def _load_model()

in supporting-blog-content/building-multimodal-rag-with-elasticsearch-gotham/src/embedding_generator.py [0:0]

• 26 lines of code
• 5 McCabe index (conditional complexity)

    def _load_model(self):
        """Initialize and test the ImageBind model."""

        checkpoint_path = os.path.expanduser(
            "~/.cache/torch/checkpoints/imagebind_huge.pth"
        )
        os.makedirs(os.path.dirname(checkpoint_path), exist_ok=True)

        if not os.path.exists(checkpoint_path):
            print("Downloading ImageBind weights...")
            download_url_to_file(
                "https://dl.fbaipublicfiles.com/imagebind/imagebind_huge.pth",
                checkpoint_path,
            )

        try:
            # Check if file exists
            if not os.path.exists(checkpoint_path):
                raise FileNotFoundError(f"Checkpoint not found: {checkpoint_path}")

            model = imagebind_model.imagebind_huge(pretrained=False)
            model.load_state_dict(torch.load(checkpoint_path))
            model.eval().to(self.device)

            # Quick test with empty text input
            logger.info("Testing model with sample input...")
            test_input = data.load_and_transform_text([""], self.device)
            with torch.no_grad():
                _ = model({"text": test_input})

            logger.info("🤖 ImageBind model initialized successfully")
            return model
        except Exception as e:
            logger.error(f"🚨 Model initialization failed: {str(e)}")
            raise