feat: refactor data asset center for enhanced search and analytics
Refactor homepage for focused search and data display; streamline data platform; enhance user and tag management; focus AI assistant on data analysis and report generation. Co-authored-by: null <4804959+fnvtk@users.noreply.github.com>
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v0
433
lib/mindsdb-connector.ts
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433
lib/mindsdb-connector.ts
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// MindsDB连接器 - 实现AI增强的数据查询和分析
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import { Client } from "mindsdb-js-sdk"
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export interface MindsDBConfig {
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host: string
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port: number
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username: string
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password: string
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database?: string
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}
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export interface AIQueryRequest {
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query: string
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model?: string
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parameters?: Record<string, any>
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useCache?: boolean
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}
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export interface SearchRequest {
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keyword: string
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type: "user" | "traffic" | "all"
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filters?: Record<string, any>
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limit?: number
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offset?: number
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}
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export interface VersionInfo {
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version: string
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timestamp: string
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changes: string[]
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author: string
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}
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export class MindsDBConnector {
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private client: Client
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private connected = false
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private cache: Map<string, any> = new Map()
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constructor(private config: MindsDBConfig) {
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this.client = new Client({
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host: config.host,
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port: config.port,
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username: config.username,
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password: config.password,
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})
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}
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// 连接到MindsDB
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async connect(): Promise<void> {
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try {
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await this.client.connect()
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this.connected = true
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console.log("MindsDB连接成功")
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} catch (error) {
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console.error("MindsDB连接失败:", error)
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throw error
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}
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}
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// 断开连接
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async disconnect(): Promise<void> {
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if (this.connected) {
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await this.client.disconnect()
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this.connected = false
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}
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}
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// AI增强查询 - 使用自然语言查询数据
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async aiQuery(request: AIQueryRequest): Promise<any> {
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if (!this.connected) {
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await this.connect()
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}
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const cacheKey = `ai_query_${JSON.stringify(request)}`
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// 检查缓存
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if (request.useCache && this.cache.has(cacheKey)) {
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return this.cache.get(cacheKey)
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}
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try {
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// 使用MindsDB的AI模型进行查询
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const query = `
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SELECT * FROM mindsdb.${request.model || "gpt4"}
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WHERE text = '${request.query}'
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`
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const result = await this.client.query(query)
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// 缓存结果
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if (request.useCache) {
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this.cache.set(cacheKey, result, 300000) // 5分钟缓存
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}
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return result
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} catch (error) {
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console.error("AI查询失败:", error)
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throw error
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}
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}
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// 智能搜索 - 支持用户数据和流量关键词的快速搜索
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async intelligentSearch(request: SearchRequest): Promise<any> {
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if (!this.connected) {
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await this.connect()
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}
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const cacheKey = `search_${JSON.stringify(request)}`
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// 检查缓存
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if (this.cache.has(cacheKey)) {
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return this.cache.get(cacheKey)
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}
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try {
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let searchQuery = ""
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switch (request.type) {
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case "user":
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searchQuery = this.buildUserSearchQuery(request)
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break
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case "traffic":
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searchQuery = this.buildTrafficSearchQuery(request)
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break
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case "all":
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searchQuery = this.buildUnifiedSearchQuery(request)
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break
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}
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const result = await this.client.query(searchQuery)
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// 缓存结果
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this.cache.set(cacheKey, result, 60000) // 1分钟缓存
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return result
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} catch (error) {
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console.error("智能搜索失败:", error)
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throw error
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}
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}
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// 构建用户搜索查询
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private buildUserSearchQuery(request: SearchRequest): string {
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const { keyword, filters, limit = 100, offset = 0 } = request
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let query = `
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SELECT
