255 lines
8.5 KiB
TypeScript
255 lines
8.5 KiB
TypeScript
import { NextRequest, NextResponse } from 'next/server'
|
|
import { isAuthenticatedNextjs } from "@convex-dev/auth/nextjs/server";
|
|
import { z } from 'zod'
|
|
import type { EnhancedProductAnalysis, Opportunity, DorkQuery } from '@/lib/types'
|
|
|
|
// Search result from any source
|
|
interface SearchResult {
|
|
title: string
|
|
url: string
|
|
snippet: string
|
|
source: string
|
|
}
|
|
|
|
const bodySchema = z.object({
|
|
analysis: z.object({
|
|
productName: z.string(),
|
|
dorkQueries: z.array(z.object({
|
|
query: z.string(),
|
|
platform: z.string(),
|
|
intent: z.string(),
|
|
priority: z.string()
|
|
})),
|
|
keywords: z.array(z.object({
|
|
term: z.string()
|
|
})),
|
|
personas: z.array(z.object({
|
|
name: z.string(),
|
|
searchBehavior: z.array(z.string())
|
|
})),
|
|
problemsSolved: z.array(z.object({
|
|
problem: z.string(),
|
|
searchTerms: z.array(z.string())
|
|
}))
|
|
})
|
|
})
|
|
|
|
export async function POST(request: NextRequest) {
|
|
try {
|
|
if (!(await isAuthenticatedNextjs())) {
|
|
const redirectUrl = new URL("/auth", request.url);
|
|
const referer = request.headers.get("referer");
|
|
const nextPath = referer ? new URL(referer).pathname + new URL(referer).search : "/";
|
|
redirectUrl.searchParams.set("next", nextPath);
|
|
return NextResponse.redirect(redirectUrl);
|
|
}
|
|
|
|
const body = await request.json()
|
|
const { analysis } = bodySchema.parse(body)
|
|
|
|
console.log(`🔍 Finding opportunities for: ${analysis.productName}`)
|
|
|
|
// Sort queries by priority
|
|
const sortedQueries = analysis.dorkQueries
|
|
.sort((a, b) => {
|
|
const priorityOrder = { high: 0, medium: 1, low: 2 }
|
|
return priorityOrder[a.priority as keyof typeof priorityOrder] - priorityOrder[b.priority as keyof typeof priorityOrder]
|
|
})
|
|
.slice(0, 15) // Limit to top 15 queries
|
|
|
|
const allResults: SearchResult[] = []
|
|
|
|
// Execute searches
|
|
for (const query of sortedQueries) {
|
|
try {
|
|
console.log(` Searching: ${query.query.substring(0, 60)}...`)
|
|
const results = await searchGoogle(query.query, 5)
|
|
allResults.push(...results)
|
|
|
|
// Small delay to avoid rate limiting
|
|
await new Promise(r => setTimeout(r, 500))
|
|
} catch (e) {
|
|
console.error(` Search failed for query: ${query.query.substring(0, 40)}`)
|
|
}
|
|
}
|
|
|
|
console.log(` Found ${allResults.length} raw results`)
|
|
|
|
// Analyze and score opportunities
|
|
const opportunities = await analyzeOpportunities(allResults, analysis as EnhancedProductAnalysis)
|
|
console.log(` ✓ Analyzed ${opportunities.length} opportunities`)
|
|
|
|
return NextResponse.json({
|
|
success: true,
|
|
data: {
|
|
totalFound: opportunities.length,
|
|
opportunities: opportunities.slice(0, 20),
|
|
searchStats: {
|
|
queriesUsed: sortedQueries.length,
|
|
platformsSearched: [...new Set(sortedQueries.map(q => q.platform))],
|
|
averageRelevance: opportunities.reduce((a, o) => a + o.relevanceScore, 0) / opportunities.length || 0
|
|
}
|
|
}
|
|
})
|
|
|
|
} catch (error: any) {
|
|
console.error('❌ Search error:', error)
|
|
|
|
return NextResponse.json(
|
|
{ error: error.message || 'Failed to find opportunities' },
|
|
{ status: 500 }
|
|
)
|
|
}
|
|
}
|
|
|
|
async function searchGoogle(query: string, num: number): Promise<SearchResult[]> {
|
|
// Try Serper first
|
|
if (process.env.SERPER_API_KEY) {
|
|
try {
|
|
return await searchSerper(query, num)
|
|
} catch (e) {
|
|
console.error('Serper failed, falling back to direct')
|
|
}
|
|
}
|
|
return searchDirect(query, num)
|
|
}
|
|
|
|
async function searchSerper(query: string, num: number): Promise<SearchResult[]> {
|
|
const response = await fetch('https://google.serper.dev/search', {
|
|
method: 'POST',
|
|
headers: {
|
|
'X-API-KEY': process.env.SERPER_API_KEY!,
|
|
'Content-Type': 'application/json'
|
|
},
|
|
body: JSON.stringify({ q: query, num })
|
|
})
|
|
|
|
if (!response.ok) throw new Error('Serper API error')
|
|
|
|
const data = await response.json()
|
|
return (data.organic || []).map((r: any) => ({
|
|
title: r.title,
|
|
url: r.link,
|
|
snippet: r.snippet,
|
|
source: getSource(r.link)
|
|
}))
|
|
}
|
|
|
|
async function searchDirect(query: string, num: number): Promise<SearchResult[]> {
|
|
const encodedQuery = encodeURIComponent(query)
|
|
const url = `https://www.google.com/search?q=${encodedQuery}&num=${num}`
|
