# -*- coding: utf-8 -*-
"""
群聊知识库插件，支持向量数据库检索
"""
import time
import uuid
from core.managers.command_manager import matcher
from models.events.message import GroupMessageEvent, PrivateMessageEvent
from core.managers.vectordb_manager import vectordb_manager
from core.utils.logger import ModuleLogger
from core.permission import Permission

logger = ModuleLogger("GroupKnowledgeBase")

__plugin_meta__ = {
    "name": "知识库",
    "description": "基于向量数据库的知识库，支持个人和群聊独立记忆",
    "usage": "/kb_add <问题> <答案> - 添加个人知识库\n/kb_add_group <问题> <答案> - 添加群聊知识库 (仅管理员)\n/kb_search <关键词> - 搜索知识库\n/kb_remove_person - 清除个人所有记忆\n/kb_remove_group - 清除群聊所有记忆 (仅管理员)"
}

@matcher.command("kb_add")
async def kb_add_person_command(event: GroupMessageEvent | PrivateMessageEvent, args: list[str]):
    """添加个人知识库条目"""
    if len(args) < 2:
        await event.reply("用法: /kb_add <问题> <答案>")
        return
        
    question = args[0]
    answer = " ".join(args[1:])
    user_id = event.user_id
    
    try:
        collection_name = f"knowledge_base_user_{user_id}"
        doc_id = str(uuid.uuid4())
        
        text_to_embed = f"问题: {question}\n答案: {answer}"
        metadata = {
            "user_id": user_id,
            "question": question,
            "answer": answer,
            "timestamp": int(time.time())
        }
        
        success = vectordb_manager.add_texts(
            collection_name=collection_name,
            texts=[text_to_embed],
            metadatas=[metadata],
            ids=[doc_id]
        )
        
        if success:
            await event.reply(f"个人知识库条目添加成功！\n问题: {question}")
        else:
            await event.reply("个人知识库条目添加失败，请查看日志。")
    except Exception as e:
        logger.error(f"添加个人知识库失败: {e}")
        await event.reply(f"添加失败: {str(e)}")

@matcher.command("kb_add_group", permission=Permission.ADMIN)
async def kb_add_group_command(event: GroupMessageEvent, args: list[str]):
    """添加群聊知识库条目"""
    if len(args) < 2:
        await event.reply("用法: /kb_add_group <问题> <答案>")
        return
        
    question = args[0]
    answer = " ".join(args[1:])
    group_id = event.group_id
    
    try:
        collection_name = f"knowledge_base_group_{group_id}"
        doc_id = str(uuid.uuid4())
        
        text_to_embed = f"问题: {question}\n答案: {answer}"
        metadata = {
            "group_id": group_id,
            "question": question,
            "answer": answer,
            "added_by": event.user_id,
            "timestamp": int(time.time())
        }
        
        success = vectordb_manager.add_texts(
            collection_name=collection_name,
            texts=[text_to_embed],
            metadatas=[metadata],
            ids=[doc_id]
        )
        
        if success:
            await event.reply(f"群聊知识库条目添加成功！\n问题: {question}")
        else:
            await event.reply("群聊知识库条目添加失败，请查看日志。")
    except Exception as e:
        logger.error(f"添加群聊知识库失败: {e}")
        await event.reply(f"添加失败: {str(e)}")

@matcher.command("kb_search")
async def kb_search_command(event: GroupMessageEvent | PrivateMessageEvent, args: list[str]):
    """搜索知识库条目（优先搜索个人，再搜索群聊）"""
    if not args:
        await event.reply("用法: /kb_search <关键词>")
        return
        
    query = " ".join(args)
    user_id = event.user_id
    group_id = getattr(event, 'group_id', None)
    
    try:
        reply_msg = f"为您找到以下相关知识：\n"
        found = False
        
        # 1. 搜索个人知识库
        person_collection = f"knowledge_base_user_{user_id}"
        person_results = vectordb_manager.query_texts(
            collection_name=person_collection,
            query_texts=[query],
            n_results=2
        )
        
        if person_results and person_results.get("documents") and person_results["documents"][0]:
            reply_msg += "\n【个人记忆】"
            for i, metadata in enumerate(person_results["metadatas"][0], 1):
                question = metadata.get("question", "")
                answer = metadata.get("answer", "")
                reply_msg += f"\n{i}. Q: {question}\n   A: {answer}"
            found = True
            
        # 2. 搜索群聊知识库
        if group_id:
            group_collection = f"knowledge_base_group_{group_id}"
            group_results = vectordb_manager.query_texts(
                collection_name=group_collection,
                query_texts=[query],
                n_results=2
            )
            
            if group_results and group_results.get("documents") and group_results["documents"][0]:
                reply_msg += "\n\n【群聊记忆】"
                for i, metadata in enumerate(group_results["metadatas"][0], 1):
                    question = metadata.get("question", "")
                    answer = metadata.get("answer", "")
                    reply_msg += f"\n{i}. Q: {question}\n   A: {answer}"
                found = True
                
        if not found:
            await event.reply("未找到相关的知识库条目。")
            return
            
        await event.reply(reply_msg)
    except Exception as e:
        logger.error(f"搜索知识库失败: {e}")
        await event.reply(f"搜索失败: {str(e)}")

@matcher.command("kb_remove_person")
async def kb_remove_person_command(event: GroupMessageEvent | PrivateMessageEvent):
    """清除个人所有记忆"""
    user_id = event.user_id
    collection_name = f"knowledge_base_user_{user_id}"
    
    try:
        # ChromaDB 不支持直接删除整个 collection 的所有数据，最简单的方法是删除 collection
        if vectordb_manager._client:
            try:
                vectordb_manager._client.delete_collection(collection_name)
                if collection_name in vectordb_manager._collections:
                    del vectordb_manager._collections[collection_name]
                await event.reply("已成功清除您的所有个人记忆。")
            except ValueError:
                await event.reply("您还没有任何个人记忆。")
        else:
            await event.reply("向量数据库未初始化。")
    except Exception as e:
        logger.error(f"清除个人记忆失败: {e}")
        await event.reply(f"清除失败: {str(e)}")

@matcher.command("kb_remove_group", permission=Permission.ADMIN)
async def kb_remove_group_command(event: GroupMessageEvent):
    """清除群聊所有记忆"""
    group_id = event.group_id
    collection_name = f"knowledge_base_group_{group_id}"
    
    try:
        if vectordb_manager._client:
            try:
                vectordb_manager._client.delete_collection(collection_name)
                if collection_name in vectordb_manager._collections:
                    del vectordb_manager._collections[collection_name]
                await event.reply("已成功清除本群的所有群聊记忆。")
            except ValueError:
                await event.reply("本群还没有任何群聊记忆。")
        else:
            await event.reply("向量数据库未初始化。")
    except Exception as e:
        logger.error(f"清除群聊记忆失败: {e}")
        await event.reply(f"清除失败: {str(e)}")