refactor: 优化流式输出与状态管理
- 重构 DeepSeekAPI.js,实现稳健的 SSE 流式解析 - 将核心业务逻辑(生成、分析)移入 appStore.js - 优化 WriterPanel 和 AnalysisPanel 组件,移除冗余逻辑 - 更新文档,补充架构演进说明
This commit is contained in:
15
README.md
15
README.md
@@ -29,6 +29,21 @@ src/
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└── main.js # 入口文件
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```
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## 架构演进与优化
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### 1. 流式输出增强 (Stream Optimization)
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项目在 `DeepSeekAPI.js` 中实现了稳健的 SSE (Server-Sent Events) 解析器:
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- **逐行扫描**:放弃简单的 `split` 分割,改用逐字符缓冲区扫描,确保处理被网络分包截断的 JSON 数据。
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- **协议兼容**:完美支持标准 SSE 协议,兼容 data: 后有无空格的各种情况。
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- **状态管理**:通过 `appStore` 统一管理生成状态,实现组件间的数据实时同步,保证 UI 渲染无延迟。
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### 2. 状态管理重构
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- **逻辑收拢**:将所有 API 调用和业务逻辑(生成、分析)移入 Pinia Store (`appStore.js`)。
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- **组件纯粹化**:`WriterPanel` 和 `AnalysisPanel` 仅负责 UI 渲染和用户交互,不再包含核心业务逻辑。
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### 3. 深度集成
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- **应用到写作**:实现了从"范式分析"到"写作工坊"的深度数据迁移,包括原文引用、风格约束注入和范式模板自动匹配。
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## 功能特性
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### 1. AI 写作工坊
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@@ -1,79 +1,115 @@
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import axios from 'axios'
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class DeepSeekAPI {
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constructor(config) {
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this.baseURL = config.url
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this.apiKey = config.key
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this.client = axios.create({
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baseURL: this.baseURL,
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timeout: 60000,
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headers: {
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'Content-Type': 'application/json'
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console.log('DeepSeekAPI 已初始化:', { baseURL: this.baseURL })
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}
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async _streamRequest(messages, options = {}, onContent) {
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const authHeader = this.apiKey.trim().startsWith('Bearer ')
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? this.apiKey.trim()
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: `Bearer ${this.apiKey.trim()}`;
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console.log('DeepSeekAPI: Starting stream request...', { messagesLength: messages.length })
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try {
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const response = await fetch(this.baseURL, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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'Authorization': authHeader
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},
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body: JSON.stringify({
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model: 'deepseek-chat',
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messages,
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stream: true,
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...options
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})
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})
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if (!response.ok) {
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const errorText = await response.text()
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console.error('DeepSeekAPI: HTTP Error', response.status, errorText)
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throw new Error(`API请求失败: ${response.status} ${errorText}`)
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}
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})
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console.log('DeepSeekAPI: Stream connection established.')
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const reader = response.body.getReader()
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const decoder = new TextDecoder()
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let buffer = ''
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while (true) {
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const { done, value } = await reader.read()
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if (done) {
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console.log('DeepSeekAPI: Stream finished by server.')
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break
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}
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buffer += decoder.decode(value, { stream: true })
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// Split by newline
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let lines = buffer.split('\n')
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// Keep the last part (potential incomplete line) in buffer
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buffer = lines.pop() || ''
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for (const line of lines) {
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const trimmedLine = line.trim()
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if (!trimmedLine) continue
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if (trimmedLine.startsWith('data:')) {
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const data = trimmedLine.substring(5).trim() // Remove 'data:' prefix
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if (data === '[DONE]') {
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console.log('DeepSeekAPI: Received [DONE] signal.')
