feat: implement hybrid image extraction and memory management

Backend:
- Add hybrid image extraction for Direct track (inline image blocks)
- Add render_inline_image_regions() fallback when OCR doesn't find images
- Add check_document_for_missing_images() for detecting missing images
- Add memory management system (MemoryGuard, ModelManager, ServicePool)
- Update pdf_generator_service to handle HYBRID processing track
- Add ElementType.LOGO for logo extraction

Frontend:
- Fix PDF viewer re-rendering issues with memoization
- Add TaskNotFound component and useTaskValidation hook
- Disable StrictMode due to react-pdf incompatibility
- Fix task detail and results page loading states

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

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

backend/app/core/config.py

@@ -104,6 +104,37 @@ class Settings(BaseSettings):
     enable_cudnn_benchmark: bool = Field(default=True)  # Optimize convolution algorithms
     num_threads: int = Field(default=4)  # CPU threads for preprocessing
 
+    # ===== Enhanced Memory Management Configuration =====
+    # Memory thresholds (as ratio of total GPU memory)
+    memory_warning_threshold: float = Field(default=0.80)  # 80% - start warning
+    memory_critical_threshold: float = Field(default=0.95)  # 95% - throttle operations
+    memory_emergency_threshold: float = Field(default=0.98)  # 98% - emergency cleanup
+
+    # Memory monitoring
+    memory_check_interval_seconds: int = Field(default=30)  # Background check interval
+    enable_memory_alerts: bool = Field(default=True)  # Enable memory alerts
+
+    # Model lifecycle management
+    enable_model_lifecycle_management: bool = Field(default=True)  # Use ModelManager
+    pp_structure_idle_timeout_seconds: int = Field(default=300)  # Unload PP-Structure after idle
+    structure_model_memory_mb: int = Field(default=2000)  # Estimated memory for PP-StructureV3
+    ocr_model_memory_mb: int = Field(default=500)  # Estimated memory per OCR language model
+
+    # Service pool configuration
+    enable_service_pool: bool = Field(default=True)  # Use OCRServicePool
+    max_services_per_device: int = Field(default=1)  # Max OCRService per GPU
+    max_total_services: int = Field(default=2)  # Max total OCRService instances
+    service_acquire_timeout_seconds: float = Field(default=300.0)  # Timeout for acquiring service
+    max_queue_size: int = Field(default=50)  # Max pending tasks per device
+
+    # Concurrency control
+    max_concurrent_predictions: int = Field(default=2)  # Max concurrent PP-StructureV3 predictions
+    enable_cpu_fallback: bool = Field(default=True)  # Fall back to CPU when GPU memory low
+
+    # Emergency recovery
+    enable_emergency_cleanup: bool = Field(default=True)  # Auto-cleanup on memory pressure
+    enable_worker_restart: bool = Field(default=False)  # Restart workers on OOM (requires supervisor)
+
     # ===== File Upload Configuration =====
     max_upload_size: int = Field(default=52428800)  # 50MB
     allowed_extensions: str = Field(default="png,jpg,jpeg,pdf,bmp,tiff,doc,docx,ppt,pptx")

backend/app/main.py

@@ -7,10 +7,103 @@ from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 from contextlib import asynccontextmanager
 import logging
+import signal
+import sys
+import asyncio
 from pathlib import Path
+from typing import Optional
 
 from app.core.config import settings
 
+
+# =============================================================================
+# Section 6.1: Signal Handlers
+# =============================================================================
+
+# Flag to indicate graceful shutdown is in progress
+_shutdown_requested = False
+_shutdown_complete = asyncio.Event()
+
+# Track active connections for draining
+_active_connections = 0
+_connection_lock = asyncio.Lock()
+
+
+async def increment_connections():
+    """Track active connection count"""
+    global _active_connections
+    async with _connection_lock:
+        _active_connections += 1
+
+
+async def decrement_connections():
+    """Track active connection count"""
+    global _active_connections
+    async with _connection_lock:
+        _active_connections -= 1
+
+
+def get_active_connections() -> int:
+    """Get current active connection count"""
+    return _active_connections
+
+
+def is_shutdown_requested() -> bool:
+    """Check if graceful shutdown has been requested"""
+    return _shutdown_requested
+
+
+def _signal_handler(signum: int, frame) -> None:
+    """
+    Signal handler for SIGTERM and SIGINT.
+
+    Initiates graceful shutdown by setting the shutdown flag.
+    The actual cleanup is handled by the lifespan context manager.
+    """
+    global _shutdown_requested
+    signal_name = signal.Signals(signum).name
+    logger = logging.getLogger(__name__)
+
+    if _shutdown_requested:
+        logger.warning(f"Received {signal_name} again, forcing immediate exit...")
+        sys.exit(1)
+
+    logger.info(f"Received {signal_name}, initiating graceful shutdown...")
+    _shutdown_requested = True
+
+    # Try to stop the event loop gracefully
+    try:
+        loop = asyncio.get_event_loop()
+        if loop.is_running():
+            # Schedule shutdown event
+            loop.call_soon_threadsafe(_shutdown_complete.set)
+    except RuntimeError:
+        pass  # No event loop running
+
+
+def setup_signal_handlers():
+    """
+    Set up signal handlers for graceful shutdown.
+
+    Handles:
+    - SIGTERM: Standard termination signal (from systemd, docker, etc.)
+    - SIGINT: Keyboard interrupt (Ctrl+C)
+    """
+    logger = logging.getLogger(__name__)
+
+    try:
+        # SIGTERM - Standard termination signal
+        signal.signal(signal.SIGTERM, _signal_handler)
+        logger.info("SIGTERM handler installed")
+
+        # SIGINT - Keyboard interrupt
+        signal.signal(signal.SIGINT, _signal_handler)
+        logger.info("SIGINT handler installed")
+
+    except (ValueError, OSError) as e:
+        # Signal handling may not be available in all contexts
+        logger.warning(f"Could not install signal handlers: {e}")
+
 # Ensure log directory exists before configuring logging
 Path(settings.log_file).parent.mkdir(parents=True, exist_ok=True)
 
@@ -38,16 +131,91 @@ for logger_name in ['app', 'app.services', 'app.services.pdf_generator_service',
 logger = logging.getLogger(__name__)
 
 
+async def drain_connections(timeout: float = 30.0):
+    """
+    Wait for active connections to complete (connection draining).
+
+    Args:
+        timeout: Maximum time to wait for connections to drain
+    """
+    logger.info(f"Draining connections (timeout={timeout}s)...")
+    start_time = asyncio.get_event_loop().time()
+
+    while get_active_connections() > 0:
+        elapsed = asyncio.get_event_loop().time() - start_time
+        if elapsed >= timeout:
+            logger.warning(
+                f"Connection drain timeout after {timeout}s. "
+                f"{get_active_connections()} connections still active."
+            )
+            break
+
+        logger.info(f"Waiting for {get_active_connections()} active connections...")
+        await asyncio.sleep(1.0)
+
+    if get_active_connections() == 0:
+        logger.info("All connections drained successfully")
+
+
 @asynccontextmanager
 async def lifespan(app: FastAPI):
     """Application lifespan events"""
     # Startup
     logger.info("Starting Tool_OCR V2 application...")
 
+    # Set up signal handlers for graceful shutdown
+    setup_signal_handlers()
+
     # Ensure all directories exist
     settings.ensure_directories()
     logger.info("All directories created/verified")
 
+    # Initialize memory management if enabled
+    if settings.enable_model_lifecycle_management:
+        try:
+            from app.services.memory_manager import get_model_manager, MemoryConfig
+
+            memory_config = MemoryConfig(
+                warning_threshold=settings.memory_warning_threshold,
+                critical_threshold=settings.memory_critical_threshold,
+                emergency_threshold=settings.memory_emergency_threshold,
+                model_idle_timeout_seconds=settings.pp_structure_idle_timeout_seconds,
+                memory_check_interval_seconds=settings.memory_check_interval_seconds,
+                enable_auto_cleanup=settings.enable_memory_optimization,
+                enable_emergency_cleanup=settings.enable_emergency_cleanup,
+                max_concurrent_predictions=settings.max_concurrent_predictions,
+                enable_cpu_fallback=settings.enable_cpu_fallback,
+                gpu_memory_limit_mb=settings.gpu_memory_limit_mb,
+            )
+            get_model_manager(memory_config)
+            logger.info("Memory management initialized")
+        except Exception as e:
+            logger.warning(f"Failed to initialize memory management: {e}")
+
+    # Initialize service pool if enabled
+    if settings.enable_service_pool:
+        try:
+            from app.services.service_pool import get_service_pool, PoolConfig
+
+            pool_config = PoolConfig(
+                max_services_per_device=settings.max_services_per_device,
+                max_total_services=settings.max_total_services,
+                acquire_timeout_seconds=settings.service_acquire_timeout_seconds,
+                max_queue_size=settings.max_queue_size,
+            )
+            get_service_pool(pool_config)
+            logger.info("OCR service pool initialized")
+        except Exception as e:
+            logger.warning(f"Failed to initialize service pool: {e}")
+
+    # Initialize prediction semaphore for controlling concurrent PP-StructureV3 predictions
+    try:
+        from app.services.memory_manager import get_prediction_semaphore
+        get_prediction_semaphore(max_concurrent=settings.max_concurrent_predictions)
+        logger.info(f"Prediction semaphore initialized (max_concurrent={settings.max_concurrent_predictions})")
+    except Exception as e:
+        logger.warning(f"Failed to initialize prediction semaphore: {e}")
+
     logger.info("Application startup complete")
 
     yield
@@ -55,6 +223,45 @@ async def lifespan(app: FastAPI):
     # Shutdown
     logger.info("Shutting down Tool_OCR application...")
 
+    # Connection draining - wait for active requests to complete
+    await drain_connections(timeout=30.0)
+
+    # Shutdown recovery manager if initialized
+    try:
+        from app.services.memory_manager import shutdown_recovery_manager
+        shutdown_recovery_manager()
+        logger.info("Recovery manager shutdown complete")
+    except Exception as e:
+        logger.debug(f"Recovery manager shutdown skipped: {e}")
+
+    # Shutdown service pool
+    if settings.enable_service_pool:
+        try:
+            from app.services.service_pool import shutdown_service_pool
+            shutdown_service_pool()
+            logger.info("Service pool shutdown complete")
+        except Exception as e:
+            logger.warning(f"Error shutting down service pool: {e}")
+
+    # Shutdown prediction semaphore
+    try:
+        from app.services.memory_manager import shutdown_prediction_semaphore
+        shutdown_prediction_semaphore()
+        logger.info("Prediction semaphore shutdown complete")
+    except Exception as e:
+        logger.warning(f"Error shutting down prediction semaphore: {e}")
+
+    # Shutdown memory manager
+    if settings.enable_model_lifecycle_management:
+        try:
+            from app.services.memory_manager import shutdown_model_manager
+            shutdown_model_manager()
+            logger.info("Memory manager shutdown complete")
+        except Exception as e:
+            logger.warning(f"Error shutting down memory manager: {e}")
+
+    logger.info("Tool_OCR shutdown complete")
+
 
 # Create FastAPI application
 app = FastAPI(
@@ -77,9 +284,7 @@ app.add_middleware(
 # Health check endpoint
 @app.get("/health")
 async def health_check():
-    """Health check endpoint with GPU status"""
-    from app.services.ocr_service import OCRService
-
+    """Health check endpoint with GPU status and memory management info"""
     response = {
         "status": "healthy",
         "service": "Tool_OCR V2",
@@ -88,10 +293,31 @@ async def health_check():
 
     # Add GPU status information
     try:
-        # Create temporary OCRService instance to get GPU status
-        # In production, this should be a singleton service
-        ocr_service = OCRService()
-        gpu_status = ocr_service.get_gpu_status()
+        # Use service pool if available to avoid creating new instances
+        gpu_status = None
+        if settings.enable_service_pool:
+            try:
+                from app.services.service_pool import get_service_pool
+                pool = get_service_pool()
+                pool_stats = pool.get_pool_stats()
+                response["service_pool"] = pool_stats
+
+                # Get GPU status from first available service
+                for device, services in pool.services.items():
+                    for pooled in services:
+                        if hasattr(pooled.service, 'get_gpu_status'):
+                            gpu_status = pooled.service.get_gpu_status()
+                            break
+                    if gpu_status:
+                        break
+            except Exception as e:
+                logger.debug(f"Could not get service pool stats: {e}")
+
+        # Fallback: create temporary instance if no pool or no service available
+        if gpu_status is None:
+            from app.services.ocr_service import OCRService
+            ocr_service = OCRService()
+            gpu_status = ocr_service.get_gpu_status()
 
         response["gpu"] = {
             "available": gpu_status.get("gpu_available", False),
@@ -120,6 +346,15 @@ async def health_check():
             "error": str(e),
         }
 
+    # Add memory management status
+    if settings.enable_model_lifecycle_management:
+        try:
+            from app.services.memory_manager import get_model_manager
+            model_manager = get_model_manager()
+            response["memory_management"] = model_manager.get_model_stats()
+        except Exception as e:
+            logger.debug(f"Could not get memory management stats: {e}")
+
     return response
 
 

backend/app/models/unified_document.py

@@ -212,26 +212,44 @@ class TableData:
         if self.caption:
             html.append(f"<caption>{self.caption}</caption>")
 
-        # Group cells by row
-        rows_data = {}
+        # Group cells by row and column for quick lookup
+        cell_map = {}
         for cell in self.cells:
-            if cell.row not in rows_data:
-                rows_data[cell.row] = []
-            rows_data[cell.row].append(cell)
+            cell_map[(cell.row, cell.col)] = cell
 
