Download model using HTTP only

app/services/model_service.py

@@ -7,8 +7,9 @@ import logging
 import torch
 from PIL import Image
 from transformers import AutoTokenizer, ViTImageProcessor
-from huggingface_hub import hf_hub_download, login
-
+from huggingface_hub import login
+import requests
+from huggingface_hub.utils import build_hf_headers
 from app.config import settings
 from app.models.vqa_model import VQAModel
 
@@ -42,74 +43,31 @@ class ModelService:
     def _download_model_from_hub(self):
         """Download the model from Hugging Face Hub if not present locally"""
         try:
-            # Create the directory if it doesn't exist
-            model_dir = os.path.dirname(settings.MODEL_PATH)
-            os.makedirs(model_dir, exist_ok=True)
-            
-            # Log environment info for debugging
-            logger.info(f"HF_HOME: {os.environ.get('HF_HOME')}")
-            logger.info(f"TMPDIR: {os.environ.get('TMPDIR')}")
-            logger.info(f"Current working directory: {os.getcwd()}")
-            logger.info(f"Model directory: {model_dir}")
-            logger.info(f"Model path: {settings.MODEL_PATH}")
-            
-            # Set up a temporary directory within our writable space
-            tmp_dir = os.environ.get("TMPDIR", "/app/tmp")
-            os.makedirs(tmp_dir, exist_ok=True)
-            logger.info(f"Using temporary directory: {tmp_dir}")
-            
-            # Use a simpler approach to download the file
-            try:                
-                # Try to download directly to the final location
-                logger.info(f"Downloading from {settings.HF_MODEL_REPO}/{settings.HF_MODEL_FILENAME}")
-                downloaded_path = hf_hub_download(
-                    repo_id=settings.HF_MODEL_REPO,
-                    filename=settings.HF_MODEL_FILENAME,
-                    local_dir=model_dir,
-                    local_dir_use_symlinks=False,
-                    cache_dir=os.environ.get("HF_HOME"),
-                    force_download=True
-                )
-                
-                logger.info(f"Model downloaded to: {downloaded_path}")
-                
-                # If needed, copy the file to the expected location
-                if downloaded_path != settings.MODEL_PATH:
-                    import shutil
-                    logger.info(f"Copying from {downloaded_path} to {settings.MODEL_PATH}")
-                    shutil.copy2(downloaded_path, settings.MODEL_PATH)
-                
-                logger.info(f"Model download successful")
-                return True
-                
-            except Exception as download_error:
-                logger.error(f"Error during Hugging Face Hub download: {download_error}")
-                
-                # Fallback method: direct download using requests
-                logger.info("Trying fallback method with direct HTTP download")
-                import requests
-                from huggingface_hub.utils import build_hf_headers
-                
-                # Get Hugging Face token from settings
-                token = settings.HUGGINGFACE_TOKEN
-                
-                # Build proper URL for the model file
-                url = f"https://huggingface.co/{settings.HF_MODEL_REPO}/resolve/main/{settings.HF_MODEL_FILENAME}"
-                logger.info(f"Downloading from URL: {url}")
-                
-                # Download with proper headers
-                headers = build_hf_headers(token=token)
-                response = requests.get(url, headers=headers, stream=True)
-                response.raise_for_status()
-                
-                # Write the file in chunks to avoid memory issues
-                logger.info(f"Writing downloaded content to {settings.MODEL_PATH}")
-                with open(settings.MODEL_PATH, 'wb') as f:
-                    for chunk in response.iter_content(chunk_size=8192):
-                        f.write(chunk)
-                
-                logger.info(f"Model downloaded successfully using fallback method")
-                return True
+            
+            # Fallback method: direct download using requests
+            logger.info("Downlaoding model from Hugging Face Hub")
+
+            
+            # Get Hugging Face token from settings
+            token = settings.HUGGINGFACE_TOKEN
+            
+            # Build proper URL for the model file
+            url = f"https://huggingface.co/{settings.HF_MODEL_REPO}/resolve/main/{settings.HF_MODEL_FILENAME}"
+            logger.info(f"Downloading from URL: {url}")
+            
+            # Download with proper headers
+            headers = build_hf_headers(token=token)
+            response = requests.get(url, headers=headers, stream=True)
+            response.raise_for_status()
+            
+            # Write the file in chunks to avoid memory issues
+            logger.info(f"Writing downloaded content to {settings.MODEL_PATH}")
+            with open(settings.MODEL_PATH, 'wb') as f:
+                for chunk in response.iter_content(chunk_size=8192):
+                    f.write(chunk)
+            
+            logger.info(f"Model downloaded successfully")
+            return True
                 
         except Exception as e:
             logger.error(f"Error downloading model from Hugging Face Hub: {e}")