"""Note summarizer — generates a compact AI summary for a note.

Called fire-and-forget from create_note / update_note tools so the
``notes.ai_summary`` column stays current without blocking the agent loop.
"""

from __future__ import annotations

import logging

from langchain_core.messages import HumanMessage, SystemMessage

from app.core.langfuse_client import get_prompt_or_fallback
from app.core.llm import get_agent_llm

logger = logging.getLogger(__name__)

_FALLBACK_PROMPT = """\
Summarize this note in <=250 characters. Be terse and dense.
Keep proper nouns, dates, decisions, and action items.
Do not start with "This note".
Respond with the summary text only — no intro, no labels.

Title: {title}
Content: {content}"""

_MAX_CONTENT_CHARS = 4000


async def generate_note_summary(title: str, content: str) -> str:
    """Return a <=250-char summary of *title* + *content*.

    Uses the Langfuse ``note_summary`` prompt (hot-swappable) with a local
    fallback.  Truncates *content* to 4000 chars before sending to avoid
    token waste on large notes.
    """
    template, _ = get_prompt_or_fallback("note_summary", _FALLBACK_PROMPT)
    trimmed = content[:_MAX_CONTENT_CHARS]
    system_prompt = template.format(title=title, content=trimmed)

    try:
        llm = get_agent_llm("note-summarizer")
        response = await llm.ainvoke([
            SystemMessage(content=system_prompt),
            HumanMessage(content="Generate the summary."),
        ])
        text = response.content if isinstance(response.content, str) else ""
        return text.strip()[:250]
    except Exception as exc:
        logger.warning("note_summarizer: failed to generate summary: %s", exc)
        return ""