-        # Generate HTML
+        # Track which cells are covered by row/col spans
+        covered = set()
+        for cell in self.cells:
+            if cell.row_span > 1 or cell.col_span > 1:
+                for r in range(cell.row, cell.row + cell.row_span):
+                    for c in range(cell.col, cell.col + cell.col_span):
+                        if (r, c) != (cell.row, cell.col):
+                            covered.add((r, c))
+
+        # Generate HTML with proper column filling
         for row_idx in range(self.rows):
             html.append("<tr>")
-            if row_idx in rows_data:
-                for cell in sorted(rows_data[row_idx], key=lambda c: c.col):
+            for col_idx in range(self.cols):
+                # Skip cells covered by row/col spans
+                if (row_idx, col_idx) in covered:
+                    continue
+
+                cell = cell_map.get((row_idx, col_idx))
+                tag = "th" if row_idx == 0 and self.headers else "td"
+
+                if cell:
                     span_attrs = []
                     if cell.row_span > 1:
                         span_attrs.append(f'rowspan="{cell.row_span}"')
                     if cell.col_span > 1:
                         span_attrs.append(f'colspan="{cell.col_span}"')
                     span_str = " ".join(span_attrs)
-                    tag = "th" if row_idx == 0 and self.headers else "td"
-                    html.append(f'<{tag} {span_str}>{cell.content}</{tag}>')
+                    content = cell.content if cell.content else ""
+                    html.append(f'<{tag} {span_str}>{content}</{tag}>')
+                else:
+                    # Fill in empty cell for missing positions
+                    html.append(f'<{tag}></{tag}>')
+
             html.append("</tr>")
 
         html.append("</table>")

backend/app/routers/tasks.py

@@ -39,6 +39,7 @@ from app.schemas.task import (
 from app.services.task_service import task_service
 from app.services.file_access_service import file_access_service
 from app.services.ocr_service import OCRService
+from app.services.service_pool import get_service_pool, PoolConfig
 
 # Import dual-track components
 try:
@@ -47,6 +48,13 @@ try:
 except ImportError:
     DUAL_TRACK_AVAILABLE = False
 
+# Service pool availability
+SERVICE_POOL_AVAILABLE = True
+try:
+    from app.services.memory_manager import get_model_manager
+except ImportError:
+    SERVICE_POOL_AVAILABLE = False
+
 logger = logging.getLogger(__name__)
 
 router = APIRouter(prefix="/api/v2/tasks", tags=["Tasks"])
@@ -63,7 +71,10 @@ def process_task_ocr(
     pp_structure_params: Optional[dict] = None
 ):
     """
-    Background task to process OCR for a task with dual-track support
+    Background task to process OCR for a task with dual-track support.
+
+    Uses OCRServicePool to acquire a shared service instance instead of
+    creating a new one, preventing GPU memory proliferation.
 
     Args:
         task_id: Task UUID string
@@ -80,6 +91,7 @@ def process_task_ocr(
 
     db = SessionLocal()
     start_time = datetime.now()
+    pooled_service = None
 
     try:
         logger.info(f"Starting OCR processing for task {task_id}, file: {filename}")
@@ -91,16 +103,39 @@ def process_task_ocr(
             logger.error(f"Task {task_id} not found in database")
             return
 
-        # Initialize OCR service
-        ocr_service = OCRService()
+        # Acquire OCR service from pool (or create new if pool disabled)
+        ocr_service = None
+        if settings.enable_service_pool and SERVICE_POOL_AVAILABLE:
+            try:
+                service_pool = get_service_pool()
+                pooled_service = service_pool.acquire(
+                    device="GPU:0",
+                    timeout=settings.service_acquire_timeout_seconds,
+                    task_id=task_id
+                )
+                if pooled_service:
+                    ocr_service = pooled_service.service
+                    logger.info(f"Acquired OCR service from pool for task {task_id}")
+                else:
+                    logger.warning(f"Timeout acquiring service from pool, creating new instance")
+            except Exception as e:
+                logger.warning(f"Failed to acquire service from pool: {e}, creating new instance")
+
+        # Fallback: create new instance if pool acquisition failed
+        if ocr_service is None:
+            logger.info("Creating new OCRService instance (pool disabled or unavailable)")
+            ocr_service = OCRService()
 
         # Create result directory before OCR processing (needed for saving extracted images)
         result_dir = Path(settings.result_dir) / task_id
         result_dir.mkdir(parents=True, exist_ok=True)
 
-        # Process the file with OCR (use dual-track if available)
-        if use_dual_track and hasattr(ocr_service, 'process'):
-            # Use new dual-track processing
+        # Process the file with OCR
+        # Use dual-track processing if:
+        # 1. use_dual_track is True (auto-detection)
+        # 2. OR force_track is specified (explicit track selection)
+        if (use_dual_track or force_track) and hasattr(ocr_service, 'process'):
+            # Use new dual-track processing (or forced track)
             ocr_result = ocr_service.process(
                 file_path=Path(file_path),
                 lang=language,
@@ -111,7 +146,7 @@ def process_task_ocr(
                 pp_structure_params=pp_structure_params
             )
         else:
-            # Fall back to traditional processing
+            # Fall back to traditional processing (no force_track support)
             ocr_result = ocr_service.process_image(
                 image_path=Path(file_path),
                 lang=language,
@@ -131,6 +166,16 @@ def process_task_ocr(
             source_file_path=Path(file_path)
         )
 
+        # Release service back to pool (success case)
+        if pooled_service:
+            try:
+                service_pool = get_service_pool()
+                service_pool.release(pooled_service, error=None)
+                logger.info(f"Released OCR service back to pool for task {task_id}")
+                pooled_service = None  # Prevent double release in finally
+            except Exception as e:
+                logger.warning(f"Failed to release service to pool: {e}")
+
         # Close old session and create fresh one to avoid MySQL timeout
         # (long OCR processing may cause connection to become stale)
         db.close()
@@ -158,6 +203,15 @@ def process_task_ocr(
     except Exception as e:
         logger.exception(f"OCR processing failed for task {task_id}")
 
+        # Release service back to pool with error
+        if pooled_service:
+            try:
+                service_pool = get_service_pool()
+                service_pool.release(pooled_service, error=e)
+                pooled_service = None
+            except Exception as release_error:
+                logger.warning(f"Failed to release service to pool: {release_error}")
+
         # Update task status to failed (direct database update)
         try:
             task = db.query(Task).filter(Task.id == task_db_id).first()
@@ -170,6 +224,13 @@ def process_task_ocr(
             logger.error(f"Failed to update task status: {update_error}")
 
     finally:
+        # Ensure service is released in case of any missed release
+        if pooled_service:
+            try:
+                service_pool = get_service_pool()
+                service_pool.release(pooled_service, error=None)
+            except Exception:
+                pass
         db.close()
 
 
@@ -330,7 +391,13 @@ async def get_task(
                 with open(result_path) as f:
                     result_data = json.load(f)
                     metadata = result_data.get("metadata", {})
-                    processing_track = metadata.get("processing_track")
+                    track_str = metadata.get("processing_track")
+                    # Convert string to enum to avoid Pydantic serialization warning
+                    if track_str:
+                        try:
+                            processing_track = ProcessingTrackEnum(track_str)
+                        except ValueError:
+                            processing_track = None
         except Exception:
             pass  # Silently ignore errors reading the result file
 

backend/app/services/direct_extraction_engine.py

@@ -247,9 +247,11 @@ class DirectExtractionEngine:
             element_counter += len(image_elements)
 
         # Extract vector graphics (charts, diagrams) from drawing commands
+        # Pass table_bboxes to filter out table border drawings before clustering
         if self.enable_image_extraction:
             vector_elements = self._extract_vector_graphics(
-                page, page_num, document_id, element_counter, output_dir
+                page, page_num, document_id, element_counter, output_dir,
+                table_bboxes=table_bboxes
             )
             elements.extend(vector_elements)
             element_counter += len(vector_elements)
@@ -705,40 +707,52 @@ class DirectExtractionEngine:
                 y1=bbox_data[3]
             )
 
-            # Extract column widths from table cells
+            # Extract column widths from table cells by analyzing X boundaries
             column_widths = []
             if hasattr(table, 'cells') and table.cells:
-                # Group cells by column
-                cols_x = {}
+                # Collect all unique X boundaries (both left and right edges)
+                x_boundaries = set()
                 for cell in table.cells:
-                    col_idx = None
-                    # Determine column index by x0 position
-                    for idx, x0 in enumerate(sorted(set(c[0] for c in table.cells))):
-                        if abs(cell[0] - x0) < 1.0:  # Within 1pt tolerance
-                            col_idx = idx
-                            break
+                    x_boundaries.add(round(cell[0], 1))  # x0 (left edge)
+                    x_boundaries.add(round(cell[2], 1))  # x1 (right edge)
 
-                    if col_idx is not None:
-                        if col_idx not in cols_x:
-                            cols_x[col_idx] = {'x0': cell[0], 'x1': cell[2]}
-                        else:
-                            cols_x[col_idx]['x1'] = max(cols_x[col_idx]['x1'], cell[2])
+                # Sort boundaries to get column edges
+                sorted_x = sorted(x_boundaries)
 
-                # Calculate width for each column
-                for col_idx in sorted(cols_x.keys()):
-                    width = cols_x[col_idx]['x1'] - cols_x[col_idx]['x0']
-                    column_widths.append(width)
+                # Calculate column widths from adjacent boundaries
+                if len(sorted_x) >= 2:
+                    column_widths = [sorted_x[i+1] - sorted_x[i] for i in range(len(sorted_x)-1)]
+                    logger.debug(f"Calculated column widths from {len(sorted_x)} boundaries: {column_widths}")
+
+            # Extract row heights from table cells by analyzing Y boundaries
+            row_heights = []
+            if hasattr(table, 'cells') and table.cells:
+                # Collect all unique Y boundaries (both top and bottom edges)
+                y_boundaries = set()
+                for cell in table.cells:
+                    y_boundaries.add(round(cell[1], 1))  # y0 (top edge)
+                    y_boundaries.add(round(cell[3], 1))  # y1 (bottom edge)
+
+                # Sort boundaries to get row edges
+                sorted_y = sorted(y_boundaries)
+
+                # Calculate row heights from adjacent boundaries
+                if len(sorted_y) >= 2:
+                    row_heights = [sorted_y[i+1] - sorted_y[i] for i in range(len(sorted_y)-1)]
+                    logger.debug(f"Calculated row heights from {len(sorted_y)} boundaries: {row_heights}")
 
             # Create table cells
+            # Note: Include ALL cells (even empty ones) to preserve table structure
+            # This is critical for correct HTML generation and PDF rendering
             cells = []
             for row_idx, row in enumerate(data):
                 for col_idx, cell_text in enumerate(row):
-                    if cell_text:
-                        cells.append(TableCell(
-                            row=row_idx,
-                            col=col_idx,
-                            content=str(cell_text) if cell_text else ""
-                        ))
+                    # Always add cell, even if empty, to maintain table structure
+                    cells.append(TableCell(
+                        row=row_idx,
+                        col=col_idx,
+                        content=str(cell_text) if cell_text else ""
+                    ))
 
             # Create table data
             table_data = TableData(
@@ -748,8 +762,13 @@ class DirectExtractionEngine:
                 headers=data[0] if data else None  # Assume first row is header
             )
 
-            # Store column widths in metadata
-            metadata = {"column_widths": column_widths} if column_widths else None
+            # Store column widths and row heights in metadata
+            metadata = {}
+            if column_widths:
+                metadata["column_widths"] = column_widths
+            if row_heights:
+                metadata["row_heights"] = row_heights
+            metadata = metadata if metadata else None
 
             return DocumentElement(
                 element_id=f"table_{page_num}_{counter}",
@@ -978,7 +997,9 @@ class DirectExtractionEngine:
                     image_filename = f"{document_id}_p{page_num}_img{img_idx}.png"
                     image_path = output_dir / image_filename
                     pix.save(str(image_path))
-                    image_data["saved_path"] = str(image_path)
+                    # Store relative filename only (consistent with OCR track)
+                    # PDF generator will join with result_dir to get full path
+                    image_data["saved_path"] = image_filename
                     logger.debug(f"Saved image to {image_path}")
 
                 element = DocumentElement(
@@ -1001,12 +1022,272 @@ class DirectExtractionEngine:
 
