Update main.py

main.py

@@ -31,7 +31,7 @@ ENGLISH_MODEL_NAME = "siebert/sentiment-roberta-large-english"
 try:
     multilingual_tokenizer = AutoTokenizer.from_pretrained(
         MULTILINGUAL_TOKENIZER_NAME,
-        use_auth_token=HF_TOKEN,
+        token=HF_TOKEN,  # Pass token here
         cache_dir=cache_dir
     )
 
@@ -39,7 +39,7 @@ try:
         "sentiment-analysis",
         model=MULTILINGUAL_MODEL_NAME,
         tokenizer=multilingual_tokenizer,
-        token=HF_TOKEN
+        token=HF_TOKEN  # Pass token here
     )
 except Exception as e:
     raise RuntimeError(f"Failed to load multilingual model: {e}")
@@ -49,7 +49,7 @@ try:
     english_model = pipeline(
         "sentiment-analysis",
         model=ENGLISH_MODEL_NAME,
-        token=HF_TOKEN
+        token=HF_TOKEN  # Pass token here
     )
 except Exception as e:
     raise RuntimeError(f"Failed to load English sentiment model: {e}")
@@ -81,7 +81,10 @@ def analyze_sentiment(request: SentimentRequest):
         raise HTTPException(status_code=400, detail="Text input cannot be empty.")
     
     language = detect_language(text)
+    
+    # Use English model if detected language is English; otherwise, use multilingual model
     model = english_model if language == "en" else multilingual_model
+
     result = model(text)
     
     return SentimentResponse(