gpatti/MediaLore
Archived
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

text-extraction-improvements #24

Merged
gpatti merged 4 commits from text-extraction-improvements into main 2026-04-13 16:29:26 +00:00
Conversation 0 Commits 4 Files Changed 19 +1015 -223
19 changed files with 1015 additions and 223 deletions
Download Patch File Download Diff File Expand all files Collapse all files

63
src/app/api/ai-jobs/route.ts Normal file
View File

@@ -0,0 +1,63 @@
import { NextRequest, NextResponse } from 'next/server'
import { requireAdmin } from '@/lib/auth'
import { getJobQueue, getJobHistory, retryJob, cancelJob, cancelAllQueued, clearJobHistory } from '@/lib/ai-jobs'
export async function GET(request: NextRequest) {
const auth = await requireAdmin(request)
if (auth instanceof NextResponse) return auth
const queue = getJobQueue()
const history = getJobHistory(50)
return NextResponse.json({ queue, history })
}
export async function POST(request: NextRequest) {
const auth = await requireAdmin(request)
if (auth instanceof NextResponse) return auth
let body: { action?: string; jobId?: string }
try {
body = await request.json()
} catch {
return NextResponse.json({ error: 'Invalid JSON body' }, { status: 400 })
}
const { action, jobId } = body
switch (action) {
case 'retry': {
if (!jobId || typeof jobId !== 'string') {
return NextResponse.json({ error: 'jobId is required' }, { status: 400 })
}
const ok = retryJob(jobId)
if (!ok) {
return NextResponse.json({ error: 'Job not found or not in failed state' }, { status: 404 })
}
return NextResponse.json({ ok: true })
}
case 'cancel': {
if (!jobId || typeof jobId !== 'string') {
return NextResponse.json({ error: 'jobId is required' }, { status: 400 })
}
const ok = cancelJob(jobId)
if (!ok) {
return NextResponse.json({ error: 'Job not found or not in queued state' }, { status: 404 })
}
return NextResponse.json({ ok: true })
}
case 'cancel-all': {
const cancelled = cancelAllQueued()
return NextResponse.json({ cancelled })
}
case 'clear-history': {
const cleared = clearJobHistory()
return NextResponse.json({ cleared })
}
default:
return NextResponse.json({ error: 'Unknown action' }, { status: 400 })
}
}

15
src/app/api/ai-settings/route.ts
View File

@@ -1,6 +1,6 @@
import { NextRequest, NextResponse } from 'next/server'
import { requireAdmin } from '@/lib/auth'
import { getAiConfig, updateAiConfig, getPreferredLanguage, setPreferredLanguage } from '@/lib/app-settings'
import { getAiConfig, updateAiConfig, getPreferredLanguage, setPreferredLanguage, getAiMaxRetries, setAiMaxRetries } from '@/lib/app-settings'
export async function GET(request: NextRequest) {
const auth = await requireAdmin(request)
@@ -8,7 +8,8 @@ export async function GET(request: NextRequest) {
const config = getAiConfig()
const preferredLanguage = getPreferredLanguage()
return NextResponse.json({ ...config, preferredLanguage })
const maxRetries = getAiMaxRetries()
return NextResponse.json({ ...config, preferredLanguage, maxRetries })
}
export async function PUT(request: NextRequest) {
@@ -28,6 +29,7 @@ export async function PUT(request: NextRequest) {
promptTagger?: string
promptExtract?: string
promptTranslate?: string
maxRetries?: number
}
try {
body = await request.json()
@@ -39,6 +41,7 @@ export async function PUT(request: NextRequest) {
endpoint, model, enabled, preferredLanguage,
modelTagging, modelDescribe, modelExtract, modelTranslate,
promptDescribe, promptTagger, promptExtract, promptTranslate,
maxRetries,
} = body
if (typeof endpoint !== 'string') {
@@ -69,6 +72,10 @@ export async function PUT(request: NextRequest) {
setPreferredLanguage(preferredLanguage.trim())
}
const config = getAiConfig()
return NextResponse.json({ ...config, preferredLanguage: getPreferredLanguage() })
if (typeof maxRetries === 'number' && Number.isFinite(maxRetries)) {
setAiMaxRetries(maxRetries)
}
const config = getAiConfig()
return NextResponse.json({ ...config, preferredLanguage: getPreferredLanguage(), maxRetries: getAiMaxRetries() })
}

25
src/app/api/ai-tagging/describe-bulk/route.ts
View File

@@ -1,6 +1,10 @@
import { NextRequest, NextResponse } from 'next/server'
import { requireLibraryAccess } from '@/lib/auth'
import { describeDirectoryItems } from '@/lib/ai-tagger'
import { enqueueBulkJobs } from '@/lib/ai-jobs'
const IMAGE_EXTENSIONS = new Set(['.jpg', '.jpeg', '.png', '.gif', '.webp', '.bmp', '.tiff', '.tif'])
const VIDEO_EXTENSIONS = new Set(['.mp4', '.mkv', '.avi', '.mov', '.wmv', '.m4v', '.webm', '.flv', '.ts', '.mpg', '.mpeg'])
const MEDIA_EXTENSIONS = new Set([...IMAGE_EXTENSIONS, ...VIDEO_EXTENSIONS])
export async function POST(request: NextRequest) {
let body: { libraryId?: string; path?: string }
@@ -18,21 +22,6 @@ export async function POST(request: NextRequest) {
const auth = await requireLibraryAccess(request, libraryId)
if (auth instanceof NextResponse) return auth
try {
const processed = await describeDirectoryItems(libraryId, dirPath ?? '')
return NextResponse.json({ processed })
} catch (err) {
const error = err as Error & { code?: string }
if (error.code === 'NOT_CONFIGURED') {
return NextResponse.json({ error: error.message }, { status: 400 })
}
if (error.code === 'NOT_FOUND') {
return NextResponse.json({ error: error.message }, { status: 404 })
}
if (error.code === 'INVALID_TYPE') {
return NextResponse.json({ error: error.message }, { status: 400 })
}
console.error('[ai-tagging/describe-bulk] Error:', error)
return NextResponse.json({ error: 'Failed to generate descriptions' }, { status: 502 })
}
const jobIds = enqueueBulkJobs(libraryId, dirPath ?? '', 'describe', 'mixed_file', MEDIA_EXTENSIONS)
return NextResponse.json({ jobIds, queued: jobIds.length }, { status: 202 })
}

21
src/app/api/ai-tagging/describe/route.ts
View File

@@ -1,6 +1,6 @@
import { NextRequest, NextResponse } from 'next/server'
import { requireLibraryAccess } from '@/lib/auth'
import { generateItemDescription } from '@/lib/ai-tagger'
import { enqueueJob } from '@/lib/ai-jobs'
export async function POST(request: NextRequest) {
let body: { itemKey?: string }
@@ -19,21 +19,6 @@ export async function POST(request: NextRequest) {
const auth = await requireLibraryAccess(request, libraryId)
if (auth instanceof NextResponse) return auth
try {
const description = await generateItemDescription(itemKey)
return NextResponse.json({ description })
} catch (err) {
const error = err as Error & { code?: string }
if (error.code === 'NOT_CONFIGURED') {
return NextResponse.json({ error: error.message }, { status: 400 })
}
if (error.code === 'NOT_FOUND') {
return NextResponse.json({ error: error.message }, { status: 404 })
}
if (error.code === 'NO_IMAGE') {
return NextResponse.json({ error: error.message }, { status: 404 })
}
console.error('[ai-tagging/describe] Error:', error)
return NextResponse.json({ error: 'Failed to generate description' }, { status: 502 })
}
const jobId = enqueueJob(itemKey, 'describe', libraryId)
return NextResponse.json({ jobId }, { status: 202 })
}

