from __future__ import annotations

from typing import Dict, List


class ContextBuilder:
    def __init__(self, recent_context_size: int = 30):
        self.recent_context_size = max(int(recent_context_size or 30), 1)

    def build(
        self,
        *,
        room_id: str,
        group_profile: Dict,
        sender: str,
        sender_name: str,
        content: str,
        recent_messages: List[Dict],
        member_context: Dict,
        trigger: Dict,
        flow_state: str,
        reply_mode: str,
        vector_memories: List[Dict],
    ) -> Dict:
        recent_lines = []
        for item in recent_messages[-self.recent_context_size:]:
            msg_sender = item.get("sender_name") or item.get("sender") or "未知成员"
            msg_content = item.get("content") or item.get("message") or ""
            if msg_content:
                recent_lines.append(f"{msg_sender}: {msg_content}")
        return {
            "group_profile": group_profile or {"room_id": room_id},
            "speaker_profile": {
                "wxid": sender,
                "display_name": sender_name,
                "member_context": member_context or {},
            },
            "recent_messages": recent_lines,
            "recent_summary": "",
            "trigger_type": trigger.get("trigger_type", "none"),
            "reply_mode": reply_mode,
            "flow_state": flow_state,
            "memory_prompt": self._build_member_memory_prompt(member_context),
            "vector_memory_prompt": self._build_vector_memory_prompt(vector_memories),
            "group_profile_prompt": self._build_group_profile_prompt(group_profile or {}),
            "current_message": f"{sender_name}: {content}",
        }

    @staticmethod
    def _build_member_memory_prompt(member_context: Dict) -> str:
        if not member_context:
            return "暂无稳定成员画像。"
        meta = member_context.get("meta", {}) or {}
        topics = member_context.get("topics_of_interest", []) or []
        recent_focus = member_context.get("recent_focus", []) or []
        lines = [
            f"成员摘要：{member_context.get('summary_text', '')}".strip(),
            f"互动风格：{member_context.get('interaction_style', '')}".strip(),
            f"回复偏好：{member_context.get('response_style_hint', '')}".strip(),
            f"长期主题：{', '.join(topics[:5])}" if topics else "",
            f"近期关注：{', '.join(recent_focus[:4])}" if recent_focus else "",
            f"群内角色：{meta.get('group_role', '')}".strip(),
        ]
        return "\n".join([line for line in lines if line])

    @staticmethod
    def _build_vector_memory_prompt(vector_memories: List[Dict]) -> str:
        if not vector_memories:
            return ""
        lines = []
        for item in vector_memories[:2]:
            summary = item.get("content_summary") or item.get("summary_text") or item.get("text") or ""
            memory_type = item.get("memory_type", "memory")
            if summary:
                lines.append(f"[{memory_type}] {summary}")
        return "\n".join(lines)

    @staticmethod
    def _build_group_profile_prompt(group_profile: Dict) -> str:
        if not group_profile:
            return "当前群没有特殊知识域限制。"
        focus = ", ".join(group_profile.get("knowledge_focus", [])[:6])
        boundaries = ", ".join(group_profile.get("topic_boundaries", [])[:6])
        summary = str(group_profile.get("group_memory_summary", "") or "").replace("\n", " ").strip()
        if len(summary) > 120:
            summary = summary[:117] + "..."
        lines = [
            f"群模式：{group_profile.get('mode', 'social')}",
            f"知识域：{group_profile.get('knowledge_domain', 'general')}",
            f"配置知识域：{group_profile.get('configured_domain', 'general')}",
            f"历史推断知识域：{group_profile.get('group_memory_domain', 'general')}",
            f"回答风格：{group_profile.get('reply_style', '自然短句')}",
            f"互动调性：{group_profile.get('interaction_tone', '自然群友感')}",
            f"幽默强度：{group_profile.get('humor_style', '轻微')}",
            f"嘴硬程度：{group_profile.get('sharpness_style', '轻微嘴硬，不刻薄')}",
            f"表达松弛度：{group_profile.get('expressiveness_style', '克制')}",
            f"知识重点：{focus}" if focus else "",
            f"群长期摘要：{summary}" if summary else "",
            f"历史推断社交风格：{ContextBuilder._build_style_summary(group_profile.get('group_memory_style', {}))}"
            if group_profile.get("group_memory_style")
            else "",
            f"边界提醒：{boundaries}" if boundaries else "",
            f"人格叠加：{group_profile.get('persona_overlay', '')}".strip(),
        ]
        return "\n".join([line for line in lines if line])

    @staticmethod
    def _build_style_summary(style_profile: Dict) -> str:
        if not style_profile:
            return ""
        return " / ".join(
            [
                str(style_profile.get("interaction_tone", "") or "").strip(),
                str(style_profile.get("humor_style", "") or "").strip(),
                str(style_profile.get("sharpness_style", "") or "").strip(),
                str(style_profile.get("expressiveness_style", "") or "").strip(),
            ]
        ).strip(" /")