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feat: Implement analysis job tracking with progress timeline and enhanced data source status management.

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This commit is contained in:
Matiss Jurevics
2026-02-03 22:43:27 +00:00
parent c47614bc66
commit 358f2a42dd
22 changed files with 2251 additions and 219 deletions
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137
app/api/analyze-manual/route.ts
View File

@@ -1,5 +1,7 @@
import { NextRequest, NextResponse } from 'next/server'
import { isAuthenticatedNextjs } from "@convex-dev/auth/nextjs/server";
import { convexAuthNextjsToken, isAuthenticatedNextjs } from "@convex-dev/auth/nextjs/server";
import { fetchMutation } from "convex/nextjs";
import { api } from "@/convex/_generated/api";
import { z } from 'zod'
import { analyzeFromText } from '@/lib/scraper'
import { performDeepAnalysis } from '@/lib/analysis-pipeline'
@@ -7,10 +9,18 @@ import { performDeepAnalysis } from '@/lib/analysis-pipeline'
const bodySchema = z.object({
productName: z.string().min(1),
description: z.string().min(1),
features: z.string()
features: z.string(),
jobId: z.optional(z.string())
})
export async function POST(request: NextRequest) {
let jobId: string | undefined
let timeline: {
key: string
label: string
status: "pending" | "running" | "completed" | "failed"
detail?: string
}[] = []
try {
if (!(await isAuthenticatedNextjs())) {
const redirectUrl = new URL("/auth", request.url);
@@ -21,9 +31,69 @@ export async function POST(request: NextRequest) {
}
const body = await request.json()
const { productName, description, features } = bodySchema.parse(body)
const parsed = bodySchema.parse(body)
const { productName, description, features } = parsed
jobId = parsed.jobId
const token = await convexAuthNextjsToken();
timeline = [
{ key: "scrape", label: "Prepare input", status: "pending" },
{ key: "features", label: "Pass 1: Features", status: "pending" },
{ key: "competitors", label: "Pass 2: Competitors", status: "pending" },
{ key: "keywords", label: "Pass 3: Keywords", status: "pending" },
{ key: "problems", label: "Pass 4: Problems & Personas", status: "pending" },
{ key: "useCases", label: "Pass 5: Use cases", status: "pending" },
{ key: "dorkQueries", label: "Pass 6: Dork queries", status: "pending" },
{ key: "finalize", label: "Finalize analysis", status: "pending" },
]
const updateTimeline = async ({
key,
status,
detail,
progress,
finalStatus,
}: {
key: string
status: "pending" | "running" | "completed" | "failed"
detail?: string
progress?: number
finalStatus?: "running" | "completed" | "failed"
}) => {
if (!jobId) return
timeline = timeline.map((item) =>
item.key === key ? { ...item, status, detail: detail ?? item.detail } : item
)
await fetchMutation(
api.analysisJobs.update,
{
jobId: jobId as any,
status: finalStatus || "running",
progress,
stage: key,
timeline,
},
{ token }
)
}
if (jobId) {
await updateTimeline({ key: "scrape", status: "running", progress: 10 })
}
if (!process.env.OPENAI_API_KEY) {
if (jobId) {
await fetchMutation(
api.analysisJobs.update,
{
jobId: jobId as any,
status: "failed",
error: "OpenAI API key not configured",
timeline: timeline.map((item) =>
item.status === "running" ? { ...item, status: "failed" } : item
),
},
{ token }
);
}
return NextResponse.json(
{ error: 'OpenAI API key not configured' },
{ status: 500 }
@@ -32,10 +102,49 @@ export async function POST(request: NextRequest) {
console.log('📝 Creating content from manual input...')
const scrapedContent = await analyzeFromText(productName, description, features)
if (jobId) {
await updateTimeline({
key: "scrape",
status: "completed",
detail: "Manual input prepared",
progress: 20,
})
}
console.log('🤖 Starting enhanced analysis...')
const analysis = await performDeepAnalysis(scrapedContent)
const progressMap: Record<string, number> = {
features: 35,
competitors: 50,
keywords: 65,
problems: 78,
useCases: 88,
dorkQueries: 95,
}
const analysis = await performDeepAnalysis(scrapedContent, async (update) => {
await updateTimeline({
key: update.key,
status: update.status,
detail: update.detail,
progress: progressMap[update.key] ?? 80,
})
})
console.log(` ✓ Analysis complete: ${analysis.features.length} features, ${analysis.keywords.length} keywords`)
if (jobId) {
await updateTimeline({
key: "finalize",
status: "running",
progress: 98,
})
}
if (jobId) {
await updateTimeline({
key: "finalize",
status: "completed",
progress: 100,
finalStatus: "completed",
})
}
return NextResponse.json({
success: true,
@@ -52,6 +161,26 @@ export async function POST(request: NextRequest) {
} catch (error: any) {
console.error('❌ Manual analysis error:', error)
if (jobId) {
try {
const token = await convexAuthNextjsToken();
await fetchMutation(
api.analysisJobs.update,
{
jobId: jobId as any,
status: "failed",
error: error.message || "Manual analysis failed",
timeline: timeline.map((item) =>
item.status === "running" ? { ...item, status: "failed" } : item
),
},
{ token }
);
} catch {
// Best-effort job update only.
}
}
if (error.name === 'ZodError') {
return NextResponse.json(