         return elements
 
+    def has_missing_images(self, page: fitz.Page) -> bool:
+        """
+        Detect if a page likely has images that weren't extracted.
+
+        This checks for inline image blocks (type=1 in text dict) which indicate
+        graphics composed of many small image blocks (like logos) that
+        page.get_images() cannot detect.
+
+        Args:
+            page: PyMuPDF page object
+
+        Returns:
+            True if there are likely missing images that need OCR extraction
+        """
+        try:
+            # Check if get_images found anything
+            standard_images = page.get_images()
+            if standard_images:
+                return False  # Standard images were found, no need for fallback
+
+            # Check for inline image blocks (type=1)
+            text_dict = page.get_text("dict", sort=True)
+            blocks = text_dict.get("blocks", [])
+
+            image_block_count = sum(1 for b in blocks if b.get("type") == 1)
+
+            # If there are many inline image blocks, likely there's a logo or graphic
+            if image_block_count >= 10:
+                logger.info(f"Detected {image_block_count} inline image blocks - may need OCR for image extraction")
+                return True
+
+            return False
+
+        except Exception as e:
+            logger.warning(f"Error checking for missing images: {e}")
+            return False
+
+    def check_document_for_missing_images(self, pdf_path: Path) -> List[int]:
+        """
+        Check a PDF document for pages that likely have missing images.
+
+        This opens the PDF and checks each page for inline image blocks
+        that weren't extracted by get_images().
+
+        Args:
+            pdf_path: Path to the PDF file
+
+        Returns:
+            List of page numbers (1-indexed) that have missing images
+        """
+        pages_with_missing_images = []
+
+        try:
+            doc = fitz.open(str(pdf_path))
+            for page_num in range(len(doc)):
+                page = doc[page_num]
+                if self.has_missing_images(page):
+                    pages_with_missing_images.append(page_num + 1)  # 1-indexed
+            doc.close()
+
+            if pages_with_missing_images:
+                logger.info(f"Document has missing images on pages: {pages_with_missing_images}")
+
+        except Exception as e:
+            logger.error(f"Error checking document for missing images: {e}")
+
+        return pages_with_missing_images
+
+    def render_inline_image_regions(
+        self,
+        pdf_path: Path,
+        unified_doc: 'UnifiedDocument',
+        pages: List[int],
+        output_dir: Optional[Path] = None
+    ) -> int:
+        """
+        Render inline image regions and add them to the unified document.
+
+        This is a fallback when OCR doesn't detect images. It clusters inline
+        image blocks (type=1) and renders them as images.
+
+        Args:
+            pdf_path: Path to the PDF file
+            unified_doc: UnifiedDocument to add images to
+            pages: List of page numbers (1-indexed) to process
+            output_dir: Directory to save rendered images
+
+        Returns:
+            Number of images added
+        """
+        images_added = 0
+
+        try:
+            doc = fitz.open(str(pdf_path))
+
+            for page_num in pages:
+                if page_num < 1 or page_num > len(doc):
+                    continue
+
+                page = doc[page_num - 1]  # 0-indexed
+                page_rect = page.rect
+
+                # Get inline image blocks
+                text_dict = page.get_text("dict", sort=True)
+                blocks = text_dict.get("blocks", [])
+
+                image_blocks = []
+                for block in blocks:
+                    if block.get("type") == 1:  # Image block
+                        bbox = block.get("bbox")
+                        if bbox:
+                            image_blocks.append(fitz.Rect(bbox))
+
+                if len(image_blocks) < 5:  # Reduced from 10
+                    logger.debug(f"Page {page_num}: Only {len(image_blocks)} inline image blocks, skipping")
+                    continue
+
+                logger.info(f"Page {page_num}: Found {len(image_blocks)} inline image blocks")
+
+                # Cluster nearby image blocks
+                regions = self._cluster_nearby_rects(image_blocks, tolerance=5.0)
+                logger.info(f"Page {page_num}: Clustered into {len(regions)} regions")
+
+                # Find the corresponding page in unified_doc
+                target_page = None
+                for p in unified_doc.pages:
+                    if p.page_number == page_num:
+                        target_page = p
+                        break
+
+                if not target_page:
+                    continue
+
+                for region_idx, region_rect in enumerate(regions):
+                    logger.info(f"Page {page_num} region {region_idx}: {region_rect} (w={region_rect.width:.1f}, h={region_rect.height:.1f})")
+
+                    # Skip very small regions
+                    if region_rect.width < 30 or region_rect.height < 30:
+                        logger.info(f"  -> Skipped: too small (min 30x30)")
+                        continue
+
+                    # Skip regions that are primarily in the table area (below top 40%)
+                    # But allow regions that START in the top portion
+                    page_30_pct = page_rect.height * 0.3
+                    page_40_pct = page_rect.height * 0.4
+                    if region_rect.y0 > page_40_pct:
+                        logger.info(f"  -> Skipped: y0={region_rect.y0:.1f} > 40% of page ({page_40_pct:.1f})")
+                        continue
+
+                    logger.info(f"Rendering inline image region {region_idx} on page {page_num}: {region_rect}")
+
+                    try:
+                        # Add small padding
+                        clip_rect = region_rect + (-2, -2, 2, 2)
+                        clip_rect.intersect(page_rect)
+
+                        # Render at 2x resolution
+                        mat = fitz.Matrix(2, 2)
+                        pix = page.get_pixmap(clip=clip_rect, matrix=mat, alpha=False)
+
+                        # Create bounding box
+                        bbox = BoundingBox(
+                            x0=clip_rect.x0,
+                            y0=clip_rect.y0,
+                            x1=clip_rect.x1,
+                            y1=clip_rect.y1
+                        )
+
+                        image_data = {
+                            "width": pix.width,
+                            "height": pix.height,
+                            "colorspace": "rgb",
+                            "type": "inline_region"
+                        }
+
+                        # Save image if output directory provided
+                        if output_dir:
+                            output_dir.mkdir(parents=True, exist_ok=True)
+                            doc_id = unified_doc.document_id or "unknown"
+                            image_filename = f"{doc_id}_p{page_num}_logo{region_idx}.png"
+                            image_path = output_dir / image_filename
+                            pix.save(str(image_path))
+                            image_data["saved_path"] = image_filename
+                            logger.info(f"Saved inline image region to {image_path}")
+
+                        element = DocumentElement(
+                            element_id=f"logo_{page_num}_{region_idx}",
+                            type=ElementType.LOGO,
+                            content=image_data,
+                            bbox=bbox,
+                            confidence=0.9,
+                            metadata={
+                                "region_type": "inline_image_blocks",
+                                "block_count": len(image_blocks)
+                            }
+                        )
+                        target_page.elements.append(element)
+                        images_added += 1
+
+                        pix = None  # Free memory
+
+                    except Exception as e:
+                        logger.error(f"Error rendering inline image region {region_idx}: {e}")
+
+            doc.close()
+
+            if images_added > 0:
+                current_images = unified_doc.metadata.total_images or 0
+                unified_doc.metadata.total_images = current_images + images_added
+                logger.info(f"Added {images_added} inline image regions to document")
+
+        except Exception as e:
+            logger.error(f"Error rendering inline image regions: {e}")
+
+        return images_added
+
+    def _cluster_nearby_rects(self, rects: List[fitz.Rect], tolerance: float = 5.0) -> List[fitz.Rect]:
+        """Cluster nearby rectangles into regions."""
+        if not rects:
+            return []
+
+        sorted_rects = sorted(rects, key=lambda r: (r.y0, r.x0))
+
+        merged = []
+        for rect in sorted_rects:
+            merged_with_existing = False
+            for i, region in enumerate(merged):
+                expanded = region + (-tolerance, -tolerance, tolerance, tolerance)
+                if expanded.intersects(rect):
+                    merged[i] = region | rect
+                    merged_with_existing = True
+                    break
+            if not merged_with_existing:
+                merged.append(rect)
+
+        # Second pass: merge any regions that now overlap
+        changed = True
+        while changed:
+            changed = False
+            new_merged = []
+            skip = set()
+
+            for i, r1 in enumerate(merged):
+                if i in skip:
+                    continue
+                current = r1
+                for j, r2 in enumerate(merged[i+1:], start=i+1):
+                    if j in skip:
+                        continue
+                    expanded = current + (-tolerance, -tolerance, tolerance, tolerance)
+                    if expanded.intersects(r2):
+                        current = current | r2
+                        skip.add(j)
+                        changed = True
+                new_merged.append(current)
+            merged = new_merged
+
+        return merged
+
     def _extract_vector_graphics(self,
                                  page: fitz.Page,
                                  page_num: int,
                                  document_id: str,
                                  counter: int,
-                                 output_dir: Optional[Path]) -> List[DocumentElement]:
+                                 output_dir: Optional[Path],
+                                 table_bboxes: Optional[List[BoundingBox]] = None) -> List[DocumentElement]:
         """
         Extract vector graphics (charts, diagrams) from page.
 
@@ -1020,6 +1301,7 @@ class DirectExtractionEngine:
             document_id: Unique document identifier
             counter: Starting counter for element IDs
             output_dir: Directory to save rendered graphics
+            table_bboxes: List of table bounding boxes to exclude table border drawings
 
         Returns:
             List of DocumentElement objects representing vector graphics
@@ -1034,16 +1316,25 @@ class DirectExtractionEngine:
 
             logger.debug(f"Page {page_num} contains {len(drawings)} vector drawing commands")
 
+            # Filter out drawings that are likely table borders
+            # Table borders are typically thin rectangular lines within table regions
+            non_table_drawings = self._filter_table_border_drawings(drawings, table_bboxes)
+            logger.debug(f"After filtering table borders: {len(non_table_drawings)} drawings remain")
+
+            if not non_table_drawings:
+                logger.debug("All drawings appear to be table borders, no vector graphics to extract")
+                return elements
+
             # Cluster drawings into groups (charts, diagrams, etc.)
             try:
-                # PyMuPDF's cluster_drawings() groups nearby drawings automatically
-                drawing_clusters = page.cluster_drawings()
+                # Use custom clustering that only considers non-table drawings
+                drawing_clusters = self._cluster_non_table_drawings(page, non_table_drawings)
                 logger.debug(f"Clustered into {len(drawing_clusters)} groups")
             except (AttributeError, TypeError) as e:
                 # cluster_drawings not available or has different signature
                 # Fallback: try to identify charts by analyzing drawing density
-                logger.warning(f"cluster_drawings() failed ({e}), using fallback method")
-                drawing_clusters = self._cluster_drawings_fallback(page, drawings)
+                logger.warning(f"Custom clustering failed ({e}), using fallback method")
+                drawing_clusters = self._cluster_drawings_fallback(page, non_table_drawings)
 
             for cluster_idx, bbox in enumerate(drawing_clusters):
                 # Ignore small regions (likely noise or separator lines)
@@ -1148,6 +1439,124 @@ class DirectExtractionEngine:
 
         return filtered_clusters
 
+    def _filter_table_border_drawings(self, drawings: list, table_bboxes: Optional[List[BoundingBox]]) -> list:
+        """
+        Filter out drawings that are likely table borders.
+
+        Table borders are typically:
+        - Thin rectangular lines (height or width < 5pt)
+        - Located within or on the edge of table bounding boxes
+
+        Args:
+            drawings: List of PyMuPDF drawing objects
+            table_bboxes: List of table bounding boxes
+
+        Returns:
+            List of drawings that are NOT table borders (likely logos, charts, etc.)
+        """
+        if not table_bboxes:
+            return drawings
+
+        non_table_drawings = []
+        table_border_count = 0
+
+        for drawing in drawings:
+            rect = drawing.get('rect')
+            if not rect:
+                continue
+
+            draw_rect = fitz.Rect(rect)
+
+            # Check if this drawing is a thin line (potential table border)
+            is_thin_line = draw_rect.width < 5 or draw_rect.height < 5
+
+            # Check if drawing overlaps significantly with any table
+            overlaps_table = False
+            for table_bbox in table_bboxes:
+                table_rect = fitz.Rect(table_bbox.x0, table_bbox.y0, table_bbox.x1, table_bbox.y1)
+
+                # Expand table rect slightly to include border lines on edges
+                expanded_table = table_rect + (-5, -5, 5, 5)
+
+                if expanded_table.contains(draw_rect) or expanded_table.intersects(draw_rect):
+                    # Calculate overlap ratio
+                    intersection = draw_rect & expanded_table
+                    if not intersection.is_empty:
+                        overlap_ratio = intersection.get_area() / draw_rect.get_area() if draw_rect.get_area() > 0 else 0
+
+                        # If drawing is mostly inside table region, it's likely a border
+                        if overlap_ratio > 0.8:
+                            overlaps_table = True
+                            break
+
+            # Keep drawing if it's NOT (thin line AND overlapping table)
+            # This keeps: logos (complex shapes), charts outside tables, etc.
+            if is_thin_line and overlaps_table:
+                table_border_count += 1
+            else:
+                non_table_drawings.append(drawing)
+
+        if table_border_count > 0:
+            logger.debug(f"Filtered out {table_border_count} table border drawings")
+
+        return non_table_drawings
+
+    def _cluster_non_table_drawings(self, page: fitz.Page, drawings: list) -> list:
+        """
+        Cluster non-table drawings into groups.
+
+        This method clusters drawings that have been pre-filtered to exclude table borders.
+        It uses a more conservative clustering approach suitable for logos and charts.
+
+        Args:
+            page: PyMuPDF page object
+            drawings: Pre-filtered list of drawings (excluding table borders)
+
+        Returns:
+            List of fitz.Rect representing clustered drawing regions
+        """
+        if not drawings:
+            return []
+
+        # Collect all drawing bounding boxes
+        bboxes = []
+        for drawing in drawings:
+            rect = drawing.get('rect')
+            if rect:
+                bboxes.append(fitz.Rect(rect))
+
+        if not bboxes:
+            return []
+
+        # More conservative clustering with smaller tolerance
+        # This prevents grouping distant graphics together
+        clusters = []
+        tolerance = 10  # Smaller tolerance than fallback (was 20)
+
+        for bbox in bboxes:
+            # Try to merge with existing cluster
+            merged = False
+            for i, cluster in enumerate(clusters):
+                # Check if bbox is close to this cluster
+                expanded_cluster = cluster + (-tolerance, -tolerance, tolerance, tolerance)
+                if expanded_cluster.intersects(bbox):
+                    # Merge bbox into cluster
+                    clusters[i] = cluster | bbox  # Union of rectangles
+                    merged = True
+                    break
+
+            if not merged:
+                # Create new cluster
+                clusters.append(bbox)
+
+        # Filter out very small clusters (noise)
+        # Keep minimum 30x30 for logos (smaller than default 50x50)
+        filtered_clusters = [c for c in clusters if c.width >= 30 and c.height >= 30]
+
+        logger.debug(f"Non-table clustering: {len(bboxes)} drawings -> {len(clusters)} clusters -> {len(filtered_clusters)} filtered")
+
+        return filtered_clusters
+
     def _deduplicate_table_chart_overlap(self, elements: List[DocumentElement]) -> List[DocumentElement]:
         """
         Intelligently resolve TABLE-CHART overlaps based on table structure completeness.

backend/app/services/ocr_service.py

@@ -25,6 +25,7 @@ except ImportError:
 
 from app.core.config import settings
 from app.services.office_converter import OfficeConverter, OfficeConverterError
+from app.services.memory_manager import get_model_manager, MemoryConfig, MemoryGuard, prediction_context
 
 # Import dual-track components
 try:
@@ -96,6 +97,26 @@ class OCRService:
         self._model_last_used = {}  # Track last usage time for each model
         self._memory_warning_logged = False
 
+        # Initialize MemoryGuard for enhanced memory monitoring
+        self._memory_guard = None
+        if settings.enable_model_lifecycle_management:
+            try:
+                memory_config = MemoryConfig(
+                    warning_threshold=settings.memory_warning_threshold,
+                    critical_threshold=settings.memory_critical_threshold,
+                    emergency_threshold=settings.memory_emergency_threshold,
+                    model_idle_timeout_seconds=settings.pp_structure_idle_timeout_seconds,
+                    gpu_memory_limit_mb=settings.gpu_memory_limit_mb,
+                    enable_cpu_fallback=settings.enable_cpu_fallback,
+                )
+                self._memory_guard = MemoryGuard(memory_config)
+                logger.debug("MemoryGuard initialized for OCRService")
+            except Exception as e:
+                logger.warning(f"Failed to initialize MemoryGuard: {e}")
+
+        # Track if CPU fallback was activated
+        self._cpu_fallback_active = False
+
         self._detect_and_configure_gpu()
 
