Update app.py

app.py

@@ -15,6 +15,11 @@ warnings.filterwarnings("ignore", category=FutureWarning)
 
 # Get the Hugging Face token from environment variables
 hf_token = os.getenv("hemanth")
+if not hf_token:
+    raise ValueError("Hugging Face token is not set correctly.")
+else:
+    logging.info("Hugging Face token loaded successfully.")
+
 API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-dev"
 headers = {"Authorization": f"Bearer {hf_token}"}
 
@@ -26,9 +31,10 @@ tokenizer = MarianTokenizer.from_pretrained(model_name)
 # Function to query the image generation API
 def query_image_api(prompt):
     try:
-        logging.info("Querying image generation API...")
+        logging.info(f"Querying image generation API with prompt: {prompt}")
         response = requests.post(API_URL, headers=headers, json={"inputs": prompt})
         response.raise_for_status()  # Raise an error for bad status codes
+        logging.info(f"Received response with status code: {response.status_code}")
         return response.content
     except requests.exceptions.RequestException as e:
         logging.error(f"Error querying image generation API: {e}")
@@ -53,7 +59,8 @@ def generate_image(translated_text):
     if image_bytes:
         return Image.open(io.BytesIO(image_bytes))
     else:
-        return "Error generating image"
+        logging.error("Failed to generate image.")
+        return None  # Return None if image generation failed
 
 # Load GPT-Neo model for creative text generation
 text_gen_model = pipeline("text-generation", model="EleutherAI/gpt-neo-1.3B")
@@ -74,6 +81,8 @@ def process_input(tamil_input):
         translated_output = translate_text(tamil_input)
         creative_text = generate_creative_text(translated_output)
         image = generate_image(translated_output)
+        if image is None:
+            image = "Image generation failed."
         return translated_output, creative_text, image
     else:
         return "No input provided.", None, None
@@ -94,4 +103,4 @@ iface = gr.Interface(
 )
 
 # Launch the Gradio interface
-iface.launch(share=False)
+iface.launch(share=False)