23
src/app/api/ai-tagging/extract-text-bulk/route.ts
View File

@@ -1,6 +1,8 @@
import { NextRequest, NextResponse } from 'next/server'
import { requireLibraryAccess } from '@/lib/auth'
import { extractDirectoryText } from '@/lib/ai-tagger'
import { enqueueBulkJobs } from '@/lib/ai-jobs'
const IMAGE_EXTENSIONS = new Set(['.jpg', '.jpeg', '.png', '.gif', '.webp', '.bmp', '.tiff', '.tif'])
export async function POST(request: NextRequest) {
let body: { libraryId?: string; path?: string }
@@ -18,21 +20,6 @@ export async function POST(request: NextRequest) {
const auth = await requireLibraryAccess(request, libraryId)
if (auth instanceof NextResponse) return auth
try {
const processed = await extractDirectoryText(libraryId, dirPath ?? '')
return NextResponse.json({ processed })
} catch (err) {
const error = err as Error & { code?: string }
if (error.code === 'NOT_CONFIGURED') {
return NextResponse.json({ error: error.message }, { status: 400 })
}
if (error.code === 'NOT_FOUND') {
return NextResponse.json({ error: error.message }, { status: 404 })
}
if (error.code === 'INVALID_TYPE') {
return NextResponse.json({ error: error.message }, { status: 400 })
}
console.error('[ai-tagging/extract-text-bulk] Error:', error)
return NextResponse.json({ error: 'Failed to extract text' }, { status: 502 })
}
const jobIds = enqueueBulkJobs(libraryId, dirPath ?? '', 'extract', 'mixed_file', IMAGE_EXTENSIONS)
return NextResponse.json({ jobIds, queued: jobIds.length }, { status: 202 })
}

21
src/app/api/ai-tagging/extract-text/route.ts
View File

@@ -1,6 +1,6 @@
import { NextRequest, NextResponse } from 'next/server'
import { requireLibraryAccess } from '@/lib/auth'
import { extractItemText } from '@/lib/ai-tagger'
import { enqueueJob } from '@/lib/ai-jobs'
export async function POST(request: NextRequest) {
let body: { itemKey?: string }
@@ -19,21 +19,6 @@ export async function POST(request: NextRequest) {
const auth = await requireLibraryAccess(request, libraryId)
if (auth instanceof NextResponse) return auth
try {
const result = await extractItemText(itemKey)
return NextResponse.json(result)
} catch (err) {
const error = err as Error & { code?: string }
if (error.code === 'NOT_CONFIGURED') {
return NextResponse.json({ error: error.message }, { status: 400 })
}
if (error.code === 'NOT_FOUND') {
return NextResponse.json({ error: error.message }, { status: 404 })
}
if (error.code === 'NO_IMAGE' || error.code === 'INVALID_TYPE') {
return NextResponse.json({ error: error.message }, { status: 400 })
}
console.error('[ai-tagging/extract-text] Error:', error)
return NextResponse.json({ error: 'Failed to extract text' }, { status: 502 })
}
const jobId = enqueueJob(itemKey, 'extract', libraryId)
return NextResponse.json({ jobId }, { status: 202 })
}

26
src/app/api/ai-tagging/fields/route.ts
View File

@@ -1,6 +1,6 @@
import { NextRequest, NextResponse } from 'next/server'
import { requireLibraryAccess } from '@/lib/auth'
import { getAiFields } from '@/lib/ai-tagger'
import { getAiFields, updateExtractedText } from '@/lib/ai-tagger'
export async function GET(request: NextRequest) {
const { searchParams } = request.nextUrl
@@ -17,3 +17,27 @@ export async function GET(request: NextRequest) {
const fields = getAiFields(itemKey)
return NextResponse.json(fields)
}
export async function PATCH(request: NextRequest) {
let body: { itemKey?: string; extractedText?: string }
try {
body = await request.json()
} catch {
return NextResponse.json({ error: 'Invalid JSON body' }, { status: 400 })
}
const { itemKey, extractedText } = body
if (!itemKey || typeof itemKey !== 'string') {
return NextResponse.json({ error: 'itemKey is required' }, { status: 400 })
}
if (typeof extractedText !== 'string') {
return NextResponse.json({ error: 'extractedText is required' }, { status: 400 })
}
const libraryId = itemKey.split(':')[0]
const auth = await requireLibraryAccess(request, libraryId)
if (auth instanceof NextResponse) return auth
updateExtractedText(itemKey, extractedText)
return NextResponse.json({ ok: true })
}

21
src/app/api/ai-tagging/route.ts
View File

@@ -1,6 +1,6 @@
import { NextRequest, NextResponse } from 'next/server'
import { requireLibraryAccess } from '@/lib/auth'
import { tagSingleItem } from '@/lib/ai-tagger'
import { enqueueJob } from '@/lib/ai-jobs'
export async function POST(request: NextRequest) {
let body: { itemKey?: string }
@@ -19,21 +19,6 @@ export async function POST(request: NextRequest) {
const auth = await requireLibraryAccess(request, libraryId)
if (auth instanceof NextResponse) return auth
try {
const tagIds = await tagSingleItem(itemKey)
return NextResponse.json({ tagIds })
} catch (err) {
const error = err as Error & { code?: string }
if (error.code === 'NOT_CONFIGURED') {
return NextResponse.json({ error: error.message }, { status: 400 })
}
if (error.code === 'NOT_FOUND') {
return NextResponse.json({ error: error.message }, { status: 404 })
}
if (error.code === 'NO_IMAGE') {
return NextResponse.json({ error: error.message }, { status: 404 })
}
console.error('[ai-tagging] Error tagging item:', error)
return NextResponse.json({ error: 'AI tagging failed' }, { status: 502 })
}
const jobId = enqueueJob(itemKey, 'tag', libraryId)
return NextResponse.json({ jobId }, { status: 202 })
}

