"""
title: ZP Agent – overené odpovede
description: RAG/GraphRAG answers verified and rendered by ZP Agent before display.
version: 1.0.0
"""
import asyncio
import json
import urllib.request
from typing import Literal

from pydantic import BaseModel, Field


class Pipe:
    class Valves(BaseModel):
        BACKEND_URL: str = Field(default='', description='URL ZP Agent API reachable from the OpenWebUI server')
        BACKEND_API_KEY: str = Field(default='', description='SEARCH_API_KEY of ZP Agent',
                                    json_schema_extra={'input': {'type': 'password'}})
        DEFAULT_ENGINE: Literal['rag', 'graphrag'] = 'rag'
        TIMEOUT_SECONDS: int = Field(default=300, ge=10, le=600)

    def __init__(self):
        self.valves = self.Valves()

    def pipes(self):
        return [{'id': 'rag', 'name': 'ZP Agent / RAG – overené'},
                {'id': 'graphrag', 'name': 'ZP Agent / GraphRAG – overené'}]

    def _fetch(self, query: str, engine: str) -> dict:
        url = self.valves.BACKEND_URL.rstrip('/')
        if not url.startswith(('http://', 'https://')) or not self.valves.BACKEND_API_KEY:
            raise ValueError('Missing backend configuration')
        request = urllib.request.Request(url + '/answer', data=json.dumps(
            {'query': query, 'engine': engine}, ensure_ascii=False).encode(),
            headers={'Content-Type': 'application/json',
                     'Authorization': 'Bearer ' + self.valves.BACKEND_API_KEY})
        with urllib.request.urlopen(request, timeout=self.valves.TIMEOUT_SECONDS) as response:
            return json.load(response)

    async def pipe(self, body: dict):
        messages = [row for row in body.get('messages', []) if row.get('role') == 'user']
        query = messages[-1].get('content', '') if messages else ''
        if isinstance(query, list):
            query = '\n'.join(row.get('text', '') for row in query if row.get('type') == 'text')
        if not isinstance(query, str) or not query.strip():
            return 'Zadajte textovú otázku.'
        if len(query.strip()) > 500:
            return 'Otázka môže mať najviac 500 znakov.'
        model = str(body.get('model', '')).rsplit('.', 1)[-1]
        engine = model if model in {'rag', 'graphrag'} else self.valves.DEFAULT_ENGINE
        try:
            result = await asyncio.to_thread(self._fetch, query.strip(), engine)
        except Exception:
            return 'Overovací backend nie je dostupný. Neoverená odpoveď sa nezobrazí.'
        if not isinstance(result, dict):
            return 'Backend neposkytol platnú overenú odpoveď.'
        if result.get('accepted_for_delivery') is not True:
            return 'Odpoveď neprešla overením podkladov. Neoverené údaje sa nezobrazia.'
        if result.get('status') not in {'ok', 'no_answer', 'ambiguous'} or not isinstance(result.get('answer'), str):
            return 'Backend neposkytol platnú overenú odpoveď.'
        # Return the approved final text directly. Never send it to another LLM
        # for paraphrasing: that would invalidate the fact/citation checks.
        return result['answer'] or 'Backend neposkytol text odpovede.'