Update app.py

app.py

@@ -13,7 +13,7 @@ MODEL_PRICE_MICROSOFT = "SelmaNajih001/PricePredictionForMicrosoft"
 MODEL_FINBERT = "ProsusAI/finbert"
 
 TICKERS = {
-    "Tesla, Inc": "TSLA",
+    "Tesla, Inc.": "TSLA",
     "Microsoft": "MSFT"
 }
 companies = list(TICKERS.keys())
@@ -60,7 +60,7 @@ for i, row in df_multi.iterrows():
 
     # Regression (Tesla & MSFT)
     try:
-        if company == "Tesla, Inc":
+        if company == "Tesla, Inc.":
             val = price_pipeline_tesla(row['Summary'])[0]['score']
             df_multi.at[i,'Predicted'] = min(val, 1.0)
         elif company == "Microsoft":