more predictions

data/gpt_prediction.csv

@@ -1,2 +1,2 @@
 Prediction
-"ChatCompletionMessage(content=""Based on the provided data and average sentiment scores for each ticker symbol, here are the predicted next day closing prices:\n\nAAPL: $186.50\nAMZN: $173.75\nGOOGL: $141.80\nMSFT: $408.50\nTSLA: $198.20\n\nPlease note that stock price predictions are subject to market volatility and other unpredictable factors, so it's essential to conduct thorough research and analysis before making any investment decisions."", role='assistant', function_call=None, tool_calls=None)"
+"ChatCompletionMessage(content='Based on the historical data provided, here are the next day closing price predictions for the five ticker symbols:\n\n- AAPL: Predicted closing price for 2024-02-29 is $183.50\n- AMZN: Predicted closing price for 2024-02-29 is $174.00\n- GOOGL: Predicted closing price for 2024-02-29 is $142.20\n- MSFT: Predicted closing price for 2024-02-29 is $408.00\n- TSLA: Predicted closing price for 2024-02-29 is $201.20', role='assistant', function_call=None, tool_calls=None)"

src/gpt.py

@@ -28,7 +28,7 @@ def make_prediction(df_aapl, df_amzn, df_goog, df_msft, df_tsla):
         messages=[
             {
                 "role": "system",
-                "content": f"Give me a next day closing price prediction based on the five ticker symbols and data attached. {df_aapl,df_amzn,df_goog,df_msft,df_tsla}",
+                "content": f"Give me a next day closing price prediction based on the five ticker symbols and data attached. I need numbers. {df_aapl,df_amzn,df_goog,df_msft,df_tsla}",
             },
 
         ],
@@ -69,4 +69,4 @@ def main():
     print("Prediction:", prediction)
 
 if __name__ == "__main__":
-    main()
+    main()