Fix

features/text_classifier/controller.py

@@ -84,7 +84,7 @@ async def handle_sentence_level_analysis(text: str):
         text+="."
     if len(text) > 10000:
         raise HTTPException(status_code=413, detail="Text must be less than 10,000 characters")
-    
+     
     sentences = sent_tokenize(text, language="english")
     results = []
     for sentence in sentences:

features/text_classifier/model_loader.py

@@ -21,7 +21,6 @@ def warmup():
     # Ensure punkt is available
     nltk.download("punkt")
 
-    nltk.download('punkt_tab')
 
     download_model_repo()
     _model, _tokenizer = load_model()