Upload app.py

app.py

@@ -8,12 +8,12 @@ try:
     from transformers import ClapModel, ClapProcessor
     CLAP_AVAILABLE = True
     CLAP_METHOD = "transformers"
-except ImportError:
+except ImportError as e1:
     try:
         import laion_clap
         CLAP_AVAILABLE = True
         CLAP_METHOD = "laion"
-    except ImportError:
+    except ImportError as e2:
         CLAP_AVAILABLE = False
         CLAP_METHOD = None
 import torch
@@ -38,36 +38,41 @@ logger = logging.getLogger(__name__)
 
 app = FastAPI(title="CLIP Service", version="1.0.0")
 
+# Log CLAP availability after logger is initialized
+logger.info(f"CLAP availability: {CLAP_AVAILABLE}, method: {CLAP_METHOD}")
+
 class CLIPService:
     def __init__(self):
         logger.info("Loading CLIP model...")
+        self.clap_model = None
+        self.clap_processor = None
+        
         try:
             # Use CPU for Hugging Face free tier
             self.device = "cuda" if torch.cuda.is_available() else "cpu"
             logger.info(f"Using device: {self.device}")
             
             # Load CLIP model with explicit cache directory
+            logger.info("Loading CLIP model from HuggingFace...")
             self.clip_model = CLIPModel.from_pretrained(
                 "openai/clip-vit-large-patch14",
                 cache_dir=cache_dir,
                 local_files_only=False
             ).to(self.device)
             
+            logger.info("Loading CLIP processor...")
             self.clip_processor = CLIPProcessor.from_pretrained(
                 "openai/clip-vit-large-patch14",
                 cache_dir=cache_dir,
                 local_files_only=False
             )
             
-            # Initialize CLAP model placeholders (loaded on demand)
-            self.clap_model = None
-            self.clap_processor = None
-            
             logger.info(f"CLIP model loaded successfully on {self.device}")
             
         except Exception as e:
             logger.error(f"Failed to load CLIP model: {str(e)}")
-            raise RuntimeError(f"Model loading failed: {str(e)}")
+            logger.error(f"Error type: {type(e).__name__}")
+            raise RuntimeError(f"CLIP model loading failed: {str(e)}")
     
     def _load_clap_model(self):
         """Load CLAP model on demand"""
@@ -297,6 +302,7 @@ try:
     logger.info("CLIP service initialized successfully!")
 except Exception as e:
     logger.error(f"Failed to initialize CLIP service: {str(e)}")
+    logger.error(f"Error details: {type(e).__name__}: {str(e)}")
     # For now, we'll let the app start but service calls will fail gracefully
     clip_service = None