Update app.py

app.py

@@ -14,6 +14,43 @@ except Exception as e:
     print(f"GPU warmup failed: {e}")
 os.environ["GRADIO_TEMP_DIR"] = "./tmp"
 
+try:
+    # Define full dummy args with all attributes expected by load_models
+    class DummyArgs:
+        # Core model paths
+        wan_model_dir = "./models/Wan2.1-I2V-14B-720P"
+        fantasytalking_model_path = "./models/fantasytalking_model.ckpt"
+        wav2vec_model_dir = "./models/wav2vec2-base-960h"
+
+        # Required inference-related parameters
+        image_path = "./assets/images/woman.png"
+        audio_path = "./assets/audios/woman.wav"
+        prompt = "A woman is talking."
+        output_dir = "./output"
+        image_size = 512
+        audio_scale = 1.0
+        prompt_cfg_scale = 5.0
+        audio_cfg_scale = 5.0
+        max_num_frames = 81
+        inference_steps = 20
+        fps = 23
+        seed = 1111
+
+        # ✅ The missing one that caused your error:
+        num_persistent_param_in_dit = 7 * 10**9  # adjust if needed
+
+    # Preload models
+    print("🔄 Loading models into memory...")
+    args = DummyArgs()
+    pipe, fantasytalking, wav2vec_processor, wav2vec = load_models(args)
+    print("✅ Models loaded successfully.")
+
+except Exception as e:
+    print(f"❌ Error loading models: {e}")
+    pipe = fantasytalking = wav2vec_processor = wav2vec = None
+    raise e  # fail fast if model load fails
+
+
 pipe,fantasytalking,wav2vec_processor,wav2vec = None,None,None,None
 @spaces.GPU(duration=1200)
 def generate_video(
@@ -28,42 +65,35 @@ def generate_video(
     inference_steps,
     seed,
 ):
-    # Create the temp directory if it doesn't exist
-    output_dir = Path("./output")
-    output_dir.mkdir(parents=True, exist_ok=True)
+    try:
+        output_dir = Path("./output")
+        output_dir.mkdir(parents=True, exist_ok=True)
 
-    # Convert paths to absolute Path objects and normalize them
-    print(image_path)
-    image_path = Path(image_path).absolute().as_posix()
-    audio_path = Path(audio_path).absolute().as_posix()
+        image_path = Path(image_path).absolute().as_posix()
+        audio_path = Path(audio_path).absolute().as_posix()
 
-    # Parse the arguments
+        args = create_args(
+            image_path=image_path,
+            audio_path=audio_path,
+            prompt=prompt or "A person is talking.",
+            output_dir=str(output_dir),
+            audio_weight=audio_weight,
+            prompt_cfg_scale=prompt_cfg_scale,
+            audio_cfg_scale=audio_cfg_scale,
+            image_size=image_size,
+            max_num_frames=max_num_frames,
+            inference_steps=inference_steps,
+            seed=seed,
+        )
 
-    args = create_args(
-        image_path=image_path,
-        audio_path=audio_path,
-        prompt=prompt,
-        output_dir=str(output_dir),
-        audio_weight=audio_weight,
-        prompt_cfg_scale=prompt_cfg_scale,
-        audio_cfg_scale=audio_cfg_scale,
-        image_size=image_size,
-        max_num_frames=max_num_frames,
-        inference_steps=inference_steps,
-        seed=seed,
-    )
+        # ✅ Run inference using preloaded models
+        save_path = main(args, pipe, fantasytalking, wav2vec_processor, wav2vec)
+        print(f"✅ Video saved at {save_path}")
+        return save_path
 
-    try:
-        global pipe, fantasytalking, wav2vec_processor, wav2vec  
-        if pipe is None:
-            pipe,fantasytalking,wav2vec_processor,wav2vec = load_models(args)
-        output_path=main(
-            args,pipe,fantasytalking,wav2vec_processor,wav2vec
-        )
-        return output_path  # Ensure the output path is returned
     except Exception as e:
-        print(f"Error during processing: {str(e)}")
-        raise gr.Error(f"Error during processing: {str(e)}")
+        print(f"❌ Error generating video: {e}")
+        return None
 
 
 def create_args(