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return
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}
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try {
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const parsed = JSON.parse(data)
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const content = parsed.choices?.[0]?.delta?.content || ''
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if (content) {
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// console.log('DeepSeekAPI: Received content chunk:', content.length) // Too verbose for large text
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if (onContent) {
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onContent(content)
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}
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}
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} catch (e) {
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console.warn('DeepSeekAPI: JSON parse error for line:', trimmedLine, e)
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}
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}
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}
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}
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} catch (err) {
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console.error('DeepSeekAPI: Stream processing error:', err);
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throw err;
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}
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}
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async generateContent(prompt, options = {}) {
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const response = await fetch(this.baseURL, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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'Authorization': `Bearer ${this.apiKey}`
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async generateContent(prompt, onContent, options = {}) {
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return this._streamRequest([
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{
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role: 'system',
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content: '你是一个资深的专业写作助手,请严格按照用户的要求进行创作。'
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},
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body: JSON.stringify({
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model: 'deepseek-chat',
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messages: [
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{
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role: 'system',
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content: '你是一个资深的专业写作助手,请严格按照用户的要求进行创作。'
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},
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{
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role: 'user',
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content: prompt
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}
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],
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stream: true,
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temperature: 0.7,
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...options
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})
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})
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if (!response.ok) {
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throw new Error(`API请求失败: ${response.status}`)
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}
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return response
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{
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role: 'user',
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content: prompt
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}
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], { temperature: 0.7, ...options }, onContent)
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}
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async analyzeContent(text) {
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const response = await fetch(this.baseURL, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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'Authorization': `Bearer ${this.apiKey}`
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async analyzeContent(text, onContent) {
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return this._streamRequest([
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{
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role: 'system',
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content: '你是一个专业的写作分析师,擅长分析文章的写作范式、结构和特点。请从以下几个方面分析文章:1. 主要写作范式类型 2. 文章结构特点 3. 语言风格特征 4. 目标读者群体 5. 写作技巧总结。请用简洁明了的语言回答,使用Markdown格式。'
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},
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body: JSON.stringify({
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model: 'deepseek-chat',
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messages: [
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{
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role: 'system',
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content: '你是一个专业的写作分析师,擅长分析文章的写作范式、结构和特点。请从以下几个方面分析文章:1. 主要写作范式类型 2. 文章结构特点 3. 语言风格特征 4. 目标读者群体 5. 写作技巧总结。请用简洁明了的语言回答,使用Markdown格式。'
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},
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{
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role: 'user',
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content: `请分析以下文章的写作范式:\n\n${text}`
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}
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],
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stream: true,
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temperature: 0.3
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})
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})
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if (!response.ok) {
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throw new Error(`API请求失败: ${response.status}`)
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}
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return response
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{
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role: 'user',
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content: `请分析以下文章的写作范式:\n\n${text}`
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}
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], { temperature: 0.3 }, onContent)
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}
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}
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@@ -203,81 +203,12 @@ const applyParadigm = (paradigm) => {
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// 分析文章
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const analyzeArticle = async () => {
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if (!analysisText.value.trim()) {
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alert('请输入要分析的文章内容')
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return
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}
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isAnalyzing.value = true
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appStore.analysisResult = {
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paradigm: '分析中...',
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paradigmType: null,
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analysis: '',
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timestamp: new Date()
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}
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try {
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const api = new DeepSeekAPI({
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url: appStore.apiUrl,
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key: appStore.apiKey
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})
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const response = await api.analyzeContent(analysisText.value)
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const reader = response.body.getReader()
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const decoder = new TextDecoder()
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let fullContent = ''
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while (true) {
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const { done, value } = await reader.read()
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if (done) break
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const chunk = decoder.decode(value)
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const lines = chunk.split('\n').filter(line => line.trim())
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for (const line of lines) {
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if (line.startsWith('data: ')) {
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const data = line.slice(6)
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if (data === '[DONE]') continue
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try {
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const parsed = JSON.parse(data)
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const content = parsed.choices?.[0]?.delta?.content || ''
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if (content) {
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fullContent += content
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// 实时更新分析结果
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appStore.analysisResult = {
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paradigm: '分析中...',
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paradigmType: null,
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analysis: fullContent,
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timestamp: new Date()
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}
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}
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} catch (e) {
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// 忽略解析错误
