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class Retriever:
    def __init__(self, embeddings_path: str):
        self.embeddings: Dict[str, np.ndarray] = self.load_embeddings(embeddings_path)

        # Keep track of image names
        self.image_to_index = {image_name: i for i, image_name in enumerate(self.embeddings.keys())}
        self.index_to_image = {i: image_name for i, image_name in enumerate(self.embeddings.keys())}

        # Build Faiss index
        self.embeddings = np.array(list(self.embeddings.values()))
        self.dim = self.embeddings.shape[1]
        self.index = faiss.IndexFlatL2(self.dim)
        self.index.add(self.embeddings)

    @staticmethod
    def load_embeddings(embeddings_path: str) -> Dict[str, np.ndarray]:
        """Load embeddings from a file
        """
        raise NotImplementedError

    def retrieve(self, queries: np.ndarray, n_neighbors: int = 5) -> List[str]:
        """Retrieve nearest neighbors indexes from queries
        """
        dist, indexes = self.index.search(queries, n_neighbors)
        return [[self.index_to_image[i] for i in index] for index in indexes]