Update app.py

app.py

@@ -6,11 +6,16 @@ import pandas as pd
 
 
 def main():
+    # Load models
+    tokenizer_sentiment, model_sentiment = load_sentiment_analyzer()
+    tokenizer_summary, model_summary = load_summarizer()
+    pipe_ner = load_NER()
+    
     st.title("WhatsApp Analysis Tool")
     st.markdown("This app summarizes Whatsapp chats and provides named entity recognition as well as sentiment analysis for the conversation")
     st.markdown("**NOTE**: *This app can only receive chats downloaded from IOS as the downloaded chat format is different than from Android.*")
     st.markdown("Download your whatsapp chat by going to Settings > Chats > Export Chat and there select the chat you want to summarize (download 'Without Media').")
-
+    
 
     # File uploader
     uploaded_file = st.file_uploader("Choose a file (.zip)", type=['zip'])
@@ -32,45 +37,25 @@ def main():
                         st.markdown(f"```\n{text_for_analysis}\n```", unsafe_allow_html=True)
                     process = st.button('Process')
                     if process:
-                        # Load models
-                        tokenizer_sentiment, model_sentiment = load_sentiment_analyzer()
-                        tokenizer_summary, model_summary = load_summarizer()
-                        pipe_ner = load_NER()
-
-                    # Load models
-                    tokenizer_sentiment, model_sentiment = load_sentiment_analyzer()
-                    tokenizer_summary, model_summary = load_summarizer()
-                    pipe_ner = load_NER()
-
-                    # Perform analysis
-                    sentiment = get_sentiment_analysis(text_for_analysis, tokenizer_sentiment, model_sentiment)
-                    summary = generate_summary(text_for_analysis, tokenizer_summary, model_summary)
-                    ner_results = get_NER(text_for_analysis, pipe_ner)
-
-                    # Display results
-                    st.subheader("Sentiment Analysis")
-                    st.write("Sentiment:", sentiment)
-
-                    st.subheader("Summary")
-                    st.write("Summary:", summary)
-
-                    st.subheader("Named Entity Recognition")
-                    ner_df = pd.DataFrame(ner_results, columns=["Word", "Entity Group"])
-                    st.write(ner_df)
+                        # Perform analysis
+                        sentiment = get_sentiment_analysis(text_for_analysis, tokenizer_sentiment, model_sentiment)
+                        summary = generate_summary(text_for_analysis, tokenizer_summary, model_summary)
+                        ner_results = get_NER(text_for_analysis, pipe_ner)
+    
+                        # Display results
+                        st.subheader("Sentiment Analysis")
+                        st.write("Sentiment:", sentiment)
+    
+                        st.subheader("Summary")
+                        st.write("Summary:", summary)
+    
+                        st.subheader("Named Entity Recognition")
+                        ner_df = pd.DataFrame(ner_results, columns=["Word", "Entity Group"])
+                        st.write(ner_df)
         else:
             st.error("Unsupported file type. Please upload a .txt or .zip file.")
     else:
         st.info("Please upload a file to proceed.")
 
 if __name__ == "__main__":
-    main()
-
-
-
-
-
-
-
-
-
-
+    main()