"""
Custom embeddings wrapper using sentence-transformers to replace langchain HuggingFaceEmbeddings.
"""
from typing import List, Union
from sentence_transformers import SentenceTransformer


class HuggingFaceEmbeddings:
    """Wrapper around SentenceTransformer to match langchain interface."""
    
    def __init__(self, model_name: str = "sentence-transformers/all-MiniLM-L6-v2", **kwargs):
        self.model_name = model_name
        self.model = SentenceTransformer(model_name, **kwargs)
    
    def embed_documents(self, texts: List[str]) -> List[List[float]]:
        """Embed a list of documents."""
        embeddings = self.model.encode(texts, convert_to_numpy=True, show_progress_bar=False)
        return embeddings.tolist()
    
    def embed_query(self, text: str) -> List[float]:
        """Embed a single query."""
        embedding = self.model.encode([text], convert_to_numpy=True, show_progress_bar=False)
        return embedding[0].tolist()