refactor: 静态变量提到对话外 + System Prompt 模板展开可视化
- 新建 SessionBar：会话变量独立于消息气泡，显示在对话顶部
- 重写 SystemPromptView：解析 {{var}} 占位符并内联展示模板→变量映射
- 重构 MessageList：提取 static_var 到 varMap，过滤后传入气泡
- 更新 SegmentRenderer + MessageBubble：传递 varMap 到 SystemPromptView
- 更新所有 Demo：static_var 从 user 消息迁移到 system 消息，使用真实会话配置（current_date、language、knowledge_cutoff）
- 更新导出逻辑：system 消息中收集 static_var 并在模板中展开 {{var}}
- 更新测试：新增模板展开用例，18 tests pass
This commit is contained in:
carry
@@ -233,8 +233,62 @@ describe('exportToOpenAIFormat', () => {
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],
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}
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const { messages } = exportToOpenAIFormat(env)
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expect(messages[0].content).toContain('小明')
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expect(messages[0].content).toContain('says hello')
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// static_var 被提取到 system 消息中作为配置行
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expect(messages[0].role).toBe('system')
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expect(messages[0].content).toContain('user_name = 小明')
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// 用户消息中 static_var 展开为值
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expect(messages[1].role).toBe('user')
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expect(messages[1].content).toContain('小明')
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expect(messages[1].content).toContain('says hello')
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})
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it('expands static_vars in system_prompt template via {{var}} substitution', () => {
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const env: PromptEnvelope = {
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version: '1.0',
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model: 'gpt-4-turbo',
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messages: [
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{
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id: '0',
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role: 'system',
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segments: [
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{
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kind: 'static_var',
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name: 'current_date',
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value: '2026年6月7日',
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},
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{
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kind: 'static_var',
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name: 'language',
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value: '中文',
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},
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{
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kind: 'system_prompt',
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content: '今天是 {{current_date}}。请用 {{language}} 回复。',
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collapsed: true,
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},
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],
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timestamp: 0,
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},
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{
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id: '1',
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role: 'user',
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segments: [{ kind: 'text', content: '你好' }],
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timestamp: 0,
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},
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],
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}
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const result = exportToOpenAIFormat(env)
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expect(result.messages).toHaveLength(2)
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const sysMsg = result.messages[0]
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expect(sysMsg.role).toBe('system')
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// {{var}} 模板应被展开为实际值
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expect(sysMsg.content).toContain('current_date = 2026年6月7日')
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expect(sysMsg.content).toContain('language = 中文')
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expect(sysMsg.content).toContain('今天是 2026年6月7日。')
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expect(sysMsg.content).toContain('请用 中文 回复。')
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// 不应残留原始模板占位符
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expect(sysMsg.content).not.toContain('{{current_date}}')
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expect(sysMsg.content).not.toContain('{{language}}')
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})
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it('emits tool_call_request as assistant message with tool_calls', () => {
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@@ -10,9 +10,11 @@ const roleConfig = {
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interface MessageBubbleProps {
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message: Message
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/** 会话级变量映射表，用于 system_prompt 中的 {{var}} 模板展开展示 */
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varMap?: Record<string, string>
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}
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export default function MessageBubble({ message }: MessageBubbleProps) {
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export default function MessageBubble({ message, varMap = {} }: MessageBubbleProps) {
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const cfg = roleConfig[message.role]
