722 lines
17 KiB
Vue
722 lines
17 KiB
Vue
<script setup lang="ts">
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import { ref, reactive, nextTick, onMounted, watch } from 'vue'
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import { useRoute, useRouter } from 'vue-router'
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import { ElMessage } from 'element-plus'
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import MarkdownView from '@/components/MarkdownView.vue'
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import { useStreamChat } from '@/composables/useStreamChat'
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import { getCompare } from '@/api/modules/compare'
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import type { CompareTask, LoadedModel } from '@/types'
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const route = useRoute()
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const router = useRouter()
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const taskId = route.params.id as string
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/** 是否为 mock 直通模式（新建推理假数据进入，不走真实任务接口） */
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const isMock = taskId === 'mock'
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/** 当前对话使用的模型名 */
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const modelName = ref(route.query.model as string || '')
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const { message, loading, send, reset } = useStreamChat()
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interface ChatMessage {
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role: 'user' | 'assistant'
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content: string
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think?: string
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isThinking?: boolean
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isStreaming?: boolean
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done: boolean
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}
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const task = ref<CompareTask | null>(null)
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const messages = ref<ChatMessage[]>([])
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const inputQuestion = ref('')
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const systemPrompt = ref('')
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const temperature = ref(0.7)
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const top_p = ref(0.95)
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const maxTokens = ref(2048)
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const contentRef = ref<HTMLElement>()
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let activeAssistant: ChatMessage | null = null
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/** 设置面板抽屉 */
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const showSettings = ref(false)
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/** 获取任务信息，定位已启动的模型（mock 模式跳过） */
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async function loadTask() {
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if (isMock) return
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try {
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task.value = await getCompare(taskId)
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const models = parseLoadedModels(task.value)
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if (models[0]?.model_name) modelName.value = models[0].model_name
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} catch {
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// ignore
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}
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}
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function parseLoadedModels(t: CompareTask | null): LoadedModel[] {
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if (!t?.load_status) return []
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try {
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const ls = typeof t.load_status === 'string' ? JSON.parse(t.load_status) : t.load_status
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return ls.loaded_models || []
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} catch {
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return []
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}
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}
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async function handleSend() {
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const question = inputQuestion.value.trim()
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if (!question || loading.value) return
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// 推入用户消息
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messages.value.push({ role: 'user', content: question, done: true })
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// 推入占位助手消息
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const assistantMsg = reactive<ChatMessage>({
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role: 'assistant',
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content: '',
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think: '',
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isThinking: false,
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isStreaming: true,
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done: false,
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})
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messages.value.push(assistantMsg)
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inputQuestion.value = ''
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await nextTick()
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resetInputHeight()
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scrollToBottom()
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// mock 模式：直接用假数据逐字填充
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if (isMock) {
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await mockReply(assistantMsg, question)
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return
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}
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// 真实模式：获取已启动模型的端口/路径
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const models = parseLoadedModels(task.value)
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const target = models[0]
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if (!target) {
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ElMessage.error('未找到已启动的模型')
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assistantMsg.content = '未找到已启动的模型，请先返回列表加载模型'
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assistantMsg.done = true
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assistantMsg.isStreaming = false
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return
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}
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// 流式状态变化时只同步当前回复，避免固定定时器空转。
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activeAssistant = assistantMsg
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await send({
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port: target.port,
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model_name: target.model_name,
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model_path: '',
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system_prompt: systemPrompt.value,
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user_question: question,
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temperature: temperature.value,
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top_p: top_p.value,
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max_tokens: maxTokens.value,
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})
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// 完成后同步最终内容
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assistantMsg.content = message.value.displayContent || message.value.error || '(无回复)'
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assistantMsg.think = message.value.thinkContent
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assistantMsg.isThinking = false
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assistantMsg.isStreaming = false
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assistantMsg.done = true
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activeAssistant = null
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reset()
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await nextTick()
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scrollToBottom()
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}
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/**
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* Mock 模式：生成假回答并逐字填入消息（模拟流式效果）
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*/
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async function mockReply(assistantMsg: ChatMessage, question: string) {
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const answer =
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`你好！我是 **${modelName.value || '示例模型'}**（mock 演示）。\n\n` +
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`你刚才问的是：\n\n> ${question}\n\n` +
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`这是一段模拟回复，用于演示对话界面。接入真实模型后，这里会展示模型的真实推理输出。\n\n` +
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`## 说明\n- 当前为前端 mock 环境\n- 回复内容由本地生成\n- 流式打字效果为前端模拟`
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// 逐字填充，模拟流式
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for (const ch of answer) {
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assistantMsg.content += ch
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await nextTick()
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scrollToBottom()
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// 每 3 个字符暂停一下，控制速度
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if (assistantMsg.content.length % 3 === 0) {
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await new Promise((r) => setTimeout(r, 16))
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}
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}
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assistantMsg.isStreaming = false
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assistantMsg.done = true
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await nextTick()
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scrollToBottom()
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}
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watch(
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() => [
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message.value.displayContent,
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message.value.thinkContent,
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message.value.isThinking,
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message.value.done,
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] as const,
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async ([content, think, isThinking, done]) => {
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if (!activeAssistant) return
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activeAssistant.content = content
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activeAssistant.think = think
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activeAssistant.isThinking = isThinking
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activeAssistant.isStreaming = !done
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await nextTick()
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scrollToBottom()
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},
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{ flush: 'post' },
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)
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function scrollToBottom() {
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if (contentRef.value) {
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contentRef.value.scrollTop = contentRef.value.scrollHeight
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}
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}
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function handleNewChat() {
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activeAssistant = null
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messages.value = []
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reset()
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}
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/** 输入框自适应高度 */
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function autoResize(e: Event) {
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const el = e.target as HTMLTextAreaElement
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el.style.height = 'auto'
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el.style.height = Math.min(el.scrollHeight, 120) + 'px'
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}
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/** 重置输入框高度 */
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function resetInputHeight() {
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const el = document.querySelector('.input-box') as HTMLTextAreaElement
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if (el) el.style.height = 'auto'
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}
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onMounted(loadTask)
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</script>
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<template>
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<div class="chat-wrap">
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<!-- 顶部栏 -->
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<header class="chat-header">
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<div class="header-left">
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<div class="header-title">
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<span class="title-text">{{ modelName || '模型对话' }}</span>
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<span v-if="isMock" class="mock-badge">mock</span>
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</div>
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</div>
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<button class="header-btn" title="设置" @click="showSettings = true">
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<i class="fa fa-sliders" />
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</button>
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</header>
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<!-- 消息列表 -->
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<div ref="contentRef" class="chat-body">
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<div class="chat-body-inner">
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<div v-if="messages.length === 0" class="empty-hint">
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<div class="empty-logo">
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<i class="fa fa-cube" />
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</div>
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<h2>有什么我可以帮你的吗？</h2>
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<p>开始与 {{ modelName || '模型' }} 对话</p>
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</div>
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<div
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v-for="(msg, idx) in messages"
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:key="idx"
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class="msg-row"
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:class="msg.role"
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>
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<!-- 头像 -->
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<div v-if="msg.role === 'assistant'" class="avatar assistant">
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<i class="fa fa-robot" />
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</div>
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<!-- 消息内容 -->
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<div class="bubble-wrap">
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<!-- 思考过程（可折叠） -->
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<el-collapse v-if="msg.think" class="think-collapse">
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<el-collapse-item title="思考过程" name="think">
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<div class="think-content">{{ msg.think }}</div>
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</el-collapse-item>
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</el-collapse>
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<div v-if="msg.role === 'user'" class="bubble user-bubble">
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{{ msg.content }}
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</div>
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<div v-else-if="msg.done" class="bubble ai-bubble markdown">
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<MarkdownView :content="msg.content" />
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</div>
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<div v-else class="bubble ai-bubble streaming">
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<span>{{ msg.content || (msg.isThinking ? '思考中...' : '生成中') }}</span>
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<span class="typing-cursor" />
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</div>
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</div>
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</div>
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</div>
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</div>
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<!-- 输入栏 -->
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<footer class="chat-input-container">
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<div class="chat-input-inner">
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<button class="clear-btn" title="清空对话" @click="handleNewChat">
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<i class="fa fa-eraser" />
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</button>
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<div class="input-wrapper">
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<textarea
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v-model="inputQuestion"
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class="input-box"
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rows="1"
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:disabled="loading"
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placeholder="给模型发送消息..."