|
|
|
const response = await fetch(url, {
|
|
headers: { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36' }
|
|
})
|
|
|
|
const html = await response.text()
|
|
const results: SearchResult[] = []
|
|
|
|
// Simple regex parsing
|
|
const resultBlocks = html.match(/<div class="g"[^>]*>([\s\S]*?)<\/div>\s*<\/div>/g) || []
|
|
|
|
for (const block of resultBlocks.slice(0, num)) {
|
|
const titleMatch = block.match(/<h3[^>]*>(.*?)<\/h3>/)
|
|
const linkMatch = block.match(/<a href="([^"]+)"/)
|
|
const snippetMatch = block.match(/<div class="VwiC3b[^"]*"[^>]*>(.*?)<\/div>/)
|
|
|
|
if (titleMatch && linkMatch) {
|
|
results.push({
|
|
title: titleMatch[1].replace(/<[^>]+>/g, ''),
|
|
url: linkMatch[1],
|
|
snippet: snippetMatch ? snippetMatch[1].replace(/<[^>]+>/g, '') : '',
|
|
source: getSource(linkMatch[1])
|
|
})
|
|
}
|
|
}
|
|
|
|
return results
|
|
}
|
|
|
|
function getSource(url: string): string {
|
|
if (url.includes('reddit.com')) return 'Reddit'
|
|
if (url.includes('news.ycombinator.com')) return 'Hacker News'
|
|
if (url.includes('indiehackers.com')) return 'Indie Hackers'
|
|
if (url.includes('quora.com')) return 'Quora'
|
|
if (url.includes('twitter.com') || url.includes('x.com')) return 'Twitter/X'
|
|
if (url.includes('stackexchange.com') || url.includes('stackoverflow.com')) return 'Stack Exchange'
|
|
return 'Other'
|
|
}
|
|
|
|
async function analyzeOpportunities(
|
|
results: SearchResult[],
|
|
analysis: EnhancedProductAnalysis
|
|
): Promise<Opportunity[]> {
|
|
const opportunities: Opportunity[] = []
|
|
const seen = new Set<string>()
|
|
|
|
for (const result of results) {
|
|
if (seen.has(result.url)) continue
|
|
seen.add(result.url)
|
|
|
|
// Calculate relevance score
|
|
const content = (result.title + ' ' + result.snippet).toLowerCase()
|
|
|
|
// Match keywords
|
|
const matchedKeywords = analysis.keywords
|
|
.filter(k => content.includes(k.term.toLowerCase()))
|
|
.map(k => k.term)
|
|
|
|
// Match problems
|
|
const matchedProblems = analysis.problemsSolved
|
|
.filter(p => content.includes(p.problem.toLowerCase()))
|
|
.map(p => p.problem)
|
|
|
|
// Calculate score
|
|
const keywordScore = Math.min(matchedKeywords.length * 0.15, 0.6)
|
|
const problemScore = Math.min(matchedProblems.length * 0.2, 0.4)
|
|
const relevanceScore = Math.min(keywordScore + problemScore, 1)
|
|
|
|
// Determine intent
|
|
let intent: Opportunity['intent'] = 'looking-for'
|
|
if (content.includes('frustrated') || content.includes('hate') || content.includes('sucks')) {
|
|
intent = 'frustrated'
|
|
} else if (content.includes('alternative') || content.includes('switching')) {
|
|
intent = 'alternative'
|
|
} else if (content.includes('vs') || content.includes('comparison') || content.includes('better')) {
|
|
intent = 'comparison'
|
|
} else if (content.includes('how to') || content.includes('fix') || content.includes('solution')) {
|
|
intent = 'problem-solving'
|
|
}
|
|
|
|
// Find matching persona
|
|
const matchedPersona = analysis.personas.find(p =>
|
|
p.searchBehavior.some(b => content.includes(b.toLowerCase()))
|
|
)?.name
|
|
|
|
if (relevanceScore >= 0.3) {
|
|
opportunities.push({
|
|
title: result.title,
|
|
url: result.url,
|
|
source: result.source,
|
|
snippet: result.snippet.slice(0, 300),
|
|
relevanceScore,
|
|
painPoints: matchedProblems.slice(0, 3),
|
|
suggestedApproach: generateApproach(intent, analysis.productName),
|
|
matchedKeywords: matchedKeywords.slice(0, 5),
|
|
matchedPersona,
|
|
intent
|
|
})
|
|
}
|
|
}
|
|
|
|
return opportunities.sort((a, b) => b.relevanceScore - a.relevanceScore)
|
|
}
|
|
|
|
function generateApproach(intent: string, productName: string): string {
|
|
const approaches: Record<string, string> = {
|
|
'frustrated': `Empathize with their frustration. Share how ${productName} solves this specific pain point without being pushy.`,
|
|
'alternative': `Highlight key differentiators. Focus on why teams switch to ${productName} from their current solution.`,
|
|
'comparison': `Provide an honest comparison. Be helpful and mention specific features that address their needs.`,
|
|
'problem-solving': `Offer a clear solution. Share a specific example of how ${productName} solves this exact problem.`,
|
|
'looking-for': `Introduce ${productName} as a relevant option. Focus on the specific features they're looking for.`
|
|
}
|
|
return approaches[intent] || approaches['looking-for']
|
|
}
|