Update app.py

app.py

@@ -568,7 +568,7 @@ def clean_text(text):
 from collections import Counter
 import heapq
 
-def summarize_text_by_frequency(text, num_sentences=3):
+def summarize_text_by_frequency(text, num_sentences=1):
     sentences = text.split('\n')
     word_freq = Counter()
 
@@ -590,7 +590,7 @@ def summarize_text_by_frequency(text, num_sentences=3):
 
     
 
-def find_closest_lines(query, doc_texts, stop_words, top_n=5):
+def find_closest_lines(query, doc_texts, stop_words, top_n=15):
     cleaned_query = remove_stop_words(query, stop_words)
     query_words = cleaned_query.split()
 
@@ -617,14 +617,14 @@ def remove_stop_words_from_lines(lines, stop_words):
     return cleaned_lines
 
 if query:
-    closest_lines = find_closest_lines(query, doc_texts, stop_words, top_n=5)
+    closest_lines = find_closest_lines(query, doc_texts, stop_words, top_n=15)
     
     # حذف استپ‌وردها از خطوط و سپس پاکسازی نهایی متن
     cleaned_closest_lines = [
         clean_text(" ".join([word for word in line.split() if word not in stop_words]))
         for line in closest_lines
     ]
-    summarized_text = summarize_text_by_frequency("\n".join(cleaned_closest_lines), num_sentences=3)
+    summarized_text = summarize_text_by_frequency("\n".join(cleaned_closest_lines), num_sentences=1)
     summarized_cleaned = " ".join([word for word in summarized_text.split() if word not in stop_words])
 
     if summarized_text: