"""Grounded answer generation."""

from __future__ import annotations

import logging
from typing import TYPE_CHECKING

from python.ebook_search.llm_interface import request_chat_completion

if TYPE_CHECKING:
    from python.ebook_search.config import EbookSearchConfig
    from python.ebook_search.search import SearchResult

logger = logging.getLogger(__name__)


def answer_query(query: str, results: list[SearchResult], config: EbookSearchConfig) -> str:
    """Answer a question using only retrieved chunks."""
    if not config.answer_enabled:
        logger.info("ebook_answer_skipped_disabled")
        return "Answer generation is disabled. Source chunks are shown below."

    if not results:
        logger.info("ebook_answer_skipped_no_results")
        return "No relevant sources were found."

    logger.info(
        "ebook_answer_request_start base_url=%s model=%s sources=%s query_length=%s",
        config.vllm_base_url,
        config.chat_model,
        len(results),
        len(query),
    )
    context = "\n\n".join(
        f"[{index}] {result.source_title}{' - ' + result.chapter_title if result.chapter_title else ''}\n{result.text}"
        for index, result in enumerate(results, start=1)
    )
    content = request_chat_completion(
        config,
        [
            {
                "role": "system",
                "content": (
                    "Answer only from the provided context. Cite sources with bracketed numbers like [1]. "
                    "If the context is insufficient, say so."
                ),
            },
            {"role": "user", "content": f"Question:\n{query}\n\nContext:\n{context}"},
        ],
    )

    logger.info(
        "ebook_answer_request_complete model=%s answer_length=%s",
        config.chat_model,
        len(content),
    )
    return content or "The model returned an empty answer."