Update app.py

app.py

@@ -7,6 +7,7 @@ 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="♕")
 
@@ -24,11 +25,25 @@ def analyze_financial_news():
         # Perform text classification on the input text
         results = classification(text)
 
-        # Display classification results structure
-        st.write("Classification Results:", results)
+        # 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:
+                sentiment_results = sentiment_analysis(news["sequence"])[0]
+
+                # Display the sentiment analysis result for each news
+                st.write("Original Text:", news["sequence"])
+                st.write("Sentiment:", sentiment_results["label"])
+                st.write("Sentiment Score:", sentiment_results["score"])
+                st.write("---")
+        else:
+            st.write("No news relevant to Energy | Oil.")
 
 def main():
     analyze_financial_news()
 
 if __name__ == "__main__":
     main()
+