Update app.py

app.py

@@ -10,8 +10,14 @@ from joblib import load
 lstm_model = load_model('lstm_model.h5')
 scaler = load('scaler.joblib')
 
-# Define the list of stocks
-stock_list = ['GOOG', 'AAPL', 'TSLA', 'AMZN', 'MSFT']
+# Dictionary of stock tickers and their full names
+stock_dict = {
+    'GOOG': 'Alphabet Inc.',
+    'AAPL': 'Apple Inc.',
+    'TSLA': 'Tesla, Inc.',
+    'AMZN': 'Amazon.com, Inc.',
+    'MSFT': 'Microsoft Corporation'
+}
 
 # Function to get the last row of stock data
 def get_last_stock_data(ticker):
@@ -109,35 +115,47 @@ def display_historical_data(ticker):
         start_date = '2010-01-01'
         end_date = datetime.now().strftime('%Y-%m-%d')
         data = yf.download(ticker, start=start_date, end=end_date)
-        return data.tail(30)
+        return data.tail(30).iloc[::-1]  # Reverse to have the latest date on top
     except Exception as e:
         return str(e)
 
 # Streamlit interface
 st.title("Stockstream")
 
+# Sidebar for adding new stocks
+st.sidebar.header("Add a New Stock Ticker")
+new_ticker = st.sidebar.text_input("Stock Ticker", value="")
+new_full_name = st.sidebar.text_input("Full Name", value="")
+if st.sidebar.button("Add Stock Ticker"):
+    if new_ticker and new_full_name:
+        stock_dict[new_ticker.upper()] = new_full_name
+
+# Tabs for different functionalities
 tab1, tab2, tab3 = st.tabs(["Today's Price", "Next Month's Price", "Historical Data"])
 
 with tab1:
     st.header("Today's Price")
-    ticker_input = st.selectbox("Stock Ticker", stock_list, key="today_ticker")
+    ticker_input = st.selectbox("Stock Ticker", [f"{key} - {value}" for key, value in stock_dict.items()], key="today_ticker")
     open_price = st.number_input("Open Price", value=0.0, key="today_open_price")
     close_price = st.number_input("Close Price", value=0.0, key="today_close_price")
     if st.button("Predict Today's Price"):
-        result = predict_stock_price(ticker_input, open_price, close_price)
+        ticker = ticker_input.split(' - ')[0]
+        result = predict_stock_price(ticker, open_price, close_price)
         st.write(result)
 
 with tab2:
     st.header("Next Month's Price")
-    next_month_ticker_input = st.selectbox("Stock Ticker", stock_list, key="next_month_ticker")
+    next_month_ticker_input = st.selectbox("Stock Ticker", [f"{key} - {value}" for key, value in stock_dict.items()], key="next_month_ticker")
     next_month_close_price = st.number_input("Close Price", value=0.0, key="next_month_close_price")
     if st.button("Predict Next Month's Price"):
-        result = predict_next_month_price(next_month_ticker_input, next_month_close_price)
+        ticker = next_month_ticker_input.split(' - ')[0]
+        result = predict_next_month_price(ticker, next_month_close_price)
         st.write(result)
 
 with tab3:
     st.header("Historical Data")
-    historical_ticker_input = st.selectbox("Stock Ticker", stock_list, key="historical_ticker")
+    historical_ticker_input = st.selectbox("Stock Ticker", [f"{key} - {value}" for key, value in stock_dict.items()], key="historical_ticker")
     if st.button("View Data"):
-        data = display_historical_data(historical_ticker_input)
+        ticker = historical_ticker_input.split(' - ')[0]
+        data = display_historical_data(ticker)
         st.dataframe(data)