Update app.py

app.py

@@ -98,16 +98,70 @@ class PatchedModelManager(ModelManager):
         return None
 
 # Video generation logic
+
+
+
+def generate_t2v_video(self, prompt, lora_alpha, num_inference_steps, 
+                          negative_prompt, progress=gr.Progress()):
+        """Generate video from text prompt"""
+        try:
+            progress(0.1, desc="Loading models...")
+            lora_path = "./model_zoo/PusaV1/pusa_v1.pt"
+            pipe = self.load_lora_and_get_pipe("t2v", lora_path, lora_alpha)
+            
+            progress(0.3, desc="Generating video...")
+            video = pipe(
+                prompt=prompt,
+                negative_prompt=negative_prompt,
+                num_inference_steps=num_inference_steps,
+                height=720, width=1280, num_frames=81,
+                seed=0, tiled=True
+            )
+            
+            progress(0.9, desc="Saving video...")
+            timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
+            video_filename = os.path.join(self.output_dir, f"t2v_output_{timestamp}.mp4")
+            save_video(video, video_filename, fps=25, quality=5)
+            
+            progress(1.0, desc="Complete!")
+            return video_filename, f"Video generated successfully! Saved to {video_filename}"
+            
+        except Exception as e:
+            return None, f"Error: {str(e)}"
+
+
+
+            
 @spaces.GPU(duration=200)
 def generate_video(prompt: str):
     ensure_model_downloaded()
 
     # Load model using patched manager
-    manager = ModelManager(
-        file_path_list=[WAN_MODEL_PATH],
-        torch_dtype=torch.float16,
-        device="cuda"
-    )
+
+
+    model_manager = ModelManager(device="cuda")
+    base_dir = "model_zoo/PusaV1/Wan2.1-T2V-14B"
+            
+    model_files = sorted([os.path.join(self.base_dir, f) for f in os.listdir(self.base_dir) if f.endswith('.safetensors')])
+            
+    model_manager.load_models(
+                [
+                    model_files,
+                    os.path.join(self.base_dir, "models_t5_umt5-xxl-enc-bf16.pth"),
+                    os.path.join(self.base_dir, "Wan2.1_VAE.pth"),
+                ],
+                torch_dtype=torch.bfloat16,
+            )
+    
+    
+    
+    
+    
+    # manager = ModelManager(
+    #     file_path_list=[WAN_MODEL_PATH],
+    #     torch_dtype=torch.float16,
+    #     device="cuda"
+    # )
 
     
 
@@ -117,11 +171,11 @@ def generate_video(prompt: str):
     #    device="cuda" 
     #  )
    
-    model =  manager.load_model(WAN_MODEL_PATH)
+    #model =  manager.load_model(WAN_MODEL_PATH)
 
     # Set up pipeline
     pipeline = WanVideoPusaPipeline(model=model)
-    pipeline.set_lora_adapters(LORA_PATH)
+    #pipeline.set_lora_adapters(LORA_PATH)
 
     # Generate video
     result = pipeline(prompt)