/**
 * 逐篇精读模式组件 - ChatGPT风格全屏聊天
 * 修复：参考文献格式、文档切换对话独立
 */

import React, { useMemo } from 'react';
import { FileText, BookOpen, ExternalLink } from 'lucide-react';
import { ChatContainer } from '@/shared/components/Chat';
import type { KnowledgeBase, Document } from '../../api/knowledgeBaseApi';
import { getAccessToken } from '../../../../framework/auth/api';

interface DeepReadModeProps {
  kbId: string;
  kbInfo: KnowledgeBase;
  selectedDocuments: Document[];
}

// 消息渲染参数类型
interface MessageRenderParams {
  id: string | number;
  message: {
    id: string | number;
    role: string;
    content: string;
    status?: string;
    [key: string]: unknown;
  };
  status: string;
}

// 自定义消息渲染器 - 解析并格式化参考文献
const renderMessageContent = (params: MessageRenderParams) => {
  // 从params中提取消息内容
  const textContent = params?.message?.content;
  
  // 空内容处理
  if (!textContent || typeof textContent !== 'string' || textContent.trim() === '') {
    return <div className="text-slate-400 italic">加载中...</div>;
  }

  // 处理参考文献格式
  let formattedContent = textContent;
  
  // 1. 移除HTML标签，转换为可读格式
  formattedContent = formattedContent.replace(
    /<span[^>]*id="citation-detail-(\d+)"[^>]*>\[(\d+)\]<\/span>\s*\*?\*?([^*\n]+)\*?\*?/g,
    (_, _num, num2, title) => `\n📄 [${num2}] ${title.trim()}`
  );
  
  // 2. 处理其他HTML span标签
  formattedContent = formattedContent.replace(/<span[^>]*>[^<]*<\/span>/g, '');
  
  // 3. 处理Markdown加粗中的下划线（文件名）
  formattedContent = formattedContent.replace(
    /\*\*([^*]+\.pdf)\*\*/gi,
    '📄 **$1**'
  );

  return (
    <div className="prose prose-sm max-w-none">
      {formattedContent.split('\n').map((line, idx) => {
        // 检测是否是参考文献行
        if (line.startsWith('📄')) {
          return (
            <div key={idx} className="flex items-start my-2 p-2 bg-blue-50 rounded-lg border border-blue-100">
              <BookOpen className="w-4 h-4 text-blue-500 mr-2 mt-0.5 flex-shrink-0" />
              <span className="text-sm text-slate-700">{line.replace('📄 ', '')}</span>
            </div>
          );
        }
        
        // 检测是否是"参考文献"标题
        if (line.includes('**参考文献**') || line.includes('📚 **参考文献**')) {
          return (
            <div key={idx} className="font-semibold text-slate-800 mt-4 mb-2 flex items-center">
              <BookOpen className="w-4 h-4 mr-2 text-blue-600" />
              参考文献
            </div>
          );
        }
        
        // 普通文本
        return line ? <p key={idx} className="mb-2 text-slate-700 leading-relaxed">{line}</p> : null;
      })}
    </div>
  );
};

export const DeepReadMode: React.FC<DeepReadModeProps> = ({ 
  kbId, 
  selectedDocuments 
}) => {
  // 使用useMemo确保文档切换时生成新的key
  const conversationKey = useMemo(() => {
    if (!selectedDocuments || selectedDocuments.length === 0) return '';
    return `kb-deepread-${kbId}-${selectedDocuments[0].id}-${Date.now()}`;
  }, [kbId, selectedDocuments]);

  const selectedDocIds = useMemo(() => 
    selectedDocuments.map(d => d.id), 
    [selectedDocuments]
  );

  if (!selectedDocuments || selectedDocuments.length === 0) {
    return (
      <div className="h-full flex items-center justify-center bg-slate-50">
        <div className="text-center">
          <div className="w-16 h-16 mx-auto bg-purple-50 rounded-full flex items-center justify-center mb-4">
            <FileText className="w-8 h-8 text-purple-400" />
          </div>
          <h3 className="text-lg font-semibold text-slate-700 mb-2">选择文档开始精读</h3>
          <p className="text-sm text-slate-500 max-w-xs">
            请在上方"逐篇精读"下拉框中选择一篇文档进行深度分析
          </p>
        </div>
      </div>
    );
  }

  const selectedDoc = selectedDocuments[0];

  return (
    <div className="h-full flex flex-col bg-white">
      {/* 当前文档提示 */}
      <div className="flex-shrink-0 px-4 py-2 bg-purple-50 border-b border-purple-100">
        <div className="flex items-center text-sm">
          <FileText className="w-4 h-4 text-purple-500 mr-2" />
          <span className="text-purple-700">当前精读：</span>
          <span className="font-medium text-purple-900 ml-1 truncate max-w-md" title={selectedDoc.filename}>
            {selectedDoc.filename}
          </span>
        </div>
      </div>
      
      {/* Chat组件 - 使用key强制重新渲染 */}
      <div className="flex-1 overflow-hidden" key={conversationKey}>
        <ChatContainer
          conversationType="pkb"
          conversationKey={conversationKey}
          defaultMessages={[{
            id: 'welcome',
            role: 'assistant',
            content: `您好！我已准备好深度解读文档《${selectedDoc.filename}》。\n\n我可以帮您：\n- 📖 逐段解读文献内容\n- 🎯 提炼核心观点和结论\n- 💡 分析研究方法和局限性\n\n请告诉我您想深入了解哪方面？`,
            status: 'success',
            timestamp: Date.now(),
          }]}
          providerConfig={{
            apiEndpoint: '/api/v1/pkb/chat/stream',
            requestFn: async (message: string) => {
              // 🔑 关键：传递 fullTextDocumentIds 而不是 documentIds
              // fullTextDocumentIds 会触发全文加载模式，AI可以看到完整文献
              // documentIds 只是过滤RAG检索结果，AI只能看到片段
              const token = getAccessToken();
              const response = await fetch('/api/v1/pkb/chat/stream', {
                method: 'POST',
                headers: { 
                  'Content-Type': 'application/json',
                  'Accept': 'text/event-stream',
                  ...(token ? { 'Authorization': `Bearer ${token}` } : {}),
                },
                body: JSON.stringify({
                  content: message,
                  modelType: 'qwen-long',
                  knowledgeBaseIds: [kbId],
                  fullTextDocumentIds: selectedDocIds, // ✅ 改用全文模式
                }),
              });
              
              if (!response.ok) {
                throw new Error(`API请求失败: ${response.status}`);
              }
              
              const reader = response.body?.getReader();
              const decoder = new TextDecoder();
              let fullContent = '';
              
              if (reader) {
                while (true) {
                  const { done, value } = await reader.read();
                  if (done) break;
                  
                  const chunk = decoder.decode(value);
                  const lines = chunk.split('\n');
                  
                  for (const line of lines) {
                    if (line.startsWith('data: ')) {
                      const data = line.slice(6);
                      if (data === '[DONE]') break;
                      
                      try {
                        const json = JSON.parse(data);
                        if (json.content) {
                          fullContent += json.content;
                        }
                      } catch (e) {
                        // 忽略解析错误
                      }
                    }
                  }
                }
              }
              
              return {
                content: fullContent,
                messageId: Date.now().toString(),
              };
            },
          }}
          customMessageRenderer={renderMessageContent}
        />
      </div>
    </div>
  );
};