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const Icon = cfg.icon
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const isUser = message.role === 'user'
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@@ -33,7 +35,7 @@ export default function MessageBubble({ message }: MessageBubbleProps) {
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{/* Segments */}
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<div className="space-y-0.5">
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{message.segments.map((seg, i) => (
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<SegmentRenderer key={i} segment={seg} />
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<SegmentRenderer key={i} segment={seg} varMap={varMap} />
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))}
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</div>
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@@ -1,12 +1,53 @@
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import type { Message } from '../types/protocol'
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import { useMemo } from 'react'
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import type { Message, StaticVarSegment } from '../types/protocol'
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import SessionBar from './SessionBar'
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import MessageBubble from './MessageBubble'
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interface MessageListProps {
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messages: Message[]
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}
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/**
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* 从所有 system 消息中提取 static_var 片段，
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* 构建会话变量映射表并从消息体中移除这些片段。
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*/
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function extractSessionVars(messages: Message[]): {
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variables: StaticVarSegment[]
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varMap: Record<string, string>
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cleanedMessages: Message[]
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} {
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const variables: StaticVarSegment[] = []
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const varMap: Record<string, string> = {}
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const cleanedMessages = messages.map((msg) => {
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const staticVars: StaticVarSegment[] = []
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const remaining = msg.segments.filter((seg) => {
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if (seg.kind === 'static_var') {
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staticVars.push(seg)
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return false // 从消息体中移除
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}
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return true
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})
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// 收集变量
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for (const v of staticVars) {
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variables.push(v)
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varMap[v.name] = v.value
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}
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return { ...msg, segments: remaining }
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})
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return { variables, varMap, cleanedMessages }
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}
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export default function MessageList({ messages }: MessageListProps) {
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if (messages.length === 0) {
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const { variables, varMap, cleanedMessages } = useMemo(
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() => extractSessionVars(messages),
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[messages]
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)
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if (cleanedMessages.length === 0) {
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return (
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<div className="flex-1 flex items-center justify-center text-gray-300 text-sm">
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选择一个 Demo 场景开始
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@@ -15,10 +56,16 @@ export default function MessageList({ messages }: MessageListProps) {
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}
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return (
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<div className="flex-1 flex flex-col min-h-0">
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{/* 会话变量横栏 —— 在对话气泡之外 */}
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<SessionBar variables={variables} />
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{/* 消息列表 */}
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<div className="flex-1 overflow-y-auto px-4 py-4 space-y-1">
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{messages.map((msg) => (
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<MessageBubble key={msg.id} message={msg} />
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{cleanedMessages.map((msg) => (
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<MessageBubble key={msg.id} message={msg} varMap={varMap} />
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))}
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</div>
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</div>
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)
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}
