Update app_exp.py

app_exp.py

@@ -9,40 +9,57 @@ import torch
 import gradio as gr
 from torchvision.io import write_video
 
-# LongCat-Video imports
+# Define paths
 REPO_PATH = "LongCat-Video"
 CHECKPOINT_DIR = os.path.join(REPO_PATH, "weights", "LongCat-Video")
 
+# Clone the repository if it doesn't exist
 if not os.path.exists(REPO_PATH):
-    subprocess.run(
-        ["git", "clone", "https://github.com/meituan-longcat/LongCat-Video.git", REPO_PATH],
-        check=True
-    )
-
+    print(f"Cloning LongCat-Video repository to '{REPO_PATH}'...")
+    try:
+        subprocess.run(
+            ["git", "clone", "https://github.com/meituan-longcat/LongCat-Video.git", REPO_PATH],
+            check=True,
+            capture_output=True
+        )
+        print("Repository cloned successfully.")
+    except subprocess.CalledProcessError as e:
+        print(f"Error cloning repository: {e.stderr.decode()}")
+        sys.exit(1)
+
+# Add the cloned repository to the Python path to allow imports
 sys.path.insert(0, os.path.abspath(REPO_PATH))
+
+# Now that the repo is in the path, we can import its modules
 from huggingface_hub import snapshot_download
 from longcat_video.pipeline_longcat_video import LongCatVideoPipeline
 from longcat_video.modules.scheduling_flow_match_euler_discrete import FlowMatchEulerDiscreteScheduler
 from longcat_video.modules.autoencoder_kl_wan import AutoencoderKLWan
 from longcat_video.modules.longcat_video_dit import LongCatVideoTransformer3DModel
 from longcat_video.context_parallel import context_parallel_util
-import cache_dit
-
 from transformers import AutoTokenizer, UMT5EncoderModel
 from diffusers.utils import export_to_video
 
+# Download model weights from Hugging Face Hub if they don't exist
+if not os.path.exists(CHECKPOINT_DIR):
+    print(f"Downloading model weights to '{CHECKPOINT_DIR}'...")
+    try:
+        snapshot_download(
+            repo_id="meituan-longcat/LongCat-Video",
+            local_dir=CHECKPOINT_DIR,
+            local_dir_use_symlinks=False,  # Use False for better Windows compatibility
+            ignore_patterns=["*.md", "*.gitattributes", "assets/*"] # ignore non-essential files
+        )
+        print("Model weights downloaded successfully.")
+    except Exception as e:
+        print(f"Error downloading model weights: {e}")
+        sys.exit(1)
+
+# Global placeholder for the pipeline and device configuration
+pipe = None
 device = "cuda" if torch.cuda.is_available() else "cpu"
 torch_dtype = torch.bfloat16 if device == "cuda" else torch.float32
 
-# --- Download weights if missing ---
-if not os.path.exists(CHECKPOINT_DIR):
-    snapshot_download(
-        repo_id="meituan-longcat/LongCat-Video",
-        local_dir=CHECKPOINT_DIR,
-        local_dir_use_symlinks=False,
-        ignore_patterns=["*.md", "*.gitattributes", "assets/*"]
-    )
-
 # --- Initialize models ---
 cp_split_hw = context_parallel_util.get_optimal_split(1)
 tokenizer = AutoTokenizer.from_pretrained(CHECKPOINT_DIR, subfolder="tokenizer", torch_dtype=torch_dtype)