From a9881eac2645a198cff4d3ae175d6a546666a019 Mon Sep 17 00:00:00 2001 From: carry Date: Sun, 7 Jun 2026 13:44:36 +0800 Subject: [PATCH] feat: Prompt Envelope Protocol MVP MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - 定义 11 种 Segment 类型（text, static_var, system_prompt, memory, skills, tool_overview, tool_call_request/result, document, long_text, media） - 每种 Segment 有独立的颜色编码和折叠交互 - 通用 CollapsiblePanel + SegmentRenderer 路由架构 - 4 个 Demo 场景覆盖全部 9 种上下文类型 - 导出为 OpenAI Chat Completions Format（model + messages + tools） - tool_overview -> 请求级 tools[]（含 JSON Schema） - tool_call_request -> assistant.tool_calls[] - tool_call_result -> tool-role message（ID 配对） - 17 个单元测试全部通过 - React 18 + TypeScript + Vite + Tailwind CSS --- .gitignore | 3 + index.html | 12 + package-lock.json | 3522 +++++++++++++++++ package.json | 28 + postcss.config.js | 6 + src/App.tsx | 66 + src/__tests__/export.test.ts | 452 +++ src/components/ChatInput.tsx | 30 + src/components/ChatView.tsx | 16 + src/components/CollapsiblePanel.tsx | 50 + src/components/MessageBubble.tsx | 50 + src/components/MessageList.tsx | 24 + src/components/ProtocolPanel.tsx | 83 + src/components/SegmentRenderer.tsx | 48 + src/components/segments/DocumentCard.tsx | 41 + src/components/segments/LongTextView.tsx | 44 + src/components/segments/MediaView.tsx | 26 + src/components/segments/MemoryView.tsx | 25 + src/components/segments/SkillsView.tsx | 27 + src/components/segments/StaticVarBadge.tsx | 13 + src/components/segments/SystemPromptView.tsx | 21 + src/components/segments/TextSegmentView.tsx | 9 + .../segments/ToolCallRequestView.tsx | 23 + .../segments/ToolCallResultView.tsx | 51 + src/components/segments/ToolOverviewView.tsx | 54 + src/context/ChatContext.tsx | 43 + src/data/demos.ts | 624 +++ src/index.css | 22 + src/main.tsx | 10 + src/types/protocol.ts | 123 + src/utils/export.ts | 249 ++ tailwind.config.js | 11 + tsconfig.json | 21 + vite.config.ts | 6 + 34 files changed, 5833 insertions(+) create mode 100644 .gitignore create mode 100644 index.html create mode 100644 package-lock.json create mode 100644 package.json create mode 100644 postcss.config.js create mode 100644 src/App.tsx create mode 100644 src/__tests__/export.test.ts create mode 100644 src/components/ChatInput.tsx create mode 100644 src/components/ChatView.tsx create mode 100644 src/components/CollapsiblePanel.tsx create mode 100644 src/components/MessageBubble.tsx create mode 100644 src/components/MessageList.tsx create mode 100644 src/components/ProtocolPanel.tsx create mode 100644 src/components/SegmentRenderer.tsx create mode 100644 src/components/segments/DocumentCard.tsx create mode 100644 src/components/segments/LongTextView.tsx create mode 100644 src/components/segments/MediaView.tsx create mode 100644 src/components/segments/MemoryView.tsx create mode 100644 src/components/segments/SkillsView.tsx create mode 100644 src/components/segments/StaticVarBadge.tsx create mode 100644 src/components/segments/SystemPromptView.tsx create mode 100644 src/components/segments/TextSegmentView.tsx create mode 100644 src/components/segments/ToolCallRequestView.tsx create mode 100644 src/components/segments/ToolCallResultView.tsx create mode 100644 src/components/segments/ToolOverviewView.tsx create mode 100644 src/context/ChatContext.tsx create mode 100644 src/data/demos.ts create mode 100644 src/index.css create mode 100644 src/main.tsx create mode 100644 src/types/protocol.ts create mode 100644 src/utils/export.ts create mode 100644 tailwind.config.js create mode 100644 tsconfig.json create mode 100644 vite.config.ts diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..3bdd52e --- /dev/null +++ b/.gitignore @@ -0,0 +1,3 @@ +node_modules/ +dist/ +.DS_Store diff --git a/index.html b/index.html new file mode 100644 index 0000000..aa60716 --- /dev/null +++ b/index.html @@ -0,0 +1,12 @@ + + + + + + HCI Chatbox — Context Transparency + + +
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"funding": { + "url": "https://github.com/sponsors/sindresorhus" + } + } + } +} diff --git a/package.json b/package.json new file mode 100644 index 0000000..5f31f77 --- /dev/null +++ b/package.json @@ -0,0 +1,28 @@ +{ + "name": "hci-chatbox", + "private": true, + "version": "1.0.0", + "type": "module", + "scripts": { + "dev": "vite", + "build": "tsc -b && vite build", + "preview": "vite preview", + "test": "vitest run" + }, + "dependencies": { + "lucide-react": "^0.400.0", + "react": "^18.3.1", + "react-dom": "^18.3.1" + }, + "devDependencies": { + "@types/react": "^18.3.3", + "@types/react-dom": "^18.3.0", + "@vitejs/plugin-react": "^4.3.1", + "autoprefixer": "^10.4.19", + "postcss": "^8.4.38", + "tailwindcss": "^3.4.4", + "typescript": "^5.5.3", + "vite": "^5.3.4", + "vitest": "^1.6.0" + } +} diff --git a/postcss.config.js b/postcss.config.js new file mode 100644 index 0000000..2e7af2b --- /dev/null +++ b/postcss.config.js @@ -0,0 +1,6 @@ +export default { + plugins: { + tailwindcss: {}, + autoprefixer: {}, + }, +} diff --git a/src/App.tsx b/src/App.tsx new file mode 100644 index 0000000..6993323 --- /dev/null +++ b/src/App.tsx @@ -0,0 +1,66 @@ +import { ChatProvider, useChat } from './context/ChatContext' +import ChatView from './components/ChatView' +import ProtocolPanel from './components/ProtocolPanel' +import { Layers } from 'lucide-react' + +function DemoSelector() { + const { demos, activeDemo, setActiveDemo } = useChat() + + return ( +
+ {demos.map((demo, i) => ( + + ))} +
+ ) +} + +function AppContent() { + const { envelope, demos, activeDemo } = useChat() + + return ( +
+ {/* Top bar */} +
+
+ +

+ Prompt Envelope Protocol +

+ + MVP + +
+
+ + + {demos[activeDemo].description} + +
+ + {/* Main content */} +
+ + +
+
+ ) +} + +export default function App() { + return ( + + + + ) +} diff --git a/src/__tests__/export.test.ts b/src/__tests__/export.test.ts new file mode 100644 index 0000000..5e58caa --- /dev/null +++ b/src/__tests__/export.test.ts @@ -0,0 +1,452 @@ +import { describe, it, expect } from 'vitest' +import { exportToOpenAIFormat, segmentToText } from '../utils/export' +import type { PromptEnvelope } from '../types/protocol' + +describe('segmentToText', () => { + it('returns text content as-is', () => { + expect(segmentToText({ kind: 'text', content: 'Hello world' })).toBe('Hello world') + }) + + it('expands static variables to their value', () => { + expect( + segmentToText({ kind: 'static_var', name: 'user', value: 'Alice' }) + ).toBe('Alice') + }) + + it('returns null for structural segments', () => { + expect( + segmentToText({ kind: 'system_prompt', content: '...', collapsed: true }) + ).toBeNull() + expect( + segmentToText({ kind: 'memory', items: [{ title: 'x', content: 'y' }], collapsed: true }) + ).toBeNull() + expect( + segmentToText({ kind: 'skills', items: [], collapsed: true }) + ).toBeNull() + expect( + segmentToText({ kind: 'tool_overview', items: [], collapsed: true }) + ).toBeNull() + }) + + it('returns null for tool call segments (handled structurally)', () => { + expect( + segmentToText({ + kind: 'tool_call_request', + toolName: 'search', + arguments: { q: 'test' }, + collapsed: false, + }) + ).toBeNull() + expect( + segmentToText({ + kind: 'tool_call_result', + toolName: 