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@@ -1,6 +1,5 @@
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import type { Segment } from '../types/protocol'
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import TextSegmentView from './segments/TextSegmentView'
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import StaticVarBadge from './segments/StaticVarBadge'
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import SystemPromptView from './segments/SystemPromptView'
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import MemoryView from './segments/MemoryView'
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import SkillsView from './segments/SkillsView'
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@@ -13,19 +12,24 @@ import MediaView from './segments/MediaView'
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interface SegmentRendererProps {
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segment: Segment
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/** 会话级变量映射表，传递给 SystemPromptView 用于展示 {{var}} 模板渲染结果 */
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varMap?: Record<string, string>
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}
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/**
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* Route a Segment to its correct view component based on `kind`.
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* static_var 不在此处渲染 —— 已被 MessageList 提取到 SessionBar 中。
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*/
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export default function SegmentRenderer({ segment }: SegmentRendererProps) {
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export default function SegmentRenderer({ segment, varMap = {} }: SegmentRendererProps) {
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switch (segment.kind) {
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case 'text':
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return <TextSegmentView segment={segment} />
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case 'static_var':
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return <StaticVarBadge segment={segment} />
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// static_var 已由 MessageList 提取到对话外部的 SessionBar 中，
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// 不作为气泡内元素渲染。若此处仍有残留，静默跳过。
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return null
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case 'system_prompt':
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return <SystemPromptView segment={segment} />
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return <SystemPromptView segment={segment} varMap={varMap} />
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case 'memory':
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return <MemoryView segment={segment} />
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case 'skills':
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@@ -0,0 +1,39 @@
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import type { StaticVarSegment } from '../types/protocol'
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import { Sliders } from 'lucide-react'
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interface SessionBarProps {
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variables: StaticVarSegment[]
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}
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/**
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* 对话区顶部的会话变量横栏 —— 会话级别的配置变量，独立于任何消息。
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* 这些变量在对话开始时被注入到 System Prompt 模板中。
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*/
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export default function SessionBar({ variables }: SessionBarProps) {
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if (variables.length === 0) return null
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return (
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<div className="shrink-0 border-b border-gray-200 bg-gradient-to-r from-blue-50/60 to-white px-4 py-2">
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<div className="flex items-center gap-2 flex-wrap">
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{/* 标题 */}
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<span className="inline-flex items-center gap-1 text-[10px] font-semibold text-blue-400 uppercase tracking-wider mr-1">
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<Sliders size={12} />
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会话变量
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</span>
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{/* 变量列表 */}
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{variables.map((v, i) => (
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<span
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key={i}
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className="inline-flex items-center gap-1 px-2 py-0.5 rounded-md bg-white border border-blue-200 text-[11px] font-mono shadow-sm"
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title={v.description}
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>
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<span className="text-blue-400">{'{{'}{v.name}{'}}'}</span>
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<span className="text-gray-300">→</span>
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<span className="text-blue-700 font-medium">{v.value}</span>
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</span>
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))}
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</div>
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</div>
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)
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}
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@@ -1,13 +1,19 @@
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import type { StaticVarSegment } from '../../types/protocol'
