"""general / social intents: web-search answers, general LLM answers, casual persona replies."""
import asyncio
import html
import json
import logging
import os
import re
import time
import uuid
from datetime import datetime
from typing import Any, Dict, List, Literal, Optional, Tuple
from urllib.parse import quote, urlsplit

import httpx
from pydantic import BaseModel, ConfigDict, Field

from src.config import get_settings, LIBBEE_VERSION

from src.agentcore.models import ChatMessage
from src.agentcore.constants import KU_MAIN_URL, _GUARDRAIL, _URL_INSTRUCTION
from src.agentcore.utils import _build_history_messages, _get_llm, _get_runtime_config

logger = logging.getLogger(__name__)

async def _libbee_casual_response(question: str, history: List[ChatMessage], model: str, hint: str = "") -> str:
    """LLM #1 — casual social response. v3.8.1: appends _GUARDRAIL + _URL_INSTRUCTION."""
    if hint and len(hint.strip()) > 20:
        return hint.strip()
    settings = get_settings()
    if not settings.openai_api_key and not settings.anthropic_api_key:
        return "I'm <strong>LibBee</strong>, the Khalifa University Library AI Assistant — always happy to help!"
    try:
        llm = _get_llm(model, temperature=0.6, max_tokens=160)
        msgs = [{"role": "system", "content": (
            "You are LibBee, the Khalifa University Library AI Assistant. "
            "Respond warmly and naturally in 1-3 sentences as a friendly librarian. "
            "No markdown, no bullet points. "
            + _GUARDRAIL + "\n\n" + _URL_INSTRUCTION
        )}]
        _cfg = _get_runtime_config()
        _ci = _cfg.get("custom_instructions", "").strip()
        if _ci:
            msgs[0]["content"] += " " + _ci
        msgs.extend(_build_history_messages(history))
        msgs.append({"role": "user", "content": question})
        response = await llm.ainvoke(msgs)
        return response.content.strip()
    except Exception:
        return "I'm <strong>LibBee</strong>, the Khalifa University Library AI Assistant — always happy to help!"


async def _llm_general_answer(question: str, history: List[ChatMessage], model: str) -> str:
    """LLM #3 — general factual answer. v3.8.1: appends _GUARDRAIL + _URL_INSTRUCTION."""
    settings = get_settings()
    if not settings.openai_api_key and not settings.anthropic_api_key:
        return (
            "I'm <strong>LibBee</strong>, the KU Library AI Assistant. "
            f'For general university information, visit <a href="{KU_MAIN_URL}" target="_blank">ku.ac.ae</a>.'
        )
    system = (
        "You are LibBee, the Khalifa University Library AI Assistant (Abu Dhabi, UAE). "
        "Answer factually and concisely in 3-5 sentences. Use HTML <br> for line breaks. "
        "KU means Khalifa University. If the topic is academic, briefly offer to help find library resources. "
        "When referencing KU Library services, include these verified links where relevant: "
        "Library homepage: https://library.ku.ac.ae | "
        "Ask a Librarian: https://library.ku.ac.ae/AskUs | "
        "Library hours: https://library.ku.ac.ae/hours | "
        "ILL requests: https://library.ku.ac.ae/ill/ | "
        "Study rooms: https://library.ku.ac.ae/rooms/ | "
        "E-resources: https://library.ku.ac.ae/eresources | "
        "Khazna repository: https://khazna.ku.ac.ae | "
        "PRIMO discovery: https://khalifa.primo.exlibrisgroup.com/discovery/search?vid=971KUOSTAR_INST:KU. "
        "Only use these exact URLs — never invent others. "
        + _GUARDRAIL + "\n\n" + _URL_INSTRUCTION
    )
    _cfg = _get_runtime_config()
    _ci = _cfg.get("custom_instructions", "").strip()
    if _ci:
        system += " " + _ci
    try:
        llm = _get_llm(model, temperature=0.3, max_tokens=360)
        msgs = [{"role": "system", "content": system}]
        msgs.extend(_build_history_messages(history))
        msgs.append({"role": "user", "content": question})
        response = await llm.ainvoke(msgs)
        return response.content.strip()
    except Exception as e:
        logger.error(f"_llm_general_answer error: {e}")
        return f'Having trouble right now. Visit <a href="{KU_MAIN_URL}" target="_blank">ku.ac.ae</a>.'


