single sentence contradition detection refactored

app.py

@@ -197,7 +197,38 @@ if uploaded_pdf_file is not None:
             st.session_state.list_count = len(st.session_state.restored_paragraphs)
             st.write(f'The number of elements at the top level of the hierarchy: {st.session_state.list_count}')
         st.rerun()
+def contradiction_detection_for_sentence(query):
+    query_encoding = encode_sentence(query)
+
+    total_count = len(st.session_state.paragraph_sentence_encodings)
+    processing_progress_bar = st.progress(0)
+
+    sentence_scores, paragraph_scores = find_sentences_scores(
+        st.session_state.paragraph_sentence_encodings, query_encoding, processing_progress_bar, total_count)
+
+    sorted_paragraph_scores = sorted(paragraph_scores, key=lambda x: x[0], reverse=True)
+
+    st.write("Top scored paragraphs and their scores:")
+    for i, (similarity_score, commonality_score, paragraph) in enumerate(
+            sorted_paragraph_scores[:3]):  # number of paragraphs to consider
+        # st.write("top_three_sentences: ", paragraph['top_three_sentences'])
+        st.write("paragarph number ***", i)
+        prev_contradiction_detected = True
+        for top_sentence in paragraph['top_three_sentences']:
+
+            if prev_contradiction_detected:
+                contradiction_detection_result = contradiction_detection(st.session_state.premise, top_sentence[1])
+                if contradiction_detection_result == {"Contradiction"}:
+                    st.write("master document page number ", paragraph['original_text']['page_num'])
+                    st.write("master document sentence: ", top_sentence[1])
+                    st.write("secondary document sentence: ", st.session_state.premise)
+                    st.write(contradiction_detection_result)
+                #     st.write(contradiction_detection(st.session_state.premise, top_sentence[1]))
 
+                else:
+                    prev_contradiction_detected = False
+            else:
+                break
 def find_sentences_scores(paragraph_sentence_encodings, query_encoding, processing_progress_bar,total_count):
     paragraph_scores = []
     sentence_scores = []
@@ -251,42 +282,8 @@ if 'paragraph_sentence_encodings' in st.session_state:
         if 'prev_query' not in st.session_state or st.session_state.prev_query != query:
             st.session_state.prev_query = query
             st.session_state.premise = query
+            contradiction_detection_for_sentence(query)
 
-            query_encoding = encode_sentence(query)
-
-            total_count = len(st.session_state.paragraph_sentence_encodings)
-            processing_progress_bar = st.progress(0)
-
-
-
-            sentence_scores,paragraph_scores = find_sentences_scores(
-                st.session_state.paragraph_sentence_encodings, query_encoding, processing_progress_bar,total_count)
-
-            sorted_paragraph_scores = sorted(paragraph_scores, key=lambda x: x[0], reverse=True)
-
-
-
-            st.write("Top scored paragraphs and their scores:")
-            for i, (similarity_score, commonality_score, paragraph) in enumerate(
-                    sorted_paragraph_scores[:3]): #number of paragraphs to consider
-                #st.write("top_three_sentences: ", paragraph['top_three_sentences'])
-                st.write("paragarph number ***", i)
-                prev_contradiction_detected =True
-                for top_sentence in paragraph['top_three_sentences']:
-
-                    if prev_contradiction_detected:
-                        contradiction_detection_result =contradiction_detection(st.session_state.premise,top_sentence[1])
-                        if contradiction_detection_result == {"Contradiction"}:
-                            st.write("master document page number ", paragraph['original_text']['page_num'])
-                            st.write("master document sentence: ", top_sentence[1])
-                            st.write("secondary document sentence: ", st.session_state.premise)
-                            st.write(contradiction_detection_result)
-                        #     st.write(contradiction_detection(st.session_state.premise, top_sentence[1]))
-
-                        else:
-                            prev_contradiction_detected = False
-                    else:
-                        break
 
                     #print(top_sentence[1])
                 # st.write(f"Similarity Score: {similarity_score}, Commonality Score: {commonality_score}")