'search', + result: 'Found 3', + success: true, + collapsed: true, + }) + ).toBeNull() + }) + + it('returns long text as-is', () => { + expect( + segmentToText({ kind: 'long_text', content: 'a long article', charCount: 14, collapsed: true }) + ).toBe('a long article') + }) + + it('uses altText for media', () => { + expect( + segmentToText({ kind: 'media', mediaType: 'image', url: '', altText: 'a diagram' }) + ).toBe('a diagram') + }) +}) + +describe('exportToOpenAIFormat', () => { + it('includes model in output (default or from envelope)', () => { + const env: PromptEnvelope = { + version: '1.0', + messages: [ + { + id: '1', + role: 'user', + segments: [{ kind: 'text', content: 'Hi' }], + timestamp: 0, + }, + ], + } + // Default model + expect(exportToOpenAIFormat(env).model).toBe('gpt-4-turbo') + + // Custom model + const env2: PromptEnvelope = { ...env, model: 'claude-opus-4-8' } + expect(exportToOpenAIFormat(env2).model).toBe('claude-opus-4-8') + }) + + it('exports tool_overview as top-level tools array', () => { + const env: PromptEnvelope = { + version: '1.0', + model: 'gpt-4-turbo', + messages: [ + { + id: '0', + role: 'system', + segments: [ + { + kind: 'tool_overview', + items: [ + { + name: 'search', + description: 'Search the web', + parameters: 'query: string', + schema: { + type: 'object', + properties: { query: { type: 'string' } }, + required: ['query'], + }, + }, + ], + collapsed: true, + }, + ], + timestamp: 0, + }, + { + id: '1', + role: 'user', + segments: [{ kind: 'text', content: 'Hi' }], + timestamp: 0, + }, + ], + } + const result = exportToOpenAIFormat(env) + + expect(result.model).toBe('gpt-4-turbo') + expect(result.tools).toHaveLength(1) + expect(result.tools![0]).toEqual({ + type: 'function', + function: { + name: 'search', + description: 'Search the web', + parameters: { + type: 'object', + properties: { query: { type: 'string' } }, + required: ['query'], + }, + }, + }) + expect(result.messages).toHaveLength(2) // system + user + }) + + it('flattens a simple text-only conversation', () => { + const env: PromptEnvelope = { + version: '1.0', + messages: [ + { + id: '1', + role: 'user', + segments: [{ kind: 'text', content: 'Hi' }], + timestamp: 0, + }, + { + id: '2', + role: 'assistant', + segments: [{ kind: 'text', content: 'Hello!' }], + timestamp: 0, + }, + ], + } + const { messages } = exportToOpenAIFormat(env) + expect(messages).toHaveLength(2) + expect(messages[0]).toEqual({ role: 'user', content: 'Hi' }) + expect(messages[1]).toEqual({ role: 'assistant', content: 'Hello!' }) + }) + + it('collects system-message segments into a leading system message', () => { + const env: PromptEnvelope = { + version: '1.0', + messages: [ + { + id: '0', + role: 'system', + segments: [ + { kind: 'system_prompt', content: 'Be helpful.', collapsed: true }, + { + kind: 'memory', + items: [{ title: 'User', content: 'Prefers brevity' }], + collapsed: true, + }, + ], + timestamp: 0, + }, + { + id: '1', + role: 'user', + segments: [{ kind: 'text', content: 'Hi' }], + timestamp: 0, + }, + ], + } + const { messages } = exportToOpenAIFormat(env) + expect(messages).toHaveLength(2) + expect(messages[0].role).toBe('system') + expect(messages[0].content).toContain('Be helpful') + expect(messages[0].content).toContain('Prefers brevity') + expect(messages[1].role).toBe('user') + expect(messages[1].content).toBe('Hi') + }) + + it('pulls structural segments from user messages into system message', () => { + const env: PromptEnvelope = { + version: '1.0', + messages: [ + { + id: '1', + role: 'user', + segments: [ + { kind: 'system_prompt', content: 'Be concise.', collapsed: true }, + { kind: 'text', content: 'Hello' }, + ], + timestamp: 0, + }, + ], + } + const { messages } = exportToOpenAIFormat(env) + expect(messages[0].role).toBe('system') + expect(messages[0].content).toContain('Be concise') + expect(messages[1].role).toBe('user') + expect(messages[1].content).toBe('Hello') + }) + + it('expands static_vars in output', () => { + const env: PromptEnvelope = { + version: '1.0', + messages: [ + { + id: '1', + role: 'user', + segments: [ + { kind: 'static_var', name: 'user_name', value: '小明' }, + { kind: 'text', content: ' says hello' }, + ], + timestamp: 0, + }, + ], + } + const { messages } = exportToOpenAIFormat(env) + expect(messages[0].content).toContain('小明') + expect(messages[0].content).toContain('says hello') + }) + + it('emits tool_call_request as assistant message with tool_calls', () => { + const env: PromptEnvelope = { + version: '1.0', + messages: [ + { + id: '1', + role: 'assistant', + segments: [ + { kind: 'text', content: 'Let me search.' }, + { + kind: 'tool_call_request', + toolName: 'search', + arguments: { q: 'hci' }, + collapsed: false, + }, + ], + timestamp: 0, + }, + ], + } + const { messages } = exportToOpenAIFormat(env) + expect(messages).toHaveLength(1) + const msg = messages[0] + expect(msg.role).toBe('assistant') + expect(msg.content).toBe('Let me search.') + expect(msg.tool_calls).toHaveLength(1) + expect(msg.tool_calls![0].type).toBe('function') + expect(msg.tool_calls![0].function.name).toBe('search') + expect(JSON.parse(msg.tool_calls![0].function.arguments)).toEqual({ q: 'hci' }) + }) + + it('emits tool_call_result as separate tool-role message', () => { + const env: PromptEnvelope = { + version: '1.0', + messages: [ + { + id: '1', + role: 'assistant', + segments: [ + { + kind: 'tool_call_request', + toolName: 'search', + arguments: { q: 'hci' }, + collapsed: false, + }, + ], + timestamp: 0, + }, + { + id: '2', + role: 'assistant', + segments: [ + { + kind: 'tool_call_result', + toolName: 'search', + result: 'Found 3 results.', + success: true, + collapsed: true, + }, + ], + timestamp: 0, + }, + ], + } + const { messages } = exportToOpenAIFormat(env) + + expect(messages).toHaveLength(2) + + const assistantMsg = messages[0] + expect(assistantMsg.role).toBe('assistant') + expect(assistantMsg.tool_calls).toHaveLength(1) + const callId = assistantMsg.tool_calls![0].id + + const toolMsg = messages[1] + expect(toolMsg.role).toBe('tool') + expect(toolMsg.tool_call_id).toBe(callId) + expect(toolMsg.content).toBe('Found 3 results.') + }) + + it('handles a full tool call round-trip: request + result + text', () => { + const env: PromptEnvelope = { + version: '1.0', + messages: [ + { + id: '1', + role: 'assistant', + segments: [ + { kind: 'text', content: 'Searching...' }, + { + kind: 'tool_call_request', + toolName: 'fetch', + arguments: { url: '/api' }, + collapsed: false, + }, + ], + timestamp: 0, + }, + { + id: '2', + role: 'assistant', + segments: [ + { + kind: 'tool_call_result', + toolName: 'fetch', + result: '{"ok":true}', + success: true, + collapsed: true, + }, + { kind: 'text', content: 'Got it!' }, + ], + timestamp: 0, + }, + ], + } + const { messages } = exportToOpenAIFormat(env) + + // assistant (text + tool_calls) + tool + assistant (text) + expect(messages).toHaveLength(3) + + expect(messages[0].role).toBe('assistant') + expect(messages[0].content).toBe('Searching...') + expect(messages[0].tool_calls).toHaveLength(1) + + expect(messages[1].role).toBe('tool') + expect(messages[1].tool_call_id).toBe(messages[0].tool_calls![0].id) + + expect(messages[2].role).toBe('assistant') + expect(messages[2].content).toBe('Got