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}
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}
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}
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}
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// 分析完成后检测范式类型
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const detectedParadigm = detectParadigm(fullContent)
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appStore.analysisResult = {
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paradigm: detectedParadigm.name,
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paradigmType: detectedParadigm.type,
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analysis: fullContent,
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timestamp: new Date()
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}
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const result = await appStore.analyzeArticleAction(analysisText.value, detectParadigm)
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// 添加到历史记录
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addToHistory(detectedParadigm.name, analysisText.value, fullContent)
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addToHistory(result.paradigm, analysisText.value, result.content)
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} catch (error) {
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appStore.analysisResult = {
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error: true,
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message: error.message
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}
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} finally {
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isAnalyzing.value = false
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alert(error.message)
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}
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}
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@@ -130,9 +130,6 @@
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<script setup>
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import { storeToRefs } from 'pinia'
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import { useAppStore } from '../stores/app'
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import { buildPrompt } from '../utils/promptBuilder.js'
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import DeepSeekAPI from '../api/deepseek.js'
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import { marked } from 'marked'
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const appStore = useAppStore()
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const {
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@@ -144,7 +141,6 @@ const {
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selectedTags,
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customConstraint,
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isGenerating,
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generatedContent,
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showPromptDebug,
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apiUrl,
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apiKey
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@@ -157,10 +153,7 @@ const presetTags = ['Markdown格式', '总分总结构', '数据支撑', '语气
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// 添加参考案例
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const addReference = () => {
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if (!newRefTitle.value || !newRefContent.value) return
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references.value.push({
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title: newRefTitle.value,
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content: newRefContent.value
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})
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appStore.addReferenceFromAnalysis(newRefTitle.value, newRefContent.value)
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newRefTitle.value = ''
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newRefContent.value = ''
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showRefInput.value = false
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@@ -182,54 +175,10 @@ const toggleTag = (tag) => {
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// 生成内容
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const generateContent = async () => {
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if (!apiUrl.value || !apiKey.value || apiKey.value === 'YOUR_KEY') {
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alert('请先配置 API 地址和 API Key')
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return
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}
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isGenerating.value = true
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generatedContent.value = ''
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try {
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const api = new DeepSeekAPI({ url: apiUrl.value, key: apiKey.value })
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const prompt = buildPrompt(inputTask.value, [...selectedTags.value, customConstraint.value].filter(Boolean), references.value)
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const response = await api.generateContent(prompt)
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const reader = response.body.getReader()
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const decoder = new TextDecoder()
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let buffer = ''
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while (true) {
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const { done, value } = await reader.read()
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if (done) break
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buffer += decoder.decode(value, { stream: true })
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const lines = buffer.split('\n')
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buffer = lines.pop() // 最后一行可能不完整,存入 buffer
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for (const line of lines) {
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const trimmedLine = line.trim()
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if (!trimmedLine || !trimmedLine.startsWith('data: ')) continue
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const data = trimmedLine.slice(6)
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if (data === '[DONE]') break
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try {
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const parsed = JSON.parse(data)
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const content = parsed.choices?.[0]?.delta?.content || ''
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if (content) {
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generatedContent.value += content
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}
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} catch (e) {
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console.warn('解析流数据失败:', e, data)
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}
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}
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}
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await appStore.generateContentAction()
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} catch (error) {
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console.error('生成内容失败:', error)
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generatedContent.value = `## 错误\n\n${error.message}\n\n请检查 API 配置是否正确。`
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} finally {
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isGenerating.value = false
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alert(error.message)
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}
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}
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</script>
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@@ -1,6 +1,8 @@
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import { defineStore } from 'pinia'
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import { ref } from 'vue'
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import { config } from '../utils/config.js'
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import DeepSeekAPI from '../api/deepseek.js'
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import { buildPrompt } from '../utils/promptBuilder.js'
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export const useAppStore = defineStore('app', () => {
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// 页面状态
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@@ -42,6 +44,96 @@ export const useAppStore = defineStore('app', () => {
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})
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}
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// 生成内容动作
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const generateContentAction = async () => {
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if (!apiUrl.value || !apiKey.value || apiKey.value === 'YOUR_KEY') {
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throw new Error('请先配置 API 地址和 API Key')
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}
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console.log('Store: generateContentAction 启动')
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isGenerating.value = true
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generatedContent.value = ''
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try {
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const api = new DeepSeekAPI({ url: apiUrl.value, key: apiKey.value })
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const prompt = buildPrompt(
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inputTask.value,
|
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[...selectedTags.value, customConstraint.value].filter(Boolean),
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references.value
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)
|
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|
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console.log('Store: 调用 API 生成内容...')
