Update app.py

app.py

@@ -4,6 +4,17 @@ from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
 from diffusers import StableDiffusionPipeline
 import torch
 import re
+import os
+from huggingface_hub import login
+
+# Enter your Hugging Face token here (or set as environment variable)
+HF_TOKEN = "your_hf_token_here"  # Replace with your actual token
+
+# Authenticate with Hugging Face Hub
+if HF_TOKEN:
+    login(token=HF_TOKEN)
+else:
+    raise ValueError("Hugging Face token not provided!")
 
 # Initialize models
 def load_models():
@@ -13,14 +24,16 @@ def load_models():
         model="facebook/nllb-200-distilled-600M",
         src_lang="tam_Taml",
         tgt_lang="eng_Latn",
-        device=0 if torch.cuda.is_available() else -1
+        device=0 if torch.cuda.is_available() else -1,
+        use_auth_token=HF_TOKEN  # Token added here
     )
     
     # Text generation pipeline
     text_generator = pipeline(
         "text-generation", 
         model="gpt2-medium",
-        device=0 if torch.cuda.is_available() else -1
+        device=0 if torch.cuda.is_available() else -1,
+        use_auth_token=HF_TOKEN  # Token added here
     )
     
     # Image generation pipeline
@@ -28,15 +41,22 @@ def load_models():
         image_pipe = StableDiffusionPipeline.from_pretrained(
             "runwayml/stable-diffusion-v1-5",
             torch_dtype=torch.float16,
-            revision="fp16"
+            revision="fp16",
+            use_auth_token=HF_TOKEN  # Token added here
         ).to("cuda")
     else:
-        image_pipe = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5")
+        image_pipe = StableDiffusionPipeline.from_pretrained(
+            "runwayml/stable-diffusion-v1-5",
+            use_auth_token=HF_TOKEN  # Token added here
+        )
     
     return translator, text_generator, image_pipe
 
 # Load models at startup
-translator, text_generator, image_pipe = load_models()
+try:
+    translator, text_generator, image_pipe = load_models()
+except Exception as e:
+    raise RuntimeError(f"Model loading failed: {str(e)}")
 
 def clean_text(text):
     """Remove special characters and truncate to complete sentences"""
@@ -112,7 +132,7 @@ with gr.Blocks(theme=gr.themes.Soft()) as app:
     clear_btn = gr.Button("துடைத்து துவக்கவும்")
     
     def clear_all():
-        return {"": ""}, "", "", None, ""
+        return "", "", "", None, ""
     
     submit_btn.click(
         fn=process_content,