Update app.py

app.py

@@ -14,12 +14,41 @@ from dotenv import load_dotenv
 from transformers import AutoProcessor, AutoModelForCausalLM, AutoTokenizer
 from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
 from PIL import Image
+import tempfile
+
 
 # os.makedirs("./hf_cache", exist_ok=True)
 # os.environ["HF_HOME"] = "./hf_cache"
 # os.environ["TRANSFORMERS_CACHE"] = "./hf_cache/transformers"
 # os.environ["HUGGINGFACE_HUB_CACHE"] = "./hf_cache/hub"
 
+# Use system temp directories which should be writable
+TMP_DIR = tempfile.gettempdir()
+MODEL_DIR = os.path.join(TMP_DIR, "hf_models")
+
+# Set environment variables to use these directories
+os.environ["TRANSFORMERS_CACHE"] = os.path.join(TMP_DIR, "transformers_cache")
+os.environ["HF_HOME"] = os.path.join(TMP_DIR, "hf_home")
+os.environ["HUGGINGFACE_HUB_CACHE"] = os.path.join(TMP_DIR, "hf_hub_cache")
+
+# Helper function to safely create directories
+def safe_makedirs(directory):
+    try:
+        os.makedirs(directory, exist_ok=True)
+        return True
+    except (PermissionError, OSError) as e:
+        print(f"Warning: Could not create directory {directory}: {e}")
+        return False
+
+# Create necessary directories
+for directory in [MODEL_DIR, os.environ["TRANSFORMERS_CACHE"], 
+                 os.environ["HF_HOME"], os.environ["HUGGINGFACE_HUB_CACHE"]]:
+    safe_makedirs(directory)
+
+
+
+
+
 # Add GPU decorator for Hugging Face Spaces
 try:
     from spaces import GPU
@@ -45,7 +74,6 @@ stable_diffusion_pipeline = None
 MODEL_DIR = "./model"
 os.makedirs(MODEL_DIR, exist_ok=True)
 
-# Update the model loading functions
 def load_llava_model():
     """Load LLaVA model for image captioning"""
     global llava_model, llava_processor
@@ -54,20 +82,35 @@ def load_llava_model():
         print("Loading LLaVA model for image analysis...")
         model_id = "llava-hf/llava-1.5-7b-hf"
         
-        # Load processor and model with explicit cache directory
-        llava_processor = AutoProcessor.from_pretrained(
-            model_id,
-            cache_dir=os.path.join(MODEL_DIR, "llava_processor")
-        )
-        llava_model = AutoModelForCausalLM.from_pretrained(
-            model_id,
-            torch_dtype=torch.float16,
-            device_map="auto",
-            cache_dir=os.path.join(MODEL_DIR, "llava_model")
-        )
+        try:
+            # Load processor and model with system temp directory
+            llava_processor = AutoProcessor.from_pretrained(
+                model_id,
+                local_files_only=False
+            )
+            llava_model = AutoModelForCausalLM.from_pretrained(
+                model_id,
+                torch_dtype=torch.float16,
+                device_map="auto",
+                local_files_only=False
+            )
+        except Exception as e:
+            print(f"Error loading LLaVA model: {e}")
+            raise
     
     return llava_model, llava_processor
 
+
+# In the stylize_video function, replace:
+os.makedirs("outputs", exist_ok=True)
+persistent_output = os.path.join("outputs", f"stylized_{uuid.uuid4()}.mp4")
+
+# With:
+outputs_dir = os.path.join(TMP_DIR, "outputs")
+safe_makedirs(outputs_dir)
+persistent_output = os.path.join(outputs_dir, f"stylized_{uuid.uuid4()}.mp4")
+
+
 def load_stable_diffusion_model():
     """Load Stable Diffusion model for Ghibli-style image generation"""
     global stable_diffusion_pipeline