138
app/api/analyze/route.ts
View File

@@ -1,14 +1,24 @@
import { NextRequest, NextResponse } from 'next/server'
import { isAuthenticatedNextjs } from "@convex-dev/auth/nextjs/server";
import { convexAuthNextjsToken, isAuthenticatedNextjs } from "@convex-dev/auth/nextjs/server";
import { fetchMutation } from "convex/nextjs";
import { api } from "@/convex/_generated/api";
import { z } from 'zod'
import { scrapeWebsite, ScrapingError } from '@/lib/scraper'
import { performDeepAnalysis } from '@/lib/analysis-pipeline'
const bodySchema = z.object({
url: z.string().min(1)
url: z.string().min(1),
jobId: z.optional(z.string())
})
export async function POST(request: NextRequest) {
let jobId: string | undefined
let timeline: {
key: string
label: string
status: "pending" | "running" | "completed" | "failed"
detail?: string
}[] = []
try {
if (!(await isAuthenticatedNextjs())) {
const redirectUrl = new URL("/auth", request.url);
@@ -19,9 +29,70 @@ export async function POST(request: NextRequest) {
}
const body = await request.json()
const { url } = bodySchema.parse(body)
const parsed = bodySchema.parse(body)
const { url } = parsed
jobId = parsed.jobId
const token = await convexAuthNextjsToken();
timeline = [
{ key: "scrape", label: "Scrape website", status: "pending" },
{ key: "features", label: "Pass 1: Features", status: "pending" },
{ key: "competitors", label: "Pass 2: Competitors", status: "pending" },
{ key: "keywords", label: "Pass 3: Keywords", status: "pending" },
{ key: "problems", label: "Pass 4: Problems & Personas", status: "pending" },
{ key: "useCases", label: "Pass 5: Use cases", status: "pending" },
{ key: "dorkQueries", label: "Pass 6: Dork queries", status: "pending" },
{ key: "finalize", label: "Finalize analysis", status: "pending" },
]
const updateTimeline = async ({
key,
status,
detail,
progress,
finalStatus,
}: {
key: string
status: "pending" | "running" | "completed" | "failed"
detail?: string
progress?: number
finalStatus?: "running" | "completed" | "failed"
}) => {
if (!jobId) return
timeline = timeline.map((item) =>
item.key === key ? { ...item, status, detail: detail ?? item.detail } : item
)
await fetchMutation(
api.analysisJobs.update,
{
jobId: jobId as any,
status: finalStatus || "running",
progress,
stage: key,
timeline,
},
{ token }
)
}
if (jobId) {
await updateTimeline({ key: "scrape", status: "running", progress: 10 })
}
if (!process.env.OPENAI_API_KEY) {
if (jobId) {
await fetchMutation(
api.analysisJobs.update,
{
jobId: jobId as any,
status: "failed",
error: "OpenAI API key not configured",
timeline: timeline.map((item) =>
item.status === "running" ? { ...item, status: "failed" } : item
),
},
{ token }
);
}
return NextResponse.json(
{ error: 'OpenAI API key not configured' },
{ status: 500 }
@@ -31,10 +102,49 @@ export async function POST(request: NextRequest) {
console.log(`🌐 Scraping: ${url}`)
const scrapedContent = await scrapeWebsite(url)
console.log(` ✓ Scraped ${scrapedContent.headings.length} headings, ${scrapedContent.paragraphs.length} paragraphs`)
if (jobId) {
await updateTimeline({
key: "scrape",
status: "completed",
detail: `${scrapedContent.headings.length} headings, ${scrapedContent.paragraphs.length} paragraphs`,
progress: 20,
})
}
console.log('🤖 Starting enhanced analysis...')
const analysis = await performDeepAnalysis(scrapedContent)
const progressMap: Record<string, number> = {
features: 35,
competitors: 50,
keywords: 65,
problems: 78,
useCases: 88,
dorkQueries: 95,
}
const analysis = await performDeepAnalysis(scrapedContent, async (update) => {
await updateTimeline({
key: update.key,
status: update.status,
detail: update.detail,
progress: progressMap[update.key] ?? 80,
})
})
console.log(` ✓ Analysis complete: ${analysis.features.length} features, ${analysis.keywords.length} keywords, ${analysis.dorkQueries.length} queries`)
if (jobId) {
await updateTimeline({
key: "finalize",
status: "running",
progress: 98,
})
}
if (jobId) {
await updateTimeline({
key: "finalize",
status: "completed",
progress: 100,
finalStatus: "completed",
})
}
return NextResponse.json({
success: true,
@@ -51,6 +161,26 @@ export async function POST(request: NextRequest) {
} catch (error: any) {
console.error('❌ Analysis error:', error)
if (jobId) {
try {
const token = await convexAuthNextjsToken();
await fetchMutation(
api.analysisJobs.update,
{
jobId: jobId as any,
status: "failed",
error: error.message || "Analysis failed",
timeline: timeline.map((item) =>
item.status === "running" ? { ...item, status: "failed" } : item
),
},
{ token }
);
} catch {
// Best-effort job update only.
}
}
if (error instanceof ScrapingError) {
return NextResponse.json(

