refactor: simplify thinking process UI and reduce noise

- Remove redundant status steps (understanding, preparing, generating)
  from SSE stream — only emit retrieved docs and reasoning content
- ThinkingProcess: only show when there's actual reasoning or docs
- Collapse header shows concise state: thinking count or doc count
- Clean up unused icon imports

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

backend/src/rag/chains.py

@@ -133,17 +133,15 @@ class RAGChain:
         """流式调用（返回答案流和文档，包含思考过程）"""
         import time
 
-        # 0. 思考阶段开始
         start_time = time.time()
-        yield {"type": "thinking", "stage": "understanding", "message": "正在理解问题..."}
 
         # 1. 检索文档
-        yield {"type": "thinking", "stage": "retrieving", "message": "正在检索相关知识..."}
         retrieval_start = time.time()
         docs = await self.retriever.ainvoke(question)
         retrieval_time = time.time() - retrieval_start
 
-        # 发送检索结果 — 包含文档标题和摘要
+        # 发送检索结果（只在有文档时）
+        if docs:
             doc_details = []
             for i, doc in enumerate(docs[:5]):
                 metadata = doc.metadata if hasattr(doc, 'metadata') else {}
@@ -162,8 +160,7 @@ class RAGChain:
 
         context = "\n\n".join(doc.page_content for doc in docs)
 
-        # 2. 构建prompt
-        yield {"type": "thinking", "stage": "generating", "message": f"基于 {len(docs)} 篇文档生成回答..."}
+        # 2. 构建prompt并流式生成
         prompt_value = await self.prompt.ainvoke({"context": context, "question": question})
         messages = prompt_value.to_messages()
 

backend/src/rag/conversation_chains.py

@@ -85,16 +85,8 @@ class ConversationChain:
         """流式调用（包含思考过程，捕获推理模型的真实推理内容）"""
         import time
 
-        # 思考阶段
         start_time = time.time()
-        yield {"type": "thinking", "stage": "understanding", "message": "正在理解问题..."}
-
-        # 准备历史
         history_messages = self._format_history(chat_history or [])
-        history_count = len([m for m in (chat_history or []) if m["role"] == "user"])
-        yield {"type": "thinking", "stage": "preparing", "message": f"加载对话上下文（{history_count} 轮历史）..." if history_count > 0 else "准备生成回答..."}
-
-        yield {"type": "thinking", "stage": "generating", "message": "正在生成回答..."}
 
         # 直接使用原始 OpenAI SDK 捕获推理内容
         prompt_value = await self.prompt.ainvoke({

web/src/components/chat/message-item.tsx

@@ -1,7 +1,7 @@
 "use client";
 
 import { ChatMessage, ThinkingStep } from "@/types";
-import { User, Bot, Copy, Edit, RotateCcw, ThumbsUp, ThumbsDown, Loader2, CheckCircle2, FileSearch, Brain, Sparkles } from "lucide-react";
+import { User, Bot, Copy, Edit, RotateCcw, ThumbsUp, ThumbsDown, Loader2, Brain } from "lucide-react";
 import { cn } from "@/lib/utils";
 import ReactMarkdown from "react-markdown";
 import remarkGfm from "remark-gfm";
@@ -23,30 +23,29 @@ const ThinkingProcess = ({ thinking, isStreaming }: { thinking: ThinkingStep[];
   const [expanded, setExpanded] = useState(false);
   if (!thinking || thinking.length === 0) return null;
 
-  // 分离状态步骤和推理内容
-  const statusSteps = thinking.filter(s => s.stage !== 'reasoning');
+  // 只提取有实际内容的步骤：推理内容和检索文档
   const reasoningSteps = thinking.filter(s => s.stage === 'reasoning');
+  const retrievedStep = thinking.find(s => s.stage === 'retrieved');
   const hasReasoning = reasoningSteps.length > 0;
+  const hasDocs = retrievedStep?.details && retrievedStep.details.length > 0;
+
+  // 没有推理内容也没有文档详情时不显示
+  if (!hasReasoning && !hasDocs && !isStreaming) return null;
 
