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


class MomentumAgent(BaseAgent):
    """Characterises the user's recent engagement trend from profile features."""
    agent_id: ClassVar[str] = "momentum"
    ttl_seconds: ClassVar[int] = 21600  # 6h
    version: ClassVar[str] = "1.0.0"

    def compute(self, inp: AgentInput) -> AgentOutput:
        completion = inp.profile.get("completion_rate_30d")
        dismiss = inp.profile.get("dismiss_rate_30d")
        volume = inp.profile.get("tip_volume_30d")

        parts: list[str] = []

        if completion is not None:
            pct = round(completion * 100)
            if pct >= 50:
                parts.append(f"The user completes {pct}% of tips (strong engagement).")
            elif pct >= 25:
                parts.append(f"The user completes {pct}% of tips (moderate engagement).")
            else:
                parts.append(
                    f"The user completes {pct}% of tips "
                    f"(low engagement — prefer simple, immediately actionable tips)."
                )
        else:
            parts.append("No completion-rate data yet (new user).")

        if dismiss is not None:
            dpct = round(dismiss * 100)
            if dpct >= 40:
                parts.append(f"Dismiss rate is high ({dpct}%) — avoid repetitive or irrelevant tips.")
            elif dpct <= 10:
                parts.append(f"Dismiss rate is low ({dpct}%).")

        if volume is not None and int(volume) < 5:
            parts.append("Very few tips served so far — this is an early-stage user.")

        prompt = " ".join(parts) if parts else "No engagement data available yet."
        snapshot = {
            "completion_rate_30d": completion,
            "dismiss_rate_30d": dismiss,
            "tip_volume_30d": volume,
        }
        return self._make_output(inp, prompt, snapshot)