it!') + expect(messages[2].tool_calls).toBeUndefined() + }) + + it('handles multiple tool calls with correct ID pairing', () => { + const env: PromptEnvelope = { + version: '1.0', + messages: [ + { + id: '1', + role: 'assistant', + segments: [ + { + kind: 'tool_call_request', + toolName: 'search', + arguments: { q: 'a' }, + collapsed: false, + }, + { + kind: 'tool_call_request', + toolName: 'fetch', + arguments: { url: '/b' }, + collapsed: false, + }, + ], + timestamp: 0, + }, + { + id: '2', + role: 'assistant', + segments: [ + { + kind: 'tool_call_result', + toolName: 'search', + result: 'A results', + success: true, + collapsed: true, + }, + { + kind: 'tool_call_result', + toolName: 'fetch', + result: 'B results', + success: true, + collapsed: true, + }, + ], + timestamp: 0, + }, + ], + } + const { messages } = exportToOpenAIFormat(env) + + // assistant (2 tool_calls) + tool (search) + tool (fetch) + expect(messages).toHaveLength(3) + + const assistantMsg = messages[0] + expect(assistantMsg.role).toBe('assistant') + expect(assistantMsg.tool_calls).toHaveLength(2) + const searchId = assistantMsg.tool_calls![0].id + const fetchId = assistantMsg.tool_calls![1].id + + expect(messages[1].role).toBe('tool') + expect(messages[1].tool_call_id).toBe(searchId) + expect(messages[1].content).toBe('A results') + + expect(messages[2].role).toBe('tool') + expect(messages[2].tool_call_id).toBe(fetchId) + expect(messages[2].content).toBe('B results') + }) + + it('omits tools key when no tool_overview present', () => { + const env: PromptEnvelope = { + version: '1.0', + messages: [ + { + id: '1', + role: 'user', + segments: [{ kind: 'text', content: 'Hi' }], + timestamp: 0, + }, + ], + } + const result = exportToOpenAIFormat(env) + expect(result.tools).toBeUndefined() + }) +}) diff --git a/src/components/ChatInput.tsx b/src/components/ChatInput.tsx new file mode 100644 index 0000000..c683bd8 --- /dev/null +++ b/src/components/ChatInput.tsx @@ -0,0 +1,30 @@ +import { Send } from 'lucide-react' + +interface ChatInputProps { + value: string + onChange: (v: string) => void + disabled?: boolean +} + +export default function ChatInput({ value, onChange, disabled }: ChatInputProps) { + return ( +
+
+ onChange(e.target.value)} + disabled={disabled} + placeholder="输入消息（Demo 模式 — 不会调用 LLM）" + className="flex-1 rounded-lg border border-gray-200 px-4 py-2 text-sm focus:outline-none focus:ring-2 focus:ring-blue-200 focus:border-blue-300 disabled:bg-gray-50 disabled:text-gray-400" + /> + +
+
+ ) +} diff --git a/src/components/ChatView.tsx b/src/components/ChatView.tsx new file mode 100644 index 0000000..b005d6b --- /dev/null +++ b/src/components/ChatView.tsx @@ -0,0 +1,16 @@ +import { useState } from 'react' +import { useChat } from '../context/ChatContext' +import MessageList from './MessageList' +import ChatInput from './ChatInput' + +export default function ChatView() { + const { envelope } = useChat() + const [input, setInput] = useState('') + + return ( +
+ + +
+ ) +} diff --git a/src/components/CollapsiblePanel.tsx b/src/components/CollapsiblePanel.tsx new file mode 100644 index 0000000..9195be0 --- /dev/null +++ b/src/components/CollapsiblePanel.tsx @@ -0,0 +1,50 @@ +import { useState } from 'react' +import { ChevronDown, ChevronRight } from 'lucide-react' + +interface CollapsiblePanelProps { + title: string + icon: React.ReactNode + color: string // Tailwind border/text color class, e.g. 'border-purple-400 text-purple-700' + bgColor: string // Tailwind bg class, e.g. 'bg-purple-50' + defaultCollapsed: boolean + badge?: string + children: React.ReactNode +} + +export default function CollapsiblePanel({ + title, + icon, + color, + bgColor, + defaultCollapsed, + badge, + children, +}: CollapsiblePanelProps) { + const [collapsed, setCollapsed] = useState(defaultCollapsed) + + return ( +
+ +
+
{children}
+
+
+ ) +} diff --git a/src/components/MessageBubble.tsx b/src/components/MessageBubble.tsx new file mode 100644 index 0000000..0e163e5 --- /dev/null +++ b/src/components/MessageBubble.tsx @@ -0,0 +1,50 @@ +import type { Message } from '../types/protocol' +import SegmentRenderer from './SegmentRenderer' +import { User, Bot, Settings } from 'lucide-react' + +const roleConfig = { + system: { icon: Settings, label: 'SYSTEM', align: 'left', bg: 'bg-gray-100', text: 'text-gray-500' }, + user: { icon: User, label: 'YOU', align: 'right', bg: 'bg-blue-50 border-blue-100', text: 'text-blue-600' }, + assistant: { icon: Bot, label: 'ASSISTANT', align: 'left', bg: 'bg-white border-gray-100', text: 'text-green-600' }, +} + +interface MessageBubbleProps { + message: Message +} + +export default function MessageBubble({ message }: MessageBubbleProps) { + const cfg = roleConfig[message.role] + const Icon = cfg.icon + const isUser = message.role === 'user' + + return ( +
+
+ {/* Role header */} +
+ + + {cfg.label} + +
+ + {/* Segments */} +
+ {message.segments.map((seg, i) => ( + + ))} +
+ + {/* Timestamp */} +
+ {new Date(message.timestamp).toLocaleTimeString([], { + hour: '2-digit', + minute: '2-digit', + })} +
+
+
+ ) +} diff --git a/src/components/MessageList.tsx b/src/components/MessageList.tsx new file mode 100644 index 0000000..cd8fd5f --- /dev/null +++ b/src/components/MessageList.tsx @@ -0,0 +1,24 @@ +import type { Message } from '../types/protocol' +import MessageBubble from './MessageBubble' + +interface MessageListProps { + messages: Message[] +} + +export default function MessageList({ messages }: MessageListProps) { + if (messages.length === 0) { + return ( +
+ 选择一个 Demo 场景开始 +
+ ) + } + + return ( +
+ {messages.map((msg) => ( + + ))} +
+ ) +} diff --git a/src/components/ProtocolPanel.tsx b/src/components/ProtocolPanel.tsx new file mode 100644 index 0000000..1ec2b93 --- /dev/null +++ b/src/components/ProtocolPanel.tsx @@ -0,0 +1,83 @@ +import { useState, useMemo } from 'react' +import type { PromptEnvelope } from '../types/protocol' +import { exportToOpenAIFormat } from '../utils/export' +import { Code, Copy, Download, Check } from 'lucide-react' + +interface ProtocolPanelProps { + envelope: PromptEnvelope +} + +export default function ProtocolPanel({ envelope }: ProtocolPanelProps) { + const [copied, setCopied] = useState(false) + + const openaiFormat = useMemo(() => exportToOpenAIFormat(envelope), [envelope]) + + const handleCopy = async () => { + await navigator.clipboard.writeText(JSON.stringify(openaiFormat, null, 2)) + setCopied(true) + setTimeout(() => setCopied(false), 2000) + } + + const handleDownload = () => { + const blob = new Blob([JSON.stringify(openaiFormat, null, 2)], { + type: 'application/json', + }) + const url = URL.createObjectURL(blob) + const a = document.createElement('a') + a.href = url + a.download = 'openai-export.json' + a.click() + URL.revokeObjectURL(url) + } + + return ( +
+ {/* Header */} +
+ + + Protocol View + + + +
+ + {/* Tabs */} +
+
+ OpenAI Format +
+
+ Raw Protocol (soon) +
+
+ + {/* JSON Content */} +
+ 
+          {JSON.stringify(openaiFormat, null, 2)}
+
+
+ + {/* Footer stats */} +
+ model: {openaiFormat.model} + {envelope.messages.length} 条协议消息 + {openaiFormat.messages.length} OpenAI messages + {openaiFormat.tools && {openaiFormat.tools.length} tools} +
