from typing import Tuple, List, Optional
from llama_index.core.schema import NodeWithScore
import sys
from initialize import app_state
from utils import get_links_html, get_links_html_lp


async def search_with_ai_action(legal_position_json: dict) -> Tuple[str, Optional[List[NodeWithScore]]]:
    try:
        if app_state.retriever_bm25 is None:
            raise ValueError("Retriever is not initialized")

        query_text = (
            f"{legal_position_json['title']}: "
            f"{legal_position_json['text']}: "
            f"{legal_position_json['proceeding']}: "
            f"{legal_position_json['category']}"
        )

        nodes = await app_state.retriever_bm25.aretrieve(query_text)

        sources_output = "\n **Результати пошуку (наявні правові позиції ВСУ):** \n\n"
        for index, node in enumerate(nodes, start=1):
            source_title = node.node.metadata.get('title')
            doc_ids = node.node.metadata.get('doc_id')
            lp_ids = node.node.metadata.get('lp_id')
            links = get_links_html(doc_ids)
            links_lp = get_links_html_lp(lp_ids)
            sources_output += f"\n[{index}] *{source_title}* {links_lp} 👉 Score: {node.score} {links}\n"

        return sources_output, nodes

    except Exception as e:
        error_message = f"Error during search: {str(e)}"
        print(error_message, file=sys.stderr)
        return error_message, None