Update app.py

app.py

@@ -105,9 +105,9 @@ if tickerSymbol:
     
         #date = datetime.date(start_date)
         date_str = start_date.strftime("%Y-%m-%d")
-        st.write(date_str)
+        #st.write(date_str)
         df = tickerDf[tickerDf["Date"]==date_str]
-        st.write(df)
+        #st.write(df)
     
         if (df["Close"][0] > df["Open"][0] ):
             st.write("NSE has uptrend on " +date_str )
@@ -123,7 +123,7 @@ if tickerSymbol:
 
 
     
-
+    Begindatestring = start_date
     headlines = scrapper(start_date)
     index = [idx for idx, s in enumerate(headlines) if s=='Most Read' ][0]
     del headlines[index:]
@@ -136,10 +136,6 @@ if tickerSymbol:
     news = news.reset_index(drop=True)
 
 
-
-    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-
-
     tokenizer = AutoTokenizer.from_pretrained("nickmuchi/sec-bert-finetuned-finance-classification")
     model = AutoModelForSequenceClassification.from_pretrained("nickmuchi/sec-bert-finetuned-finance-classification")