Update app.py

app.py

@@ -3,6 +3,7 @@ import requests
 from PIL import Image
 import io
 import gradio as gr
+import os
 
 # Load the MarianMT model and tokenizer for translation (Tamil to English)
 model_name = "Helsinki-NLP/opus-mt-mul-en"
@@ -20,12 +21,15 @@ if text_generation_tokenizer.pad_token is None:
 
 # Hugging Face API for FLUX.1 image generation
 API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-dev"
-headers = {"Authorization": "HUGGINGFACE_API_KEY"}  # Replace with your API key
+headers = {"Authorization": f"Bearer {os.getenv('HUGGINGFACE_API_KEY')}"}
 
 # Query Hugging Face API to generate image
 def query(payload):
     response = requests.post(API_URL, headers=headers, json=payload)
-    return response.content
+    if response.status_code == 200:
+        return response.content
+    else:
+        return f"Error: {response.status_code} - {response.text}"
 
 # Translate Tamil text to English
 def translate_text(tamil_text):
@@ -37,6 +41,8 @@ def translate_text(tamil_text):
 # Generate an image based on the translated text
 def generate_image(prompt):
     image_bytes = query({"inputs": prompt})
+    if isinstance(image_bytes, str) and "Error" in image_bytes:
+        return image_bytes  # Return the error message if there's a problem with the API call
     image = Image.open(io.BytesIO(image_bytes))
     return image
 
@@ -74,4 +80,4 @@ interface = gr.Interface(
 )
 
 # Launch Gradio app
-interface.launch()
+interface.launch()