         # Log GPU optimization settings
@@ -217,53 +238,91 @@ class OCRService:
     def _check_gpu_memory_usage(self):
         """
         Check GPU memory usage and log warnings if approaching limits.
-        Implements memory optimization for RTX 4060 8GB.
+        Uses MemoryGuard for enhanced monitoring with multiple backends.
         """
         if not self.use_gpu or not settings.enable_memory_optimization:
             return
 
         try:
-            device_id = self.gpu_info.get('device_id', 0)
-            memory_allocated = paddle.device.cuda.memory_allocated(device_id)
-            memory_allocated_mb = memory_allocated / (1024**2)
-            memory_limit_mb = settings.gpu_memory_limit_mb
+            # Use MemoryGuard if available for better monitoring
+            if self._memory_guard:
+                stats = self._memory_guard.get_memory_stats()
 
-            utilization = (memory_allocated_mb / memory_limit_mb * 100) if memory_limit_mb > 0 else 0
+                # Log based on usage ratio
+                if stats.gpu_used_ratio > 0.90 and not self._memory_warning_logged:
+                    logger.warning(
+                        f"GPU memory usage critical: {stats.gpu_used_mb:.0f}MB / {stats.gpu_total_mb:.0f}MB "
+                        f"({stats.gpu_used_ratio*100:.1f}%)"
+                    )
+                    logger.warning("Consider enabling auto_unload_unused_models or reducing batch size")
+                    self._memory_warning_logged = True
 
-            if utilization > 90 and not self._memory_warning_logged:
-                logger.warning(f"GPU memory usage high: {memory_allocated_mb:.0f}MB / {memory_limit_mb}MB ({utilization:.1f}%)")
-                logger.warning("Consider enabling auto_unload_unused_models or reducing batch size")
-                self._memory_warning_logged = True
-            elif utilization > 75:
-                logger.info(f"GPU memory: {memory_allocated_mb:.0f}MB / {memory_limit_mb}MB ({utilization:.1f}%)")
+                    # Trigger emergency cleanup if enabled
+                    if settings.enable_emergency_cleanup:
+                        self._cleanup_unused_models()
+                        self._memory_guard.clear_gpu_cache()
+
+                elif stats.gpu_used_ratio > 0.75:
+                    logger.info(
+                        f"GPU memory: {stats.gpu_used_mb:.0f}MB / {stats.gpu_total_mb:.0f}MB "
+                        f"({stats.gpu_used_ratio*100:.1f}%)"
+                    )
+            else:
+                # Fallback to original implementation
+                device_id = self.gpu_info.get('device_id', 0)
+                memory_allocated = paddle.device.cuda.memory_allocated(device_id)
+                memory_allocated_mb = memory_allocated / (1024**2)
+                memory_limit_mb = settings.gpu_memory_limit_mb
+
+                utilization = (memory_allocated_mb / memory_limit_mb * 100) if memory_limit_mb > 0 else 0
+
+                if utilization > 90 and not self._memory_warning_logged:
+                    logger.warning(f"GPU memory usage high: {memory_allocated_mb:.0f}MB / {memory_limit_mb}MB ({utilization:.1f}%)")
+                    logger.warning("Consider enabling auto_unload_unused_models or reducing batch size")
+                    self._memory_warning_logged = True
+                elif utilization > 75:
+                    logger.info(f"GPU memory: {memory_allocated_mb:.0f}MB / {memory_limit_mb}MB ({utilization:.1f}%)")
 
         except Exception as e:
             logger.debug(f"Memory check failed: {e}")
 
     def _cleanup_unused_models(self):
         """
-        Clean up unused language models to free GPU memory.
+        Clean up unused models (including PP-StructureV3) to free GPU memory.
         Models idle longer than model_idle_timeout_seconds will be unloaded.
+
+        Note: PP-StructureV3 is NO LONGER exempted from cleanup - it will be
+        unloaded based on pp_structure_idle_timeout_seconds configuration.
         """
         if not settings.auto_unload_unused_models:
             return
 
         current_time = datetime.now()
-        timeout = settings.model_idle_timeout_seconds
         models_to_remove = []
 
         for lang, last_used in self._model_last_used.items():
-            if lang == 'structure':  # Don't unload structure engine
-                continue
+            # Use different timeout for structure engine vs language models
+            if lang == 'structure':
+                timeout = settings.pp_structure_idle_timeout_seconds
+            else:
+                timeout = settings.model_idle_timeout_seconds
+
             idle_seconds = (current_time - last_used).total_seconds()
             if idle_seconds > timeout:
                 models_to_remove.append(lang)
 
-        for lang in models_to_remove:
-            if lang in self.ocr_engines:
-                logger.info(f"Unloading idle OCR engine for {lang} (idle {timeout}s)")
-                del self.ocr_engines[lang]
-                del self._model_last_used[lang]
+        for model_key in models_to_remove:
+            if model_key == 'structure':
+                if self.structure_engine is not None:
+                    logger.info(f"Unloading idle PP-StructureV3 engine (idle {settings.pp_structure_idle_timeout_seconds}s)")
+                    self._unload_structure_engine()
+                    if model_key in self._model_last_used:
+                        del self._model_last_used[model_key]
+            elif model_key in self.ocr_engines:
+                logger.info(f"Unloading idle OCR engine for {model_key} (idle {settings.model_idle_timeout_seconds}s)")
+                del self.ocr_engines[model_key]
+                if model_key in self._model_last_used:
+                    del self._model_last_used[model_key]
 
         if models_to_remove and self.use_gpu:
             # Clear CUDA cache
@@ -273,6 +332,41 @@ class OCRService:
             except Exception as e:
                 logger.debug(f"Cache clear failed: {e}")
 
+    def _unload_structure_engine(self):
+        """
+        Properly unload PP-StructureV3 engine and free GPU memory.
+        """
+        if self.structure_engine is None:
+            return
+
+        try:
+            # Clear internal engine components
+            if hasattr(self.structure_engine, 'table_engine'):
+                self.structure_engine.table_engine = None
+            if hasattr(self.structure_engine, 'text_detector'):
+                self.structure_engine.text_detector = None
+            if hasattr(self.structure_engine, 'text_recognizer'):
+                self.structure_engine.text_recognizer = None
+            if hasattr(self.structure_engine, 'layout_predictor'):
+                self.structure_engine.layout_predictor = None
+
+            # Delete the engine
+            del self.structure_engine
+            self.structure_engine = None
+
+            # Force garbage collection
+            gc.collect()
+
+            # Clear GPU cache
+            if self.use_gpu:
+                paddle.device.cuda.empty_cache()
+
+            logger.info("PP-StructureV3 engine unloaded successfully")
+
+        except Exception as e:
+            logger.warning(f"Error unloading PP-StructureV3: {e}")
+            self.structure_engine = None
+
     def clear_gpu_cache(self):
         """
         Manually clear GPU memory cache.
@@ -519,46 +613,160 @@ class OCRService:
             logger.warning(f"GPU memory cleanup failed (non-critical): {e}")
             # Don't fail the processing if cleanup fails
 
-    def check_gpu_memory(self, required_mb: int = 2000) -> bool:
+    def check_gpu_memory(self, required_mb: int = 2000, enable_fallback: bool = True) -> bool:
         """
-        Check if sufficient GPU memory is available.
+        Check if sufficient GPU memory is available using MemoryGuard.
+
+        This method now uses MemoryGuard for accurate memory queries across
+        multiple backends (pynvml, torch, paddle) instead of returning True
+        blindly for PaddlePaddle-only environments.
 
         Args:
             required_mb: Required memory in MB (default 2000MB for OCR models)
+            enable_fallback: If True and CPU fallback is enabled, switch to CPU mode
+                           when memory is insufficient instead of returning False
 
         Returns:
-            True if sufficient memory is available or GPU is not used
+            True if sufficient memory is available, GPU is not used, or CPU fallback activated
         """
-        try:
-            # Check GPU memory using torch if available, otherwise use PaddlePaddle
-            free_memory = None
+        # If not using GPU, always return True
+        if not self.use_gpu:
+            return True
 
-            if TORCH_AVAILABLE and torch.cuda.is_available():
-                free_memory = torch.cuda.mem_get_info()[0] / 1024**2
-            elif paddle.device.is_compiled_with_cuda():
-                # PaddlePaddle doesn't have direct API to get free memory,
-                # so we rely on cleanup and continue
-                logger.debug("Using PaddlePaddle GPU, memory info not directly available")
+        try:
+            # Use MemoryGuard if available for accurate multi-backend memory queries
+            if self._memory_guard:
+                is_available, stats = self._memory_guard.check_memory(
+                    required_mb=required_mb,
+                    device_id=self.gpu_info.get('device_id', 0)
+                )
+
+                if not is_available:
+                    logger.warning(
+                        f"GPU memory check failed: {stats.gpu_free_mb:.0f}MB free, "
+                        f"{required_mb}MB required ({stats.gpu_used_ratio*100:.1f}% used)"
+                    )
+
+                    # Try to free memory
+                    logger.info("Attempting memory cleanup before retry...")
+                    self._cleanup_unused_models()
+                    self._memory_guard.clear_gpu_cache()
+
+                    # Check again
+                    is_available, stats = self._memory_guard.check_memory(required_mb=required_mb)
+
+                    if not is_available:
+                        # Memory still insufficient after cleanup
+                        if enable_fallback and settings.enable_cpu_fallback:
+                            logger.warning(
+                                f"Insufficient GPU memory ({stats.gpu_free_mb:.0f}MB) after cleanup. "
+                                f"Activating CPU fallback mode."
+                            )
+                            self._activate_cpu_fallback()
+                            return True  # Continue with CPU
+                        else:
+                            logger.error(
+                                f"Insufficient GPU memory: {stats.gpu_free_mb:.0f}MB available, "
+                                f"{required_mb}MB required"
+                            )
+                            return False
+
+                logger.debug(
+                    f"GPU memory check passed: {stats.gpu_free_mb:.0f}MB free "
+                    f"({stats.gpu_used_ratio*100:.1f}% used)"
+                )
                 return True
 
-            if free_memory is not None:
-                if free_memory < required_mb:
-                    logger.warning(f"Low GPU memory: {free_memory:.0f}MB available, {required_mb}MB required")
-                    # Try to free memory
-                    self.cleanup_gpu_memory()
-                    # Check again
-                    if TORCH_AVAILABLE and torch.cuda.is_available():
-                        free_memory = torch.cuda.mem_get_info()[0] / 1024**2
-                        if free_memory < required_mb:
-                            logger.error(f"Insufficient GPU memory after cleanup: {free_memory:.0f}MB")
-                            return False
-                logger.debug(f"GPU memory check passed: {free_memory:.0f}MB available")
+            else:
+                # Fallback to original implementation
+                free_memory = None
+
+                if TORCH_AVAILABLE and torch.cuda.is_available():
+                    free_memory = torch.cuda.mem_get_info()[0] / 1024**2
+                elif paddle.device.is_compiled_with_cuda():
+                    # PaddlePaddle doesn't have direct API to get free memory,
+                    # use allocated memory to estimate
+                    device_id = self.gpu_info.get('device_id', 0)
+                    allocated = paddle.device.cuda.memory_allocated(device_id) / (1024**2)
+                    total = settings.gpu_memory_limit_mb
+                    free_memory = max(0, total - allocated)
+                    logger.debug(f"Estimated free GPU memory: {free_memory:.0f}MB (total: {total}MB, allocated: {allocated:.0f}MB)")
+
+                if free_memory is not None:
+                    if free_memory < required_mb:
+                        logger.warning(f"Low GPU memory: {free_memory:.0f}MB available, {required_mb}MB required")
+                        self.cleanup_gpu_memory()
+
+                        # Recheck
+                        if TORCH_AVAILABLE and torch.cuda.is_available():
+                            free_memory = torch.cuda.mem_get_info()[0] / 1024**2
+                        else:
+                            allocated = paddle.device.cuda.memory_allocated(device_id) / (1024**2)
+                            free_memory = max(0, total - allocated)
+
+                        if free_memory < required_mb:
+                            if enable_fallback and settings.enable_cpu_fallback:
+                                logger.warning(f"Insufficient GPU memory after cleanup. Activating CPU fallback.")
+                                self._activate_cpu_fallback()
+                                return True
+                            else:
+                                logger.error(f"Insufficient GPU memory after cleanup: {free_memory:.0f}MB")
+                                return False
+
+                    logger.debug(f"GPU memory check passed: {free_memory:.0f}MB available")
+
+                return True
 
-            return True
         except Exception as e:
             logger.warning(f"GPU memory check failed: {e}")
             return True  # Continue processing even if check fails
 
