Update main.py

main.py

@@ -1,28 +1,33 @@
 import os
-from fastapi import FastAPI
+from fastapi import FastAPI, HTTPException
 from pydantic import BaseModel
-from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification
+from transformers import pipeline, AutoTokenizer
 from langdetect import detect, DetectorFactory
+from huggingface_hub import hf_hub_download
 
 # Ensure consistent language detection results
 DetectorFactory.seed = 0
 
-# Set Hugging Face cache directory to a writable location
+# Set Hugging Face cache to a writable location
 os.environ["HF_HOME"] = "/tmp/huggingface"
 os.environ["TRANSFORMERS_CACHE"] = "/tmp/huggingface"
 os.makedirs(os.environ["HF_HOME"], exist_ok=True)
 
 app = FastAPI()
 
-# Load the original tokenizer from the base model
+# Load tokenizer for multilingual model
 original_tokenizer = AutoTokenizer.from_pretrained("tabularisai/multilingual-sentiment-analysis")
 
-# Load the fine-tuned model (johndoee/sentiment) and pass the tokenizer explicitly
-multilingual_model = pipeline(
-    "sentiment-analysis",
-    model="johndoee/sentiment",
-    tokenizer=original_tokenizer
-)
+# Dynamically download fine-tuned model (avoid storage issues)
+try:
+    MODEL_PATH = hf_hub_download(repo_id="johndoee/sentiment", filename="pytorch_model.bin")
+    multilingual_model = pipeline(
+        "sentiment-analysis",
+        model="johndoee/sentiment",
+        tokenizer=original_tokenizer
+    )
+except Exception as e:
+    raise RuntimeError(f"❌ Error loading model 'johndoee/sentiment': {e}")
 
 # Load the English sentiment model
 english_model = pipeline("sentiment-analysis", model="siebert/sentiment-roberta-large-english")