Update app.py

app.py

@@ -5,7 +5,6 @@ from groq import Groq
 from deep_translator import GoogleTranslator
 from diffusers import StableDiffusionPipeline
 import torch
-import huggingface_hub
 from huggingface_hub import login
 
 # Set up Groq API key
@@ -28,7 +27,7 @@ except Exception as e:
 # Set device: CUDA if available, else CPU
 device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
 
-# Load Whisper model (if using locally, else use API as in original code)
+# Load Whisper model
 whisper_model = whisper.load_model("base")
 
 # Model IDs for Stable Diffusion pipelines
@@ -66,10 +65,11 @@ def process_audio(audio_path, image_option):
     if image_option == "Generate Image":
         try:
             # Use the Hugging Face API key to load the restricted model for image generation
-            pipe = StableDiffusionPipeline.from_pretrained(restricted_model_id, torch_dtype=torch.float16, use_auth_token=HF_API_KEY)
+            pipe = StableDiffusionPipeline.from_pretrained(restricted_model_id, torch_dtype=torch.float16, token=HF_API_KEY)
             pipe = pipe.to(device)
             image = pipe(translation).images[0]
         except Exception as e:
+            print(f"Image generation error: {str(e)}")  # Add error logging
             return tamil_text, translation, f"An error occurred during image generation: {str(e)}", None
 
     return tamil_text, translation, image