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@keydown.enter.exact.prevent="handleSend"
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@input="autoResize"
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/>
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<button
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class="send-btn"
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:class="{ active: inputQuestion.trim() && !loading }"
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:disabled="!inputQuestion.trim() || loading"
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@click="handleSend"
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>
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<i class="fa fa-arrow-up" />
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</button>
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</div>
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</div>
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<div class="footer-hint">内容由 AI 生成，请仔细甄别。</div>
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</footer>
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<!-- 设置抽屉（系统提示词等） -->
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<el-drawer v-model="showSettings" title="对话设置" size="360px">
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<el-form label-position="top">
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<el-form-item label="系统提示词">
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<el-input
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v-model="systemPrompt"
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type="textarea"
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:rows="6"
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placeholder="设置模型角色/约束（可选）"
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resize="none"
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/>
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</el-form-item>
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<el-form-item label="Temperature (温度)">
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<el-slider v-model="temperature" :min="0" :max="2" :step="0.1" show-input />
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</el-form-item>
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<el-form-item label="Top P (核心采样)">
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<el-slider v-model="top_p" :min="0" :max="1" :step="0.05" show-input />
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</el-form-item>
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<el-form-item label="Max Tokens (最大生成长度)">
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<el-slider v-model="maxTokens" :min="128" :max="8192" :step="128" show-input />
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</el-form-item>
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<el-form-item>
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<el-button type="danger" plain @click="handleNewChat" style="width: 100%; margin-top: 20px;">
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<i class="fa fa-trash-o" style="margin-right: 4px" />清空当前对话
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</el-button>
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</el-form-item>
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</el-form>
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</el-drawer>
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</div>
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</template>
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<style scoped lang="scss">
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.chat-wrap {
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height: calc(100vh - 80px);
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box-sizing: border-box;
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display: flex;
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flex-direction: column;
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background: #ffffff;
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border-radius: 12px;
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box-shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.05), 0 2px 4px -1px rgba(0, 0, 0, 0.03);
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overflow: hidden;
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border: 1px solid #f3f4f6;
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}
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/* ============ 顶部栏 ============ */
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.chat-header {
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flex-shrink: 0;
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height: 60px;
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display: flex;
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align-items: center;
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justify-content: space-between;
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padding: 0 20px;
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background: #ffffff;
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border-bottom: 1px solid #f3f4f6;
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.header-left {
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display: flex;
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align-items: center;
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gap: 12px;
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}
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.header-title {
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display: flex;
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align-items: center;
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gap: 8px;
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font-size: 16px;
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font-weight: 600;
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color: #111827;
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.title-text {
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max-width: 300px;
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overflow: hidden;
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text-overflow: ellipsis;
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white-space: nowrap;
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}
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.mock-badge {
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padding: 2px 6px;
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font-size: 11px;
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font-weight: 600;