22
src/app/api/ai-tagging/translate/route.ts
View File

@@ -1,16 +1,16 @@
import { NextRequest, NextResponse } from 'next/server'
import { requireLibraryAccess } from '@/lib/auth'
import { translateItemText } from '@/lib/ai-tagger'
import { enqueueJob } from '@/lib/ai-jobs'
export async function POST(request: NextRequest) {
let body: { itemKey?: string }
let body: { itemKey?: string; sourceLanguage?: string }
try {
body = await request.json()
} catch {
return NextResponse.json({ error: 'Invalid JSON body' }, { status: 400 })
}
const { itemKey } = body
const { itemKey, sourceLanguage } = body
if (!itemKey || typeof itemKey !== 'string') {
return NextResponse.json({ error: 'itemKey is required' }, { status: 400 })
}
@@ -19,18 +19,6 @@ export async function POST(request: NextRequest) {
const auth = await requireLibraryAccess(request, libraryId)
if (auth instanceof NextResponse) return auth
try {
const translatedText = await translateItemText(itemKey)
return NextResponse.json({ translatedText })
} catch (err) {
const error = err as Error & { code?: string }
if (error.code === 'NOT_CONFIGURED') {
return NextResponse.json({ error: error.message }, { status: 400 })
}
if (error.code === 'NOT_FOUND') {
return NextResponse.json({ error: error.message }, { status: 404 })
}
console.error('[ai-tagging/translate] Error:', error)
return NextResponse.json({ error: 'Failed to translate text' }, { status: 502 })
}
const jobId = enqueueJob(itemKey, 'translate', libraryId, sourceLanguage || undefined)
return NextResponse.json({ jobId }, { status: 202 })
}

304
src/app/manage/ai-tagging/page.tsx
View File

@@ -1,6 +1,6 @@
'use client'
import { useEffect, useState, useCallback } from 'react'
import { useEffect, useState, useCallback, useRef } from 'react'
interface AiSettings {
endpoint: string
@@ -15,6 +15,22 @@ interface AiSettings {
promptTagger: string
promptExtract: string
promptTranslate: string
maxRetries: number
}
interface AiJob {
id: string
itemKey: string
libraryId: string
jobType: string
status: string
error: string | null
attempt: number
maxRetries: number
createdAt: number
startedAt: number | null
completedAt: number | null
itemTitle: string | null
}
interface Library {
@@ -33,11 +49,24 @@ interface LibraryOverride {
promptTranslate: string
}
function formatElapsed(startedAt: number): string {
const seconds = Math.floor((Date.now() - startedAt) / 1000)
if (seconds < 60) return `${seconds}s`
const m = Math.floor(seconds / 60)
const s = seconds % 60
return `${m}m ${s}s`
}
function formatDate(ts: number): string {
return new Date(ts).toLocaleTimeString([], { hour: '2-digit', minute: '2-digit' })
}
export default function AiTaggingPage() {
const [settings, setSettings] = useState<AiSettings>({
endpoint: '', model: '', modelTagging: '', modelDescribe: '', modelExtract: '', modelTranslate: '',
enabled: false, preferredLanguage: 'English',
promptDescribe: '', promptTagger: '', promptExtract: '', promptTranslate: '',
maxRetries: 3,
})
const [loading, setLoading] = useState(true)
const [saving, setSaving] = useState(false)
@@ -54,6 +83,11 @@ export default function AiTaggingPage() {
const [librarySaving, setLibrarySaving] = useState<Record<string, boolean>>({})
const [librarySaveResult, setLibrarySaveResult] = useState<Record<string, { ok: boolean; message: string }>>({})
// Job queue state
const [jobQueue, setJobQueue] = useState<AiJob[]>([])
const [jobHistory, setJobHistory] = useState<AiJob[]>([])
const [historyExpanded, setHistoryExpanded] = useState(false)
const jobPollRef = useRef<ReturnType<typeof setInterval> | null>(null)
const fetchSettings = useCallback(async () => {
try {
const [settingsRes, librariesRes] = await Promise.all([
@@ -79,6 +113,77 @@ export default function AiTaggingPage() {
fetchSettings()
}, [fetchSettings])
// ─── Job queue polling ───────────────────────────────────────────────────────
const fetchJobs = useCallback(async () => {
try {
const res = await fetch('/api/ai-jobs')
if (res.ok) {
const data: { queue: AiJob[]; history: AiJob[] } = await res.json()
setJobQueue(data.queue)
setJobHistory(data.history)
}
} catch {
// ignore
}
}, [])
useEffect(() => {
fetchJobs()
}, [fetchJobs])
// Poll every 2s while there are active jobs
useEffect(() => {
const hasActive = jobQueue.length > 0
if (hasActive) {
jobPollRef.current = setInterval(fetchJobs, 2000)
} else {
if (jobPollRef.current) {
clearInterval(jobPollRef.current)
jobPollRef.current = null
}
}
return () => {
if (jobPollRef.current) clearInterval(jobPollRef.current)
}
}, [jobQueue.length, fetchJobs])
const handleRetryJob = async (jobId: string) => {
await fetch('/api/ai-jobs', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({ action: 'retry', jobId }),
})
fetchJobs()
}
const handleCancelJob = async (jobId: string) => {
await fetch('/api/ai-jobs', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({ action: 'cancel', jobId }),
})
fetchJobs()
}
const handleCancelAll = async () => {
await fetch('/api/ai-jobs', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({ action: 'cancel-all' }),
})
fetchJobs()
}
const handleClearHistory = async () => {
await fetch('/api/ai-jobs', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({ action: 'clear-history' }),
})
fetchJobs()
}
const fetchLibraryOverrides = useCallback(async (libraryId: string) => {
try {
const res = await fetch(`/api/ai-settings/library/${libraryId}`)
@@ -201,12 +306,182 @@ export default function AiTaggingPage() {
return (
<div className="max-w-2xl">
<h1 className="text-2xl font-semibold mb-1" style={{ color: 'var(--text-primary)' }}>
AI Tagging
AI Integrations
</h1>
<p className="text-sm mb-8" style={{ color: 'var(--text-secondary)' }}>