+    def _activate_cpu_fallback(self):
+        """
+        Activate CPU fallback mode when GPU memory is insufficient.
+        This disables GPU usage for the current service instance.
+        """
+        if self._cpu_fallback_active:
+            return  # Already in CPU mode
+
+        logger.warning("=== CPU FALLBACK MODE ACTIVATED ===")
+        logger.warning("GPU memory insufficient, switching to CPU processing")
+        logger.warning("Performance will be significantly reduced")
+
+        self._cpu_fallback_active = True
+        self.use_gpu = False
+
+        # Update GPU info to reflect fallback
+        self.gpu_info['cpu_fallback'] = True
+        self.gpu_info['fallback_reason'] = 'GPU memory insufficient'
+
+        # Clear GPU cache to free memory
+        if self._memory_guard:
+            self._memory_guard.clear_gpu_cache()
+
+    def _restore_gpu_mode(self):
+        """
+        Attempt to restore GPU mode after CPU fallback.
+        Called when memory pressure has been relieved.
+        """
+        if not self._cpu_fallback_active:
+            return
+
+        if not self.gpu_available:
+            return
+
+        # Check if GPU memory is now available
+        if self._memory_guard:
+            is_available, stats = self._memory_guard.check_memory(
+                required_mb=settings.structure_model_memory_mb
+            )
+            if is_available:
+                logger.info("GPU memory available, restoring GPU mode")
+                self._cpu_fallback_active = False
+                self.use_gpu = True
+                self.gpu_info.pop('cpu_fallback', None)
+                self.gpu_info.pop('fallback_reason', None)
+
     def convert_pdf_to_images(self, pdf_path: Path, output_dir: Path) -> List[Path]:
         """
         Convert PDF to images (one per page)
@@ -626,6 +834,24 @@ class OCRService:
         threshold = confidence_threshold if confidence_threshold is not None else self.confidence_threshold
 
         try:
+            # Pre-operation memory check: Try to restore GPU if in fallback and memory available
+            if self._cpu_fallback_active:
+                self._restore_gpu_mode()
+                if not self._cpu_fallback_active:
+                    logger.info("GPU mode restored for processing")
+
+            # Initial memory check before starting any heavy processing
+            # Estimate memory requirement based on image type
+            estimated_memory_mb = 2500  # Conservative estimate for full OCR + layout
+            if detect_layout:
+                estimated_memory_mb += 500  # Additional for PP-StructureV3
+
+            if not self.check_gpu_memory(required_mb=estimated_memory_mb, enable_fallback=True):
+                logger.warning(
+                    f"Pre-operation memory check failed ({estimated_memory_mb}MB required). "
+                    f"Processing will attempt to proceed but may encounter issues."
+                )
+
             # Check if file is Office document
             if self.office_converter.is_office_document(image_path):
                 logger.info(f"Detected Office document: {image_path.name}, converting to PDF")
@@ -748,9 +974,12 @@ class OCRService:
             # Get OCR engine (for non-PDF images)
             ocr_engine = self.get_ocr_engine(lang)
 
-            # Check GPU memory before OCR processing
-            if not self.check_gpu_memory(required_mb=1500):
-                logger.warning("Insufficient GPU memory for OCR, attempting to proceed anyway")
+            # Secondary memory check before OCR processing
+            if not self.check_gpu_memory(required_mb=1500, enable_fallback=True):
+                logger.warning(
+                    f"OCR memory check: insufficient GPU memory (1500MB required). "
+                    f"Mode: {'CPU fallback' if self._cpu_fallback_active else 'GPU (low memory)'}"
+                )
 
             # Get the actual image dimensions that OCR will use
             from PIL import Image
@@ -950,6 +1179,18 @@ class OCRService:
             Tuple of (layout_data, images_metadata)
         """
         try:
+            # Pre-operation memory check for layout analysis
+            if self._cpu_fallback_active:
+                self._restore_gpu_mode()
+                if not self._cpu_fallback_active:
+                    logger.info("GPU mode restored for layout analysis")
+
+            if not self.check_gpu_memory(required_mb=2000, enable_fallback=True):
+                logger.warning(
+                    f"Layout analysis pre-check: insufficient GPU memory (2000MB required). "
+                    f"Mode: {'CPU fallback' if self._cpu_fallback_active else 'GPU'}"
+                )
+
             structure_engine = self._ensure_structure_engine(pp_structure_params)
 
             # Try enhanced processing first
@@ -998,11 +1239,21 @@ class OCRService:
             # Standard processing (original implementation)
             logger.info(f"Running standard layout analysis on {image_path.name}")
 
-            # Check GPU memory before processing
-            if not self.check_gpu_memory(required_mb=2000):
-                logger.warning("Insufficient GPU memory for PP-StructureV3, attempting to proceed anyway")
+            # Memory check before PP-StructureV3 processing
+            if not self.check_gpu_memory(required_mb=2000, enable_fallback=True):
+                logger.warning(
+                    f"PP-StructureV3 memory check: insufficient GPU memory (2000MB required). "
+                    f"Mode: {'CPU fallback' if self._cpu_fallback_active else 'GPU (low memory)'}"
+                )
 
-            results = structure_engine.predict(str(image_path))
+            # Use prediction semaphore to control concurrent predictions
+            # This prevents OOM errors from multiple simultaneous PP-StructureV3.predict() calls
+            with prediction_context(timeout=settings.service_acquire_timeout_seconds) as acquired:
+                if not acquired:
+                    logger.error("Failed to acquire prediction slot (timeout), returning empty layout")
+                    return None, []
+
+                results = structure_engine.predict(str(image_path))
 
             layout_elements = []
             images_metadata = []
@@ -1254,6 +1505,46 @@ class OCRService:
                     if temp_pdf_path:
                         unified_doc.metadata.original_filename = file_path.name
 
+                    # HYBRID MODE: Check if Direct track missed images (e.g., inline image blocks)
+                    # If so, use OCR to extract images and merge them into the Direct result
+                    pages_with_missing_images = self.direct_extraction_engine.check_document_for_missing_images(
+                        actual_file_path
+                    )
+                    if pages_with_missing_images:
+                        logger.info(f"Hybrid mode: Direct track missing images on pages {pages_with_missing_images}, using OCR to extract images")
+                        try:
+                            # Run OCR on the file to extract images
+                            ocr_result = self.process_file_traditional(
+                                actual_file_path, lang, detect_layout=True,
+                                confidence_threshold=confidence_threshold,
+                                output_dir=output_dir, pp_structure_params=pp_structure_params
+                            )
+
+                            # Convert OCR result to extract images
+                            ocr_unified = self.ocr_to_unified_converter.convert(
+                                ocr_result, actual_file_path, 0.0, lang
+                            )
+
+                            # Merge OCR-extracted images into Direct track result
+                            images_added = self._merge_ocr_images_into_direct(
+                                unified_doc, ocr_unified, pages_with_missing_images
+                            )
+                            if images_added > 0:
+                                logger.info(f"Hybrid mode: Added {images_added} images from OCR to Direct track result")
+                                unified_doc.metadata.processing_track = ProcessingTrack.HYBRID
+                            else:
+                                # Fallback: OCR didn't find images either, render inline image blocks directly
+                                logger.info("Hybrid mode: OCR didn't find images, falling back to inline image rendering")
+                                images_added = self.direct_extraction_engine.render_inline_image_regions(
+                                    actual_file_path, unified_doc, pages_with_missing_images, output_dir
+                                )
+                                if images_added > 0:
+                                    logger.info(f"Hybrid mode: Rendered {images_added} inline image regions")
+                                    unified_doc.metadata.processing_track = ProcessingTrack.HYBRID
+                        except Exception as e:
+                            logger.warning(f"Hybrid mode image extraction failed: {e}")
+                            # Continue with Direct track result without images
+
             # Use OCR track (either by recommendation or fallback)
             if recommendation.track == "ocr":
                 # Use OCR for scanned documents, images, etc.
@@ -1269,17 +1560,19 @@ class OCRService:
                 )
                 unified_doc.document_id = document_id
 
-            # Update processing track metadata
-            unified_doc.metadata.processing_track = (
-                ProcessingTrack.DIRECT if recommendation.track == "direct"
-                else ProcessingTrack.OCR
-            )
+            # Update processing track metadata (only if not already set to HYBRID)
+            if unified_doc.metadata.processing_track != ProcessingTrack.HYBRID:
+                unified_doc.metadata.processing_track = (
+                    ProcessingTrack.DIRECT if recommendation.track == "direct"
+                    else ProcessingTrack.OCR
+                )
 
             # Calculate total processing time
             processing_time = (datetime.now() - start_time).total_seconds()
             unified_doc.metadata.processing_time = processing_time
 
-            logger.info(f"Document processing completed in {processing_time:.2f}s using {recommendation.track} track")
+            actual_track = unified_doc.metadata.processing_track.value
+            logger.info(f"Document processing completed in {processing_time:.2f}s using {actual_track} track")
 
             return unified_doc
 
@@ -1290,6 +1583,75 @@ class OCRService:
                 file_path, lang, detect_layout, confidence_threshold, output_dir, pp_structure_params
             )
 
+    def _merge_ocr_images_into_direct(
+        self,
+        direct_doc: 'UnifiedDocument',
+        ocr_doc: 'UnifiedDocument',
+        pages_with_missing_images: List[int]
+    ) -> int:
+        """
+        Merge OCR-extracted images into Direct track result.
+
+        This is used in hybrid mode when Direct track couldn't extract certain
+        images (like logos composed of inline image blocks).
+
+        Args:
+            direct_doc: UnifiedDocument from Direct track
+            ocr_doc: UnifiedDocument from OCR track
+            pages_with_missing_images: List of page numbers (1-indexed) that need images
+
+        Returns:
+            Number of images added
+        """
+        images_added = 0
+
+        try:
+            # Get image element types to look for
+            image_types = {ElementType.FIGURE, ElementType.IMAGE, ElementType.LOGO}
+
+            for page_num in pages_with_missing_images:
+                # Find the target page in direct_doc
+                direct_page = None
+                for page in direct_doc.pages:
+                    if page.page_number == page_num:
+                        direct_page = page
+                        break
+
+                if not direct_page:
+                    continue
+
+                # Find the source page in ocr_doc
+                ocr_page = None
+                for page in ocr_doc.pages:
+                    if page.page_number == page_num:
+                        ocr_page = page
+                        break
+
+                if not ocr_page:
+                    continue
+
+                # Extract image elements from OCR page
+                for element in ocr_page.elements:
+                    if element.type in image_types:
+                        # Assign new element ID to avoid conflicts
+                        new_element_id = f"hybrid_{element.element_id}"
+                        element.element_id = new_element_id
+
+                        # Add to direct page
+                        direct_page.elements.append(element)
+                        images_added += 1
+                        logger.debug(f"Added image element {new_element_id} to page {page_num}")
+
+            # Update image count in direct_doc metadata
+            if images_added > 0:
+                current_images = direct_doc.metadata.total_images or 0
+                direct_doc.metadata.total_images = current_images + images_added
+
+        except Exception as e:
+            logger.error(f"Error merging OCR images into Direct track: {e}")
+
+        return images_added
+
     def process_file_traditional(
         self,
         file_path: Path,
@@ -1441,13 +1803,16 @@ class OCRService:
             UnifiedDocument if dual-track is enabled and use_dual_track=True,
             Dict with legacy format otherwise
         """
-        if use_dual_track and self.dual_track_enabled:
-            # Use dual-track processing
+        # Use dual-track processing if:
+        # 1. use_dual_track is True (auto-detection), OR
+        # 2. force_track is specified (explicit track selection)
+        if (use_dual_track or force_track) and self.dual_track_enabled:
+            # Use dual-track processing (or forced track)
             return self.process_with_dual_track(
                 file_path, lang, detect_layout, confidence_threshold, output_dir, force_track, pp_structure_params
             )
         else:
-            # Use traditional OCR processing
+            # Use traditional OCR processing (no force_track support)
             return self.process_file_traditional(
                 file_path, lang, detect_layout, confidence_threshold, output_dir, pp_structure_params
             )

backend/app/services/pdf_generator_service.py

@@ -572,8 +572,10 @@ class PDFGeneratorService:
                     processing_track = unified_doc.metadata.get('processing_track')
 
             # Route to track-specific rendering method
-            is_direct_track = (processing_track == 'direct' or
-                              processing_track == ProcessingTrack.DIRECT)
+            # ProcessingTrack is (str, Enum), so comparing with enum value works for both string and enum
+            # HYBRID track uses Direct track rendering (Direct text/tables + OCR images)
+            is_direct_track = (processing_track == ProcessingTrack.DIRECT or
+                               processing_track == ProcessingTrack.HYBRID)
 
             logger.info(f"Processing track: {processing_track}, using {'Direct' if is_direct_track else 'OCR'} track rendering")
 
@@ -675,8 +677,11 @@ class PDFGeneratorService:
             logger.info("=== Direct Track PDF Generation ===")
             logger.info(f"Total pages: {len(unified_doc.pages)}")
 
-            # Set current track for helper methods
-            self.current_processing_track = 'direct'
+            # Set current track for helper methods (may be DIRECT or HYBRID)
+            if hasattr(unified_doc, 'metadata') and unified_doc.metadata:
+                self.current_processing_track = unified_doc.metadata.processing_track
+            else:
+                self.current_processing_track = ProcessingTrack.DIRECT
 
             # Get page dimensions from first page (for canvas initialization)
             if not unified_doc.pages:
@@ -1074,11 +1079,16 @@ class PDFGeneratorService:
         # *** 優先級 1: 檢查 ocr_dimensions (UnifiedDocument 轉換來的) ***
         if 'ocr_dimensions' in ocr_data:
             dims = ocr_data['ocr_dimensions']
-            w = float(dims.get('width', 0))
-            h = float(dims.get('height', 0))
-            if w > 0 and h > 0:
-                logger.info(f"使用 ocr_dimensions 欄位的頁面尺寸: {w:.1f} x {h:.1f}")
-                return (w, h)
+            # Handle both dict format {'width': w, 'height': h} and
+            # list format [{'page': 1, 'width': w, 'height': h}, ...]
+            if isinstance(dims, list) and len(dims) > 0:
+                dims = dims[0]  # Use first page dimensions
+            if isinstance(dims, dict):
+                w = float(dims.get('width', 0))
+                h = float(dims.get('height', 0))
+                if w > 0 and h > 0:
+                    logger.info(f"使用 ocr_dimensions 欄位的頁面尺寸: {w:.1f} x {h:.1f}")
+                    return (w, h)
 
         # *** 優先級 2: 檢查原始 JSON 的 dimensions ***
         if 'dimensions' in ocr_data:
@@ -1418,8 +1428,8 @@ class PDFGeneratorService:
             # Set font with track-specific styling
             # Note: OCR track has no StyleInfo (extracted from images), so no advanced formatting
             style_info = region.get('style')
-            is_direct_track = (self.current_processing_track == 'direct' or
-                              self.current_processing_track == ProcessingTrack.DIRECT)
+            is_direct_track = (self.current_processing_track == ProcessingTrack.DIRECT or
+                               self.current_processing_track == ProcessingTrack.HYBRID)
 
             if style_info and is_direct_track:
                 # Direct track: Apply rich styling from StyleInfo
@@ -1661,10 +1671,15 @@ class PDFGeneratorService:
                 return
 