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color: #b45309;
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background: #fef3c7;
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border-radius: 4px;
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text-transform: uppercase;
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}
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}
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.header-btn {
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width: 36px;
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height: 36px;
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border: none;
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background: transparent;
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border-radius: 8px;
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font-size: 18px;
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color: #6b7280;
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cursor: pointer;
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display: flex;
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align-items: center;
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justify-content: center;
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transition: all 0.2s;
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&:hover {
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background: #f3f4f6;
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color: #111827;
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}
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}
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}
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/* ============ 消息列表 ============ */
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.chat-body {
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flex: 1;
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overflow-y: auto;
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padding: 24px 0;
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scroll-behavior: smooth;
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/* 隐藏滚动条但保留功能 */
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&::-webkit-scrollbar {
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width: 6px;
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}
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&::-webkit-scrollbar-thumb {
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background: #e5e7eb;
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border-radius: 3px;
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}
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&::-webkit-scrollbar-track {
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background: transparent;
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}
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}
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.chat-body-inner {
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max-width: 800px;
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margin: 0 auto;
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padding: 0 20px;
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display: flex;
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flex-direction: column;
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gap: 32px;
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}
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.empty-hint {
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margin-top: 10vh;
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display: flex;
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flex-direction: column;
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align-items: center;
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justify-content: center;
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color: #6b7280;
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.empty-logo {
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width: 64px;
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height: 64px;
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border-radius: 16px;
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background: #f3f4f6;
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display: flex;
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align-items: center;
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justify-content: center;
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margin-bottom: 24px;
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i {
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font-size: 32px;
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color: #9ca3af;
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}
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}
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h2 {
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font-size: 24px;
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font-weight: 600;
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color: #111827;
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margin: 0 0 8px 0;
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}
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p {
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margin: 0;
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font-size: 15px;
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}
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}
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.msg-row {
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display: flex;
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gap: 16px;
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align-items: flex-start;
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width: 100%;
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/* 用户消息：靠右排列 */
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&.user {
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flex-direction: row-reverse;
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}
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/* AI 消息：靠左排列 */
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&.assistant {
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flex-direction: row;
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}
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}
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/* 头像 */
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.avatar {
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flex-shrink: 0;