def _response_field(value: Any, name: str, default: Any = None) -> Any:
    """Read SDK objects and dictionaries without depending on a provider SDK."""
    return value.get(name, default) if isinstance(value, dict) else getattr(value, name, default)


def _citation_source(citation: Any) -> Optional[dict]:
    url = str(_response_field(citation, "url", "") or "").strip()
    try:
        parsed = urlsplit(url)
        if (parsed.scheme not in ("http", "https") or not parsed.hostname
                or parsed.username or parsed.password or any(ord(c) < 32 for c in url)):
            return None
    except ValueError:
        return None
    return {"title": str(_response_field(citation, "title", "") or parsed.hostname),
            "url": url, "source": "web_search"}


def _render_web_text(block: Any, sources: List[dict], anthropic: bool = False) -> str:
    """Escape provider prose and attach real, clickable citations at their source span."""
    raw = str(_response_field(block, "text", "") or "")
    if not raw:
        return ""
    citations = _response_field(block, "citations" if anthropic else "annotations", []) or []
    insertions: Dict[int, List[str]] = {}
    for citation in citations:
        kind = _response_field(citation, "type", "")
        if kind != ("web_search_result_location" if anthropic else "url_citation"):
            continue
        source = _citation_source(citation)
        if not source:
            continue
        existing = next((i for i, item in enumerate(sources) if item["url"] == source["url"]), None)
        if existing is None:
            sources.append(source)
            existing = len(sources) - 1
        position = len(raw) if anthropic else _response_field(citation, "end_index", len(raw))
        if not isinstance(position, int) or not 0 <= position <= len(raw):
            position = len(raw)
        link = (f' <a href="{html.escape(source["url"], quote=True)}" target="_blank" '
                f'rel="noopener noreferrer" title="{html.escape(source["title"], quote=True)}">'
                f'[{existing + 1}]</a>')
        if link not in insertions.setdefault(position, []):
            insertions[position].append(link)

    def escaped(segment: str) -> str:
        # SDK citation tokens have no meaning to a browser; links above replace them.
        segment = re.sub(r"\ue200cite[^\ue201]*\ue201", "", segment)
        return html.escape(segment).replace("\n", "<br>")

    answer, previous = [], 0
    for position in sorted(insertions):
        answer.append(escaped(raw[previous:position]))
        answer.extend(insertions[position])
        previous = position
    answer.append(escaped(raw[previous:]))
    return "".join(answer)


def _parse_web_response(response: Any, provider: str) -> dict:
    """Only label an answer live when a search completed and returned cited sources."""
    sources: List[dict] = []
    parts: List[str] = []
    searched = False
    if provider == "claude":
        for block in _response_field(response, "content", []) or []:
            kind = _response_field(block, "type", "")
            if kind == "web_search_tool_result":
                # API search errors are objects inside a successful HTTP response.
                result = _response_field(block, "content")
                searched = searched or isinstance(result, list)
            elif kind == "text":
                parts.append(_render_web_text(block, sources, anthropic=True))
        finished = _response_field(response, "stop_reason", "end_turn") == "end_turn"
    else:
        for item in _response_field(response, "output", []) or []:
            if (_response_field(item, "type", "") == "web_search_call"
                    and _response_field(item, "status", "") == "completed"):
                searched = True
            for block in _response_field(item, "content", []) or []:
                if _response_field(block, "type", "") == "output_text":
                    parts.append(_render_web_text(block, sources))
        finished = _response_field(response, "status", "completed") == "completed"
    live = searched and finished and bool(sources)
    return {"answer": "".join(parts).strip(), "sources": sources,
            "tools_used": ["web_search"] if searched else [],
            "live_search": live, "model_used": provider}


