Update app.py

app.py

@@ -7,7 +7,6 @@ def analyze_financial_news():
 
     # Load the text classification model pipeline
     classification = pipeline("text-classification", model="nickmuchi/finbert-tone-finetuned-finance-topic-classification", token=access+token)
-    sentiment_analysis = pipeline("sentiment-analysis")
 
     st.set_page_config(page_title="Financial News Analysis", page_icon="♕")
 
@@ -25,22 +24,8 @@ def analyze_financial_news():
         # Perform text classification on the input text
         results = classification(text)
 
-        # Filter only the news related to "Energy | Oil"
-        energy_oil_news = [news for news in results if news["label"] == "Energy | Oil"]
-        
-        if energy_oil_news:
-            # If there are news related to "Energy | Oil", perform sentiment analysis for each news
-            for news in energy_oil_news:
-                text = news["text"]  # Corrected this line
-                sentiment_results = sentiment_analysis(text)[0]
-
-                # Display the sentiment analysis result for each news
-                st.write("Original Text:", text)
-                st.write("Sentiment:", sentiment_results["label"])
-                st.write("Sentiment Score:", sentiment_results["score"])
-                st.write("---")
-        else:
-            st.write("No news relevant to Energy | Oil.")
+        # Display classification results structure
+        st.write("Classification Results:", results)
 
 def main():
     analyze_financial_news()