Update sentiment_api.py

sentiment_api.py

@@ -1,20 +1,25 @@
+import os
+
+# Force cache inside local folder
+os.environ["TRANSFORMERS_CACHE"] = "./hf_cache"
+os.environ["HF_HOME"] = "./hf_cache"
+os.environ["XDG_CACHE_HOME"] = "./hf_cache"
+os.environ["TORCH_HOME"] = "./hf_cache"
+os.environ["HF_DATASETS_CACHE"] = "./hf_cache"
+os.environ["SAFE_TENSORS_CACHE"] = "./hf_cache"
+
 from fastapi import FastAPI, Request
 from pydantic import BaseModel
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 import torch
-import os
-
-# Set a custom cache directory
-os.environ["TRANSFORMERS_CACHE"] = "./hf_cache"
 
-# Load model and tokenizer once at startup
+# Load model
 model_name = "tabularisai/multilingual-sentiment-analysis"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModelForSequenceClassification.from_pretrained(model_name)
 
 app = FastAPI()
 
-# Sentiment map
 sentiment_map = {
     0: "Very Negative",
     1: "Negative",
@@ -23,7 +28,6 @@ sentiment_map = {
     4: "Very Positive"
 }
 
-# Request body schema
 class ReviewRequest(BaseModel):
     text: str