feat(ocr): Implement persistent worker pool with SQLite job queue

Major OCR infrastructure improvements:
- Add persistent SQLite-based job queue for OCR tasks
- Implement worker pool with process isolation and auto-restart
- Add OCR engine selector dropdown (Tesseract/PaddleOCR) in upload zone
- Optimize Tesseract preprocessing based on benchmark results (8x faster)
- Add recognize_cif_optimized() with multi-strategy CIF extraction
- Add Romanian CIF checksum validation
- Increase Telegram long polling timeout from 10s to 30s

Squashed commits:
- feat(ocr): Implement persistent worker pool with SQLite job queue
- feat(ocr): Add OCR engine selector dropdown to upload zone
- perf(telegram): Increase long polling timeout from 10s to 30s
- perf(ocr): Optimize Tesseract preprocessing based on benchmark results

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

src/modules/data-entry/components/ocr/OCRUploadZone.vue

@@ -21,8 +21,8 @@
           style="width: 50px; height: 50px"
           strokeWidth="4"
         />
-        <p class="processing-text">Se proceseaza imaginea...</p>
-        <p class="processing-subtext">Acest proces poate dura cateva secunde</p>
+        <p class="processing-text">{{ processingMessage }}</p>
+        <p class="processing-subtext">{{ processingSubtext }}</p>
       </div>
 
       <div v-else-if="selectedFile" class="file-selected-state">
@@ -52,6 +52,15 @@
         size="small"
         @click="triggerFileInput"
       />
+      <!-- OCR Engine Selector -->
+      <Dropdown
+        v-model="selectedEngine"
+        :options="engineOptions"
+        optionLabel="label"
+        optionValue="value"
+        placeholder="Motor OCR"
+        class="engine-selector dropdown-borderless"
+      />
       <Button
         label="Proceseaza OCR"
         icon="pi pi-cog"
@@ -68,7 +77,8 @@
 </template>
 
 <script setup>
-import { ref } from 'vue'
+import { ref, computed } from 'vue'
+import Dropdown from 'primevue/dropdown'
 import api from '@data-entry/services/api'
 
 const emit = defineEmits(['ocr-result', 'file-selected', 'error'])
@@ -79,6 +89,42 @@ const isDragging = ref(false)
 const processing = ref(false)
 const error = ref(null)
 
+// OCR Engine selection
+const selectedEngine = ref('auto')
+const engineOptions = [
+  { label: 'Auto (Recomandat)', value: 'auto' },
+  { label: 'PaddleOCR', value: 'paddleocr' },
+  { label: 'Tesseract', value: 'tesseract' }
+]
+
+// Job queue state
+const jobId = ref(null)
+const queuePosition = ref(null)
+const estimatedWait = ref(null)
+const jobStatus = ref(null)
+let pollInterval = null
+
+// Dynamic processing messages
+const processingMessage = computed(() => {
+  if (jobStatus.value === 'pending' && queuePosition.value > 0) {
+    return `In coada... Pozitia ${queuePosition.value}`
+  }
+  if (jobStatus.value === 'processing') {
+    return 'Se proceseaza imaginea...'
+  }
+  return 'Se trimite...'
+})
+
+const processingSubtext = computed(() => {
+  if (jobStatus.value === 'pending' && estimatedWait.value > 0) {
+    return `Timp estimat: ~${estimatedWait.value} secunde`
+  }
+  if (jobStatus.value === 'processing') {
+    return 'Extragere date cu OCR'
+  }
+  return 'Asteptati...'
+})
+
 const onDragOver = () => {
   isDragging.value = true
 }
@@ -130,37 +176,130 @@ const processOCR = async () => {
 
   processing.value = true
   error.value = null
+  jobId.value = null
+  queuePosition.value = null
+  estimatedWait.value = null
+  jobStatus.value = 'submitting'
 
   try {
     const formData = new FormData()
     formData.append('file', selectedFile.value)
 
-    // Don't set Content-Type header - let browser set it with boundary for multipart/form-data
-    // The API interceptor will add Authorization header automatically
-    const response = await api.post('/ocr/extract', formData, {
-      timeout: 60000, // 60 second timeout for OCR
+    console.log('🔍 OCR Submit:', {
+      fileName: selectedFile.value?.name,
+      fileSize: selectedFile.value?.size,
+      fileType: selectedFile.value?.type,
+      engine: selectedEngine.value
     })
 
