from __future__ import annotations

from typing import Dict


class ResponsePlanner:
    def choose_reply_mode(self, trigger: Dict, flow_state: str) -> str:
        if trigger.get("is_question"):
            return "qa_with_context" if flow_state in {"engaged", "deep_engaged"} else "qa_fast"
        if trigger.get("is_followup"):
            return "qa_with_context"
        if trigger.get("is_social_call"):
            return "social_short"
        if trigger.get("is_returning_member"):
            return "social_short"
        return "social_short" if flow_state in {"deep_engaged"} else "refuse_or_skip"

    def should_reply(
        self,
        trigger: Dict,
        flow_state: str,
        allow_proactive: bool,
        acceptance_state: str = "neutral",
        conversation_hints: Dict | None = None,
    ) -> bool:
        conversation_hints = conversation_hints or {}
        if trigger.get("is_at"):
            return True
        if trigger.get("is_question") and conversation_hints.get("has_recent_human_solver") and flow_state != "deep_engaged":
            return False
        if trigger.get("is_question"):
            if trigger.get("is_directed"):
                return True
            if acceptance_state == "warm" and flow_state == "deep_engaged" and trigger.get("priority", 0) >= 0.95:
                return True
            return False
        if trigger.get("is_followup"):
            return False
        if trigger.get("is_social_call"):
            if acceptance_state == "cold":
                return False
            return flow_state in {"engaged", "deep_engaged"}
        if trigger.get("is_returning_member"):
            return False
        if not allow_proactive:
            return False
        if acceptance_state == "cold":
            return False
        if acceptance_state == "neutral":
            return flow_state in {"deep_engaged"} and trigger.get("priority", 0) >= 0.8
        return flow_state in {"engaged", "deep_engaged"} and trigger.get("priority", 0) >= 0.65