markdown("# 📈 Multivariate Stock Forecasting (AAPL)\nCompare ARIMA, Prophet, and LSTM.")
+    gr.Markdown("# Multivariate Stock Forecasting (AAPL)\nCompare ARIMA, Prophet, and LSTM.")
     with gr.Tab("Forecast"):
         with gr.Row():
             horizon = gr.Slider(7, 90, value=30, step=1, label="Forecast horizon (days)")

requirements.txt

@@ -10,5 +10,4 @@ ujson==5.10.0
 tensorflow-cpu==2.12.0
 joblib==1.4.2
 tqdm==4.67.1
-seaborn==0.12.2
-tensorflow==2.12.0
+seaborn==0.12.2