-    if (response.data.success) {
-      // Include the OCR message in the data for debugging
-      const resultData = {
-        ...response.data.data,
-        _ocr_message: response.data.message
-      }
-      emit('ocr-result', resultData)
-    } else {
-      error.value = response.data.message || 'OCR processing failed'
-      emit('error', error.value)
-    }
+    // Step 1: Submit job to queue (returns immediately)
+    // Include engine parameter in query string
+    const submitResponse = await api.post(`/ocr/extract?engine=${selectedEngine.value}`, formData, {
+      timeout: 30000, // 30s timeout for submission
+    })
+
+    const job = submitResponse.data
+    jobId.value = job.job_id
+    queuePosition.value = job.queue_position
+    estimatedWait.value = job.estimated_wait_seconds
+    jobStatus.value = job.status
+
+    console.log('📋 OCR Job Created:', job)
+
+    // Step 2: Start polling for result
+    await pollJobStatus(job.job_id)
+
   } catch (err) {
+    console.error('🔴 OCR Error:', {
+      message: err.message,
+      code: err.code,
+      response: err.response?.data
+    })
     const message = err.response?.data?.detail || err.message || 'Eroare la procesarea OCR'
     error.value = message
     emit('error', message)
-  } finally {
     processing.value = false
   }
 }
 
+const pollJobStatus = async (id) => {
+  const maxAttempts = 120 // 2 minutes max (120 * 1s)
+  let attempts = 0
+
+  const poll = async () => {
+    try {
+      const response = await api.get(`/ocr/jobs/${id}`)
+      const job = response.data
+
+      jobStatus.value = job.status
+      queuePosition.value = job.queue_position
+      estimatedWait.value = job.estimated_wait_seconds
+
+      console.log('📊 OCR Poll:', { status: job.status, position: job.queue_position })
+
+      if (job.status === 'completed') {
+        // Success! Emit result
+        clearInterval(pollInterval)
+        pollInterval = null
+        processing.value = false
+
+        if (job.result) {
+          console.log('✅ OCR Complete:', job.result)
+          emit('ocr-result', {
+            ...job.result,
+            _processing_time_ms: job.processing_time_ms
+          })
+        } else {
+          error.value = 'OCR completed but no result returned'
+          emit('error', error.value)
+        }
+        return
+      }
+
+      if (job.status === 'failed') {
+        // Failed
+        clearInterval(pollInterval)
+        pollInterval = null
+        processing.value = false
+
+        error.value = job.error || 'OCR processing failed'
+        emit('error', error.value)
+        return
+      }
+
+      // Still pending/processing - continue polling
+      attempts++
+      if (attempts >= maxAttempts) {
+        clearInterval(pollInterval)
+        pollInterval = null
+        processing.value = false
+        error.value = 'Timeout - procesarea a durat prea mult'
+        emit('error', error.value)
+      }
+
+    } catch (err) {
+      console.error('🔴 Poll Error:', err.message)
+      attempts++
+      // Don't stop on poll errors - network might be flaky
+      if (attempts >= maxAttempts) {
+        clearInterval(pollInterval)
+        pollInterval = null
+        processing.value = false
+        error.value = 'Eroare la verificarea starii job-ului'
+        emit('error', error.value)
+      }
+    }
+  }
+
+  // Initial poll immediately
+  await poll()
+
+  // Continue polling every 1 second if still processing
+  if (processing.value) {
+    pollInterval = setInterval(poll, 1000)
+  }
+}
+
 const formatFileSize = (bytes) => {
   if (bytes < 1024) return bytes + ' B'
   if (bytes < 1024 * 1024) return (bytes / 1024).toFixed(1) + ' KB'
@@ -170,6 +309,14 @@ const formatFileSize = (bytes) => {
 const reset = () => {
   selectedFile.value = null
   error.value = null
+  jobId.value = null
+  queuePosition.value = null
+  estimatedWait.value = null
+  jobStatus.value = null
+  if (pollInterval) {
+    clearInterval(pollInterval)
+    pollInterval = null
+  }
   if (fileInput.value) {
     fileInput.value.value = ''
   }
@@ -262,6 +409,23 @@ defineExpose({ reset, processOCR })
   gap: 0.5rem;
   margin-top: 0.75rem;
   justify-content: center;
+  align-items: center;
+  flex-wrap: wrap;
+}
+
+/* Engine selector dropdown */
+.engine-selector {
+  min-width: 150px;
+}
+
+.engine-selector:deep(.p-dropdown-label) {
+  padding: 0.5rem 0.75rem !important;
+  font-size: 0.875rem;
+  color: #475569;
+}
+
+.engine-selector:deep(.p-dropdown-trigger) {
+  width: 2rem !important;
 }
 