async def _web_search_result(question: str, history: List[ChatMessage], model: str) -> dict:
    """Return source evidence alongside text, with bounded calls and honest fallback metadata."""
    settings = get_settings()
    system = (
        "You are LibBee, the Khalifa University Library AI Assistant (Abu Dhabi, UAE). "
        "Search the web and answer using current sources. Be concise and factual. "
        "Use plain text with paragraph breaks, no HTML or Markdown. "
        "Cite factual claims using the search tool's citations; never invent sources or URLs. "
        "The application renders citation links, so do not write HTML links yourself. "
        + _GUARDRAIL
    )
    messages = _build_history_messages(history)
    messages.append({"role": "user", "content": question})
    if settings.anthropic_api_key and (model == "claude" or not settings.openai_api_key):
        try:
            import anthropic
            async with anthropic.AsyncAnthropic(
                api_key=settings.anthropic_api_key, timeout=16.0, max_retries=0
            ) as client:
                response = await asyncio.wait_for(client.messages.create(
                    model=os.getenv("ANTHROPIC_WEB_MODEL", "claude-haiku-4-5-20251001"),
                    max_tokens=620,
                    system=system,
                    tools=[{"type": "web_search_20250305", "name": "web_search", "max_uses": 2}],
                    messages=messages,
                ), timeout=18.0)
            result = _parse_web_response(response, "claude")
            if result["answer"] and result["live_search"]:
                return result
            logger.info("Claude web response had no complete cited search answer")
        except Exception as exc:
            logger.warning("Claude web search failed (%s)", type(exc).__name__)
    if settings.openai_api_key:
        try:
            from openai import AsyncOpenAI
            async with AsyncOpenAI(
                api_key=settings.openai_api_key, timeout=16.0, max_retries=0
            ) as client:
                response = await asyncio.wait_for(client.responses.create(
                    model=os.getenv("OPENAI_WEB_MODEL", "gpt-4.1-mini"),
                    # Preview remains supported and works with the pinned 1.x SDK.
                    tools=[{"type": "web_search_preview"}],
                    tool_choice={"type": "web_search_preview"},
                    instructions=system,
                    input=messages,
                    max_output_tokens=620,
                    store=False,
                ), timeout=18.0)
            result = _parse_web_response(response, "gpt")
            if result["answer"] and result["live_search"]:
                return result
            logger.info("GPT web response had no complete cited search answer")
        except Exception as exc:
            logger.warning("GPT web search failed (%s)", type(exc).__name__)
    fallback = await _llm_general_answer(question, history, model)
    provider = "claude" if settings.anthropic_api_key and (model == "claude" or not settings.openai_api_key) else "gpt"
    return {
        "answer": "<em>I couldn’t verify current web information. The following is general guidance and may be out of date.</em><br><br>" + fallback,
        "sources": [], "tools_used": ["general_knowledge"], "live_search": False,
        "model_used": provider,
    }


async def _web_search_answer(question: str, history: List[ChatMessage], model: str) -> str:
    """Compatibility wrapper; orchestration uses _web_search_result for source metadata."""
    return (await _web_search_result(question, history, model))["answer"]


def _general_follow_up(question: str) -> Tuple[str, List[dict]]:
    return (
        "Would you like a brief explanation, current web information, or KU Library resources on this topic?",
        [
            {"label": "Shorter explanation", "question": f"Give me a shorter explanation of {question}"},
            {"label": "Current web information", "question": f"Show current web information on {question}"},
            {"label": "Find KU Library resources", "question": f"Find KU Library resources on {question}"},
        ],
    )


def _social_follow_up() -> Tuple[str, List[dict]]:
    return (
        "What would you like help with next?",
        [
            {"label": "Find articles on a topic", "question": "Find articles on a topic"},
            {"label": "Check a library service", "question": "Check a library service"},
            {"label": "Contact a librarian", "question": "Contact a librarian"},
        ],
    )