             # Construct full path to image
+            # saved_path is relative to result_dir (e.g., "imgs/element_id.png")
             image_path = result_dir / image_path_str
 
+            # Fallback for legacy data
             if not image_path.exists():
-                logger.warning(f"Image not found: {image_path}")
+                image_path = result_dir / Path(image_path_str).name
+
+            if not image_path.exists():
+                logger.warning(f"Image not found: {image_path_str} (in {result_dir})")
                 return
 
             # Get bbox for positioning
@@ -2289,12 +2304,30 @@ class PDFGeneratorService:
                 col_widths = element.metadata['column_widths']
                 logger.debug(f"Using extracted column widths: {col_widths}")
 
-            # Create table without rowHeights (will use canvas scaling instead)
-            t = Table(table_content, colWidths=col_widths)
+            # Use original row heights from extraction if available
+            # Row heights must match the number of data rows exactly
+            row_heights_list = None
+            if element.metadata and 'row_heights' in element.metadata:
+                extracted_row_heights = element.metadata['row_heights']
+                num_data_rows = len(table_content)
+                num_height_rows = len(extracted_row_heights)
+
+                if num_height_rows == num_data_rows:
+                    row_heights_list = extracted_row_heights
+                    logger.debug(f"Using extracted row heights ({num_height_rows} rows): {row_heights_list}")
+                else:
+                    # Row counts don't match - this can happen with merged cells or empty rows
+                    logger.warning(f"Row height mismatch: {num_height_rows} heights for {num_data_rows} data rows, falling back to auto-sizing")
+
+            # Create table with both column widths and row heights for accurate sizing
+            t = Table(table_content, colWidths=col_widths, rowHeights=row_heights_list)
 
             # Apply style with minimal padding to reduce table extension
+            # Use Chinese font to support special characters (℃, μm, ≦, ×, Ω, etc.)
+            font_for_table = self.font_name if self.font_registered else 'Helvetica'
             style = TableStyle([
                 ('GRID', (0, 0), (-1, -1), 0.5, colors.grey),
+                ('FONTNAME', (0, 0), (-1, -1), font_for_table),
                 ('FONTSIZE', (0, 0), (-1, -1), 8),
                 ('ALIGN', (0, 0), (-1, -1), 'LEFT'),
                 ('VALIGN', (0, 0), (-1, -1), 'TOP'),
@@ -2307,8 +2340,8 @@ class PDFGeneratorService:
             ])
             t.setStyle(style)
 
-            # CRITICAL: Use canvas scaling to fit table within bbox
-            # This is more reliable than rowHeights which doesn't always work
+            # Use canvas scaling as fallback to fit table within bbox
+            # With proper row heights, scaling should be minimal (close to 1.0)
 
             # Step 1: Wrap to get actual rendered size
             actual_width, actual_height = t.wrapOn(pdf_canvas, table_width * 10, table_height * 10)
@@ -2358,11 +2391,16 @@ class PDFGeneratorService:
                 logger.warning(f"No image path for element {element.element_id}")
                 return
 
-            # Construct full path
+            # Construct full path to image
+            # saved_path is relative to result_dir (e.g., "document_id_p1_img0.png")
             image_path = result_dir / image_path_str
 
+            # Fallback for legacy data
             if not image_path.exists():
-                logger.warning(f"Image not found: {image_path}")
+                image_path = result_dir / Path(image_path_str).name
+
+            if not image_path.exists():
+                logger.warning(f"Image not found: {image_path_str} (in {result_dir})")
                 return
 
             # Get bbox
@@ -2388,7 +2426,7 @@ class PDFGeneratorService:
                 preserveAspectRatio=True
             )
 
-            logger.debug(f"Drew image: {image_path_str}")
+            logger.debug(f"Drew image: {image_path} (from: {original_path_str})")
 
         except Exception as e:
             logger.error(f"Failed to draw image element {element.element_id}: {e}")

backend/app/services/pp_structure_enhanced.py

@@ -21,6 +21,8 @@ except ImportError:
 import paddle
 from paddleocr import PPStructureV3
 from app.models.unified_document import ElementType
+from app.core.config import settings
+from app.services.memory_manager import prediction_context
 
 logger = logging.getLogger(__name__)
 
@@ -96,8 +98,22 @@ class PPStructureEnhanced:
         try:
             logger.info(f"Enhanced PP-StructureV3 analysis on {image_path.name}")
 
-            # Perform structure analysis
-            results = self.structure_engine.predict(str(image_path))
+            # Perform structure analysis with semaphore control
+            # This prevents OOM errors from multiple simultaneous predictions
+            with prediction_context(timeout=settings.service_acquire_timeout_seconds) as acquired:
+                if not acquired:
+                    logger.error("Failed to acquire prediction slot (timeout), returning empty result")
+                    return {
+                        'has_parsing_res_list': False,
+                        'elements': [],
+                        'total_elements': 0,
+                        'images': [],
+                        'tables': [],
+                        'element_types': {},
+                        'error': 'Prediction slot timeout'
+                    }
+
+                results = self.structure_engine.predict(str(image_path))
 
             all_elements = []
             all_images = []

backend/app/services/service_pool.py

@@ -0,0 +1,468 @@
+"""
+Tool_OCR - OCR Service Pool
+Manages a pool of OCRService instances to prevent duplicate model loading
+and control concurrent GPU operations.
+"""
+
+import asyncio
+import logging
+import threading
+import time
+from contextlib import contextmanager
+from dataclasses import dataclass, field
+from enum import Enum
+from typing import Any, Dict, List, Optional, TYPE_CHECKING
+
+from app.services.memory_manager import get_model_manager, MemoryConfig
+
+if TYPE_CHECKING:
+    from app.services.ocr_service import OCRService
+
+logger = logging.getLogger(__name__)
+
+
+class ServiceState(Enum):
+    """State of a pooled service"""
+    AVAILABLE = "available"
+    IN_USE = "in_use"
+    UNHEALTHY = "unhealthy"
+    INITIALIZING = "initializing"
+
+
+@dataclass
+class PooledService:
+    """Wrapper for a pooled OCRService instance"""
+    service: Any  # OCRService
+    device: str
+    state: ServiceState = ServiceState.AVAILABLE
+    created_at: float = field(default_factory=time.time)
+    last_used: float = field(default_factory=time.time)
+    use_count: int = 0
+    error_count: int = 0
+    current_task_id: Optional[str] = None
+
+
+class PoolConfig:
+    """Configuration for the service pool"""
+
+    def __init__(
+        self,
+        max_services_per_device: int = 1,
+        max_total_services: int = 2,
+        acquire_timeout_seconds: float = 300.0,
+        max_queue_size: int = 50,
+        health_check_interval_seconds: int = 60,
+        max_consecutive_errors: int = 3,
+        service_idle_timeout_seconds: int = 600,
+        enable_auto_scaling: bool = False,
+    ):
+        self.max_services_per_device = max_services_per_device
+        self.max_total_services = max_total_services
+        self.acquire_timeout_seconds = acquire_timeout_seconds
+        self.max_queue_size = max_queue_size
+        self.health_check_interval_seconds = health_check_interval_seconds
+        self.max_consecutive_errors = max_consecutive_errors
+        self.service_idle_timeout_seconds = service_idle_timeout_seconds
+        self.enable_auto_scaling = enable_auto_scaling
+
+
+class OCRServicePool:
+    """
+    Pool of OCRService instances with concurrency control.
+
+    Features:
+    - Per-device instance management (one service per GPU)
+    - Queue-based task distribution
+    - Semaphore-based concurrency limits
+    - Health monitoring
+    - Automatic service recovery
+    """
+
+    _instance = None
+    _lock = threading.Lock()
+
+    def __new__(cls, *args, **kwargs):
+        """Singleton pattern"""
+        with cls._lock:
+            if cls._instance is None:
+                cls._instance = super().__new__(cls)
+                cls._instance._initialized = False
+            return cls._instance
+
+    def __init__(self, config: Optional[PoolConfig] = None):
+        if self._initialized:
+            return
+
+        self.config = config or PoolConfig()
+        self.services: Dict[str, List[PooledService]] = {}
+        self.semaphores: Dict[str, threading.Semaphore] = {}
+        self.queues: Dict[str, List] = {}
+        self._pool_lock = threading.RLock()
+        self._condition = threading.Condition(self._pool_lock)
+
+        # Metrics
+        self._metrics = {
+            "total_acquisitions": 0,
+            "total_releases": 0,
+            "total_timeouts": 0,
+            "total_errors": 0,
+            "queue_waits": 0,
+        }
+
+        # Initialize default device pool
+        self._initialize_device("GPU:0")
+
+        self._initialized = True
+        logger.info("OCRServicePool initialized")
+
+    def _initialize_device(self, device: str):
+        """Initialize pool resources for a device"""
+        with self._pool_lock:
+            if device not in self.services:
+                self.services[device] = []
+                self.semaphores[device] = threading.Semaphore(
+                    self.config.max_services_per_device
+                )
+                self.queues[device] = []
+                logger.info(f"Initialized pool for device {device}")
+
+    def _create_service(self, device: str) -> PooledService:
+        """
+        Create a new OCRService instance for the pool.
+
+        Args:
+            device: Device identifier (e.g., "GPU:0", "CPU")
+
+        Returns:
+            PooledService wrapper
+        """
+        # Import here to avoid circular imports
+        from app.services.ocr_service import OCRService
+
+        logger.info(f"Creating new OCRService for device {device}")
+        start_time = time.time()
+
+        # Create service instance
+        service = OCRService()
+
+        creation_time = time.time() - start_time
+        logger.info(f"OCRService created in {creation_time:.2f}s for device {device}")
+
+        return PooledService(
+            service=service,
+            device=device,
+            state=ServiceState.AVAILABLE
+        )
+
+    def acquire(
+        self,
+        device: str = "GPU:0",
+        timeout: Optional[float] = None,
+        task_id: Optional[str] = None
+    ) -> Optional[PooledService]:
+        """
+        Acquire an OCRService from the pool.
+
+        Args:
+            device: Preferred device (e.g., "GPU:0")
+            timeout: Maximum time to wait for a service
+            task_id: Optional task ID for tracking
+
+        Returns:
+            PooledService if available, None if timeout
+        """
+        timeout = timeout or self.config.acquire_timeout_seconds
+        self._initialize_device(device)
+
+        start_time = time.time()
+        deadline = start_time + timeout
+
+        with self._condition:
+            while True:
+                # Try to get an available service
+                service = self._try_acquire_service(device, task_id)
+                if service:
+                    self._metrics["total_acquisitions"] += 1
+                    return service
+
+                # Check if we can create a new service
+                if self._can_create_service(device):
+                    try:
+                        pooled = self._create_service(device)
+                        pooled.state = ServiceState.IN_USE
+                        pooled.current_task_id = task_id
+                        pooled.use_count += 1
+                        self.services[device].append(pooled)
+                        self._metrics["total_acquisitions"] += 1
+                        logger.info(f"Created and acquired new service for {device}")
+                        return pooled
+                    except Exception as e:
+                        logger.error(f"Failed to create service for {device}: {e}")
+                        self._metrics["total_errors"] += 1
+
+                # Wait for a service to become available
+                remaining = deadline - time.time()
+                if remaining <= 0:
+                    self._metrics["total_timeouts"] += 1
+                    logger.warning(f"Timeout waiting for service on {device}")
+                    return None
+
+                self._metrics["queue_waits"] += 1
+                logger.debug(f"Waiting for service on {device} (timeout: {remaining:.1f}s)")
+                self._condition.wait(timeout=min(remaining, 1.0))
+
+    def _try_acquire_service(self, device: str, task_id: Optional[str]) -> Optional[PooledService]:
+        """Try to acquire an available service without waiting"""
+        for pooled in self.services.get(device, []):
+            if pooled.state == ServiceState.AVAILABLE:
+                pooled.state = ServiceState.IN_USE
+                pooled.last_used = time.time()
+                pooled.use_count += 1
+                pooled.current_task_id = task_id
+                logger.debug(f"Acquired existing service for {device} (use #{pooled.use_count})")
+                return pooled
+        return None
+
+    def _can_create_service(self, device: str) -> bool:
+        """Check if a new service can be created"""
+        device_count = len(self.services.get(device, []))
+        total_count = sum(len(services) for services in self.services.values())
+
+        return (
+            device_count < self.config.max_services_per_device and
+            total_count < self.config.max_total_services
+        )
+
+    def release(self, pooled: PooledService, error: Optional[Exception] = None):
+        """
+        Release a service back to the pool.
+
+        Args:
+            pooled: The pooled service to release
+            error: Optional error that occurred during use
+        """
+        with self._condition:
+            if error:
+                pooled.error_count += 1
+                self._metrics["total_errors"] += 1
+                logger.warning(f"Service released with error: {error}")
+
+                # Mark unhealthy if too many errors
+                if pooled.error_count >= self.config.max_consecutive_errors:
+                    pooled.state = ServiceState.UNHEALTHY
+                    logger.error(f"Service marked unhealthy after {pooled.error_count} errors")
+                else:
+                    pooled.state = ServiceState.AVAILABLE
+            else:
+                pooled.error_count = 0  # Reset error count on success
+                pooled.state = ServiceState.AVAILABLE
+
+            pooled.last_used = time.time()
+            pooled.current_task_id = None
+            self._metrics["total_releases"] += 1
+
+            # Clean up GPU memory after release
+            try:
+                model_manager = get_model_manager()
+                model_manager.memory_guard.clear_gpu_cache()
+            except Exception as e:
+                logger.debug(f"Cache clear after release failed: {e}")
+
+            # Notify waiting threads
+            self._condition.notify_all()
+
+        logger.debug(f"Service released for device {pooled.device}")
+
+    @contextmanager
+    def acquire_context(
+        self,
+        device: str = "GPU:0",
+        timeout: Optional[float] = None,
+        task_id: Optional[str] = None
+    ):
+        """
+        Context manager for acquiring and releasing a service.
+
+        Usage:
+            with pool.acquire_context("GPU:0") as pooled:
+                result = pooled.service.process(...)
+        """
+        pooled = None
+        error = None
+        try:
+            pooled = self.acquire(device, timeout, task_id)
+            if pooled is None:
+                raise TimeoutError(f"Failed to acquire service for {device}")
+            yield pooled
+        except Exception as e:
+            error = e
+            raise
+        finally:
+            if pooled:
+                self.release(pooled, error)
+
+    def get_service(self, device: str = "GPU:0") -> Optional["OCRService"]:
+        """
+        Get a service directly (for backward compatibility).
+
+        This acquires a service and returns the underlying OCRService.
+        The caller is responsible for calling release_service() when done.
+
+        Args:
+            device: Device identifier
+
+        Returns:
+            OCRService instance or None
+        """
+        pooled = self.acquire(device)
+        if pooled:
+            return pooled.service
+        return None
+
+    def get_pool_stats(self) -> Dict:
+        """Get current pool statistics"""
+        with self._pool_lock:
+            stats = {
+                "devices": {},
+                "metrics": self._metrics.copy(),
+                "total_services": 0,
+                "available_services": 0,
+                "in_use_services": 0,
+            }
+
+            for device, services in self.services.items():
+                available = sum(1 for s in services if s.state == ServiceState.AVAILABLE)
+                in_use = sum(1 for s in services if s.state == ServiceState.IN_USE)
+                unhealthy = sum(1 for s in services if s.state == ServiceState.UNHEALTHY)
+
+                stats["devices"][device] = {
+                    "total": len(services),
+                    "available": available,
+                    "in_use": in_use,
+                    "unhealthy": unhealthy,
+                    "max_allowed": self.config.max_services_per_device,
+                }
+
+                stats["total_services"] += len(services)
+                stats["available_services"] += available
+                stats["in_use_services"] += in_use
+
+            return stats
+
+    def health_check(self) -> Dict:
+        """
+        Perform health check on all pooled services.
+
+        Returns:
+            Health check results
+        """
+        results = {
+            "healthy": True,
+            "services": [],
+            "timestamp": time.time()
+        }
+
+        with self._pool_lock:
+            for device, services in self.services.items():
+                for idx, pooled in enumerate(services):
+                    service_health = {
+                        "device": device,
+                        "index": idx,
+                        "state": pooled.state.value,
+                        "error_count": pooled.error_count,
+                        "use_count": pooled.use_count,
+                        "idle_seconds": time.time() - pooled.last_used,
+                    }
+
+                    # Check if service is responsive
+                    if pooled.state == ServiceState.AVAILABLE:
+                        try:
+                            # Simple check - verify service has required attributes
+                            has_process = hasattr(pooled.service, 'process')
+                            has_gpu_status = hasattr(pooled.service, 'get_gpu_status')
+                            service_health["responsive"] = has_process and has_gpu_status
+                        except Exception as e:
+                            service_health["responsive"] = False
+                            service_health["error"] = str(e)
+                            results["healthy"] = False
+                    else:
+                        service_health["responsive"] = pooled.state != ServiceState.UNHEALTHY
+
+                    if pooled.state == ServiceState.UNHEALTHY:
+                        results["healthy"] = False
+
+                    results["services"].append(service_health)
+
+        return results
+
+    def recover_unhealthy(self):
+        """
+        Attempt to recover unhealthy services.
+        """
+        with self._pool_lock:
+            for device, services in self.services.items():
+                for idx, pooled in enumerate(services):
+                    if pooled.state == ServiceState.UNHEALTHY:
+                        logger.info(f"Attempting to recover unhealthy service {device}:{idx}")
+                        try:
+                            # Remove old service
+                            services.remove(pooled)
+
+                            # Create new service
+                            new_pooled = self._create_service(device)
+                            services.append(new_pooled)
+                            logger.info(f"Successfully recovered service {device}:{idx}")
+
+                        except Exception as e:
+                            logger.error(f"Failed to recover service {device}:{idx}: {e}")
+
+    def shutdown(self):
+        """
+        Shutdown the pool and cleanup all services.
+        """
+        logger.info("OCRServicePool shutdown started")
+
+        with self._pool_lock:
+            for device, services in self.services.items():
+                for pooled in services:
+                    try:
+                        # Clean up service resources
+                        if hasattr(pooled.service, 'cleanup_gpu_memory'):
+                            pooled.service.cleanup_gpu_memory()
+                    except Exception as e:
+                        logger.warning(f"Error cleaning up service: {e}")
+
+            # Clear all pools
+            self.services.clear()
+            self.semaphores.clear()
+            self.queues.clear()
+
+        logger.info("OCRServicePool shutdown completed")
+
+
+# Global singleton instance
+_service_pool: Optional[OCRServicePool] = None
+
+
+def get_service_pool(config: Optional[PoolConfig] = None) -> OCRServicePool:
+    """
+    Get the global OCRServicePool instance.
+
+    Args:
+        config: Optional configuration (only used on first call)
+
+    Returns:
+        OCRServicePool singleton instance
+    """
+    global _service_pool
+    if _service_pool is None:
+        _service_pool = OCRServicePool(config)
+    return _service_pool
+
+
+def shutdown_service_pool():
+    """Shutdown the global service pool"""
+    global _service_pool
+    if _service_pool is not None:
+        _service_pool.shutdown()
+        _service_pool = None