Automatically tag media using a vision-capable LLM on your network.
Manage AI-powered tagging, descriptions, and text extraction.
</p>
{/* ─── Job Queue ─────────────────────────────────────────────────────── */}
<Section title="Job Queue">
{(() => {
const running = jobQueue.filter((j) => j.status === 'running')
const queued = jobQueue.filter((j) => j.status === 'queued')
if (running.length === 0 && queued.length === 0) {
return (
<p className="text-sm" style={{ color: 'var(--text-secondary)' }}>
No active jobs.
</p>
)
}
return (
<div className="flex flex-col gap-3">
<div className="flex items-center justify-between">
<p className="text-xs" style={{ color: 'var(--text-secondary)' }}>
{running.length > 0 && <span>{running.length} running</span>}
{running.length > 0 && queued.length > 0 && ', '}
{queued.length > 0 && <span>{queued.length} queued</span>}
</p>
{queued.length > 0 && (
<button
type="button"
onClick={handleCancelAll}
className="text-xs px-2 py-1 rounded transition-colors"
style={{ color: '#fca5a5', backgroundColor: '#7f1d1d33' }}
>
Cancel All
</button>
)}
</div>
<div className="flex flex-col divide-y" style={{ borderColor: 'var(--border)' }}>
{running.map((job) => (
<div key={job.id} className="flex items-center gap-3 py-2">
<span
className="text-xs px-2 py-0.5 rounded-full animate-pulse"
style={{ backgroundColor: '#16a34a33', color: '#4ade80' }}
>
Running
</span>
<span className="text-sm flex-1 truncate" style={{ color: 'var(--text-primary)' }}>
{job.itemTitle || job.itemKey}
</span>
<span className="text-xs" style={{ color: 'var(--text-secondary)' }}>
{job.jobType}
</span>
{job.startedAt && (
<span className="text-xs tabular-nums" style={{ color: 'var(--text-secondary)' }}>
{formatElapsed(job.startedAt)}
</span>
)}
</div>
))}
{queued.map((job) => (
<div key={job.id} className="flex items-center gap-3 py-2">
<span
className="text-xs px-2 py-0.5 rounded-full"
style={{ backgroundColor: 'var(--border)', color: 'var(--text-secondary)' }}
>
Queued
</span>
<span className="text-sm flex-1 truncate" style={{ color: 'var(--text-primary)' }}>
{job.itemTitle || job.itemKey}
</span>
<span className="text-xs" style={{ color: 'var(--text-secondary)' }}>
{job.jobType}
</span>
<button
type="button"
onClick={() => handleCancelJob(job.id)}
className="text-xs px-2 py-0.5 rounded transition-colors"
style={{ color: 'var(--text-secondary)' }}
>
✕
</button>
</div>
))}
</div>
</div>
)
})()}
</Section>
{/* ─── Job History ───────────────────────────────────────────────────── */}
<Section title="Job History">
{jobHistory.length === 0 ? (
<p className="text-sm" style={{ color: 'var(--text-secondary)' }}>
No recent jobs.
</p>
) : (
<div className="flex flex-col gap-3">
<button
type="button"
onClick={() => setHistoryExpanded((v) => !v)}
className="flex items-center gap-2 text-left"
style={{ color: 'var(--text-secondary)' }}
>
<span
className="text-xs transition-transform inline-block"
style={{ transform: historyExpanded ? 'rotate(180deg)' : 'rotate(0deg)' }}
>
▾
</span>
<span className="text-xs">
{jobHistory.length} recent job{jobHistory.length !== 1 ? 's' : ''}
</span>
</button>
{historyExpanded && (
<>
<div className="flex flex-col divide-y" style={{ borderColor: 'var(--border)' }}>
{jobHistory.map((job) => (
<div key={job.id} className="flex items-center gap-3 py-2">
<span
className="text-xs px-2 py-0.5 rounded-full whitespace-nowrap"
style={{
backgroundColor: job.status === 'completed' ? '#14532d33' : '#7f1d1d33',
color: job.status === 'completed' ? '#4ade80' : '#fca5a5',
}}
>
{job.status === 'completed' ? 'Done' : 'Failed'}
</span>
<div className="flex-1 min-w-0">
<span className="text-sm truncate block" style={{ color: 'var(--text-primary)' }}>
{job.itemTitle || job.itemKey}
</span>
{job.status === 'failed' && job.error && (
<span className="text-xs truncate block" style={{ color: '#fca5a5' }}>
{job.error}
</span>
)}
</div>
<span className="text-xs whitespace-nowrap" style={{ color: 'var(--text-secondary)' }}>
{job.jobType}
</span>
<span className="text-xs whitespace-nowrap" style={{ color: 'var(--text-secondary)' }}>
{job.completedAt ? formatDate(job.completedAt) : ''}
</span>
{job.status === 'failed' && (
<button
type="button"
onClick={() => handleRetryJob(job.id)}
className="text-xs px-2 py-0.5 rounded transition-colors whitespace-nowrap"
style={{ color: 'var(--accent)' }}
>
Retry
</button>
)}
</div>
))}
</div>
<div>
<button
type="button"
onClick={handleClearHistory}
className="text-xs px-3 py-1.5 rounded-lg transition-colors"
style={{
backgroundColor: 'var(--surface)',
color: 'var(--text-secondary)',
border: '1px solid var(--border)',
}}
>
Clear History
</button>
</div>
</>
)}
</div>
)}
</Section>
<Section title="Connection">
{loading ? (
<LoadingRows />
@@ -365,6 +640,29 @@ export default function AiTaggingPage() {
</p>
</Field>
<Field label="Max Retries">
<input
type="number"
min={0}
max={10}
value={settings.maxRetries}
onChange={(e) =>
setSettings((s) => ({ ...s, maxRetries: Math.max(0, Math.min(10, parseInt(e.target.value) || 0)) }))
}
className="w-24 rounded-lg px-3 py-2 text-sm outline-none focus:ring-2"
style={{
backgroundColor: 'var(--background)',
border: '1px solid var(--border)',
color: 'var(--text-primary)',
}}
onFocus={(e) => ((e.currentTarget as HTMLElement).style.borderColor = 'var(--accent)')}
onBlur={(e) => ((e.currentTarget as HTMLElement).style.borderColor = 'var(--border)')}
/>
<p className="mt-1 text-xs" style={{ color: 'var(--text-secondary)' }}>
Number of times to automatically retry a failed AI job before marking it as failed (0–10).
</p>
</Field>
{saveError && (
<p
className="text-sm rounded-lg px-3 py-2"

