Update main.py

main.py

@@ -1,7 +1,7 @@
 import os
 from fastapi import FastAPI
 from pydantic import BaseModel
-from transformers import pipeline
+from transformers import pipeline, AutoTokenizer
 from langdetect import detect, DetectorFactory
 
 # Ensure consistent language detection results
@@ -9,12 +9,21 @@ DetectorFactory.seed = 0
 
 # Set Hugging Face cache directory to a writable location
 os.environ["HF_HOME"] = "/tmp/huggingface"
-os.makedirs(os.environ["HF_HOME"], exist_ok=True)  # Ensure the directory exists
+os.makedirs(os.environ["HF_HOME"], exist_ok=True)
 
 app = FastAPI()
 
-# Load sentiment analysis models
-multilingual_model = pipeline("sentiment-analysis", model="tabularisai/multilingual-sentiment-analysis")
+# Load the original tokenizer from the base model
+original_tokenizer = AutoTokenizer.from_pretrained("tabularisai/multilingual-sentiment-analysis")
+
+# Load the fine-tuned model and pass the tokenizer explicitly
+multilingual_model = pipeline(
+    "sentiment-analysis",
+    model="models/",
+    tokenizer=original_tokenizer
+)
+
+# English model remains unchanged
 english_model = pipeline("sentiment-analysis", model="siebert/sentiment-roberta-large-english")
 
 class SentimentRequest(BaseModel):
@@ -29,7 +38,7 @@ class SentimentResponse(BaseModel):
 def detect_language(text):
     try:
         return detect(text)
-    except:
+    except Exception:
         return "unknown"
 
 @app.get("/")