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import { Variable } from 'lucide-react'
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import { Sliders } from 'lucide-react'
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/**
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* 会话级静态变量 —— 这些变量在对话开始时被注入到 System Prompt 模板中展开。
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* 例如：{{current_date}} → 2026年6月7日，{{language}} → 中文
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*
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* 视觉上呈现为紧凑的配置项卡片，一行展示所有会话级变量。
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*/
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export default function StaticVarBadge({ segment }: { segment: StaticVarSegment }) {
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return (
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<span className="inline-flex items-center gap-1 px-2 py-1 rounded-full bg-blue-100 text-blue-700 text-xs font-mono border border-blue-200">
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<Variable size={12} />
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<span className="inline-flex items-center gap-1 px-2 py-0.5 rounded-md bg-blue-50 border border-blue-200 text-[11px] font-mono">
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<Sliders size={11} className="text-blue-400 shrink-0" />
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<span className="text-blue-400">{'{{'}{segment.name}{'}}'}</span>
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<span className="text-blue-300">→</span>
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<span className="font-semibold">{segment.value}</span>
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<span className="text-blue-300 mx-0.5">=</span>
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<span className="text-blue-700 font-medium">{segment.value}</span>
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</span>
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)
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}
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@@ -1,9 +1,55 @@
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import type { SystemPromptSegment } from '../../types/protocol'
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import type { SystemPromptSegment, StaticVarSegment } from '../../types/protocol'
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import CollapsiblePanel from '../CollapsiblePanel'
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import { Bot } from 'lucide-react'
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export default function SystemPromptView({ segment }: { segment: SystemPromptSegment }) {
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interface SystemPromptViewProps {
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segment: SystemPromptSegment
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varMap?: Record<string, string> // 来自会话变量的 name→value 映射
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}
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/**
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* 将一个带 {{var}} 模板占位符的字符串解析为混合内容片段。
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* 普通文本渲染为纯文本，{{var}} 渲染为带解析值的内联标签。
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*/
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function renderTemplate(content: string, varMap: Record<string, string>) {
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// 按 {{...}} 分割，捕获分隔符
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const parts = content.split(/(\{\{[^}]+\}\})/g)
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return parts.map((part, i) => {
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const match = part.match(/^\{\{([^}]+)\}\}$/)
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if (!match) {
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// 普通文本
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return <span key={i}>{part}</span>
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}
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const varName = match[1].trim()
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const resolved = varMap[varName]
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return (
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<span
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key={i}
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className="inline-flex items-baseline gap-0.5 px-1 rounded bg-blue-100/70 border border-blue-200 text-[11px] font-mono align-baseline"
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title={resolved ? `模板变量 {{${varName}}} 已展开为 "${resolved}"` : `模板变量 {{${varName}}} —— 未找到对应值`}
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>
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<span className="text-blue-400">{'{{'}{varName}{'}}'}</span>
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{resolved && (
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<>
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<span className="text-blue-300 text-[9px]">→</span>
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<span className="text-blue-700 font-semibold">{resolved}</span>
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</>
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)}
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{!resolved && (
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<span className="text-red-400 text-[9px] italic">未解析</span>
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)}
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</span>
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)
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})
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}
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export default function SystemPromptView({ segment, varMap = {} }: SystemPromptViewProps) {
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const lineCount = segment.content.split('\n').length