5
src/components/DoomScrollView.tsx
View File

@@ -196,6 +196,11 @@ export default function DoomScrollView({ items, videoContext = 'mixed', onClose,
const data = await res.json().catch(() => ({}))
throw new Error((data as { error?: string }).error ?? 'Extraction failed')
}
if (res.status === 202) {
setExtractError('Queued — check AI Integrations for progress')
setTimeout(() => setExtractError(null), 4000)
return
}
const result = await res.json()
setExtractedText(result.extractedText || null)
setTranslatedText(result.translatedText || null)

2
src/components/ManageSubNav.tsx
View File

@@ -8,7 +8,7 @@ const TABS = [
{ href: '/manage/tags', label: 'Tags' },
{ href: '/manage/users', label: 'Users' },
{ href: '/manage/scanning', label: 'Scanning' },
{ href: '/manage/ai-tagging', label: 'AI Tagging' },
{ href: '/manage/ai-tagging', label: 'AI Integrations' },
]
export default function ManageSubNav() {

76
src/components/mixed/ImageLightbox.tsx
View File

@@ -27,6 +27,9 @@ export default function ImageLightbox({ url, name, onClose, onPrev, onNext, item
const [extracting, setExtracting] = useState(false)
const [extractError, setExtractError] = useState<string | null>(null)
const [retranslating, setRetranslating] = useState(false)
const [editedExtractedText, setEditedExtractedText] = useState<string>('')
const [savingText, setSavingText] = useState(false)
const [sourceLanguage, setSourceLanguage] = useState('')
// Text overlay state
const [showTextOverlay, setShowTextOverlay] = useState(false)
@@ -45,6 +48,7 @@ export default function ImageLightbox({ url, name, onClose, onPrev, onNext, item
.then((r) => r.json())
.then((data: { extractedText: string | null; extractedTextTranslated: string | null }) => {
setExtractedText(data.extractedText)
setEditedExtractedText(data.extractedText ?? '')
setTranslatedText(data.extractedTextTranslated)
})
.catch(() => {})
@@ -179,14 +183,14 @@ export default function ImageLightbox({ url, name, onClose, onPrev, onNext, item
</div>
{showTags ? (
<div className="flex gap-4 w-full flex-1 min-h-0 items-start overflow-hidden max-h-full">
<div className="flex gap-4 w-full flex-1 min-h-0 items-start overflow-hidden max-h-fit max-w-fit">
{/* Image */}
<div className="w-full flex-1 min-h-0 flex items-center justify-center overflow-hidden max-h-screen relative">
<div className="w-full flex-1 min-w-0 min-h-0 h-full flex items-center justify-center overflow-hidden relative">
{/* eslint-disable-next-line @next/next/no-img-element */}
<img
src={url}
alt={name}
className="object-contain rounded-lg"
className="max-w-full max-h-full w-auto h-auto object-contain rounded-lg"
onClick={(e) => e.stopPropagation()}
/>
{onPrev && (
@@ -265,8 +269,14 @@ export default function ImageLightbox({ url, name, onClose, onPrev, onNext, item
const data = await res.json().catch(() => ({}))
throw new Error((data as { error?: string }).error ?? 'Failed to extract text')
}
if (res.status === 202) {
setExtractError('Queued — check AI Integrations for progress')
setTimeout(() => setExtractError(null), 4000)
return
}
const result = await res.json()
setExtractedText(result.extractedText || null)
setEditedExtractedText(result.extractedText || '')
setTranslatedText(result.translatedText || null)
} catch (err) {
setExtractError(err instanceof Error ? err.message : 'Failed to extract text')
@@ -302,12 +312,41 @@ export default function ImageLightbox({ url, name, onClose, onPrev, onNext, item
<p className="text-xs font-medium mb-1" style={{ color: 'var(--text-secondary)' }}>
Extracted Text
</p>
<pre
className="text-xs whitespace-pre-wrap rounded-lg p-2 max-h-40 overflow-y-auto"
style={{ backgroundColor: 'var(--background)', color: 'var(--text-primary)', border: '1px solid var(--border)' }}
<textarea
value={editedExtractedText}
onChange={(e) => setEditedExtractedText(e.target.value)}
className="text-xs whitespace-pre-wrap rounded-lg p-2 w-full resize-y outline-none"
style={{
backgroundColor: 'var(--background)',
color: 'var(--text-primary)',
border: '1px solid var(--border)',
minHeight: '4rem',
maxHeight: '10rem',
fontFamily: 'inherit',
}}
/>
{editedExtractedText !== extractedText && (
<button
onClick={async () => {
setSavingText(true)
try {
await fetch('/api/ai-tagging/fields', {
method: 'PATCH',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({ itemKey, extractedText: editedExtractedText }),
})
setExtractedText(editedExtractedText)
} finally {
setSavingText(false)
}
}}
disabled={savingText}
className="mt-1 text-xs px-2 py-0.5 rounded-full transition-colors disabled:opacity-50"
style={{ backgroundColor: 'var(--accent)', color: '#fff' }}
>
{extractedText}
</pre>
{savingText ? '⟳ Saving…' : 'Save'}
</button>
)}
</div>
{translatedText && (
@@ -324,6 +363,20 @@ export default function ImageLightbox({ url, name, onClose, onPrev, onNext, item
</div>
)}
<div className="flex items-center gap-1.5 flex-wrap">
<input
type="text"
value={sourceLanguage}
onChange={(e) => setSourceLanguage(e.target.value)}
placeholder="Source lang…"
className="text-xs px-2 py-0.5 rounded-full outline-none"
style={{
backgroundColor: 'var(--background)',
border: '1px solid var(--border)',
color: 'var(--text-primary)',
width: 100,
}}
/>
<button
onClick={async () => {
setRetranslating(true)
@@ -331,14 +384,16 @@ export default function ImageLightbox({ url, name, onClose, onPrev, onNext, item
const res = await fetch('/api/ai-tagging/translate', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({ itemKey }),
body: JSON.stringify({ itemKey, ...(sourceLanguage.trim() && { sourceLanguage: sourceLanguage.trim() }) }),
})
if (!res.ok) {
const data = await res.json().catch(() => ({}))
throw new Error((data as { error?: string }).error ?? 'Failed to translate')
}
if (res.status !== 202) {
const result = await res.json()
setTranslatedText(result.translatedText || null)
}
} catch {
// ignore
} finally {
@@ -346,7 +401,7 @@ export default function ImageLightbox({ url, name, onClose, onPrev, onNext, item
}
}}
disabled={retranslating}
className="self-start text-xs px-2 py-0.5 rounded-full transition-colors disabled:opacity-50"
className="text-xs px-2 py-0.5 rounded-full transition-colors disabled:opacity-50"
style={{ backgroundColor: 'var(--border)', color: 'var(--text-secondary)' }}
onMouseEnter={(e) => {
if (!retranslating) {
@@ -362,6 +417,7 @@ export default function ImageLightbox({ url, name, onClose, onPrev, onNext, item
{retranslating ? '⟳ Translating…' : '🌐 Re-translate'}
</button>
</div>
</div>
)}
</div>
)}

5
src/components/tags/TagSelector.tsx
View File

@@ -192,6 +192,11 @@ export default function TagSelector({ itemKey, onTagsChanged, refreshKey }: Prop
const data = await res.json().catch(() => ({}))
throw new Error((data as { error?: string }).error ?? 'Failed to generate description')
}
if (res.status === 202) {
setDescError('Queued — check AI Integrations for progress')
setTimeout(() => setDescError(null), 4000)
return
}
const { description } = await res.json()
setAiDescription(description)
} catch (err) {

3
src/instrumentation.ts
View File

@@ -5,5 +5,8 @@ export async function register() {
const { startScheduler } = await import('./lib/scheduler')
startScheduler()
const { initJobProcessor } = await import('./lib/ai-jobs')
initJobProcessor()
}
}

