Update processing.py

processing.py

@@ -107,7 +107,7 @@ def load_text(file_path: str) -> str:
     with open(file_path, 'r', encoding='utf-8') as file:
         return file.read().strip()
 
-def truncate_text(text: str, max_tokens: int = 10000) -> str:
+def truncate_text(text: str, max_tokens: int = 16000) -> str:
     words = text.split()
     if len(words) > max_tokens:
         return ' '.join(words[:max_tokens])
@@ -144,6 +144,11 @@ Please provide a comprehensive analysis for each speaker, including:
 Respond with a JSON object containing an array of speaker analyses under the key 'speaker_analyses'. Each speaker analysis should include all four aspects mentioned above.
 Analysis:"""
 
+    truncated_input_tokents_count = count_tokens(truncated_input)
+    print('truncated_input_tokents_count:', truncated_input_tokents_count)
+    input_tokens_count = count_tokens(prompt)
+    print('input_tokens_count', input_tokens_count)
+    
     response = llm.invoke(prompt)
     
     print("Raw LLM Model Output:")