+
+ ) +} diff --git a/src/components/SegmentRenderer.tsx b/src/components/SegmentRenderer.tsx new file mode 100644 index 0000000..af4d2aa --- /dev/null +++ b/src/components/SegmentRenderer.tsx @@ -0,0 +1,48 @@ +import type { Segment } from '../types/protocol' +import TextSegmentView from './segments/TextSegmentView' +import StaticVarBadge from './segments/StaticVarBadge' +import SystemPromptView from './segments/SystemPromptView' +import MemoryView from './segments/MemoryView' +import SkillsView from './segments/SkillsView' +import ToolOverviewView from './segments/ToolOverviewView' +import ToolCallRequestView from './segments/ToolCallRequestView' +import ToolCallResultView from './segments/ToolCallResultView' +import DocumentCard from './segments/DocumentCard' +import LongTextView from './segments/LongTextView' +import MediaView from './segments/MediaView' + +interface SegmentRendererProps { + segment: Segment +} + +/** + * Route a Segment to its correct view component based on `kind`. + */ +export default function SegmentRenderer({ segment }: SegmentRendererProps) { + switch (segment.kind) { + case 'text': + return + case 'static_var': + return + case 'system_prompt': + return + case 'memory': + return + case 'skills': + return + case 'tool_overview': + return + case 'tool_call_request': + return + case 'tool_call_result': + return + case 'document': + return + case 'long_text': + return + case 'media': + return + default: + return null + } +} diff --git a/src/components/segments/DocumentCard.tsx b/src/components/segments/DocumentCard.tsx new file mode 100644 index 0000000..c8a4423 --- /dev/null +++ b/src/components/segments/DocumentCard.tsx @@ -0,0 +1,41 @@ +import type { DocumentSegment } from '../../types/protocol' +import { FileText, FileImage, FileAudio, File } from 'lucide-react' + +const mimeIcons: Record> = { + 'text/': FileText, + 'image/': FileImage, + 'audio/': FileAudio, +} + +function getIcon(mimeType: string) { + for (const [prefix, Icon] of Object.entries(mimeIcons)) { + if (mimeType.startsWith(prefix)) return + } + return +} + +function formatBytes(bytes: number): string { + if (bytes < 1024) return `${bytes}B` + if (bytes < 1024 * 1024) return `${(bytes / 1024).toFixed(1)}KB` + return `${(bytes / (1024 * 1024)).toFixed(1)}MB` +} + +export default function DocumentCard({ segment }: { segment: DocumentSegment }) { + return ( +
+
{getIcon(segment.mimeType)}
+
+
+ + {segment.fileName} + + {formatBytes(segment.sizeBytes)} +
+

{segment.mimeType}

+

+ {segment.snippet} +

+
+
+ ) +} diff --git a/src/components/segments/LongTextView.tsx b/src/components/segments/LongTextView.tsx new file mode 100644 index 0000000..0944ac7 --- /dev/null +++ b/src/components/segments/LongTextView.tsx @@ -0,0 +1,44 @@ +import { useState } from 'react' +import type { LongTextSegment } from '../../types/protocol' +import { ChevronDown, ChevronRight, Text } from 'lucide-react' + +export default function LongTextView({ segment }: { segment: LongTextSegment }) { + const [collapsed, setCollapsed] = useState(segment.collapsed) + + // Show first ~2 lines when collapsed + const preview = segment.content.split('\n').slice(0, 2).join('\n') + + return ( +
+ + {!collapsed && ( +
+

+ {segment.content} +

+
+ )} + {collapsed && ( +
+

+ {preview} +

+
+ )} +
+ ) +} diff --git a/src/components/segments/MediaView.tsx b/src/components/segments/MediaView.tsx new file mode 100644 index 0000000..3b9ec6c --- /dev/null +++ b/src/components/segments/MediaView.tsx @@ -0,0 +1,26 @@ +import type { MediaSegment } from '../../types/protocol' +import { Image, Music, Video } from 'lucide-react' + +const mediaConfig = { + image: { icon: Image, label: '图片', bg: 'bg-blue-50', color: 'text-blue-600' }, + audio: { icon: Music, label: '音频', bg: 'bg-pink-50', color: 'text-pink-600' }, + video: { icon: Video, label: '视频', bg: 'bg-indigo-50', color: 'text-indigo-600' }, +} + +export default function MediaView({ segment }: { segment: MediaSegment }) { + const cfg = mediaConfig[segment.mediaType] + const Icon = cfg.icon + + return ( +
+ +
+ {cfg.label} + {segment.altText && ( + {segment.altText} + )} +
+ {segment.mediaType} +
+ ) +} diff --git a/src/components/segments/MemoryView.tsx b/src/components/segments/MemoryView.tsx new file mode 100644 index 0000000..d4eb057 --- /dev/null +++ b/src/components/segments/MemoryView.tsx @@ -0,0 +1,25 @@ +import type { MemorySegment } from '../../types/protocol' +import CollapsiblePanel from '../CollapsiblePanel' +import { Brain } from 'lucide-react' + +export default function MemoryView({ segment }: { segment: MemorySegment }) { + return ( + } + color="border-purple-400 text-purple-700" + bgColor="bg-purple-50" + defaultCollapsed={segment.collapsed} + badge={`${segment.items.length} 条记忆`} + > +
    + {segment.items.map((item, i) => ( +
  • +
    {item.title}
    +
    {item.content}
    +
    • + ))} +
+ + ) +} diff --git a/src/components/segments/SkillsView.tsx b/src/components/segments/SkillsView.tsx new file mode 100644 index 0000000..726e4cd --- /dev/null +++ b/src/components/segments/SkillsView.tsx @@ -0,0 +1,27 @@ +import type { SkillSegment } from '../../types/protocol' +import CollapsiblePanel from '../CollapsiblePanel' +import { Zap } from 'lucide-react' + +export default function SkillsView({ segment }: { segment: SkillSegment }) { + return ( + } + color="border-green-400 text-green-700" + bgColor="bg-green-50" + defaultCollapsed={segment.collapsed} + badge={`${segment.items.length} skills`} + > +
    + {segment.items.map((item, i) => ( +
  • + + /{item.name} + + {item.description} +
    • + ))} +
+ + ) +} diff --git a/src/components/segments/StaticVarBadge.tsx b/src/components/segments/StaticVarBadge.tsx new file mode 100644 index 0000000..f29ed47 --- /dev/null +++ b/src/components/segments/StaticVarBadge.tsx @@ -0,0 +1,13 @@ +import type { StaticVarSegment } from '../../types/protocol' +import { Variable } from 'lucide-react' + +export default function StaticVarBadge({ segment }: { segment: StaticVarSegment }) { + return ( + + + {'{{'}{segment.name}{'}}'} + → + {segment.value} + + ) +} diff --git a/src/components/segments/SystemPromptView.tsx b/src/components/segments/SystemPromptView.tsx new file mode 100644 index 0000000..88ac4ea --- /dev/null +++ b/src/components/segments/SystemPromptView.tsx @@ -0,0 +1,21 @@ +import type { SystemPromptSegment } from '../../types/protocol' +import CollapsiblePanel from '../CollapsiblePanel' +import { Bot } from 'lucide-react' + +export default function SystemPromptView({ segment }: { segment: SystemPromptSegment }) { + const lineCount = segment.content.split('\n').length + return ( + } + color="border-gray-400 text-gray-600" + bgColor="bg-gray-50" + defaultCollapsed={segment.collapsed} + badge={`${lineCount} 行`} + > + 
+        {segment.content}
+
+ + ) +} diff --git a/src/components/segments/TextSegmentView.tsx b/src/components/segments/TextSegmentView.tsx new file mode 100644 index 0000000..f895e79 --- /dev/null +++ b/src/components/segments/TextSegmentView.tsx @@ -0,0 +1,9 @@ +import type { TextSegment } from '../../types/protocol' + +export default function TextSegmentView({ segment }: { segment: TextSegment }) { + return ( +

+ {segment.content} +