backend/tests/services/test_ocr_memory_integration.py

@@ -0,0 +1,380 @@
+"""
+Tests for OCR Service Memory Integration
+
+Tests the integration of MemoryGuard with OCRService patterns,
+including pre-operation memory checks and CPU fallback logic.
+"""
+
+import pytest
+from unittest.mock import Mock, patch, MagicMock
+import sys
+
+# Mock paddle before importing memory_manager
+paddle_mock = MagicMock()
+paddle_mock.is_compiled_with_cuda.return_value = False
+paddle_mock.device.cuda.device_count.return_value = 0
+paddle_mock.device.cuda.memory_allocated.return_value = 0
+paddle_mock.device.cuda.memory_reserved.return_value = 0
+paddle_mock.device.cuda.empty_cache = MagicMock()
+sys.modules['paddle'] = paddle_mock
+
+from app.services.memory_manager import (
+    MemoryGuard,
+    MemoryConfig,
+    MemoryStats,
+)
+
+
+class TestMemoryGuardIntegration:
+    """Tests for MemoryGuard integration patterns used in OCRService"""
+
+    def setup_method(self):
+        """Setup for each test"""
+        self.config = MemoryConfig(
+            warning_threshold=0.80,
+            critical_threshold=0.95,
+            emergency_threshold=0.98,
+            enable_cpu_fallback=True,
+        )
+
+    def teardown_method(self):
+        """Cleanup after each test"""
+        pass
+
+    def test_memory_check_below_threshold_allows_processing(self):
+        """Test that memory check returns True when below thresholds"""
+        guard = MemoryGuard(self.config)
+
+        # Mock stats below warning threshold
+        with patch.object(guard, 'get_memory_stats') as mock_stats:
+            mock_stats.return_value = MemoryStats(
+                gpu_used_ratio=0.50,
+                gpu_free_mb=4000,
+                gpu_total_mb=8000,
+            )
+
+            is_available, stats = guard.check_memory(required_mb=2000)
+
+            assert is_available is True
+            assert stats.gpu_free_mb >= 2000
+
+        guard.shutdown()
+
+    def test_memory_check_above_critical_blocks_processing(self):
+        """Test that memory check returns False when above critical threshold"""
+        guard = MemoryGuard(self.config)
+
+        # Mock stats above critical threshold
+        with patch.object(guard, 'get_memory_stats') as mock_stats:
+            mock_stats.return_value = MemoryStats(
+                gpu_used_ratio=0.96,
+                gpu_free_mb=320,
+                gpu_total_mb=8000,
+            )
+
+            is_available, stats = guard.check_memory(required_mb=1000)
+
+            assert is_available is False
+
+        guard.shutdown()
+
+    def test_memory_check_insufficient_free_memory(self):
+        """Test that memory check returns False when free memory < required"""
+        guard = MemoryGuard(self.config)
+
+        # Mock stats with insufficient free memory but below critical ratio
+        with patch.object(guard, 'get_memory_stats') as mock_stats:
+            mock_stats.return_value = MemoryStats(
+                gpu_used_ratio=0.70,
+                gpu_free_mb=500,
+                gpu_total_mb=8000,
+            )
+
+            is_available, stats = guard.check_memory(required_mb=1000)
+
+            # Should return False (not enough free memory)
+            assert is_available is False
+
+        guard.shutdown()
+
+
+class TestCPUFallbackPattern:
+    """Tests for CPU fallback pattern as used in OCRService"""
+
+    def test_cpu_fallback_activation_pattern(self):
+        """Test the CPU fallback activation pattern"""
+        # Simulate the pattern used in OCRService._activate_cpu_fallback
+
+        class MockOCRService:
+            def __init__(self):
+                self._cpu_fallback_active = False
+                self.use_gpu = True
+                self.gpu_available = True
+                self.gpu_info = {'device_id': 0}
+                self._memory_guard = Mock()
+
+            def _activate_cpu_fallback(self):
+                if self._cpu_fallback_active:
+                    return
+
+                self._cpu_fallback_active = True
+                self.use_gpu = False
+                self.gpu_info['cpu_fallback'] = True
+                self.gpu_info['fallback_reason'] = 'GPU memory insufficient'
+
+                if self._memory_guard:
+                    self._memory_guard.clear_gpu_cache()
+
+        service = MockOCRService()
+
+        # Verify initial state
+        assert service._cpu_fallback_active is False
+        assert service.use_gpu is True
+
+        # Activate fallback
+        service._activate_cpu_fallback()
+
+        # Verify fallback state
+        assert service._cpu_fallback_active is True
+        assert service.use_gpu is False
+        assert service.gpu_info.get('cpu_fallback') is True
+        service._memory_guard.clear_gpu_cache.assert_called_once()
+
+    def test_cpu_fallback_idempotent(self):
+        """Test that CPU fallback activation is idempotent"""
+        class MockOCRService:
+            def __init__(self):
+                self._cpu_fallback_active = False
+                self.use_gpu = True
+                self._memory_guard = Mock()
+                self.gpu_info = {}
+
+            def _activate_cpu_fallback(self):
+                if self._cpu_fallback_active:
+                    return
+                self._cpu_fallback_active = True
+                self.use_gpu = False
+                if self._memory_guard:
+                    self._memory_guard.clear_gpu_cache()
+
+        service = MockOCRService()
+
+        # Activate twice
+        service._activate_cpu_fallback()
+        service._activate_cpu_fallback()
+
+        # clear_gpu_cache should only be called once
+        assert service._memory_guard.clear_gpu_cache.call_count == 1
+
+    def test_gpu_mode_restoration_pattern(self):
+        """Test the GPU mode restoration pattern"""
+        # Simulate the pattern used in OCRService._restore_gpu_mode
+
+        class MockOCRService:
+            def __init__(self):
+                self._cpu_fallback_active = True
+                self.use_gpu = False
+                self.gpu_available = True
+                self.gpu_info = {
+                    'device_id': 0,
+                    'cpu_fallback': True,
+                    'fallback_reason': 'test'
+                }
+                self._memory_guard = Mock()
+
+            def _restore_gpu_mode(self):
+                if not self._cpu_fallback_active:
+                    return
+
+                if not self.gpu_available:
+                    return
+
+                # Check if GPU memory is now available
+                if self._memory_guard:
+                    is_available, stats = self._memory_guard.check_memory(required_mb=2000)
+                    if is_available:
+                        self._cpu_fallback_active = False
+                        self.use_gpu = True
+                        self.gpu_info.pop('cpu_fallback', None)
+                        self.gpu_info.pop('fallback_reason', None)
+
+        service = MockOCRService()
+
+        # Mock memory guard to indicate sufficient memory
+        mock_stats = Mock()
+        mock_stats.gpu_free_mb = 5000
+        service._memory_guard.check_memory.return_value = (True, mock_stats)
+
+        # Restore GPU mode
+        service._restore_gpu_mode()
+
+        # Verify GPU mode restored
+        assert service._cpu_fallback_active is False
+        assert service.use_gpu is True
+        assert 'cpu_fallback' not in service.gpu_info
+
+    def test_gpu_mode_not_restored_when_memory_still_low(self):
+        """Test that GPU mode is not restored when memory is still low"""
+        class MockOCRService:
+            def __init__(self):
+                self._cpu_fallback_active = True
+                self.use_gpu = False
+                self.gpu_available = True
+                self.gpu_info = {'cpu_fallback': True}
+                self._memory_guard = Mock()
+
+            def _restore_gpu_mode(self):
+                if not self._cpu_fallback_active:
+                    return
+                if not self.gpu_available:
+                    return
+                if self._memory_guard:
+                    is_available, stats = self._memory_guard.check_memory(required_mb=2000)
+                    if is_available:
+                        self._cpu_fallback_active = False
+                        self.use_gpu = True
+
+        service = MockOCRService()
+
+        # Mock memory guard to indicate insufficient memory
+        mock_stats = Mock()
+        mock_stats.gpu_free_mb = 500
+        service._memory_guard.check_memory.return_value = (False, mock_stats)
+
+        # Try to restore GPU mode
+        service._restore_gpu_mode()
+
+        # Verify still in fallback mode
+        assert service._cpu_fallback_active is True
+        assert service.use_gpu is False
+
+
+class TestPreOperationMemoryCheckPattern:
+    """Tests for pre-operation memory check pattern as used in OCRService"""
+
+    def test_pre_operation_check_with_fallback(self):
+        """Test the pre-operation memory check pattern with fallback"""
+        guard = MemoryGuard(MemoryConfig(
+            warning_threshold=0.80,
+            critical_threshold=0.95,
+            enable_cpu_fallback=True,
+        ))
+
+        # Simulate the pattern:
+        # 1. Check if in CPU fallback mode
+        # 2. Try to restore GPU mode if memory available
+        # 3. Perform memory check for operation
+
+        class MockService:
+            def __init__(self):
+                self._cpu_fallback_active = False
+                self.use_gpu = True
+                self.gpu_available = True
+                self._memory_guard = guard
+
+            def _restore_gpu_mode(self):
+                pass  # Simplified
+
+            def pre_operation_check(self, required_mb: int) -> bool:
+                # Try restore first
+                if self._cpu_fallback_active:
+                    self._restore_gpu_mode()
+
+                # Perform memory check
+                if not self.use_gpu:
+                    return True  # CPU mode, no GPU check needed
+
+                is_available, stats = self._memory_guard.check_memory(required_mb=required_mb)
+                return is_available
+
+        service = MockService()
+
+        # Mock sufficient memory
+        with patch.object(guard, 'get_memory_stats') as mock_stats:
+            mock_stats.return_value = MemoryStats(
+                gpu_used_ratio=0.50,
+                gpu_free_mb=4000,
+                gpu_total_mb=8000,
+            )
+
+            result = service.pre_operation_check(required_mb=2000)
+            assert result is True
+
+        guard.shutdown()
+
+    def test_pre_operation_check_returns_true_in_cpu_mode(self):
+        """Test that pre-operation check returns True when in CPU mode"""
+        class MockService:
+            def __init__(self):
+                self._cpu_fallback_active = True
+                self.use_gpu = False
+                self._memory_guard = Mock()
+
+            def pre_operation_check(self, required_mb: int) -> bool:
+                if not self.use_gpu:
+                    return True  # CPU mode, no GPU check needed
+                return False
+
+        service = MockService()
+        result = service.pre_operation_check(required_mb=5000)
+
+        # Should return True because we're in CPU mode
+        assert result is True
+        # Memory guard should not be called
+        service._memory_guard.check_memory.assert_not_called()
+
+
+class TestMemoryCheckWithCleanup:
+    """Tests for memory check with cleanup pattern"""
+
+    def test_memory_check_triggers_cleanup_on_failure(self):
+        """Test that memory check triggers cleanup when insufficient"""
+        guard = MemoryGuard(MemoryConfig(
+            warning_threshold=0.80,
+            critical_threshold=0.95,
+        ))
+
+        # Track cleanup calls
+        cleanup_called = False
+
+        def mock_cleanup():
+            nonlocal cleanup_called
+            cleanup_called = True
+
+        class MockService:
+            def __init__(self):
+                self._memory_guard = guard
+                self.cleanup_func = mock_cleanup
+
+            def check_gpu_memory(self, required_mb: int) -> bool:
+                # First check
+                with patch.object(self._memory_guard, 'get_memory_stats') as mock_stats:
+                    # First call - low memory
+                    mock_stats.return_value = MemoryStats(
+                        gpu_used_ratio=0.96,
+                        gpu_free_mb=300,
+                        gpu_total_mb=8000,
+                    )
+
+                    is_available, stats = self._memory_guard.check_memory(required_mb=required_mb)
+
+                    if not is_available:
+                        # Trigger cleanup
+                        self.cleanup_func()
+                        self._memory_guard.clear_gpu_cache()
+                        return False
+
+                return True
+
+        service = MockService()
+        result = service.check_gpu_memory(required_mb=1000)
+
+        # Cleanup should have been triggered
+        assert cleanup_called is True
+        assert result is False
+
+        guard.shutdown()
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])

