style: refine model badge typography to match competitor

components/canvas/CanvasChatPanel.tsx

@@ -5,7 +5,7 @@ import { DefaultChatTransport } from "ai";
 import { useEffect, useRef, useState, useCallback, useMemo } from "react";
 import { createPortal } from "react-dom";
 import useSWR, { useSWRConfig } from "swr";
-import { Send, Loader2, ImagePlus, Paperclip, X, Plus, History, LayoutGrid, Maximize2, RefreshCw, Globe, Box, ArrowUp, Video, Sparkles, Check, ChevronDown, ChevronUp, AlertCircle, CheckCircle2, Brain, ThumbsUp, ThumbsDown } from "lucide-react";
+import { Send, Loader2, ImagePlus, Paperclip, X, Plus, History, LayoutGrid, Maximize2, RefreshCw, Globe, Box, ArrowUp, Video, Sparkles, Check, ChevronDown, ChevronUp, AlertCircle, CheckCircle2, Brain, ThumbsUp, ThumbsDown, Eye } from "lucide-react";
 import { Button } from "@/components/ui/button";
 import { Textarea } from "@/components/ui/textarea";
 import {
@@ -5492,8 +5492,9 @@ export function CanvasChatPanel({ chatId, initialMessages = [], onClose, onOpenF
                         </div>
                         <div className="mt-1 flex items-center gap-2 text-[#8f96a3]">
                           {showModelMeta ? (
-                            <span className="text-[12px] font-medium tracking-tight text-[#8d94a2]">
-                              ◈ {assistantModelName}
+                            <span className="inline-flex items-center gap-1.5 text-[11px] font-medium tracking-tight text-[#a2a9b5]">
+                              <Eye className="h-3.5 w-3.5 opacity-80" />
+                              <span>{assistantModelName}</span>
                             </span>
                           ) : null}
                           {showVoteActions ? (

components/message.tsx

@@ -1,6 +1,7 @@
 "use client";
 import type { UseChatHelpers } from "@ai-sdk/react";
 import equal from "fast-deep-equal";
+import { Eye } from "lucide-react";
 import { memo, useState } from "react";
 import type { Vote } from "@/lib/db/schema";
 import type { ChatMessage } from "@/lib/types";
@@ -174,18 +175,22 @@ function filterAgentRoutingNoise(text: string): string {
 }
 
 const IMAGE_DONE_SUMMARY = "已完成本次生成，如需微调可继续告诉我。";
-const MODEL_BADGE_REGEX =
-  /^\s*[◈◇◆🔹⬡✦•·]\s*[A-Za-z][A-Za-z0-9 .:+\-_/()]{2,}\s*$/im;
+const MODEL_BADGE_LINE_REGEX =
+  /^\s*[◈◇◆🔹⬡✦•·]\s*([A-Za-z][A-Za-z0-9 .:+\-_/()]{2,})\s*$/im;
+const MODEL_BADGE_LINE_GLOBAL_REGEX =
+  /^\s*[◈◇◆🔹⬡✦•·]\s*[A-Za-z][A-Za-z0-9 .:+\-_/()]{2,}\s*$/gim;
 
-function ensureImageModelBadge(text: string, fallbackModelName?: string): string {
-  if (!text) return text;
-  const normalized = String(text || "").trim();
-  if (!normalized) return normalized;
-  const modelName = String(fallbackModelName || "").trim();
-  if (!modelName) return normalized;
-  if (!/!\[[^\]]*\]\((https?:\/\/[^\s)]+)\)/i.test(normalized)) return normalized;
-  if (MODEL_BADGE_REGEX.test(normalized)) return normalized;
-  return `◈ ${modelName}\n\n${normalized}`;
+function extractModelBadgeName(text: string): string {
+  if (!text) return "";
+  const match = String(text || "").match(MODEL_BADGE_LINE_REGEX);
+  return match?.[1]?.trim() || "";
+}
+
+function stripModelBadgeLines(text: string): string {
+  return String(text || "")
+    .replace(MODEL_BADGE_LINE_GLOBAL_REGEX, "")
+    .replace(/\n{3,}/g, "\n\n")
+    .trim();
 }
 
 function appendImageDoneSummary(text: string): string {
@@ -342,19 +347,39 @@ const PurePreviewMessage = ({
                 }
                 
                 // 应用视频内容过滤
+                const routedFilteredText =
+                  message.role === "assistant"
+                    ? filterAgentRoutingNoise(filterVideoContent(part.text))
+                    : part.text;
+                const extractedModelName =
+                  message.role === "assistant"
+                    ? extractModelBadgeName(routedFilteredText)
+                    : "";
+                const contentWithoutBadge =
+                  message.role === "assistant"
+                    ? stripModelBadgeLines(routedFilteredText)
+                    : routedFilteredText;
+                const inferredFallbackModelName =
+                  message.role === "assistant" &&
+                  !extractedModelName &&
+                  extractImageUrlsFromText(contentWithoutBadge).length > 0
+                    ? String(fallbackImageModelName || "").trim()
+                    : "";
+                const displayModelName = extractedModelName || inferredFallbackModelName;
                 const filteredText =
                   message.role === "assistant"
-                    ? appendImageDoneSummary(
-                        ensureImageModelBadge(
-                          filterAgentRoutingNoise(filterVideoContent(part.text)),
-                          fallbackImageModelName
-                        )
-                      )
-                    : part.text;
+                    ? appendImageDoneSummary(contentWithoutBadge)
+                    : contentWithoutBadge;
                 const textParts = parseAnnotations(filteredText);
 
                 return (
                   <div key={key}>
+                    {message.role === "assistant" && displayModelName ? (
+                      <div className="mb-2 inline-flex items-center gap-1.5 text-[12px] font-medium leading-none text-[#a2a9b5]">
+                        <Eye className="h-3.5 w-3.5 opacity-80" />
+                        <span className="tracking-tight">{displayModelName}</span>
+                      </div>
+                    ) : null}
                     <MessageContent
                       className={cn({
                         "w-fit break-words rounded-2xl px-3 py-2 text-right text-white":