+ ) +} diff --git a/src/components/segments/ToolCallRequestView.tsx b/src/components/segments/ToolCallRequestView.tsx new file mode 100644 index 0000000..099ff52 --- /dev/null +++ b/src/components/segments/ToolCallRequestView.tsx @@ -0,0 +1,23 @@ +import type { ToolCallRequestSegment } from '../../types/protocol' +import { Play } from 'lucide-react' + +export default function ToolCallRequestView({ + segment, +}: { + segment: ToolCallRequestSegment +}) { + return ( +
+
+ + + {segment.toolName} + + request +
+ 
+        {JSON.stringify(segment.arguments, null, 2)}
+
+
+ ) +} diff --git a/src/components/segments/ToolCallResultView.tsx b/src/components/segments/ToolCallResultView.tsx new file mode 100644 index 0000000..736a0cc --- /dev/null +++ b/src/components/segments/ToolCallResultView.tsx @@ -0,0 +1,51 @@ +import { useState } from 'react' +import type { ToolCallResultSegment } from '../../types/protocol' +import { CheckCircle, XCircle, ChevronDown, ChevronRight } from 'lucide-react' + +export default function ToolCallResultView({ + segment, +}: { + segment: ToolCallResultSegment +}) { + const [collapsed, setCollapsed] = useState(segment.collapsed) + + return ( +
+ +
+ 
+          {segment.result}
+
+
+
+ ) +} diff --git a/src/components/segments/ToolOverviewView.tsx b/src/components/segments/ToolOverviewView.tsx new file mode 100644 index 0000000..3163762 --- /dev/null +++ b/src/components/segments/ToolOverviewView.tsx @@ -0,0 +1,54 @@ +import { useState } from 'react' +import type { ToolOverviewSegment } from '../../types/protocol' +import CollapsiblePanel from '../CollapsiblePanel' +import { Wrench, ChevronDown, ChevronRight, Braces } from 'lucide-react' + +function ToolItemRow({ item }: { item: ToolOverviewSegment['items'][number] }) { + const [showSchema, setShowSchema] = useState(false) + + return ( +
  • +
    + {item.name} + ({item.parameters}) +
    +
    {item.description}
    + {item.schema && ( + <> + + {showSchema && ( + 
    +              {JSON.stringify(item.schema, null, 2)}
+
    + )} + + )} +
    • + ) +} + +export default function ToolOverviewView({ segment }: { segment: ToolOverviewSegment }) { + return ( + } + color="border-orange-400 text-orange-700" + bgColor="bg-orange-50" + defaultCollapsed={segment.collapsed} + badge={`${segment.items.length} tools`} + > +
      + {segment.items.map((item, i) => ( + + ))} +
    +     + ) +} diff --git a/src/context/ChatContext.tsx b/src/context/ChatContext.tsx new file mode 100644 index 0000000..ae3b217 --- /dev/null +++ b/src/context/ChatContext.tsx @@ -0,0 +1,43 @@ +import { createContext, useContext, useState, type ReactNode } from 'react' +import type { PromptEnvelope } from '../types/protocol' +import { demos } from '../data/demos' + +interface ChatContextValue { + envelope: PromptEnvelope + setEnvelope: (e: PromptEnvelope) => void + demos: typeof demos + activeDemo: number + setActiveDemo: (i: number) => void +} + +const ChatContext = createContext(null) + +export function ChatProvider({ children }: { children: ReactNode }) { + const [activeDemo, setActiveDemo] = useState(3) // Start with comprehensive demo + const [envelope, setEnvelope] = useState(demos[3].envelope) + + const switchDemo = (i: number) => { + setActiveDemo(i) + setEnvelope(demos[i].envelope) + } + + return ( + + {children} + + ) +} + +export function useChat() { + const ctx = useContext(ChatContext) + if (!ctx) throw new Error('useChat must be used within ChatProvider') + return ctx +} diff --git a/src/data/demos.ts b/src/data/demos.ts new file mode 100644 index 0000000..3fd6632 --- /dev/null +++ b/src/data/demos.ts @@ -0,0 +1,624 @@ +import type { PromptEnvelope } from '../types/protocol' + +export interface DemoScenario { + id: string + label: string + description: string + envelope: PromptEnvelope +} + +const now = Date.now() + +// ============================================================ +// Scenario A: Simple chat + system prompt + memory +// ============================================================ +const demoA: PromptEnvelope = { + version: '1.0', + model: 'gpt-4-turbo', + messages: [ + { + id: 'a-1', + role: 'system', + segments: [ + { + kind: 'system_prompt', + 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。 +回答应简洁、有结构，鼓励学生从用户体验角度分析问题。 +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。`, + collapsed: true, + }, + { + kind: 'memory', + items: [ + { + title: '用户背景', + content: '设计系研二学生，正在做 HCI 课程设计，关注 LLM 交互的透明性', + }, + { + title: '偏好', + content: '喜欢简洁的表达，反感术语堆砌。倾向用图示辅助理解。', + }, + { + title: '上次对话', + content: '讨论过 chatbox UI 过度封装的问题，确认了 9 种需要区分的 prompt 类型', + }, + ], + collapsed: true, + }, + { + kind: 'tool_overview', + items: [ + { + name: 'search', + description: '搜索学术文献和设计案例', + parameters: 'query: string, limit?: number', + schema: { + type: 'object', + properties: { + query: { type: 'string', description: '搜索关键词' }, + limit: { type: 'number', description: '返回结果数量上限' }, + }, + required: ['query'], + }, + }, + { + name: 'get_example', + description: '获取 UI 设计案例截图和说明', + parameters: 'topic: string, count?: number', + schema: { + type: 'object', + properties: { + topic: { type: 'string', description: '设计主题' }, + count: { type: 'number', description: '案例数量' }, + }, + required: ['topic'], + }, + }, + ], + collapsed: true, + }, + ], + timestamp: now - 300000, + }, + { + id: 'a-2', + role: 'user', + segments: [ + { + kind: 'static_var', + name: 'user_name', + value: '小明', + }, + { + kind: 'text', + 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？', + }, + ], + timestamp: now - 240000, + }, + { + id: 'a-3', + role: 'assistant', + segments: [ + { + kind: 'text', + content: + '我觉得你的 9 种分类很全面！从信息架构的角度看，你已经覆盖了 LLM 上下文的三个主要来源：\n\n1. **静态配置**（变量、system prompt）\n2. **能力声明**（skills、tools）\n3. **动态输入**（文档、长文本、多模态）\n\n加上工具调用的过程性信息，形成了一个完整的上下文可见性模型。这种分类本身就值得在课程设计中展开讨论。', + }, + ], + timestamp: now - 180000, + }, + ], +} + +// ============================================================ +// Scenario B: Tool call flow (request → result) +// ============================================================ +const demoB: PromptEnvelope = { + version: '1.0', + model: 'gpt-4-turbo', + messages: [ + { + id: 'b-1', + role: 'system', + segments: [ + { + kind: 'system_prompt', + content: + '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。', + collapsed: true, + }, + { + kind: 'tool_overview', + items: [ + { + name: 'run_query', + description: '执行 SQL 查询', + parameters: 'sql: string', + schema: { + type: 'object', + properties: { + sql: { type: 'string', description: 'SQL 查询语句' }, + }, + required: ['sql'], + }, + }, + { + name: 'plot_chart', + description: '生成图表', + parameters: 'type: string, data: object, output_format?: string', + schema: { + type: 'object', + properties: { + type: { type: 'string', enum: ['line', 'bar', 'scatter'], description: '图表类型' }, + title: { type: 'string', description: '图表标题' }, + x_label: { type: 'string', description: 'X 轴标签' }, + y_label: { type: 'string', description: 'Y 轴标签' }, + data: { type: 'array', description: '数据点数组' }, + output_format: { type: 'string', enum: ['png', 'svg'], description: '输出格式' }, + }, + required: ['type', 'data', 'output_format'], + }, + }, + { + name: 'fetch_data', + description: '获取远程数据', + parameters: 'url: string, format: string', + schema: { + type: 'object', + properties: { + url: { type: 'string', description: '数据 URL' }, + format: { type: 'string', enum: ['json', 'csv'], description: '数据格式' }, + }, + required: ['url', 'format'], + }, + }, + ], + collapsed: true, + }, + ], + timestamp: now - 200000, + }, + { + id: 'b-2', + role: 'user', + segments: [ + { + kind: 'text', + content: '帮我看看过去一周的用户注册数据，按天统计，用折线图展示趋势。', + }, + ], + timestamp: now - 180000, + }, + { + id: 'b-3', + role: 'assistant', + segments: [ + { + kind: 'text', + content: '好的，我先查询数据库获取注册数据。', + }, + { + kind: 'tool_call_request', + toolName: 'run_query', + arguments: { + sql: `SELECT DATE(created_at) as date, COUNT(*) as count +FROM users +WHERE created_at >= DATE('now', '-7 days') +GROUP BY DATE(created_at) +ORDER BY date`, + }, + collapsed: false, + }, + ], + timestamp: now - 160000, + }, + { + id: 'b-4', + role: 'assistant', + segments: [ + { + kind: 'tool_call_result', + toolName: 'run_query', + success: true, + result: `[ + {"date": "2026-06-01", "count": 42}, + {"date": "2026-06-02", "count": 38}, + {"date": "2026-06-03", "count": 55}, + {"date": "2026-06-04", "count": 47}, + {"date": "2026-06-05", "count": 61}, + {"date": "2026-06-06", "count": 73}, + {"date": "2026-06-07", "count": 58} +]`, + collapsed: true, + }, + ], + timestamp: now - 140000, + }, + { + id: 'b-5', + role: 'assistant', + segments: [ + { + kind: 'text', + content: '查询成功。现在生成折线图——', + }, + { + kind: 'tool_call_request', + toolName: 'plot_chart', + arguments: { + type: 'line', + title: 'Daily User Registrations (Past 7 Days)', + x_label: 'Date', + y_label: 'New Users', + data: [ + { date: '06-01', count: 42 }, + { date: '06-02', count: 38 }, + { date: '06-03', count: 55 }, + { date: '06-04', count: 47 }, + { date: '06-05', count: 61 }, + { date: '06-06', count: 73 }, + { date: '06-07', count: 58 }, + ], + }, + collapsed: false, + }, + ], + timestamp: now - 130000, + }, + { + id: 'b-6', + role: 'assistant', + segments: [ + { + kind: 'tool_call_result', + toolName: 'plot_chart', + success: false, + result: 'Error: plot_chart requires "output_format" parameter (png | svg). Please retry with format specified.', + collapsed: false, + }, + ], + timestamp: now - 120000, + }, + ], +} + +// ============================================================ +// Scenario C: Long text + document + image +// ============================================================ +const longArticleContent_C = '# 大语言模型交互中的上下文透明性问题\n\n## 摘要\n\n近年来，以 ChatGPT 为代表的对话式 AI 产品迅速普及。然而，这些产品的交互设计普遍存在"上下文不透明"的问题——用户无法了解模型在生成回复时参考了哪些信息、使用了哪些工具、被施加了怎样的约束。\n\n## 1. 问题定义\n\n当前的聊天界面（chatbox UI）将 LLM 的完整上下文封装在黑盒之中。用户看到的是一个"魔法对话框"：输入问题，得到回答。但这个过程掩盖了大量关键信息：\n\n- **System Prompt**：模型的行为准则和角色设定，直接决定了回复的风格和边界\n- **User Memory**：跨对话持久化的用户信息，可能包含过时或不准确的记忆\n- **Tools & Skills**：模型可调用的外部能力，用户可能完全不知道它们的存在\n- **Variable Injection**：模板变量在用户不知情的情况下被替换为具体值\n\n这种不透明性导致了一系列用户体验问题：信任缺失、纠错困难、意外行为难以解释。\n\n## 2. 设计目标\n\n本文提出一套"Prompt Envelope Protocol"——一种结构化的 prompt 表达格式，使得：\n\n1. 每种上下文元素都有明确的视觉呈现\n2. 用户可以按需展开或折叠细节\n3. 协议可以无损导出为标准 API 格式\n4. 视觉语言保持简约，不增加认知负荷\n\n## 3. 核心设计原则\n\n### 3.1 信息密度梯度\n\n核心对话文本始终可见，元信息默认折叠。用户不会在每次对话中都被无关的 system prompt 和工具列表淹没。\n\n### 3.2 颜色编码系统\n\n每种上下文类型有独立的颜色标记，形成可学习的视觉语言：\n- 蓝色 = 变量\n- 灰色 = 系统指令\n- 紫色 = 用户记忆\n- 绿色 = 技能\n- 橙色 = 工具\n\n### 3.3 协议即视图\n\n折叠状态存储在协议数据中而非 UI 状态中。这意味着相同的协议数据在任何渲染器下都产生相同的视图——协议本身就是 view model。' + +const demoC: PromptEnvelope = { + version: '1.0', + model: 'gpt-4-turbo', + messages: [ + { + id: 'c-1', + role: 'system', + segments: [ + { + 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。', + collapsed: true, + }, + { + kind: 'skills', + items: [ + { name: 'summarize', description: '生成文档摘要' }, + { name: 'translate', description: '翻译文档内容' }, + { name: 'qa', description: '基于文档回答具体问题' }, + ], + collapsed: true, + }, + ], + timestamp: now - 150000, + }, + { + id: 'c-2', + role: 'user', + segments: [ + { + kind: 'text', + content: '帮我审阅这篇论文草稿，看看结构上有什么问题：', + }, + { + kind: 'long_text', + content: longArticleContent_C, + charCount: longArticleContent_C.length, + collapsed: true, + }, + { + kind: 'document', + fileName: 'hci-paper-draft.pdf', + mimeType: 'application/pdf', + snippet: + '# 大语言模型交互中的上下文透明性问题\n\n## 摘要\n\n近年来，以 ChatGPT 为代表的对话式 AI 产品迅速普及。然而，这些产品的交互设计普遍存在"上下文不透明"的问题——用户无法了解模型在生成回复时参考了哪些信息...', + sizeBytes: 245760, + }, + { + kind: 'media', + mediaType: 'image', + url: '', + altText: '论文框架图：Context Layers 分层示意图', + }, + ], + timestamp: now - 120000, + }, + { + id: 'c-3', + role: 'assistant', + segments: [ + { + kind: 'text', + content: + '我读完了你的草稿。整体框架很清晰，但有几个建议：\n\n1. **第3节的设计原则**是目前最强的部分，可以考虑将这部分提前到第2节\n2. "信息密度梯度"这个概念很有原创性，建议在摘要中就提及\n3. 缺少用户研究部分——如果你有做可用性测试的计划，可以加一节"4. 评估方法"\n4. 颜色编码系统部分写得很好，可以加一个视觉化的表格来展示颜色-类型映射\n\n需要我展开其中某一点吗？', + }, + ], + timestamp: now - 60000, + }, + ], +} + +// ============================================================ +// Scenario D: Comprehensive — all 9 segments +// ============================================================ +const comprehensiveArticleContent = '在过去的18个月里，我们对127名LLM聊天产品用户进行了纵向研究。研究分为三个阶段：基线观察期（3个月）、干预实验期（6个月）、后续跟踪期（9个月）。在干预实验期，我们为实验组用户提供了一套上下文可视化工具，包括：system prompt查看面板、memory编辑界面、tool call实时展示和long text折叠功能。对照组使用标准的聊天界面。\n\n实验组在以下维度上表现出显著改善：\n- 任务完成率提升 23.4%（p < 0.01）\n- 纠错响应时间缩短 41.7%（p < 0.001）\n- 用户信任度评分从 3.2/5 提升至 4.1/5\n- 对话轮次平均减少 2.8 轮（更高效的信息交换）\n\n这些结果表明上下文透明性不仅仅是"nice to have"的设计细节，而是直接影响LLM交互效率的关键因素。特别是在以下场景中效果最为显著：\n1. 长文档分析：用户能够看到哪些文档片段被模型引用\n2. 多工具调用：工具链的可视化帮助用户理解推理过程\n3. 跨会话任务：memory可见性减少重复说明\n\n我们建议将上下文透明性作为LLM聊天产品的基础设计原则，而非可选特性。' + +const demoD: PromptEnvelope = { + version: '1.0', + model: 'gpt-4-turbo', + messages: [ + // --- System message with all structural segments --- + { + id: 'd-1', + role: 'system', + segments: [ + { + 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。 + +核心原则： +- 鼓励从用户体验角度分析，而非技术实现角度 +- 用具体例子说明抽象概念 +- 如果学生的方案有改进空间，以提问的方式引导而非直接批评 +- 始终记住你拥有工具调用、skills 和跨对话 memory 能力，但不必每次都全部用到`, + collapsed: true, + }, + { + kind: 'memory', + items: [ + { + title: '用户身份', + content: '小明，设计系研二，HCI 方向。正在做课程设计项目。', + }, + { + title: '项目背景', + content: '设计一个透明化 LLM 上下文的聊天协议。已确定了 9 种 prompt 类型的分类方案。', + }, + { + title: '沟通偏好', + content: '喜欢用图示和表格辅助理解。反感过度术语化。