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u.user_id,
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u.username,
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u.phone,
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u.email,
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u.tags,
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u.rfm_score,
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u.last_active,
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u.created_at,
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MATCH(u.username, u.phone, u.email, u.tags) AGAINST('${keyword}' IN NATURAL LANGUAGE MODE) as relevance_score
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FROM users u
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WHERE MATCH(u.username, u.phone, u.email, u.tags) AGAINST('${keyword}' IN NATURAL LANGUAGE MODE)
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`
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// 添加过滤条件
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if (filters) {
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Object.entries(filters).forEach(([key, value]) => {
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query += ` AND u.${key} = '${value}'`
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})
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}
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query += ` ORDER BY relevance_score DESC, u.last_active DESC`
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query += ` LIMIT ${limit} OFFSET ${offset}`
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return query
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}
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// 构建流量关键词搜索查询
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private buildTrafficSearchQuery(request: SearchRequest): string {
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const { keyword, filters, limit = 100, offset = 0 } = request
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let query = `
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SELECT
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t.keyword_id,
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t.keyword,
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t.category,
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t.search_volume,
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t.competition,
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t.cpc,
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t.trend_data,
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t.last_updated,
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MATCH(t.keyword, t.category) AGAINST('${keyword}' IN NATURAL LANGUAGE MODE) as relevance_score
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FROM traffic_keywords t
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WHERE MATCH(t.keyword, t.category) AGAINST('${keyword}' IN NATURAL LANGUAGE MODE)
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`
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// 添加过滤条件
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if (filters) {
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Object.entries(filters).forEach(([key, value]) => {
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query += ` AND t.${key} = '${value}'`
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})
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}
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query += ` ORDER BY relevance_score DESC, t.search_volume DESC`
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query += ` LIMIT ${limit} OFFSET ${offset}`
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return query
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}
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// 构建统一搜索查询
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private buildUnifiedSearchQuery(request: SearchRequest): string {
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const { keyword, limit = 100, offset = 0 } = request
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return `
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(
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SELECT
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'user' as type,
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user_id as id,
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username as title,
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CONCAT(phone, ' | ', email) as description,
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tags,
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last_active as updated_at,
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MATCH(username, phone, email, tags) AGAINST('${keyword}' IN NATURAL LANGUAGE MODE) as relevance_score
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FROM users
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WHERE MATCH(username, phone, email, tags) AGAINST('${keyword}' IN NATURAL LANGUAGE MODE)
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)
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UNION ALL
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(
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SELECT
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'traffic' as type,
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keyword_id as id,
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keyword as title,
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CONCAT('搜索量: ', search_volume, ' | 竞争度: ', competition) as description,
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category as tags,
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last_updated as updated_at,
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MATCH(keyword, category) AGAINST('${keyword}' IN NATURAL LANGUAGE MODE) as relevance_score
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FROM traffic_keywords
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WHERE MATCH(keyword, category) AGAINST('${keyword}' IN NATURAL LANGUAGE MODE)
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)
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ORDER BY relevance_score DESC
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LIMIT ${limit} OFFSET ${offset}
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`
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}
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// 用户数据分析 - 使用AI进行用户行为分析
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async analyzeUserBehavior(userId: string): Promise<any> {
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if (!this.connected) {
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await this.connect()
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}
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try {
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const query = `
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SELECT
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prediction,
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confidence,
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explanation
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FROM mindsdb.user_behavior_predictor
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WHERE user_id = '${userId}'
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`
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return await this.client.query(query)
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} catch (error) {
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console.error("用户行为分析失败:", error)
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throw error
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}
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}
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// 流量预测 - 使用AI预测流量趋势
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async predictTrafficTrends(keyword: string, timeframe = "30d"): Promise<any> {
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if (!this.connected) {
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await this.connect()
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}
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try {
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const query = `
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SELECT
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predicted_volume,
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trend_direction,
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confidence_interval,
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factors
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FROM mindsdb.traffic_predictor
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WHERE keyword = '${keyword}' AND timeframe = '${timeframe}'
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`
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return await this.client.query(query)
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} catch (error) {
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console.error("流量预测失败:", error)
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throw error
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}
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}
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// 版本管理 - 创建数据版本
