Update app.py

app.py

@@ -15,14 +15,16 @@ MODEL_NAME = "databricks/dolly-v2-3b"
 FINBERT_MODEL_NAME = "yiyanghkust/finbert-tone"
 SYMBOL = '^KLSE'  # KLCI index symbol
 START_DATE = '2020-01-01'
-END_DATE = '2023-12-31'
+END_DATE = '2024-07-31'
 
 # Initialize Alpaca API
 api = REST(ALPACA_API_KEY, ALPACA_SECRET_KEY, ALPACA_BASE_URL)
 
 # Load Models
 dolly_tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
-dolly_model = AutoModelForCausalLM.from_pretrained(MODEL_NAME)
+dolly_model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, torch_dtype.float16) # half precision
+dolly_model.gradient_checkpointing_enable() # memory-efficient loading
+print("Loading FinBERT model...")
 finbert_tokenizer = AutoTokenizer.from_pretrained(FINBERT_MODEL_NAME)
 finbert_model = AutoModelForSequenceClassification.from_pretrained(FINBERT_MODEL_NAME)
 
@@ -59,7 +61,7 @@ def generate_prediction(prompt):
     return dolly_tokenizer.decode(outputs[0], skip_special_tokens=True)
 
 # Step 5: Execute Trade with Alpaca
-def execute_trade(signal, symbol='AAPL', qty=1):
+def execute_trade(signal, symbol='Genting Bhd', qty=1):
     print(f"Executing trade signal: {signal}")
     if signal == "buy":
         api.submit_order(symbol=symbol, qty=qty, side='buy', type='market', time_in_force='gtc')