 /* Processing state */
@@ -276,6 +440,7 @@ defineExpose({ reset, processOCR })
   font-size: 1rem;
   color: #475569;
   margin: 0.5rem 0 0 0;
+  font-weight: 500;
 }
 
 .processing-subtext {

src/modules/data-entry/services/api.js

@@ -1,7 +1,18 @@
 import axios from 'axios'
 
+// Detect if we're accessing from remote (not localhost)
+const isRemoteAccess = !['localhost', '127.0.0.1'].includes(window.location.hostname)
+
+// For remote access, use direct backend URL (same host, port 8000)
+// For local access, use proxy through Vite
+const baseURL = isRemoteAccess
+  ? `http://${window.location.hostname}:8000/api/data-entry`
+  : import.meta.env.BASE_URL + 'api/data-entry'
+
+console.log('📡 API Config:', { isRemoteAccess, baseURL, hostname: window.location.hostname })
+
 const api = axios.create({
-  baseURL: import.meta.env.BASE_URL + 'api/data-entry',
+  baseURL,
   headers: { 'Content-Type': 'application/json' }
 })
 
@@ -49,8 +60,17 @@ api.interceptors.request.use((config) => {
 
 // Response interceptor for error handling
 api.interceptors.response.use(
-  (response) => response,
+  (response) => {
+    console.log('✅ API Response:', response.config.url, response.status)
+    return response
+  },
   (error) => {
+    console.error('❌ API Error:', {
+      url: error.config?.url,
+      method: error.config?.method,
+      code: error.code,
+      message: error.message
+    })
     if (error.response?.status === 401) {
       // Token expired or invalid - redirect to login
       localStorage.removeItem('access_token')

src/modules/data-entry/views/receipts/ReceiptCreateView.vue

@@ -987,33 +987,63 @@ const rescanAttachmentOCR = async (attachment) => {
     // Create a File object from the blob
     const file = new File([response.data], attachment.filename, { type: attachment.mime_type })
 
-    // Send to OCR
+    // Send to OCR job queue
     const formData = new FormData()
     formData.append('file', file)
 
-    const ocrResponse = await apiService.post('/ocr/extract', formData, {
-      headers: { 'Content-Type': 'multipart/form-data' },
-      timeout: 60000,
+    // Submit job
+    const submitResponse = await apiService.post('/ocr/extract', formData, {
+      timeout: 30000,
     })
 
-    if (ocrResponse.data.success) {
-      const resultData = {
-        ...ocrResponse.data.data,
-        _ocr_message: ocrResponse.data.message
+    const jobId = submitResponse.data.job_id
+    console.log('📋 OCR Rescan Job:', submitResponse.data)
+
+    // Poll for result
+    const maxAttempts = 120
+    let attempts = 0
+
+    while (attempts < maxAttempts) {
+      await new Promise(resolve => setTimeout(resolve, 1000)) // Wait 1 second
+
+      const pollResponse = await apiService.get(`/ocr/jobs/${jobId}`)
+      const job = pollResponse.data
+
+      if (job.status === 'completed') {
+        if (job.result) {
+          ocrData.value = {
+            ...job.result,
+            _processing_time_ms: job.processing_time_ms
+          }
+          ocrCollapsed.value = false
+          toast.add({
+            severity: 'success',
+            summary: 'OCR Procesare',
+            detail: 'Datele au fost re-extrase din atasament',
+            life: 3000,
+          })
+        }
+        break
       }
-      ocrData.value = resultData
-      ocrCollapsed.value = false
-      toast.add({
-        severity: 'success',
-        summary: 'OCR Procesare',
-        detail: 'Datele au fost re-extrase din atasament',
-        life: 3000,
-      })
-    } else {
+
+      if (job.status === 'failed') {
+        toast.add({
+          severity: 'error',
+          summary: 'Eroare OCR',
+          detail: job.error || 'Procesare OCR esuata',
+          life: 5000,
+        })
+        break
+      }
+
+      attempts++
+    }
+
+    if (attempts >= maxAttempts) {
       toast.add({
         severity: 'error',
         summary: 'Eroare OCR',
-        detail: ocrResponse.data.message || 'Procesare OCR esuata',
+        detail: 'Timeout - procesarea a durat prea mult',
         life: 5000,
       })
     }