"""Calendar agent — events, conflict detection, and scheduling."""

from __future__ import annotations

import json
from typing import Any

from langchain_core.messages import HumanMessage, SystemMessage
from langchain_core.tools import tool
from langchain_openai import ChatOpenAI

from app.config.settings import settings
from app.core.agent_registry import ChatAgent, registry

_SYSTEM_PROMPT = (
    "You are a calendar management assistant. Help the user manage events, "
    "detect scheduling conflicts, and suggest reschedules.\n"
    "Rules:\n"
    "  - Work exclusively with event metadata provided in context\n"
    "  - Never store or reference raw calendar data\n"
    "  - date_range format: ISO 8601 interval, e.g. '2024-01-01/2024-01-07'\n"
    "  - Always confirm the date/time scope of any operation"
)


@tool
async def list_events(date_range: str) -> str:
    """List calendar events in a date range (ISO 8601 interval, e.g. '2024-01-01/2024-01-07')."""
    return json.dumps({
        "action": "list",
        "table": "events",
        "filters": {"date_range": date_range},
    })


@tool
async def detect_conflicts(events: str) -> str:
    """Detect scheduling conflicts in a JSON array of event metadata objects."""
    return json.dumps({
        "action": "analyse",
        "table": "events",
        "input": events,
        "result": "conflicts_detected",
    })


@tool
async def suggest_reschedule(conflict: str) -> str:
    """Suggest a reschedule for a conflicting event. Pass the conflict as a JSON string."""
    return json.dumps({
        "action": "suggest_reschedule",
        "table": "events",
        "input": conflict,
    })


@registry.register
class CalendarAgent(ChatAgent):
    def get_name(self) -> str:
        return "calendar_agent"

    def get_description(self) -> str:
        return "Calendar management: events, conflicts, scheduling"

    def get_tools(self) -> list[Any]:
        return [list_events, detect_conflicts, suggest_reschedule]

    async def handle(self, query: str, context: dict[str, Any]) -> str:
        llm = ChatOpenAI(model="gpt-4o", temperature=0, api_key=settings.OPENAI_API_KEY)
        messages = [
            SystemMessage(content=_SYSTEM_PROMPT),
            HumanMessage(
                content=f"User query: {query}\nContext: {json.dumps(context)[:1000]}"
            ),
        ]
        return await self._tool_loop(llm, messages, self.get_tools())