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const hasVars = /\{\{[^}]+\}\}/.test(segment.content)
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return (
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<CollapsiblePanel
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title="System Prompt"
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@@ -11,10 +57,10 @@ export default function SystemPromptView({ segment }: { segment: SystemPromptSeg
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color="border-gray-400 text-gray-600"
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bgColor="bg-gray-50"
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defaultCollapsed={segment.collapsed}
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badge={`${lineCount} 行`}
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badge={`${lineCount} 行${hasVars ? ' · 模板' : ''}`}
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>
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<pre className="text-xs text-gray-600 whitespace-pre-wrap font-mono leading-relaxed max-h-48 overflow-y-auto">
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{segment.content}
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{renderTemplate(segment.content, varMap)}
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</pre>
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</CollapsiblePanel>
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)
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+106
-22
@@ -20,9 +20,31 @@ const demoA: PromptEnvelope = {
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id: 'a-1',
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role: 'system',
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segments: [
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{
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kind: 'static_var',
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name: 'current_date',
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value: '2026年6月7日',
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description: '当前对话日期，注入到 System Prompt 模板中',
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},
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{
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kind: 'static_var',
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name: 'language',
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value: '中文（简体）',
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description: '模型回复的首选语言',
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},
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{
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kind: 'static_var',
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name: 'user_name',
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value: '小明',
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description: '当前用户名称',
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},
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{
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kind: 'system_prompt',
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content: `你是 HCI 课程设计助手。你帮助学生对聊天界面的信息架构进行批判性思考。
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content: `当前日期：{{current_date}}
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用户名称：{{user_name}}
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回复语言：{{language}}
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你是 HCI 课程设计助手。你帮助学生对聊天界面的信息架构进行批判性思考。
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回答应简洁、有结构，鼓励学生从用户体验角度分析问题。
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如果学生对某个概念不清楚，用通俗的例子解释，不要用术语堆砌。`,
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collapsed: true,
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@@ -86,11 +108,6 @@ const demoA: PromptEnvelope = {
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id: 'a-2',
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role: 'user',
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segments: [
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{
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kind: 'static_var',
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name: 'user_name',
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value: '小明',
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},
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{
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kind: 'text',
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content: '你好，我想讨论一下我设计的聊天协议方案。你觉得 9 种 prompt 类型的分类合理吗？',
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@@ -124,10 +141,23 @@ const demoB: PromptEnvelope = {
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id: 'b-1',
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role: 'system',
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segments: [
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{
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kind: 'static_var',
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name: 'current_date',
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value: '2026年6月7日',
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description: '当前日期，SQL 查询中用于计算相对日期',
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},
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{
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kind: 'static_var',
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name: 'knowledge_cutoff',
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value: '2026年1月',
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description: '模型训练数据的截止时间',
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},
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{
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kind: 'system_prompt',
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content:
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'你是一个数据分析助手，可以使用 Python 工具进行数据查询和可视化。',
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content: `当前日期：{{current_date}}。知识截止：{{knowledge_cutoff}}。