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width: 32px;
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height: 32px;
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border-radius: 50%;
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display: flex;
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align-items: center;
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justify-content: center;
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color: #fff;
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font-size: 16px;
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&.assistant {
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background: #111827;
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}
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}
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/* 气泡容器 */
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.bubble-wrap {
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max-width: 85%;
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min-width: 0;
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}
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/* 气泡 */
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.bubble {
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font-size: 15px;
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line-height: 1.6;
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word-break: break-word;
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white-space: pre-wrap;
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}
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.user-bubble {
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background: #f3f4f6;
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color: #111827;
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padding: 12px 20px;
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border-radius: 20px;
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border-top-right-radius: 4px;
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}
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.ai-bubble {
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color: #111827;
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padding: 4px 0;
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&.markdown {
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white-space: normal;
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:deep(.markdown-view p:last-child) {
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margin-bottom: 0;
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}
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:deep(pre) {
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border-radius: 8px;
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background: #f9fafb !important;
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border: 1px solid #e5e7eb;
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margin: 12px 0;
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||
}
|
||
|
||
:deep(code) {
|
||
background: #f3f4f6;
|
||
padding: 2px 6px;
|
||
border-radius: 4px;
|
||
font-size: 0.9em;
|
||
}
|
||
}
|
||
}
|
||
|
||
/* 思考过程折叠 */
|
||
.think-collapse {
|
||
margin-bottom: 12px;
|
||
max-width: 100%;
|
||
border: 1px solid #e5e7eb;
|
||
border-radius: 8px;
|
||
background: #f9fafb;
|
||
overflow: hidden;
|
||
|
||
:deep(.el-collapse-item__header) {
|
||
padding: 0 16px;
|
||
font-size: 13px;
|
||
font-weight: 500;
|
||
color: #6b7280;
|
||
height: 36px;
|
||
background: transparent;
|
||
border-bottom: none;
|
||
}
|
||
|
||
:deep(.el-collapse-item__wrap) {
|
||
border-bottom: none;
|
||
background: transparent;
|
||
}
|
||
|
||
.think-content {
|
||
padding: 0 16px 12px;
|
||
font-size: 13px;
|
||
color: #4b5563;
|
||
line-height: 1.6;
|
||
white-space: pre-wrap;
|
||
border-top: 1px dashed #e5e7eb;
|
||
margin-top: 4px;
|
||
padding-top: 12px;
|
||
}
|
||
}
|
||
|
||
/* 流式打字光标 */
|
||
.streaming .typing-cursor {
|
||
display: inline-block;
|
||
width: 4px;
|
||
height: 16px;
|
||
background: #111827;
|
||
border-radius: 2px;
|
||
margin-left: 4px;
|
||
vertical-align: middle;
|
||
animation: blink 1s steps(1) infinite;
|
||
}
|
||
|
||
@keyframes blink {
|
||
0%, 50% { opacity: 1; }
|
||
51%, 100% { opacity: 0; }
|
||
}
|
||
|
||
/* ============ 输入栏 ============ */
|
||
.chat-input-container {
|
||
flex-shrink: 0;
|
||
padding: 16px 20px 24px;
|
||
background: linear-gradient(180deg, rgba(255, 255, 255, 0) 0%, #ffffff 20%);
|
||
display: flex;
|
||
flex-direction: column;
|
||
align-items: center;
|
||
}
|
||
|
||
.chat-input-inner {
|
||
width: 100%;
|
||
max-width: 800px;
|
||
display: flex;
|
||
align-items: flex-end;
|
||
gap: 12px;
|
||
}
|
||
|
||
.clear-btn {
|
||
flex-shrink: 0;
|
||
width: 40px;
|
||
height: 40px;
|
||
margin-bottom: 4px;
|
||
border: 1px solid #e5e7eb;
|
||
background: #ffffff;
|
||
border-radius: 50%;
|
||
font-size: 16px;
|
||
color: #6b7280;
|
||
cursor: pointer;
|
||
display: flex;
|
||
align-items: center;
|
||
justify-content: center;
|
||
transition: all 0.2s;
|
||
box-shadow: 0 1px 2px rgba(0, 0, 0, 0.05);
|
||
|
||
&:hover {
|
||
background: #f9fafb;
|
||
color: #ef4444;
|
||
border-color: #fca5a5;
|
||
}
|
||
}
|
||
|
||
.input-wrapper {
|
||
flex: 1;
|
||
position: relative;
|
||
background: #f4f4f5;
|
||
border-radius: 24px;
|
||
padding: 8px 16px;
|
||
display: flex;
|
||
align-items: flex-end;
|
||
transition: all 0.2s;
|
||
border: 1px solid transparent;
|
||
|
||
&:focus-within {
|
||
background: #ffffff;
|
||
border-color: #d1d5db;
|
||
box-shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.05), 0 2px 4px -1px rgba(0, 0, 0, 0.03);
|
||
}
|
||
}
|
||
|
||
.input-box {
|
||
flex: 1;
|
||
max-height: 200px;
|
||
padding: 4px 44px 4px 0;
|
||
border: none;
|
||
background: transparent;
|
||
font-size: 15px;
|
||
line-height: 1.5;
|
||
color: #111827;
|
||
resize: none;
|
||
outline: none;
|
||
font-family: inherit;
|
||
|
||
&::placeholder {
|
||
color: #9ca3af;
|
||
}
|
||
}
|
||
|
||
.send-btn {
|
||
position: absolute;
|
||
right: 12px;
|
||
bottom: 8px;
|
||
width: 32px;
|
||
height: 32px;
|
||
border: none;
|
||
border-radius: 50%;
|
||
background: #e5e7eb;
|
||
color: #ffffff;
|
||
font-size: 14px;
|
||
cursor: not-allowed;
|
||
display: flex;
|
||
align-items: center;
|
||
justify-content: center;
|
||
transition: all 0.2s;
|
||
|
||
&.active {
|
||
background: #111827;
|
||
cursor: pointer;
|
||
|
||
&:hover {
|
||
background: #374151;
|
||
transform: translateY(-1px);
|
||
}
|
||
|
||
&:active {
|
||
transform: translateY(1px);
|
||
}
|
||
}
|
||
}
|
||
|
||
.footer-hint {
|
||
margin-top: 12px;
|
||
font-size: 12px;
|
||
color: #9ca3af;
|
||
}
|
||
</style>
|