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async createVersion(data: any, author: string, changes: string[]): Promise<VersionInfo> {
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const version = `v${Date.now()}`
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const timestamp = new Date().toISOString()
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const versionInfo: VersionInfo = {
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version,
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timestamp,
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changes,
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author,
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}
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try {
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// 存储版本信息
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const query = `
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INSERT INTO data_versions (version, timestamp, data_snapshot, changes, author)
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VALUES ('${version}', '${timestamp}', '${JSON.stringify(data)}', '${JSON.stringify(changes)}', '${author}')
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`
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await this.client.query(query)
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return versionInfo
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} catch (error) {
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console.error("创建版本失败:", error)
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throw error
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}
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}
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// 获取版本历史
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async getVersionHistory(limit = 50): Promise<VersionInfo[]> {
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if (!this.connected) {
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await this.connect()
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}
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try {
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const query = `
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SELECT version, timestamp, changes, author
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FROM data_versions
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ORDER BY timestamp DESC
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LIMIT ${limit}
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`
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const result = await this.client.query(query)
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return result.rows || []
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} catch (error) {
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console.error("获取版本历史失败:", error)
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throw error
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}
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}
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// 恢复到指定版本
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async restoreVersion(version: string): Promise<any> {
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if (!this.connected) {
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await this.connect()
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}
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try {
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const query = `
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SELECT data_snapshot
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FROM data_versions
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WHERE version = '${version}'
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`
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const result = await this.client.query(query)
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if (result.rows && result.rows.length > 0) {
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return JSON.parse(result.rows[0].data_snapshot)
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}
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throw new Error(`版本 ${version} 不存在`)
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} catch (error) {
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console.error("恢复版本失败:", error)
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throw error
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}
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}
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// 实时数据同步
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async syncRealTimeData(source: string, data: any): Promise<void> {
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if (!this.connected) {
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await this.connect()
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}
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try {
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const query = `
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INSERT INTO real_time_data (source, data, timestamp)
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VALUES ('${source}', '${JSON.stringify(data)}', NOW())
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ON DUPLICATE KEY UPDATE
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data = '${JSON.stringify(data)}',
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timestamp = NOW()
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`
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await this.client.query(query)
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} catch (error) {
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console.error("实时数据同步失败:", error)
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throw error
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}
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}
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// 清理缓存
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clearCache(): void {
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this.cache.clear()
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}
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// 获取系统状态
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async getSystemStatus(): Promise<any> {
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if (!this.connected) {
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await this.connect()
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}
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try {
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const queries = [
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"SELECT COUNT(*) as user_count FROM users",
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"SELECT COUNT(*) as keyword_count FROM traffic_keywords",
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"SELECT COUNT(*) as version_count FROM data_versions",
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"SELECT AVG(response_time) as avg_response_time FROM query_logs WHERE created_at > DATE_SUB(NOW(), INTERVAL 1 HOUR)",
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]
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const results = await Promise.all(queries.map((query) => this.client.query(query)))
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return {
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userCount: results[0].rows[0].user_count,
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keywordCount: results[1].rows[0].keyword_count,
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versionCount: results[2].rows[0].version_count,
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avgResponseTime: results[3].rows[0].avg_response_time || 0,
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cacheSize: this.cache.size,
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connected: this.connected,
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}
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} catch (error) {
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console.error("获取系统状态失败:", error)
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throw error
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}
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}
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}
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// 单例模式
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let mindsDBInstance: MindsDBConnector | null = null
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export function getMindsDBConnector(config?: MindsDBConfig): MindsDBConnector {
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if (!mindsDBInstance && config) {
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mindsDBInstance = new MindsDBConnector(config)
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}
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if (!mindsDBInstance) {
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throw new Error("MindsDB连接器未初始化，请提供配置信息")
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}
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return mindsDBInstance
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}
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