351
src/lib/ai-jobs.ts Normal file
View File

@@ -0,0 +1,351 @@
import crypto from 'crypto'
import { getDb } from './db'
import { getAiMaxRetries } from './app-settings'
import { tagSingleItem, generateItemDescription, extractItemText, translateItemText } from './ai-tagger'
export type AiJobType = 'tag' | 'describe' | 'extract' | 'translate'
export type AiJobStatus = 'queued' | 'running' | 'completed' | 'failed'
export interface AiJob {
id: string
itemKey: string
libraryId: string
jobType: AiJobType
status: AiJobStatus
error: string | null
attempt: number
maxRetries: number
createdAt: number
startedAt: number | null
completedAt: number | null
itemTitle: string | null
}
interface AiJobRow {
id: string
item_key: string
library_id: string
job_type: string
status: string
error: string | null
attempt: number
max_retries: number
created_at: number
started_at: number | null
completed_at: number | null
item_title: string | null
}
function rowToJob(row: AiJobRow): AiJob {
return {
id: row.id,
itemKey: row.item_key,
libraryId: row.library_id,
jobType: row.job_type as AiJobType,
status: row.status as AiJobStatus,
error: row.error,
attempt: row.attempt,
maxRetries: row.max_retries,
createdAt: row.created_at,
startedAt: row.started_at,
completedAt: row.completed_at,
itemTitle: row.item_title,
}
}
/**
* Look up the title of a media item for display purposes.
*/
function resolveItemTitle(itemKey: string): string | null {
const db = getDb()
const row = db
.prepare('SELECT title FROM media_items WHERE item_key = ?')
.get(itemKey) as { title: string | null } | undefined
return row?.title ?? null
}
// ─── Enqueue ─────────────────────────────────────────────────────────────────
/**
* Enqueue an AI job. Deduplicates: if a queued/running job with the same
* item_key + job_type already exists, returns its ID instead.
*/
export function enqueueJob(
itemKey: string,
jobType: AiJobType,
libraryId: string,
sourceLanguage?: string,
): string {
const db = getDb()
// Deduplication: check for existing queued/running job
const existing = db
.prepare(
`SELECT id FROM ai_jobs
WHERE item_key = ? AND job_type = ? AND status IN ('queued', 'running')`
)
.get(itemKey, jobType) as { id: string } | undefined
if (existing) return existing.id
const id = crypto.randomUUID()
const maxRetries = getAiMaxRetries()
const title = resolveItemTitle(itemKey)
// Store sourceLanguage in the error field temporarily for translate jobs
// (it's null at creation, so we repurpose it briefly — cleared when the job runs)
const metadata = jobType === 'translate' && sourceLanguage ? sourceLanguage : null
db.prepare(
`INSERT INTO ai_jobs (id, item_key, library_id, job_type, status, error, attempt, max_retries, created_at, item_title)
VALUES (?, ?, ?, ?, 'queued', ?, 0, ?, ?, ?)`
).run(id, itemKey, libraryId, jobType, metadata, maxRetries, Date.now(), title)
// Wake the processor
wakeProcessor()
return id
}
/**
* Enqueue jobs for all media items in a directory (for bulk operations).
* Returns the list of job IDs created.
*/
export function enqueueBulkJobs(
libraryId: string,
dirPath: string,
jobType: AiJobType,
itemTypeFilter?: string,
extFilter?: Set<string>,
): string[] {
const db = getDb()
const prefix = dirPath
? `${libraryId}:mixed_file:${encodeURIComponent(dirPath + '/')}`
: `${libraryId}:mixed_file:`
const items = db
.prepare('SELECT item_key, item_type, file_path FROM media_items WHERE item_key LIKE ? AND item_type = ?')
.all(`${prefix}%`, itemTypeFilter ?? 'mixed_file') as Array<{ item_key: string; item_type: string; file_path: string | null }>
const path = require('path')
const jobIds: string[] = []
for (const item of items) {
if (!item.file_path) continue
if (extFilter) {
const ext = path.extname(item.file_path).toLowerCase()
if (!extFilter.has(ext)) continue
}
const jobId = enqueueJob(item.item_key, jobType, libraryId)
jobIds.push(jobId)
}
return jobIds
}
// ─── Query ───────────────────────────────────────────────────────────────────
export function getJobQueue(): AiJob[] {
const db = getDb()
const rows = db
.prepare(
`SELECT * FROM ai_jobs
WHERE status IN ('running', 'queued')
ORDER BY
CASE status WHEN 'running' THEN 0 ELSE 1 END,
created_at ASC`
)
.all() as AiJobRow[]
return rows.map(rowToJob)
}
export function getJobHistory(limit = 50): AiJob[] {
const db = getDb()
const rows = db
.prepare(
`SELECT * FROM ai_jobs
WHERE status IN ('completed', 'failed')
ORDER BY completed_at DESC
LIMIT ?`
)
.all(limit) as AiJobRow[]
return rows.map(rowToJob)
}
export function getJob(jobId: string): AiJob | null {
const db = getDb()
const row = db
.prepare('SELECT * FROM ai_jobs WHERE id = ?')
.get(jobId) as AiJobRow | undefined
return row ? rowToJob(row) : null
}
// ─── Actions ─────────────────────────────────────────────────────────────────
export function retryJob(jobId: string): boolean {
const db = getDb()
const result = db
.prepare(
`UPDATE ai_jobs SET status = 'queued', error = NULL, attempt = 0, started_at = NULL, completed_at = NULL
WHERE id = ? AND status = 'failed'`
)
.run(jobId)
if (result.changes > 0) {
wakeProcessor()
return true
}
return false
}
export function cancelJob(jobId: string): boolean {
const db = getDb()
const result = db
.prepare("DELETE FROM ai_jobs WHERE id = ? AND status = 'queued'")
.run(jobId)
return result.changes > 0
}
export function cancelAllQueued(): number {
const db = getDb()
const result = db
.prepare("DELETE FROM ai_jobs WHERE status = 'queued'")
.run()
return result.changes
}
export function clearJobHistory(): number {
const db = getDb()
const result = db
.prepare("DELETE FROM ai_jobs WHERE status IN ('completed', 'failed')")
.run()
return result.changes
}
// ─── Processor ───────────────────────────────────────────────────────────────
let processorRunning = false
let processorWake: (() => void) | null = null
function wakeProcessor(): void {
if (processorWake) {
processorWake()
} else if (!processorRunning) {
runProcessor()
}
}
async function processNextJob(): Promise<boolean> {
const db = getDb()
const row = db
.prepare(
`SELECT * FROM ai_jobs
WHERE status = 'queued'
ORDER BY created_at ASC
LIMIT 1`
)
.get() as AiJobRow | undefined
if (!row) return false
const now = Date.now()
// Extract sourceLanguage for translate jobs (stored in error field at enqueue)
const sourceLanguage = row.job_type === 'translate' ? row.error : null
db.prepare(
"UPDATE ai_jobs SET status = 'running', started_at = ?, error = NULL WHERE id = ?"
).run(now, row.id)
try {
switch (row.job_type) {
case 'tag':
await tagSingleItem(row.item_key)
break
case 'describe':
await generateItemDescription(row.item_key)
break
case 'extract':
await extractItemText(row.item_key)
break
case 'translate':
await translateItemText(row.item_key, sourceLanguage || undefined)
break
}
db.prepare(
"UPDATE ai_jobs SET status = 'completed', completed_at = ? WHERE id = ?"
).run(Date.now(), row.id)
} catch (err) {
const errorMessage = err instanceof Error ? err.message : String(err)
const attempt = row.attempt + 1
if (attempt < row.max_retries) {
// Re-queue for retry
db.prepare(
"UPDATE ai_jobs SET status = 'queued', attempt = ?, error = ?, started_at = NULL WHERE id = ?"
).run(attempt, errorMessage, row.id)
} else {
// Final failure
db.prepare(
"UPDATE ai_jobs SET status = 'failed', attempt = ?, error = ?, completed_at = ? WHERE id = ?"
).run(attempt, errorMessage, Date.now(), row.id)
}
console.warn(
`[ai-jobs] Job ${row.id} (${row.job_type} for "${row.item_key}") failed (attempt ${attempt}/${row.max_retries}):`,
errorMessage
)
}
return true
}
async function runProcessor(): Promise<void> {
if (processorRunning) return
processorRunning = true
console.log('[ai-jobs] Processor started')
try {
while (true) {
const hadWork = await processNextJob()
if (!hadWork) {
// Wait for a wake signal or timeout after 60s (then check again for safety)
await new Promise<void>((resolve) => {
processorWake = resolve
setTimeout(() => {
processorWake = null
resolve()
}, 60_000)
})
processorWake = null
}
}
} catch (err) {
console.error('[ai-jobs] Processor crashed:', err)
} finally {
processorRunning = false
console.log('[ai-jobs] Processor stopped')
}
}
/**
* Initialize the job processor. Called on server startup.
* Resets any jobs stuck in 'running' state (from a previous crash) back to 'queued'.
*/
export function initJobProcessor(): void {
const db = getDb()
const result = db
.prepare("UPDATE ai_jobs SET status = 'queued', started_at = NULL WHERE status = 'running'")
.run()
if (result.changes > 0) {
console.log(`[ai-jobs] Reset ${result.changes} stuck running job(s) to queued`)
}
// Check if there are any queued jobs and start the processor
const pending = db
.prepare("SELECT COUNT(*) as count FROM ai_jobs WHERE status = 'queued'")
.get() as { count: number }
if (pending.count > 0) {
runProcessor()
}
}

