Update app.py

app.py

@@ -3,11 +3,15 @@ from thronetrader import StrategicSignals
 import requests
 import pandas as pd
 
+import streamlit as st
+import requests
+import pandas as pd
+
 # Hard-coded API key for demonstration purposes
 API_KEY = "QR8F9B7T6R2SWTAT"
 
-def fetch_alpha_vantage_data(api_key):
-    url = f'https://www.alphavantage.co/query?function=TIME_SERIES_INTRADAY&symbol=IBM&interval=5min&apikey={api_key}'
+def fetch_alpha_vantage_data(api_key, symbol):
+    url = f'https://www.alphavantage.co/query?function=TIME_SERIES_INTRADAY&symbol={symbol}&interval=5min&apikey={api_key}'
     response = requests.get(url)
     alpha_vantage_data = response.json()
     return alpha_vantage_data
@@ -15,11 +19,18 @@ def fetch_alpha_vantage_data(api_key):
 def main():
     st.title("Stock Trend Predictor")
 
+    # User input for stock symbol
+    symbol = st.text_input("Enter Stock Symbol (e.g., IBM):")
+
+    if not symbol:
+        st.warning("Please enter a valid stock symbol.")
+        st.stop()
+
     # Use the hard-coded API key
     api_key = API_KEY
 
     # Fetch Alpha Vantage data
-    alpha_vantage_data = fetch_alpha_vantage_data(api_key)
+    alpha_vantage_data = fetch_alpha_vantage_data(api_key, symbol)
 
     # Extract relevant data from Alpha Vantage response
     alpha_vantage_time_series = alpha_vantage_data.get('Time Series (5min)', {})
@@ -27,15 +38,13 @@ def main():
     df.index = pd.to_datetime(df.index)
     df = df.dropna(axis=0)
 
-    # Print DataFrame for observation
+    # Display the raw data
     st.subheader("Raw Data:")
     st.write(df)
 
-    # Uncomment the next line if you want to stop the execution here to observe the data
-    # st.stop()
-
 if __name__ == "__main__":
     main()
+
 def main():
     st.title("Strategic Trading Signals")