Update app.py

app.py

@@ -3,6 +3,11 @@ from transformers import pipeline
 import torch
 from pydantic import BaseModel
 import os
+import numpy as np  # Explicit numpy import
+
+# Fix numpy initialization
+np.zeros(1)  # Force numpy load before model
+
 
 app = FastAPI()
 
@@ -11,17 +16,23 @@ torch.backends.cuda.enable_flash_sdp(False)
 torch.backends.cuda.enable_mem_efficient_sdp(False)
 
 
-# Set cache directory to a writable location
-os.environ["TRANSFORMERS_CACHE"] = "/tmp/huggingface_cache"
+# Configure paths and device
+os.environ["TRANSFORMERS_CACHE"] = "/tmp/huggingface"
 os.makedirs(os.environ["TRANSFORMERS_CACHE"], exist_ok=True)
 
 
-# Load model
-model = pipeline(
-    "text-classification",
-    model="win2win/3-epochs-classifier-ver2",
-    device="cuda" if torch.cuda.is_available() else "cpu"
-)
+# Load model with error handling
+try:
+    model = pipeline(
+        "text-classification",
+        model="win2win/3-epochs-classifier-ver2",
+        device="cpu",  # Force CPU for free tier
+        torch_dtype=torch.float32  # Avoid mixed precision
+    )
+    print("Model loaded successfully!")
+except Exception as e:
+    print(f"Model loading failed: {str(e)}")
+    raise
 
 class Request(BaseModel):
     text: str