149
src/lib/ai-tagger.ts
View File

@@ -225,7 +225,7 @@ async function callVisionApi(
/**
* Run AI tagging for a single library. Called after the scanner finishes.
* Processes up to BATCH_LIMIT untagged items per invocation.
* Enqueues up to BATCH_LIMIT untagged items as jobs for the processor.
*/
export async function runAiTagging(library: Library, libraryRoot: string): Promise<void> {
const config = getEffectiveAiConfig(library.id)
@@ -234,14 +234,10 @@ export async function runAiTagging(library: Library, libraryRoot: string): Promi
const activeCategoryIds = new Set(getActiveCategoryIdsForLibrary(library.id))
const allTags = getTags()
const allCategories = getCategories()
const tags = allTags.filter((t) => activeCategoryIds.has(t.categoryId))
const categories = allCategories.filter((c) => activeCategoryIds.has(c.id))
if (tags.length === 0) return
const validTagIds = new Set(tags.map((t) => t.id))
const db = getDb()
const untaggedItems = db
.prepare(
@@ -254,18 +250,13 @@ export async function runAiTagging(library: Library, libraryRoot: string): Promi
if (untaggedItems.length === 0) return
console.log(`[ai-tagger] Processing ${untaggedItems.length} items in library "${library.name}"`)
// Import enqueueJob lazily to avoid circular dependency
const { enqueueJob } = await import('./ai-jobs')
let tagged = 0
let consecutiveFailures = 0
let enqueued = 0
const markTagged = db.prepare('UPDATE media_items SET ai_tagged_at = ? WHERE item_key = ?')
for (const item of untaggedItems) {
if (consecutiveFailures >= MAX_CONSECUTIVE_FAILURES) {
console.warn(`[ai-tagger] Aborting after ${MAX_CONSECUTIVE_FAILURES} consecutive failures`)
break
}
const resolvedMedia = resolveItemImage(libraryRoot, item)
if (!resolvedMedia) {
// No image or video available — mark as tagged so we don't retry every scan
@@ -273,48 +264,14 @@ export async function runAiTagging(library: Library, libraryRoot: string): Promi
continue
}
try {
let base64Images: string[]
if (resolvedMedia.mediaType === 'video') {
const framePaths = await getVideoFramePaths(resolvedMedia.path, library.id, VIDEO_FRAME_PERCENTAGES)
base64Images = framePaths.map((p) => fs.readFileSync(p, 'base64'))
} else {
const thumbnailPath = await getAiImagePath(resolvedMedia.path, library.id)
base64Images = [fs.readFileSync(thumbnailPath, 'base64')]
}
const { tags: currentItemTags } = getResolvedTagsForItem(item.item_key)
const aiFields = getAiFields(item.item_key)
const systemPrompt = buildTagPrompt(tags, categories, {
currentTags: currentItemTags,
mediaContext: resolvedMedia.mediaType,
aiDescription: aiFields.aiDescription,
extractedText: aiFields.extractedTextTranslated ?? aiFields.extractedText,
customInstruction: config.promptTagger || undefined,
})
const suggestedIds = await callVisionApi(config.endpoint, taggingModel, base64Images, systemPrompt)
// Filter to valid tags only
const validIds = suggestedIds.filter((id) => validTagIds.has(id))
for (const tagId of validIds) {
addTagToItem(item.item_key, tagId)
}
enqueueJob(item.item_key, 'tag', library.id)
// Mark as tagged immediately so subsequent scans don't re-enqueue
markTagged.run(Date.now(), item.item_key)
tagged++
consecutiveFailures = 0
} catch (err) {
consecutiveFailures++
console.warn(
`[ai-tagger] Failed to tag "${item.item_key}":`,
err instanceof Error ? err.message : err
)
}
enqueued++
}
if (tagged > 0) {
console.log(`[ai-tagger] Tagged ${tagged}/${untaggedItems.length} items in library "${library.name}"`)
if (enqueued > 0) {
console.log(`[ai-tagger] Enqueued ${enqueued} tagging jobs for library "${library.name}"`)
}
}
@@ -554,6 +511,24 @@ export async function generateItemDescription(itemKey: string): Promise<string>
* If the extracted text is not in the user's preferred language, auto-translates it.
* Returns { extractedText, translatedText }.
*/
/**
* Parse a structured extraction response from the AI.
* Returns null if the response cannot be parsed as valid JSON with the expected shape.
*/
function parseStructuredExtraction(raw: string): { text: string; needsTranslation: boolean } | null {
const jsonMatch = raw.match(/\{[\s\S]*\}/)
if (!jsonMatch) return null
try {
const parsed = JSON.parse(jsonMatch[0])
if (typeof parsed.text === 'string' && typeof parsed.needsTranslation === 'boolean') {
return { text: parsed.text, needsTranslation: parsed.needsTranslation }
}
} catch {
// fall through
}
return null
}
export async function extractItemText(itemKey: string): Promise<{ extractedText: string; translatedText: string | null }> {
const libraryId = itemKey.split(':')[0]
const config = getEffectiveAiConfig(libraryId)
@@ -590,9 +565,46 @@ export async function extractItemText(itemKey: string): Promise<{ extractedText:
const thumbnailPath = await getAiImagePath(resolvedMedia.path, libraryId)
const base64Images = [fs.readFileSync(thumbnailPath, 'base64')]
const systemPrompt = `You are an OCR assistant. Extract ALL text visible in the image exactly as it appears. Preserve line breaks and formatting.${config.promptExtract ? ' ' + config.promptExtract : ''} If there is no text in the image, respond with exactly: [NO TEXT]`
const preferredLanguage = getPreferredLanguage()
const customInstruction = config.promptExtract ? ' ' + config.promptExtract : ''
const extractedText = await callVisionApiText(config.endpoint, extractModel, base64Images, systemPrompt)
// When a preferred language is configured, ask the AI to also flag whether translation is needed.
// This avoids a separate translation API call for text already in the target language.
let systemPrompt: string
if (preferredLanguage) {
systemPrompt = `You are an OCR assistant. Extract ALL text visible in the image exactly as it appears. Preserve line breaks and formatting.${customInstruction}
Respond ONLY with a valid JSON object — no markdown, no explanation:
{"needsTranslation": boolean, "text": "extracted text"}
Rules:
- Set needsTranslation to true if the text is NOT already written in ${preferredLanguage}.
- Set needsTranslation to false if the text IS in ${preferredLanguage}, or if there is no text.
- If there is no text in the image, use exactly: {"needsTranslation": false, "text": "[NO TEXT]"}`
} else {
systemPrompt = `You are an OCR assistant. Extract ALL text visible in the image exactly as it appears. Preserve line breaks and formatting.${customInstruction} If there is no text in the image, respond with exactly: [NO TEXT]`
}
const rawResponse = await callVisionApiText(config.endpoint, extractModel, base64Images, systemPrompt)
// Parse the response — structured JSON when a preferred language is set, plain text otherwise
let extractedText: string
let needsTranslation: boolean
if (preferredLanguage) {
const parsed = parseStructuredExtraction(rawResponse)
if (parsed) {
extractedText = parsed.text
needsTranslation = parsed.needsTranslation
} else {
// Malformed JSON fallback: treat raw response as plain text and attempt translation
extractedText = rawResponse
needsTranslation = true
}
} else {
extractedText = rawResponse
needsTranslation = false
}
if (!extractedText || extractedText === '[NO TEXT]') {
db.prepare('UPDATE media_items SET extracted_text = NULL, extracted_text_translated = NULL WHERE item_key = ?').run(itemKey)
@@ -601,10 +613,9 @@ export async function extractItemText(itemKey: string): Promise<{ extractedText:
db.prepare('UPDATE media_items SET extracted_text = ? WHERE item_key = ?').run(extractedText, itemKey)
// Auto-translate if preferred language is set
const preferredLanguage = getPreferredLanguage()
// Only translate if the extraction step determined the text is not already in the preferred language
let translatedText: string | null = null
if (preferredLanguage) {
if (preferredLanguage && needsTranslation) {
const translateModel = config.modelTranslate || config.model
try {
translatedText = await translateText(config.endpoint, translateModel, extractedText, preferredLanguage, config.promptTranslate)
@@ -623,7 +634,7 @@ export async function extractItemText(itemKey: string): Promise<{ extractedText:
* Translate the extracted_text of an item into the preferred language.
* Returns the translated text or null if no text to translate.
*/
export async function translateItemText(itemKey: string): Promise<string | null> {
export async function translateItemText(itemKey: string, sourceLanguage?: string): Promise<string | null> {
const libraryId = itemKey.split(':')[0]
const config = getEffectiveAiConfig(libraryId)
const translateModel = config.modelTranslate || config.model
@@ -645,7 +656,7 @@ export async function translateItemText(itemKey: string): Promise<string | null>
const preferredLanguage = getPreferredLanguage()
if (!preferredLanguage) return null
const translatedText = await translateText(config.endpoint, translateModel, row.extracted_text, preferredLanguage, config.promptTranslate)
const translatedText = await translateText(config.endpoint, translateModel, row.extracted_text, preferredLanguage, config.promptTranslate, sourceLanguage)
if (translatedText) {
db.prepare('UPDATE media_items SET extracted_text_translated = ? WHERE item_key = ?').run(translatedText, itemKey)
}
@@ -653,6 +664,14 @@ export async function translateItemText(itemKey: string): Promise<string | null>
return translatedText
}
/**
* Update the extracted_text of an item.
*/
export function updateExtractedText(itemKey: string, text: string): void {
const db = getDb()
db.prepare('UPDATE media_items SET extracted_text = ? WHERE item_key = ?').run(text, itemKey)
}
/**
* Translate text to a target language using the chat API.
* Returns null if the text is already in the target language.
@@ -663,16 +682,22 @@ async function translateText(
text: string,
targetLanguage: string,
customInstruction = '',
sourceLanguage?: string,
): Promise<string | null> {
const systemPrompt = `You are a translator. Determine if the following text is already in ${targetLanguage}. If it is, respond with exactly: [ALREADY_TARGET_LANGUAGE]. If it is not, translate it to ${targetLanguage}.${customInstruction ? ' ' + customInstruction : ''}`
let systemPrompt: string
if (sourceLanguage) {
systemPrompt = `You are a translator. Translate the following text from ${sourceLanguage} to ${targetLanguage}.${customInstruction ? ' ' + customInstruction : ''}`
} else {
systemPrompt = `You are a translator. Determine if the following text is already in ${targetLanguage}. If it is, respond with exactly: [ALREADY_TARGET_LANGUAGE]. If it is not, translate it to ${targetLanguage}.${customInstruction ? ' ' + customInstruction : ''}`
}
const result = await callChatApiText(endpoint, model, systemPrompt, text)
if (result === '[ALREADY_TARGET_LANGUAGE]' || !result) {
if (!sourceLanguage && (result === '[ALREADY_TARGET_LANGUAGE]' || !result)) {
return null
}
return result
return result || null
}
/**

