工具与测评 | 用Cursor构建基于AI的搜索引擎实战教学

npx create-next-app@latest ai-search-enginecd ai-search-engine

npm install @supabase/supabase-js

npm install ioredis

npm install openai

import SearchForm from '../components/SearchForm'
export default function Home() {  return (    <main>      <h1>AI Search Engine</h1>      <SearchForm />    </main>  )}

'use client'
import { useState } from 'react'import { useRouter } from 'next/navigation'
export default function SearchForm() {  const [query, setQuery] = useState('')  const router = useRouter()
  const handleSubmit = (e) => {    e.preventDefault()    router.push(`/search?q=${encodeURIComponent(query)}`)  }
  return (    <form onSubmit={handleSubmit}>      <input         type="text"         value={query}         onChange={(e) => setQuery(e.target.value)}        placeholder="Enter your search query"      />      <button type="submit">Search</button>    </form>  )}

import { getSearchResults } from '../../lib/search'
export default async function SearchResults({ searchParams }) {  const { q } = searchParams  const results = await getSearchResults(q)
  return (    <div>      <h1>Search Results for: {q}</h1>      <ul>        {results.map((result) => (          <li key={result.id}>{result.title}</li>        ))}      </ul>    </div>  )}

import { createClient } from '@supabase/supabase-js'import Redis from 'ioredis'import { Configuration, OpenAIApi } from 'openai'
const supabase = createClient(process.env.SUPABASE_URL, process.env.SUPABASE_KEY)const redis = new Redis(process.env.REDIS_URL)
const openai = new OpenAIApi(new Configuration({  apiKey: process.env.OPENAI_API_KEY,}))
export async function getSearchResults(query) {  // 检查Redis缓存  const cachedResults = await redis.get(query)  if (cachedResults) {    return JSON.parse(cachedResults)  }
  // 使用AI生成搜索结果  const aiResponse = await openai.createCompletion({    model: "text-davinci-002",    prompt: `Generate search results for: ${query}`,    max_tokens: 100  })
  const results = aiResponse.data.choices[0].text
  // 存储结果到Supabase  await supabase.from('searches').insert({ query, results })
  // 缓存结果到Redis  await redis.set(query, JSON.stringify(results), 'EX', 3600) // 1小时过期
  return results}

npm install @azure/openai

import { createClient } from '@supabase/supabase-js'import Redis from 'ioredis'import { OpenAIClient, AzureKeyCredential } from "@azure/openai";
const supabase = createClient(process.env.SUPABASE_URL, process.env.SUPABASE_KEY)const redis = new Redis(process.env.REDIS_URL)
const client = new OpenAIClient(  process.env.AZURE_OPENAI_ENDPOINT,  new AzureKeyCredential(process.env.AZURE_OPENAI_API_KEY));
export async function getSearchResults(query) {  // 检查Redis缓存  const cachedResults = await redis.get(query)  if (cachedResults) {    return JSON.parse(cachedResults)  }
  // 使用Azure OpenAI生成搜索结果  const response = await client.getCompletions(    process.env.AZURE_OPENAI_DEPLOYMENT_NAME,    [      `Generate search results for: ${query}`    ],    {      maxTokens: 100,      temperature: 0.7    }  );
  const results = response.choices[0].text;
  // 存储结果到Supabase  await supabase.from('searches').insert({ query, results })
  // 缓存结果到Redis  await redis.set(query, JSON.stringify(results), 'EX', 3600) // 1小时过期
  return results}

AZURE_OPENAI_ENDPOINT=your_azure_openai_endpointAZURE_OPENAI_API_KEY=your_azure_openai_api_keyAZURE_OPENAI_DEPLOYMENT_NAME=your_model_deployment_name