Update app.py

app.py

@@ -5,6 +5,16 @@ from PIL import Image
 import torch
 import io
 import os
+
+# Load Hugging Face API key securely
+HF_API_KEY = os.getenv("HF_API_KEY")
+if not HF_API_KEY:
+    raise ValueError("HF_API_KEY is not set. Add it in Hugging Face 'Variables and Secrets'.")
+
+# API Endpoint for Image Generation
+IMAGE_GEN_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-schnell"
+HEADERS = {"Authorization": f"Bearer {HF_API_KEY}"}
+
 # Check if GPU is available
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
@@ -20,11 +30,6 @@ generator_tokenizer = AutoTokenizer.from_pretrained(generator_model)
 if generator_tokenizer.pad_token is None:
     generator_tokenizer.pad_token = generator_tokenizer.eos_token
 
-# Hugging Face API for Image Generation
-HF_API_KEY = os.getenv("HF_API_KEY")
-IMAGE_GEN_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-schnell"
-HEADERS = {"Authorization": f"Bearer {HF_API_KEY}"}
-
 def translate_tamil_to_english(text):
     """Translates Tamil text to English."""
     inputs = translator_tokenizer(text, return_tensors="pt", padding=True, truncation=True).to(device)
@@ -42,7 +47,7 @@ def generate_image(prompt):
     response = requests.post(IMAGE_GEN_URL, headers=HEADERS, json={"inputs": prompt})
     if response.status_code == 200:
         return Image.open(io.BytesIO(response.content))
-    return Image.new("RGB", (300, 300), "red")  # Error placeholder image
+    return Image.new("RGB", (300, 300), "red")  # Placeholder image for errors
 
 def process_input(tamil_text):
     """Complete pipeline: Translation, Text Generation, and Image Generation."""