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你是一个数据分析助手，可以使用 Python 工具进行数据查询和可视化。`,
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collapsed: true,
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},
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{
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@@ -298,10 +328,23 @@ const demoC: PromptEnvelope = {
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id: 'c-1',
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role: 'system',
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segments: [
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{
|
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kind: 'static_var',
|
||||
name: 'current_date',
|
||||
value: '2026年6月7日',
|
||||
description: '当前日期',
|
||||
},
|
||||
{
|
||||
kind: 'static_var',
|
||||
name: 'language',
|
||||
value: '中文（简体）',
|
||||
description: '文档审阅的默认输出语言',
|
||||
},
|
||||
{
|
||||
kind: 'system_prompt',
|
||||
content:
|
||||
'你是文档审阅助手。帮助用户分析长文档、提取要点、回答关于文档内容的问题。',
|
||||
content: `当前日期：{{current_date}}，回复语言：{{language}}。
|
||||
|
||||
你是文档审阅助手。帮助用户分析长文档、提取要点、回答关于文档内容的问题。`,
|
||||
collapsed: true,
|
||||
},
|
||||
{
|
||||
@@ -396,9 +439,38 @@ const demoD: PromptEnvelope = {
|
||||
id: 'd-1',
|
||||
role: 'system',
|
||||
segments: [
|
||||
{
|
||||
kind: 'static_var',
|
||||
name: 'current_date',
|
||||
value: '2026年6月7日',
|
||||
description: '当前对话日期',
|
||||
},
|
||||
{
|
||||
kind: 'static_var',
|
||||
name: 'language',
|
||||
value: '中文（简体）',
|
||||
description: '模型回复的首选语言',
|
||||
},
|
||||
{
|
||||
kind: 'static_var',
|
||||
name: 'knowledge_cutoff',
|
||||
value: '2026年1月',
|
||||
description: '模型训练数据截止日期',
|
||||
},
|
||||
{
|
||||
kind: 'static_var',
|
||||
name: 'user_name',
|
||||
value: '小明',
|
||||
description: '当前用户名称',
|
||||
},
|
||||
{
|
||||
kind: 'system_prompt',
|
||||
content: `你是 Claude，一个 HCI 研究助手。你的角色是帮助学生批判性地思考聊天界面的设计问题。
|
||||
content: `当前日期：{{current_date}}
|
||||
用户：{{user_name}}
|
||||
回复语言：{{language}}
|
||||
知识截止：{{knowledge_cutoff}}
|
||||
|
||||
你是 Claude，一个 HCI 研究助手。你的角色是帮助学生批判性地思考聊天界面的设计问题。
|
||||
|
||||
核心原则：
|
||||
- 鼓励从用户体验角度分析，而非技术实现角度
|
||||
@@ -538,11 +610,6 @@ const demoD: PromptEnvelope = {
|
||||
id: 'd-2',
|
||||
role: 'user',
|
||||
segments: [
|
||||
{
|
||||
kind: 'static_var',
|
||||
name: 'user_name',
|
||||
value: '小明',
|
||||
},
|
||||
{
|
||||
kind: 'text',
|
||||
content: '你好！我在准备课程设计的文献综述部分。我找到了一篇相关的研究报告，帮我分析一下它是否可以支持我的论点。',
|
||||
@@ -665,9 +732,31 @@ const demoE: PromptEnvelope = {
|
||||
id: 'e-1',
|
||||
role: 'system',
|
||||
segments: [
|
||||
{
|
||||
kind: 'static_var',
|
||||
name: 'current_date',
|
||||
value: '2026年6月7日',
|
||||
description: '当前对话日期',
|
||||
},
|
||||
{
|
||||
kind: 'static_var',
|
||||
name: 'language',
|
||||
value: '中文（简体）',
|
||||
description: '模型回复的首选语言',
|
||||
},
|
||||
{
|
||||
kind: 'static_var',
|
||||
name: 'knowledge_cutoff',
|
||||
value: '2026年1月',
|
||||
description: '模型训练数据截止日期',
|
||||
},
|
||||
{
|
||||
kind: 'system_prompt',
|
||||
content: `你是 HCI 课程设计助手，具备 Anthropic Skills 机制。
|
||||
content: `当前日期：{{current_date}}
|
||||
回复语言：{{language}}
|
||||
知识截止：{{knowledge_cutoff}}
|
||||
|
||||
你是 HCI 课程设计助手，具备 Anthropic Skills 机制。
|
||||
|
||||
你有以下 skills 可用。用户输入以 / 开头的命令时会直接触发对应 skill。你也可以在分析用户意图后，主动建议合适的 skill。
|
||||
|
||||
@@ -764,11 +853,6 @@ const demoE: PromptEnvelope = {
|
||||
id: 'e-2',
|
||||
role: 'user',
|
||||
segments: [
|
||||
{
|
||||
kind: 'static_var',
|
||||
name: 'user_name',
|
||||
value: '小明',
|
||||
},
|
||||
{
|
||||
kind: 'text',
|
||||
content: '我想深入了解 Anthropic Skills 的渐进式披露机制（Progressive Disclosure），作为我的 HCI 课程论文的案例研究对象。请帮我调研一下这个机制的设计原理、交互模式和学术界相关讨论。',
|
||||
|
||||
@@ -38,10 +38,16 @@ export interface TextSegment {
|
||||
content: string
|
||||
}
|
||||
|
||||
/**
|
||||
* 会话级静态变量 —— 在对话开始时注入到 System Prompt 模板中展开。
|
||||
* 例如 {{current_date}} 在模板中展开为 "2026年6月7日"。
|
||||
* 这些变量对用户可见，解释了模型"看到"的上下文配置。
|
||||
*/
|
||||
export interface StaticVarSegment {
|
||||
kind: 'static_var'
|
||||
name: string // e.g. "user_name"
|
||||
value: string // e.g. "张三"
|
||||
name: string // 模板变量名，e.g. "current_date"
|
||||
value: string // 展开后的值，e.g. "2026年6月7日"
|
||||
description?: string // 简短说明该变量的用途
|
||||
}
|
||||
|
||||
export interface SystemPromptSegment {
|
||||
|
||||
+24
-2
@@ -85,6 +85,8 @@ export function segmentToText(seg: Segment): string | null {
|
||||
/** Render a structural segment into text for the system message */
|
||||
function formatStructural(seg: Segment): string | null {
|
||||
switch (seg.kind) {
|
||||
case 'static_var':
|
||||
return `${seg.name} = ${seg.value}`
|
||||
case 'system_prompt':
|
||||
return `[System Prompt]\n${seg.content}`
|
||||
case 'memory':
|
||||
@@ -148,14 +150,34 @@ export function exportToOpenAIFormat(envelope: PromptEnvelope): OpenAIExport {
|
||||
for (const msg of envelope.messages) {
|
||||
// ── System ──
|
||||
if (msg.role === 'system') {
|
||||
// 第一遍：收集 static_var 用于模板展开
|
||||
const varMap: Record<string, string> = {}
|
||||
for (const seg of msg.segments) {
|
||||
if (seg.kind === 'static_var') {
|
||||
varMap[seg.name] = seg.value
|
||||
}
|
||||
}
|
||||
|
||||
const contentParts: string[] = []
|
||||
for (const seg of msg.segments) {
|
||||
if (seg.kind === 'tool_overview') {
|
||||
// tool_overview → top-level tools array
|
||||
seg.items.forEach(item => tools.push(toolItemToOpenAI(item)))
|
||||
// Also add a text summary to the system message
|
||||
const summary = formatStructural(seg)
|
||||
if (summary) contentParts.push(summary)
|
||||
} else if (seg.kind === 'static_var') {
|
||||
// 静态变量：导出为配置行
|
||||
const s = formatStructural(seg)
|
||||
if (s) contentParts.push(s)
|
||||
} else if (seg.kind === 'system_prompt') {
|
||||
// 展开模板中的 {{var}} 占位符
|
||||
let expanded = seg.content
|
||||
for (const [name, value] of Object.entries(varMap)) {
|
||||
expanded = expanded.replace(
|
||||
new RegExp(`\\{\\{${name}\\}\\}`, 'g'),
|
||||
value
|
||||
)
|
||||
}
|
||||
contentParts.push(expanded)
|
||||
} else {
|
||||
const t = segmentToText(seg)
|
||||
if (t !== null) contentParts.push(t)
|
||||
|
||||
Reference in New Issue
Block a user