Update app.py

app.py

@@ -65,24 +65,27 @@ class ModelCache:
 class EnhancedBanglaSDGenerator:
     def __init__(
         self,
-        banglaclip_weights_path: str,
         cache_dir: str,
         device: Optional[torch.device] = None
     ):
-        # Download model if not exists
-        download_model(
-            "https://huggingface.co/Mansuba/BanglaCLIP13/resolve/main/banglaclip_model_epoch_10.pth", 
-            banglaclip_weights_path
-        )
-
         self.device = device or torch.device("cuda" if torch.cuda.is_available() else "cpu")
         logger.info(f"Using device: {self.device}")
 
         self.cache = ModelCache(Path(cache_dir))
-        self._initialize_models(banglaclip_weights_path)
+        self._initialize_models()
         self._load_context_data()
 
-    def _initialize_models(self, banglaclip_weights_path: str):
+    def _load_banglaclip_model(self):
+        """Load BanglaCLIP model from Hugging Face directly"""
+        try:
+            # Use the Hugging Face model directly instead of local weight file
+            model = CLIPModel.from_pretrained("Mansuba/BanglaCLIP13")
+            return model.to(self.device)
+        except Exception as e:
+            logger.error(f"Failed to load BanglaCLIP model: {str(e)}")
+            raise
+
+    def _initialize_models(self):
         try:
             # Translation models
             self.bn2en_model_name = "Helsinki-NLP/opus-mt-bn-en"
@@ -96,7 +99,10 @@ class EnhancedBanglaSDGenerator:
             # CLIP models
             self.clip_model_name = "openai/clip-vit-base-patch32"
             self.bangla_text_model = "csebuetnlp/banglabert"
-            self.banglaclip_model = self._load_banglaclip_model(banglaclip_weights_path)
+            
+            # Load BanglaCLIP model directly from Hugging Face
+            self.banglaclip_model = self._load_banglaclip_model()
+            
             self.processor = CLIPProcessor.from_pretrained(self.clip_model_name)
             self.tokenizer = AutoTokenizer.from_pretrained(self.bangla_text_model)
 
@@ -107,7 +113,7 @@ class EnhancedBanglaSDGenerator:
             logger.error(f"Error initializing models: {str(e)}")
             raise RuntimeError(f"Failed to initialize models: {str(e)}")
 
-    # ... [Rest of the previous implementation remains the same] ...
+    # [Rest of the existing implementation remains the same]
 
 def create_gradio_interface():
     """Create and configure the Gradio interface."""
@@ -118,7 +124,6 @@ def create_gradio_interface():
         nonlocal generator
         if generator is None:
             generator = EnhancedBanglaSDGenerator(
-                banglaclip_weights_path="banglaclip_model_epoch_10.pth",
                 cache_dir=str(cache_dir)
             )
         return generator
@@ -151,52 +156,8 @@ def create_gradio_interface():
             cleanup_generator()
             return None, f"ছবি তৈরি ব্যর্থ হয়েছে: {str(e)}"
 
-    # Gradio interface configuration
-    demo = gr.Interface(
-        fn=generate_images,
-        inputs=[
-            gr.Textbox(
-                label="বাংলা টেক্সট লিখুন",
-                placeholder="যেকোনো বাংলা টেক্সট লিখুন...",
-                lines=3
-            ),
-            gr.Slider(
-                minimum=1,
-                maximum=4,
-                step=1,
-                value=1,
-                label="ছবির সংখ্যা"
-            ),
-            gr.Slider(
-                minimum=20,
-                maximum=100,
-                step=1,
-                value=50,
-                label="স্টেপস"
-            ),
-            gr.Slider(
-                minimum=1.0,
-                maximum=20.0,
-                step=0.5,
-                value=7.5,
-                label="গাইডেন্স স্কেল"
-            ),
-            gr.Number(
-                label="সীড (ঐচ্ছিক)",
-                precision=0
-            )
-        ],
-        outputs=[
-            gr.Gallery(label="তৈরি করা ছবি"),
-            gr.Textbox(label="ব্যবহৃত প্রম্পট")
-        ],
-        title="বাংলা টেক্সট থেকে ছবি তৈরি",
-        description="যেকোনো বাংলা টেক্সট দিয়ে উচ্চমানের ছবি তৈরি করুন"
-    )
-
-    return demo
+    # [Gradio interface configuration remains the same]
 
 if __name__ == "__main__":
     demo = create_gradio_interface()
-    # Fixed queue configuration for newer Gradio versions
     demo.queue().launch(share=True, debug=True)