from langchain_community.document_loaders import WebBaseLoader
from langchain_text_splitters import RecursiveCharacterTextSplitter
from langchain_core.documents import Document
from typing import Iterable


def load_documents(website: str) -> list[Document]:
    """
    Loads documents from a given website.

    Args:
        website (str): The URL of the website to load documents from.

    Returns:
        list[Document]: A list of loaded documents.
    """
    loader = WebBaseLoader(website)
    return loader.load()


def format_documents(docs: list[Document]) -> str:
    """
    Formats a list of documents into a single string.

    Args:
        docs (list[Document]): The list of documents to format.

    Returns:
        str: The formatted documents as a single string.
    """
    formatted = []
    for doc in docs:
        source = doc.metadata.get("source", "")
        text = doc.page_content
        if source:
            text += f"\n[Source: {source}]"
        formatted.append(text)
    return "\n\n".join(formatted)


def split_documents(documents: Iterable[Document], chunk_size: int = 768, chunk_overlap: int = 100) -> list[Document]:
    """
    Splits documents into smaller chunks.

    Args:
        documents (Iterable[Document]): The documents to split.
        chunk_size (int): Maximum size of each chunk in characters.
        chunk_overlap (int): Number of overlapping characters between chunks.

    Returns:
        list[Document]: A list of split documents.
    """
    text_splitter = RecursiveCharacterTextSplitter(
        chunk_size=chunk_size,
        chunk_overlap=chunk_overlap,
        separators=["\n\n", "\n", ". ", " ", ""],
    )
    return text_splitter.split_documents(documents)