from __future__ import annotations

from collections import defaultdict
from typing import ClassVar

from .base import BaseAgent, AgentInput, AgentOutput
from .manifest import AgentManifest


MANIFEST = AgentManifest(
    id="focus-area",
    version="1.1.0",  # bumped: preferred_areas pref is now honoured in compute (#113)
    description="Identifies the most congested project/area in the user's task list.",
    pref_schema={
        "type": "object",
        "additionalProperties": False,
        "properties": {
            "preferred_areas": {
                "type": "array",
                "items": {"type": "string"},
                "default": [],
                "description": "Project / label names to prioritise when multiple areas tie.",
            },
        },
    },
    context_schema=["todoist.tasks"],
    required_consents=["data:core", "data:todoist", "agent:focus-area"],
    output_contract={"type": "snippet", "format": "free_text"},
    ttl_sec=43_200,
    # No inferred_params: preferred_areas requires project-level feedback linkage
    # that isn't available in feedback_history alone. Revisit with #78 (signal
    # abstraction) once per-task reactions can be traced back to a project.
)


class FocusAreaAgent(BaseAgent):
    """Identifies the most congested project/area in the user's task list."""
    agent_id: ClassVar[str] = MANIFEST.id
    ttl_seconds: ClassVar[int] = MANIFEST.ttl_sec
    version: ClassVar[str] = MANIFEST.version

    def compute(self, inp: AgentInput) -> AgentOutput:
        preferred: list[str] = inp.agent_prefs.get("preferred_areas", [])
        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})

        def score(project: str, tasks: list[dict]) -> tuple[float, bool]:
            base = sum(2.0 if t.get("is_overdue") else 1.0 for t in tasks)
            # Boost preferred areas to break ties in their favour
            boosted = project in preferred or any(p in project for p in preferred)
            return (base + (0.5 if boosted else 0.0), boosted)

        top_project, top_tasks = max(
            by_project.items(),
            key=lambda kv: score(kv[0], 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)
        boosted = top_project in preferred or any(p in top_project for p in preferred)

        parts = [
            f"The user's most congested area is {label} "
            f"({n} task{'s' if n != 1 else ''}, {overdue_in_top} overdue)."
        ]
        if boosted:
            parts.append("This area matches the user's stated focus preferences.")
        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),
            "preferred_areas": preferred,
        }
        return self._make_output(inp, prompt, snapshot)