from __future__ import annotations
from collections import defaultdict
from typing import ClassVar
from .base import BaseAgent, AgentInput, AgentOutput


class FocusAreaAgent(BaseAgent):
    """Identifies the most congested project/area in the user's task list."""
    agent_id: ClassVar[str] = "focus-area"
    ttl_seconds: ClassVar[int] = 43_200  # 12h
    version: ClassVar[str] = "1.0.0"

    def compute(self, inp: AgentInput) -> AgentOutput:
        by_project: dict[str, list[dict]] = defaultdict(list)
        for task in inp.tasks:
            project = task.get("project_id") or task.get("project") or "default"
            by_project[project].append(task)

        if not by_project:
            prompt = "No tasks available to identify a focus area."
            return self._make_output(inp, prompt, {"project_count": 0})

        # Score each project: overdue tasks count double
        def score(tasks: list[dict]) -> float:
            return sum(2.0 if t.get("is_overdue") else 1.0 for t in tasks)

        top_project, top_tasks = max(by_project.items(), key=lambda kv: score(kv[1]))
        overdue_in_top = sum(1 for t in top_tasks if t.get("is_overdue"))
        label = "the default project" if top_project == "default" else f'"{top_project}"'
        n = len(top_tasks)

        parts = [
            f"The user's most congested area is {label} "
            f"({n} task{'s' if n != 1 else ''}, {overdue_in_top} overdue)."
        ]
        if overdue_in_top >= 3:
            parts.append("Consider surfacing an action from this area.")

        prompt = " ".join(parts)
        snapshot = {
            "top_project": top_project,
            "top_task_count": n,
            "top_overdue_count": overdue_in_top,
            "project_count": len(by_project),
        }
        return self._make_output(inp, prompt, snapshot)