   // 合并推理文本
   const reasoningText = reasoningSteps.map(s => s.message).join('');
 
-  // 汇总信息
-  const retrievedStep = statusSteps.find(s => s.stage === 'retrieved');
-  const totalTime = statusSteps.reduce((sum, s) => sum + (s.time || 0), 0);
-
-  // 流式时显示最后状态
-  const lastStatusStep = statusSteps[statusSteps.length - 1];
+  // 流式时是否正在推理
   const isReasoningNow = isStreaming && thinking[thinking.length - 1]?.stage === 'reasoning';
 
   // 折叠标题
   const collapsedTitle = isStreaming
-    ? isReasoningNow
-      ? '深度思考中...'
-      : lastStatusStep?.message || '思考中...'
+    ? isReasoningNow ? '思考中...' : '检索中...'
     : hasReasoning
       ? `思考过程 (${reasoningText.length} 字)`
-      : `思考过程${totalTime > 0 ? ` (${totalTime.toFixed(1)}s)` : ''}`;
+      : retrievedStep
+        ? `检索到 ${retrievedStep.doc_count} 篇相关文档`
+        : '思考过程';
 
   return (
     <div className="mb-2.5">
@@ -62,37 +61,14 @@ const ThinkingProcess = ({ thinking, isStreaming }: { thinking: ThinkingStep[];
         </svg>
         <Brain className={cn("h-3 w-3", isReasoningNow && "animate-pulse text-primary")} />
         <span>{collapsedTitle}</span>
-        {retrievedStep?.doc_count != null && (
-          <span className="opacity-60 ml-1">· {retrievedStep.doc_count} 篇文档</span>
-        )}
-        {totalTime > 0 && !isStreaming && (
-          <span className="opacity-50 ml-1">· {totalTime.toFixed(1)}s</span>
-        )}
       </button>
       {expanded && (
         <div className="mt-1.5 ml-4 space-y-2 text-xs border-l-2 border-border pl-3">
-          {/* 状态步骤 */}
-          {statusSteps.map((step, index) => (
-            <div key={`s-${index}`} className="flex items-center gap-1.5 text-muted-foreground">
-              {step.stage === 'retrieving' ? (
-                <FileSearch className="h-3 w-3" />
-              ) : step.stage === 'retrieved' ? (
-                <CheckCircle2 className="h-3 w-3 text-green-500" />
-              ) : step.stage === 'generating' ? (
-                <Sparkles className="h-3 w-3" />
-              ) : (
-                <div className="h-1.5 w-1.5 rounded-full bg-current" />
-              )}
-              <span>{step.message}</span>
-              {step.time != null && <span className="opacity-50">{step.time.toFixed(1)}s</span>}
-            </div>
-          ))}
-
           {/* 检索到的文档详情 */}
-          {retrievedStep?.details && retrievedStep.details.length > 0 && (
-            <div className="mt-1 space-y-1">
+          {hasDocs && (
+            <div className="space-y-1">
               <div className="text-muted-foreground font-medium">参考文档：</div>
-              {retrievedStep.details.map((detail: string, i: number) => (
+              {retrievedStep?.details?.map((detail: string, i: number) => (
                 <div key={i} className="text-muted-foreground/80 pl-2 border-l border-border/50">
                   {detail}
                 </div>
@@ -103,9 +79,6 @@ const ThinkingProcess = ({ thinking, isStreaming }: { thinking: ThinkingStep[];
           {/* 推理内容 */}
           {hasReasoning && (
             <div className="mt-1">
-              <div className="text-muted-foreground font-medium mb-1">
-                {isReasoningNow ? '推理进行中...' : '推理过程：'}
-              </div>
               <div className="text-foreground/80 whitespace-pre-wrap leading-relaxed bg-muted/30 rounded-lg p-2.5 max-h-80 overflow-y-auto">
                 {reasoningText}
               </div>