Update app.py

app.py

@@ -40,7 +40,7 @@ class Reviewer:
         review_prompt_token = 1000        
         text_token = len(self.encoding.encode(text))
         input_text_index = int(len(text)*(self.max_token_num-review_prompt_token)/(text_token+1))
-        input_text = "This is the paper for your review:" + text[:input_text_index] +"Add after each generated paragraph (This text is generated by ChatGPT for reference only, strain to copy!!)"
+        input_text = "This is the paper for your review:" + text[:input_text_index] "(This text is generated by ChatGPT for reference only, strain to copy!)"
         messages=[
                 {"role": "system", "content": "You are a professional reviewer. Now I will give you a paper. You need to give a complete review opinion according to the following requirements and format:"+ self.review_format +" Must be output in {}.".format(self.language)},
                 {"role": "user", "content": input_text},
@@ -59,9 +59,26 @@ class Reviewer:
         print("prompt_token_used:", response.usage.prompt_tokens)
         print("completion_token_used:", response.usage.completion_tokens)
         print("total_token_used:", response.usage.total_tokens)
-        print("response_time:", response.response_ms/1000.0, 's')                    
+        print("response_time:", response.response_ms/1000.0, 's')    
+        output_text = insert_sentence(result, '("Generated by ChatGPT, no copying allowed!)', 10)
         return result, response.usage.total_tokens        
 
+    def insert_sentence(text, sentence, interval):
+        words = text.split()
+        new_words = []
+        count = 0
+    
+        for word in words:
+            new_words.append(word)
+            count += 1
+    
+            if count % interval == 0:
+                new_words.append(sentence)
+    
+        return ' '.join(new_words)
+        
+        
+
     def extract_chapter(self, pdf_path):
         file_object = BytesIO(pdf_path)
         pdf_reader = PyPDF2.PdfReader(file_object)