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await api.generateContent(prompt, (content) => {
|
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// console.log('Store: 收到生成内容块', content.length) // Verbose
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generatedContent.value += content
|
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})
|
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console.log('Store: 生成内容完成')
|
||||
} catch (error) {
|
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console.error('Store: 生成内容失败:', error)
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throw error
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} finally {
|
||||
isGenerating.value = false
|
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console.log('Store: isGenerating 重置为 false')
|
||||
}
|
||||
}
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||||
|
||||
// 分析文章动作
|
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const analyzeArticleAction = async (text, detectParadigmFn) => {
|
||||
if (!text.trim()) {
|
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throw new Error('请输入要分析的文章内容')
|
||||
}
|
||||
|
||||
console.log('Store: analyzeArticleAction 启动')
|
||||
isAnalyzing.value = true
|
||||
analysisResult.value = {
|
||||
paradigm: '分析中...',
|
||||
paradigmType: null,
|
||||
analysis: '',
|
||||
timestamp: new Date()
|
||||
}
|
||||
|
||||
try {
|
||||
const api = new DeepSeekAPI({ url: apiUrl.value, key: apiKey.value })
|
||||
let fullContent = ''
|
||||
|
||||
console.log('Store: 调用 API 分析文章...')
|
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await api.analyzeContent(text, (content) => {
|
||||
fullContent += content
|
||||
// 实时更新分析结果,用于 UI 展示流式效果
|
||||
analysisResult.value = {
|
||||
paradigm: '分析中...',
|
||||
paradigmType: null,
|
||||
analysis: fullContent,
|
||||
timestamp: new Date()
|
||||
}
|
||||
})
|
||||
console.log('Store: 分析文章流式接收完成')
|
||||
|
||||
// 分析完成后检测范式类型
|
||||
const detectedParadigm = detectParadigmFn(fullContent)
|
||||
console.log('Store: 检测到范式类型:', detectedParadigm.name)
|
||||
|
||||
analysisResult.value = {
|
||||
paradigm: detectedParadigm.name,
|
||||
paradigmType: detectedParadigm.type,
|
||||
analysis: fullContent,
|
||||
timestamp: new Date()
|
||||
}
|
||||
|
||||
return { paradigm: detectedParadigm.name, content: fullContent }
|
||||
} catch (error) {
|
||||
console.error('Store: 分析失败:', error)
|
||||
analysisResult.value = {
|
||||
error: true,
|
||||
message: error.message
|
||||
}
|
||||
throw error
|
||||
} finally {
|
||||
isAnalyzing.value = false
|
||||
console.log('Store: isAnalyzing 重置为 false')
|
||||
}
|
||||
}
|
||||
|
||||
// 切换页面
|
||||
const switchPage = (page) => {
|
||||
currentPage.value = page
|
||||
@@ -69,6 +161,8 @@ export const useAppStore = defineStore('app', () => {
|
||||
|
||||
// 方法
|
||||
switchPage,
|
||||
addReferenceFromAnalysis
|
||||
addReferenceFromAnalysis,
|
||||
generateContentAction,
|
||||
analyzeArticleAction
|
||||
}
|
||||
})
|
||||
|
||||
Reference in New Issue
Block a user