需要看到具体例子。', + }, + { + title: '上次进度', + content: '用户已确认了 MVP 范围：Web 应用，数据协议+视觉规范，可导出 OpenAI Format。', + }, + ], + collapsed: true, + }, + { + kind: 'skills', + items: [ + { name: 'deep-research', description: '深度研究 — 多源搜索、交叉验证、生成引用报告' }, + { name: 'code-review', description: '审查代码变更，发现正确性问题和简化机会' }, + { name: 'simplify', description: '审查代码的复用性、简洁性和效率，并应用修复' }, + { name: 'verify', description: '运行应用并观察行为来验证变更是否正确' }, + ], + collapsed: true, + }, + { + kind: 'tool_overview', + items: [ + { + name: 'search', + description: '搜索学术文献和设计案例', + parameters: 'query: string, limit?: number', + schema: { + type: 'object', + properties: { + query: { type: 'string', description: '搜索关键词' }, + limit: { type: 'number', description: '返回结果数量' }, + }, + required: ['query'], + }, + }, + { + name: 'read_file', + description: '读取文件内容', + parameters: 'path: string', + schema: { + type: 'object', + properties: { + path: { type: 'string', description: '文件路径' }, + }, + required: ['path'], + }, + }, + { + name: 'fetch_url', + description: '获取网页内容并转为 markdown', + parameters: 'url: string', + schema: { + type: 'object', + properties: { + url: { type: 'string', description: '网页 URL' }, + }, + required: ['url'], + }, + }, + { + name: 'run_code', + description: '在沙箱中执行代码', + parameters: 'language: string, code: string', + schema: { + type: 'object', + properties: { + language: { type: 'string', enum: ['python', 'javascript', 'r'], description: '编程语言' }, + code: { type: 'string', description: '代码内容' }, + }, + required: ['language', 'code'], + }, + }, + ], + collapsed: true, + }, + ], + timestamp: now - 600000, + }, + // --- User message 1 --- + { + 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。', + }, + { + kind: 'long_text', + content: comprehensiveArticleContent, + charCount: comprehensiveArticleContent.length, + collapsed: true, + }, + { + kind: 'document', + fileName: 'context-transparency-study-2025.pdf', + mimeType: 'application/pdf', + snippet: + 'DOI: 10.1145/3613904.3642000\n\nContext Transparency in LLM-Powered Chat Interfaces: A Longitudinal Study with 127 Users\n\nIn the past 18 months, we conducted a longitudinal study...', + sizeBytes: 2457600, + }, + { + kind: 'media', + mediaType: 'image', + url: '', + altText: 'Fig 3: 实验组 vs 对照组任务完成率对比图（p<0.01）', + }, + ], + timestamp: now - 500000, + }, + // --- Assistant response --- + { + id: 'd-3', + role: 'assistant', + segments: [ + { + kind: 'text', + content: '这是一篇非常有力的参考文献！它恰恰支持了你的核心论点——上下文透明性是"基础设计原则，而非可选特性"。', + }, + ], + timestamp: now - 480000, + }, + // --- Assistant tool call --- + { + id: 'd-4', + role: 'assistant', + segments: [ + { + kind: 'tool_call_request', + toolName: 'search', + arguments: { + query: 'LLM context transparency HCI chat interface user study 2024 2025', + limit: 5, + }, + collapsed: false, + }, + ], + timestamp: now - 470000, + }, + { + id: 'd-5', + role: 'assistant', + segments: [ + { + kind: 'tool_call_result', + toolName: 'search', + success: true, + result: `Found 5 results: + +1. "Transparent AI: Designing Explainable Chat Interfaces" — CHI 2024 + → 提出了"分层透明度"框架，与本项目的"信息密度梯度"高度一致 + +2. "User Mental Models of LLM Context" — CSCW 2025 + → 发现 78% 的用户低估了 system prompt 对输出的影响 + +3. "Folding as a Visual Strategy for Complex Chat UIs" — DIS 2024 + → 验证了折叠/展开对降低认知负荷的效果 + +4. "Beyond the Black Box: Visualizing LLM Reasoning in Chat" — TOCHI 2025 + → 工具调用可视化的用户研究，与本项目的 tool call request/result 设计一致 + +5. "Memory-Aware Interfaces for Persistent LLM Interactions" — IUI 2025 + → 讨论了用户记忆的可编辑性和可遗忘性`, + collapsed: true, + }, + ], + timestamp: now - 450000, + }, + // --- Assistant final response --- + { + id: 'd-6', + role: 'assistant', + segments: [ + { + kind: 'text', + content: `搜索结果显示，你的研究方向和当前学术界的热点高度一致。以下是我对文献支持度的评估： + +**强相关（可直接引用）：** +- 第2篇（CSCW 2025）直接量化了用户对 LLM 上下文的理解不足——这是你"问题定义"部分的关键论据 +- 第3篇（DIS 2024）为你的"折叠设计"提供了实证基础 + +**建议阅读方向：** +- 第1篇的"分层透明度"框架可以与你的 9 种类型分类做对比讨论 +- 第5篇的 memory 可编辑性可能是你下一个值得探索的方向 + +这篇研究报告 + 这5篇文献构成了一个很好的文献基础。需要我帮你整理成引用格式吗？`, + }, + ], + timestamp: now - 400000, + }, + ], +} + +export const demos: DemoScenario[] = [ + { + id: 'a', + label: '场景 A', + description: '基础对话 + System Prompt + Memory', + envelope: demoA, + }, + { + id: 'b', + label: '场景 B', + description: '工具调用：请求 → 执行（成功 & 失败）', + envelope: demoB, + }, + { + id: 'c', + label: '场景 C', + description: '长文本 + 文档附件 + 多模态', + envelope: demoC, + }, + { + id: 'd', + label: '场景 D ⭐', + description: '综合：全部 9 种 Segment', + envelope: demoD, + }, +] diff --git a/src/index.css b/src/index.css new file mode 100644 index 0000000..0ebab97 --- /dev/null +++ b/src/index.css @@ -0,0 +1,22 @@ +@tailwind base; +@tailwind components; +@tailwind utilities; + +body { + margin: 0; + font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif; +} + +/* Smooth collapse animation */ +.collapsible-content { + overflow: hidden; + transition: max-height 0.25s ease-in-out, opacity 0.2s ease; +} +.collapsible-content.collapsed { + max-height: 0; + opacity: 0; +} +.collapsible-content.expanded { + max-height: 2000px; + opacity: 1; +} diff --git a/src/main.tsx b/src/main.tsx new file mode 100644 index 0000000..964aeb4 --- /dev/null +++ b/src/main.tsx @@ -0,0 +1,10 @@ +import React from 'react' +import ReactDOM from 'react-dom/client' +import App from './App' +import './index.css' + +ReactDOM.createRoot(document.getElementById('root')!).render( + + + , +) diff --git a/src/types/protocol.ts b/src/types/protocol.ts new file mode 100644 index 0000000..25da220 --- /dev/null +++ b/src/types/protocol.ts @@ -0,0 +1,123 @@ +// ============================================================ +// Prompt Envelope Protocol — Type Definitions +// ============================================================ + +// --- 顶层信封 --- +export interface PromptEnvelope { + version: '1.0' + model?: string // 导出时使用的 model 名称，如 'gpt-4-turbo' + messages: Message[] +} + +// --- 单条消息 --- +export interface Message { + id: string + role: 'system' | 'user' | 'assistant' + segments: Segment[] + timestamp: number +} + +// --- Segment 联合类型 --- +export type Segment = + | TextSegment + | StaticVarSegment + | SystemPromptSegment + | MemorySegment + | SkillSegment + | ToolOverviewSegment + | ToolCallRequestSegment + | ToolCallResultSegment + | DocumentSegment + | LongTextSegment + | MediaSegment + +// --- 各 Segment 类型 --- + +export interface TextSegment { + kind: 'text' + content: string +} + +export interface StaticVarSegment { + kind: 'static_var' + name: string // e.g. "user_name" + value: string // e.g. "张三" +} + +export interface SystemPromptSegment { + kind: 'system_prompt' + content: string + collapsed: boolean // default: true +} + +export interface MemorySegment { + kind: 'memory' + items: MemoryItem[] + collapsed: boolean +} + +export interface MemoryItem { + title: string + content: string +} + +export interface SkillSegment { + kind: 'skills' + items: SkillItem[] + collapsed: boolean +} + +export interface SkillItem { + name: string + description: string +} + +export interface ToolOverviewSegment { + kind: 'tool_overview' + items: ToolItem[] + collapsed: boolean +} + +export interface ToolItem { + name: string + description: string + parameters: string // 人类可读的参数摘要 + schema?: Record // JSON Schema — 导出时作为 tools[].function.parameters +} + +export interface ToolCallRequestSegment { + kind: 'tool_call_request' + toolName: string + arguments: Record + collapsed: boolean // default: false +} + +export interface ToolCallResultSegment { + kind: 'tool_call_result' + toolName: string + result: string // 摘要文本 + success: boolean + collapsed: boolean // default: true +} + +export interface DocumentSegment { + kind: 'document' + fileName: string + mimeType: string + snippet: string // 前 200 字符预览 + sizeBytes: number +} + +export interface LongTextSegment { + kind: 'long_text' + content: string + charCount: number + collapsed: boolean // default: true +} + +export interface MediaSegment { + kind: 'media' + mediaType: 'image' | 'audio' | 'video' + url: string + altText?: string +} diff --git a/src/utils/export.ts b/src/utils/export.ts new file mode 100644 index 0000000..ff99c10 --- /dev/null +++ b/src/utils/export.ts @@ -0,0 +1,249 @@ +import type { PromptEnvelope, Segment, ToolItem } from '../types/protocol' + +// --- OpenAI Chat Completions API request shape --- + +export interface