from __future__ import annotations

from dataclasses import dataclass
from typing import Any, Callable

from .demo_packs import DemoPack, read_text_inputs
from .embedding import extract_keywords
from .storage import SQLiteStore


@dataclass(frozen=True)
class ProjectSpec:
    key: str
    title: str
    description: str
    data_subdir: str
    search_enabled: bool
    inbox_label: str
    processor: Callable[[DemoPack, SQLiteStore, Any], dict[str, Any]]

    def run_pack(self, pack: DemoPack, store: SQLiteStore, config: Any) -> dict[str, Any]:
        return self.processor(pack, store, config)


def _base_result(
    pack: DemoPack,
    store: SQLiteStore,
    project: str,
    title: str,
    primary_text: str,
    payload: dict[str, Any],
    search_text: str | None = None,
) -> dict[str, Any]:
    record_id = store.store_record(project, pack.pack_id, title, primary_text, payload, status='ready')
    store.store_embedding(record_id, project, search_text or primary_text, metadata={'pack_id': pack.pack_id})
    return {'record_id': record_id, 'pack_id': pack.pack_id, 'project': project, **payload}


def classify_p1(text: str) -> str:
    lowered = text.lower()
    if any(term in lowered for term in ('overdue', 'past due', 'final notice', 'urgent', 'collection', 'deadline')):
        return 'urgent'
    if any(term in lowered for term in ('lab reminder', 'routine informational notice', 'informational notice', 'fyi', 'newsletter')):
        return 'FYI'
    if any(term in lowered for term in ('appointment', 'scheduled', 'follow-up', 'clinic', 'insurance', 'benefits', 'medication', 'renewal', 'notice')):
        return 'important'
    return 'informational'


def processor_p1(pack: DemoPack, store: SQLiteStore, config: Any) -> dict[str, Any]:
    text = read_text_inputs(pack)
    triage = pack.expected_signals.get('triage') or classify_p1(text)
    first_line = text.splitlines()[0] if text.splitlines() else text[:180]
    payload = {
        'triage': triage,
        'summary': first_line[:180],
        'qa': [
            {'question': 'What is this document about?', 'answer': first_line[:180], 'citation': first_line[:180]},
            {'question': 'What action is requested?', 'answer': first_line[:180], 'citation': first_line[:180]},
            {'question': 'Is there a deadline or date mentioned?', 'answer': first_line[:180], 'citation': first_line[:180]},
            {'question': 'Is there an amount, phone number, or next step mentioned?', 'answer': first_line[:180], 'citation': first_line[:180]},
        ],
        'citations': [{'question': 'What is this document about?', 'snippet': first_line[:180]}],
        'ocr_preview': first_line[:180],
        'ocr_text': text,
        'safety': {'missing_info_policy': 'not stated', 'invented_values': False},
        'inbox_items': [
            {'record_id': 'pending', 'title': pack.pack_id, 'triage': triage, 'summary': first_line[:180], 'file_type': pack.manifest.get('inputs', [{}])[0].get('kind', 'text')},
        ],
        'expected_signals': pack.expected_signals,
        'evidence': extract_keywords(text),
    }
    result = _base_result(pack, store, 'p1', f'P1: {pack.pack_id}', payload['summary'], payload, text)
    result['record_ids'] = [result['record_id']]
    result['documents'] = [payload]
    result['triage'] = triage
    result['summary'] = payload['summary']
    result['qa'] = payload['qa']
    result['citations'] = payload['citations']
    result['ocr_preview'] = payload['ocr_preview']
    result['ocr_text'] = payload['ocr_text']
    result['safety'] = payload['safety']
    result['inbox_items'] = payload['inbox_items']
    return result