88
app/api/opportunities/route.ts
View File

@@ -1,6 +1,6 @@
import { NextRequest, NextResponse } from 'next/server'
import { convexAuthNextjsToken, isAuthenticatedNextjs } from "@convex-dev/auth/nextjs/server";
import { fetchQuery } from "convex/nextjs";
import { fetchMutation, fetchQuery } from "convex/nextjs";
import { api } from "@/convex/_generated/api";
import { z } from 'zod'
import { generateSearchQueries, getDefaultPlatforms } from '@/lib/query-generator'
@@ -9,13 +9,14 @@ import type { EnhancedProductAnalysis, SearchConfig, PlatformConfig } from '@/li
const searchSchema = z.object({
projectId: z.string(),
jobId: z.optional(z.string()),
config: z.object({
platforms: z.array(z.object({
id: z.string(),
name: z.string(),
icon: z.string(),
icon: z.string().optional(),
enabled: z.boolean(),
searchTemplate: z.string(),
searchTemplate: z.string().optional(),
rateLimit: z.number()
})),
strategies: z.array(z.string()),
@@ -25,6 +26,7 @@ const searchSchema = z.object({
})
export async function POST(request: NextRequest) {
let jobId: string | undefined
try {
if (!(await isAuthenticatedNextjs())) {
const redirectUrl = new URL("/auth", request.url);
@@ -35,9 +37,18 @@ export async function POST(request: NextRequest) {
}
const body = await request.json()
const { projectId, config } = searchSchema.parse(body)
const parsed = searchSchema.parse(body)
const { projectId, config } = parsed
jobId = parsed.jobId
const token = await convexAuthNextjsToken();
if (jobId) {
await fetchMutation(
api.searchJobs.update,
{ jobId: jobId as any, status: "running", progress: 10 },
{ token }
);
}
const searchContext = await fetchQuery(
api.projects.getSearchContext,
{ projectId: projectId as any },
@@ -45,6 +56,13 @@ export async function POST(request: NextRequest) {
);
if (!searchContext.context) {
if (jobId) {
await fetchMutation(
api.searchJobs.update,
{ jobId: jobId as any, status: "failed", error: "No analysis available." },
{ token }
);
}
return NextResponse.json(
{ error: 'No analysis available for selected sources.' },
{ status: 400 }
@@ -60,18 +78,51 @@ export async function POST(request: NextRequest) {
// Generate queries
console.log(' Generating search queries...')
const queries = generateSearchQueries(analysis as EnhancedProductAnalysis, config as SearchConfig)
const enforcedConfig: SearchConfig = {
...(config as SearchConfig),
maxResults: Math.min((config as SearchConfig).maxResults || 50, 50),
}
const queries = generateSearchQueries(analysis as EnhancedProductAnalysis, enforcedConfig)
console.log(` ✓ Generated ${queries.length} queries`)
if (jobId) {
await fetchMutation(
api.searchJobs.update,
{ jobId: jobId as any, status: "running", progress: 40 },
{ token }
);
}
// Execute searches
console.log(' Executing searches...')
const searchResults = await executeSearches(queries)
console.log(` ✓ Found ${searchResults.length} raw results`)
if (jobId) {
await fetchMutation(
api.searchJobs.update,
{ jobId: jobId as any, status: "running", progress: 70 },
{ token }
);
}
// Score and rank
console.log(' Scoring opportunities...')
const opportunities = scoreOpportunities(searchResults, analysis as EnhancedProductAnalysis)
console.log(` ✓ Scored ${opportunities.length} opportunities`)
if (jobId) {
await fetchMutation(
api.searchJobs.update,
{ jobId: jobId as any, status: "running", progress: 90 },
{ token }
);
}
if (jobId) {
await fetchMutation(
api.searchJobs.update,
{ jobId: jobId as any, status: "completed", progress: 100 },
{ token }
);
}
return NextResponse.json({
success: true,
@@ -97,17 +148,36 @@ export async function POST(request: NextRequest) {
})
} catch (error: any) {
console.error('❌ Opportunity search error:', error)
const errorMessage =
error instanceof Error ? error.message : typeof error === "string" ? error : "Search failed"
console.error("❌ Opportunity search error:", errorMessage)
if (jobId) {
try {
const token = await convexAuthNextjsToken();
await fetchMutation(
api.searchJobs.update,
{
jobId: jobId as any,
status: "failed",
error: errorMessage
},
{ token }
);
} catch {
// Best-effort job update only.
}
}
if (error.name === 'ZodError') {
if (error?.name === 'ZodError') {
return NextResponse.json(
{ error: 'Invalid request format', details: error.errors },
{ error: 'Invalid request format', details: error?.errors },
{ status: 400 }
)
}
return NextResponse.json(
{ error: error.message || 'Failed to search for opportunities' },
{ error: errorMessage || 'Failed to search for opportunities' },
{ status: 500 }
)
}