OpenAIToolCall { + id: string + type: 'function' + function: { + name: string + arguments: string // JSON-encoded + } +} + +export interface OpenAIMessage { + role: 'system' | 'user' | 'assistant' | 'tool' + content?: string | null + tool_calls?: OpenAIToolCall[] + tool_call_id?: string +} + +export interface OpenAITool { + type: 'function' + function: { + name: string + description: string + parameters: Record // JSON Schema + } +} + +/** + * The full OpenAI Chat Completions request body + * (minus stream, temperature etc. which are out of scope for MVP). + */ +export interface OpenAIExport { + model: string + messages: OpenAIMessage[] + tools?: OpenAITool[] +} + +// --- Helpers --- + +function formatBytes(bytes: number): string { + if (bytes < 1024) return `${bytes}B` + if (bytes < 1024 * 1024) return `${(bytes / 1024).toFixed(1)}KB` + return `${(bytes / (1024 * 1024)).toFixed(1)}MB` +} + +/** + * Convert a "text-like" segment to its plain-text representation. + * Returns null for structural segments (system/memory/skills/tool_overview) + * and for tool_call segments (handled structurally in exportToOpenAIFormat). + */ +export function segmentToText(seg: Segment): string | null { + switch (seg.kind) { + case 'text': + return seg.content + + case 'static_var': + return seg.value + + case 'system_prompt': + case 'memory': + case 'skills': + case 'tool_overview': + return null + + case 'tool_call_request': + case 'tool_call_result': + return null + + case 'document': + return `[Document: ${seg.fileName} (${formatBytes(seg.sizeBytes)})]\n${seg.snippet}` + + case 'long_text': + return seg.content + + case 'media': + return seg.altText ?? `[${seg.mediaType}]` + + default: + return null + } +} + +/** Render a structural segment into text for the system message */ +function formatStructural(seg: Segment): string | null { + switch (seg.kind) { + case 'system_prompt': + return `[System Prompt]\n${seg.content}` + case 'memory': + return `[Memory]\n${seg.items.map(i => `- ${i.title}: ${i.content}`).join('\n')}` + case 'skills': + return `[Skills]\n${seg.items.map(i => `- /${i.name}: ${i.description}`).join('\n')}` + case 'tool_overview': + return `[Available Tools]\n${seg.items.map(i => `- ${i.name}: ${i.description}`).join('\n')}` + default: + return null + } +} + +/** + * Convert a ToolItem (from tool_overview) into an OpenAI Tool definition. + */ +function toolItemToOpenAI(item: ToolItem): OpenAITool { + return { + type: 'function', + function: { + name: item.name, + description: item.description, + parameters: (item.schema as Record) ?? { + type: 'object', + properties: {}, + }, + }, + } +} + +// --- Main export function --- + +/** + * Export a PromptEnvelope to an OpenAI Chat Completions request body. + * + * Mapping: + * + * Protocol Segment → OpenAI Representation + * ─────────────────────────────────────────────────────── + * text → message.content + * static_var → expanded value in content + * system_prompt → system message content + * memory → system message content + * skills → system message content + * tool_overview → top-level tools[] array + * tool_call_request → assistant message with tool_calls[] + * tool_call_result → tool-role message with tool_call_id + * document → content with [Document: …] annotation + * long_text → content (full text) + * media → content with altText / [type] placeholder + */ +export function exportToOpenAIFormat(envelope: PromptEnvelope): OpenAIExport { + const messages: OpenAIMessage[] = [] + const systemParts: string[] = [] + const tools: OpenAITool[] = [] + + let callCounter = 0 + const nextCallId = () => `call_${String(++callCounter).padStart(4, '0')}` + const pendingCallIds: Map = new Map() + + for (const msg of envelope.messages) { + // ── System ── + if (msg.role === 'system') { + 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 { + const t = segmentToText(seg) + if (t !== null) contentParts.push(t) + const s = formatStructural(seg) + if (s && !t) contentParts.push(s) + } + } + const content = contentParts.filter(Boolean).join('\n') + if (content.trim()) { + systemParts.push(content) + } + continue + } + + // ── User ── + if (msg.role === 'user') { + for (const seg of msg.segments) { + if (seg.kind === 'tool_overview') { + seg.items.forEach(item => tools.push(toolItemToOpenAI(item))) + } + const s = formatStructural(seg) + if (s) systemParts.push(s) + } + const content = msg.segments + .map(segmentToText) + .filter(Boolean) + .join('\n') + if (content.trim()) { + messages.push({ role: 'user', content }) + } + continue + } + + // ── Assistant ── + if (msg.role === 'assistant') { + const textParts: string[] = [] + const toolCalls: OpenAIToolCall[] = [] + + for (const seg of msg.segments) { + if (seg.kind === 'tool_call_request') { + const callId = nextCallId() + const queue = pendingCallIds.get(seg.toolName) || [] + queue.push(callId) + pendingCallIds.set(seg.toolName, queue) + + toolCalls.push({ + id: callId, + type: 'function', + function: { + name: seg.toolName, + arguments: JSON.stringify(seg.arguments), + }, + }) + } else if (seg.kind === 'tool_call_result') { + const queue = pendingCallIds.get(seg.toolName) + const callId = queue?.shift() || nextCallId() + + messages.push({ + role: 'tool', + tool_call_id: callId, + content: seg.result, + }) + } else if (seg.kind === 'tool_overview') { + seg.items.forEach(item => tools.push(toolItemToOpenAI(item))) + } else { + const t = segmentToText(seg) + if (t) textParts.push(t) + } + } + + if (textParts.length > 0 || toolCalls.length > 0) { + messages.push({ + role: 'assistant', + content: textParts.length > 0 ? textParts.join('\n') : null, + ...(toolCalls.length > 0 ? { tool_calls: toolCalls } : {}), + }) + } + } + } + + // Prepend merged system message + if (systemParts.length > 0) { + messages.unshift({ role: 'system', content: systemParts.join('\n\n') }) + } + + return { + model: envelope.model ?? 'gpt-4-turbo', + messages, + ...(tools.length > 0 ? { tools } : {}), + } +} diff --git a/tailwind.config.js b/tailwind.config.js new file mode 100644 index 0000000..dca8ba0 --- /dev/null +++ b/tailwind.config.js @@ -0,0 +1,11 @@ +/** @type {import('tailwindcss').Config} */ +export default { + content: [ + "./index.html", + "./src/**/*.{js,ts,jsx,tsx}", + ], + theme: { + extend: {}, + }, + plugins: [], +} diff --git a/tsconfig.json b/tsconfig.json new file mode 100644 index 0000000..75e2ff7 --- /dev/null +++ b/tsconfig.json @@ -0,0 +1,21 @@ +{ + "compilerOptions": { + "target": "ES2020", + "useDefineForClassFields": true, + "lib": ["ES2020", "DOM", "DOM.Iterable"], + "module": "ESNext", + "skipLibCheck": true, + "moduleResolution": "bundler", + "allowImportingTsExtensions": true, + "isolatedModules": true, + "moduleDetection": "force", + "noEmit": true, + "jsx": "react-jsx", + "strict": true, + "noUnusedLocals": false, + "noUnusedParameters": false, + "noFallthroughCasesInSwitch": true, + "forceConsistentCasingInFileNames": true + }, + "include": ["src"] +} diff --git a/vite.config.ts b/vite.config.ts new file mode 100644 index 0000000..9ffcc67 --- /dev/null +++ b/vite.config.ts @@ -0,0 +1,6 @@ +import { defineConfig } from 'vite' +import react from '@vitejs/plugin-react' + +export default defineConfig({ + plugins: [react()], +})