12
src/lib/app-settings.ts
View File

@@ -202,3 +202,15 @@ export function getEffectiveAiConfig(libraryId: string): AiConfig {
promptTranslate: overrides.promptTranslate || global.promptTranslate,
}
}
// ─── AI Max Retries ──────────────────────────────────────────────────────────
export function getAiMaxRetries(): number {
const raw = getSetting('ai_max_retries')
const parsed = parseInt(raw ?? '3', 10)
return Number.isFinite(parsed) && parsed >= 0 ? parsed : 3
}
export function setAiMaxRetries(n: number): void {
setSetting('ai_max_retries', String(Math.max(0, Math.floor(n))))
}

24
src/lib/db.ts
View File

@@ -105,6 +105,7 @@ function initDb(db: Database.Database): void {
migrateMediaItemsAiTagged(db)
migrateMediaItemsAiFields(db)
migrateLibraryAiSettings(db)
migrateAiJobs(db)
seedAppSettings(db)
}
@@ -117,6 +118,7 @@ function seedAppSettings(db: Database.Database): void {
ai_endpoint: '',
ai_model: '',
preferred_language: 'English',
ai_max_retries: '3',
}
const insert = db.prepare(
'INSERT OR IGNORE INTO app_settings (key, value) VALUES (?, ?)'
@@ -298,3 +300,25 @@ function migrateLibrariesType(db: Database.Database): void {
`)
}
}
function migrateAiJobs(db: Database.Database): void {
db.exec(`
CREATE TABLE IF NOT EXISTS ai_jobs (
id TEXT PRIMARY KEY,
item_key TEXT NOT NULL,
library_id TEXT NOT NULL,
job_type TEXT NOT NULL CHECK(job_type IN ('tag','describe','extract','translate')),
status TEXT NOT NULL DEFAULT 'queued' CHECK(status IN ('queued','running','completed','failed')),
error TEXT,
attempt INTEGER NOT NULL DEFAULT 0,
max_retries INTEGER NOT NULL DEFAULT 3,
created_at INTEGER NOT NULL,
started_at INTEGER,
completed_at INTEGER,
item_title TEXT
);
CREATE INDEX IF NOT EXISTS ai_jobs_status ON ai_jobs(status);
CREATE INDEX IF NOT EXISTS ai_jobs_created_at ON ai_jobs(created_at);
`)
}