backend/tests/services/test_service_pool.py

@@ -0,0 +1,387 @@
+"""
+Tests for OCR Service Pool
+
+Tests OCRServicePool functionality including acquire, release, and concurrency.
+"""
+
+import pytest
+import threading
+import time
+from unittest.mock import Mock, patch, MagicMock
+import sys
+
+# Mock paddle before importing service_pool to avoid import errors
+# when paddle is not installed in the test environment
+paddle_mock = MagicMock()
+paddle_mock.is_compiled_with_cuda.return_value = False
+paddle_mock.device.cuda.device_count.return_value = 0
+paddle_mock.device.cuda.memory_allocated.return_value = 0
+paddle_mock.device.cuda.memory_reserved.return_value = 0
+paddle_mock.device.cuda.empty_cache = MagicMock()
+sys.modules['paddle'] = paddle_mock
+
+from app.services.service_pool import (
+    OCRServicePool,
+    PooledService,
+    PoolConfig,
+    ServiceState,
+    get_service_pool,
+    shutdown_service_pool,
+)
+
+
+class TestPoolConfig:
+    """Tests for PoolConfig class"""
+
+    def test_default_values(self):
+        """Test default configuration values"""
+        config = PoolConfig()
+        assert config.max_services_per_device == 1
+        assert config.max_total_services == 2
+        assert config.acquire_timeout_seconds == 300.0
+        assert config.max_queue_size == 50
+        assert config.max_consecutive_errors == 3
+
+    def test_custom_values(self):
+        """Test custom configuration values"""
+        config = PoolConfig(
+            max_services_per_device=2,
+            max_total_services=4,
+            acquire_timeout_seconds=60.0,
+        )
+        assert config.max_services_per_device == 2
+        assert config.max_total_services == 4
+        assert config.acquire_timeout_seconds == 60.0
+
+
+class TestPooledService:
+    """Tests for PooledService class"""
+
+    def test_creation(self):
+        """Test PooledService creation"""
+        mock_service = Mock()
+        pooled = PooledService(
+            service=mock_service,
+            device="GPU:0",
+        )
+        assert pooled.service is mock_service
+        assert pooled.device == "GPU:0"
+        assert pooled.state == ServiceState.AVAILABLE
+        assert pooled.use_count == 0
+        assert pooled.error_count == 0
+
+
+class TestOCRServicePool:
+    """Tests for OCRServicePool class"""
+
+    def setup_method(self):
+        """Reset singleton before each test"""
+        shutdown_service_pool()
+        OCRServicePool._instance = None
+        OCRServicePool._lock = threading.Lock()
+
+    def teardown_method(self):
+        """Cleanup after each test"""
+        shutdown_service_pool()
+        OCRServicePool._instance = None
+
+    def test_singleton_pattern(self):
+        """Test that OCRServicePool is a singleton"""
+        pool1 = OCRServicePool()
+        pool2 = OCRServicePool()
+        assert pool1 is pool2
+        pool1.shutdown()
+
+    def test_initialize_device(self):
+        """Test device initialization"""
+        config = PoolConfig()
+        pool = OCRServicePool(config)
+
+        # Default device should be initialized
+        assert "GPU:0" in pool.services
+        assert "GPU:0" in pool.semaphores
+
+        # Test adding new device
+        pool._initialize_device("GPU:1")
+        assert "GPU:1" in pool.services
+        assert "GPU:1" in pool.semaphores
+
+        pool.shutdown()
+
+    def test_acquire_creates_service(self):
+        """Test that acquire creates a new service if none available"""
+        config = PoolConfig(max_services_per_device=1)
+        pool = OCRServicePool(config)
+
+        # Pre-populate with a mock service
+        mock_service = Mock()
+        mock_service.process = Mock()
+        mock_service.get_gpu_status = Mock()
+        pooled_service = PooledService(service=mock_service, device="GPU:0")
+        pool.services["GPU:0"].append(pooled_service)
+
+        pooled = pool.acquire(device="GPU:0", timeout=5.0)
+        assert pooled is not None
+        assert pooled.state == ServiceState.IN_USE
+        assert pooled.use_count == 1
+
+        pool.shutdown()
+
+    def test_acquire_reuses_available_service(self):
+        """Test that acquire reuses available services"""
+        config = PoolConfig(max_services_per_device=1)
+        pool = OCRServicePool(config)
+
+        # Pre-populate with a mock service
+        mock_service = Mock()
+        pooled_service = PooledService(service=mock_service, device="GPU:0")
+        pool.services["GPU:0"].append(pooled_service)
+
+        # First acquire
+        pooled1 = pool.acquire(device="GPU:0")
+        service_id = id(pooled1.service)
+        pool.release(pooled1)
+
+        # Second acquire should get the same service
+        pooled2 = pool.acquire(device="GPU:0")
+        assert id(pooled2.service) == service_id
+        assert pooled2.use_count == 2
+
+        pool.shutdown()
+
+    def test_release_makes_service_available(self):
+        """Test that release makes service available again"""
+        config = PoolConfig()
+        pool = OCRServicePool(config)
+
+        # Pre-populate with a mock service
+        mock_service = Mock()
+        pooled_service = PooledService(service=mock_service, device="GPU:0")
+        pool.services["GPU:0"].append(pooled_service)
+
+        pooled = pool.acquire(device="GPU:0")
+        assert pooled.state == ServiceState.IN_USE
+
+        pool.release(pooled)
+        assert pooled.state == ServiceState.AVAILABLE
+
+        pool.shutdown()
+
+    def test_release_with_error(self):
+        """Test that release with error increments error count"""
+        config = PoolConfig(max_consecutive_errors=3)
+        pool = OCRServicePool(config)
+
+        # Pre-populate with a mock service
+        mock_service = Mock()
+        pooled_service = PooledService(service=mock_service, device="GPU:0")
+        pool.services["GPU:0"].append(pooled_service)
+
+        pooled = pool.acquire(device="GPU:0")
+        pool.release(pooled, error=Exception("Test error"))
+
+        assert pooled.error_count == 1
+        assert pooled.state == ServiceState.AVAILABLE
+
+        pool.shutdown()
+
+    def test_release_marks_unhealthy_after_errors(self):
+        """Test that service is marked unhealthy after too many errors"""
+        config = PoolConfig(max_consecutive_errors=2)
+        pool = OCRServicePool(config)
+
+        # Pre-populate with a mock service
+        mock_service = Mock()
+        pooled_service = PooledService(service=mock_service, device="GPU:0")
+        pool.services["GPU:0"].append(pooled_service)
+
+        pooled = pool.acquire(device="GPU:0")
+        pool.release(pooled, error=Exception("Error 1"))
+
+        pooled = pool.acquire(device="GPU:0")
+        pool.release(pooled, error=Exception("Error 2"))
+
+        assert pooled.state == ServiceState.UNHEALTHY
+        assert pooled.error_count == 2
+
+        pool.shutdown()
+
+    def test_acquire_context_manager(self):
+        """Test context manager for acquire/release"""
+        config = PoolConfig()
+        pool = OCRServicePool(config)
+
+        # Pre-populate with a mock service
+        mock_service = Mock()
+        pooled_service = PooledService(service=mock_service, device="GPU:0")
+        pool.services["GPU:0"].append(pooled_service)
+
+        with pool.acquire_context(device="GPU:0") as pooled:
+            assert pooled is not None
+            assert pooled.state == ServiceState.IN_USE
+
+        # After context, service should be available
+        assert pooled.state == ServiceState.AVAILABLE
+
+        pool.shutdown()
+
+    def test_acquire_context_manager_with_error(self):
+        """Test context manager releases on error"""
+        config = PoolConfig()
+        pool = OCRServicePool(config)
+
+        # Pre-populate with a mock service
+        mock_service = Mock()
+        pooled_service = PooledService(service=mock_service, device="GPU:0")
+        pool.services["GPU:0"].append(pooled_service)
+
+        with pytest.raises(ValueError):
+            with pool.acquire_context(device="GPU:0") as pooled:
+                raise ValueError("Test error")
+
+        # Service should still be available after error
+        assert pooled.error_count == 1
+
+        pool.shutdown()
+
+    def test_acquire_timeout(self):
+        """Test that acquire times out when no service available"""
+        config = PoolConfig(
+            max_services_per_device=1,
+            max_total_services=1,
+        )
+        pool = OCRServicePool(config)
+
+        # Pre-populate with a mock service
+        mock_service = Mock()
+        pooled_service = PooledService(service=mock_service, device="GPU:0")
+        pool.services["GPU:0"].append(pooled_service)
+
+        # Acquire the only service
+        pooled1 = pool.acquire(device="GPU:0")
+        assert pooled1 is not None
+
+        # Try to acquire another - should timeout
+        pooled2 = pool.acquire(device="GPU:0", timeout=0.5)
+        assert pooled2 is None
+
+        pool.shutdown()
+
+    def test_get_pool_stats(self):
+        """Test pool statistics"""
+        config = PoolConfig()
+        pool = OCRServicePool(config)
+
+        # Pre-populate with a mock service
+        mock_service = Mock()
+        pooled_service = PooledService(service=mock_service, device="GPU:0")
+        pool.services["GPU:0"].append(pooled_service)
+
+        # Acquire a service
+        pooled = pool.acquire(device="GPU:0")
+
+        stats = pool.get_pool_stats()
+        assert stats["total_services"] == 1
+        assert stats["in_use_services"] == 1
+        assert stats["available_services"] == 0
+        assert stats["metrics"]["total_acquisitions"] == 1
+
+        pool.release(pooled)
+
+        stats = pool.get_pool_stats()
+        assert stats["available_services"] == 1
+        assert stats["metrics"]["total_releases"] == 1
+
+        pool.shutdown()
+
+    def test_health_check(self):
+        """Test health check functionality"""
+        config = PoolConfig()
+        pool = OCRServicePool(config)
+
+        # Pre-populate with a mock service
+        mock_service = Mock()
+        mock_service.process = Mock()
+        mock_service.get_gpu_status = Mock()
+        pooled_service = PooledService(service=mock_service, device="GPU:0")
+        pool.services["GPU:0"].append(pooled_service)
+
+        # Acquire and release to update use_count
+        pooled = pool.acquire(device="GPU:0")
+        pool.release(pooled)
+
+        health = pool.health_check()
+        assert health["healthy"] is True
+        assert len(health["services"]) == 1
+        assert health["services"][0]["responsive"] is True
+
+        pool.shutdown()
+
+    def test_concurrent_acquire(self):
+        """Test concurrent service acquisition"""
+        config = PoolConfig(
+            max_services_per_device=2,
+            max_total_services=2,
+        )
+        pool = OCRServicePool(config)
+
+        # Pre-populate with 2 mock services
+        for i in range(2):
+            mock_service = Mock()
+            pooled_service = PooledService(service=mock_service, device="GPU:0")
+            pool.services["GPU:0"].append(pooled_service)
+
+        results = []
+
+        def worker(worker_id):
+            pooled = pool.acquire(device="GPU:0", timeout=5.0, task_id=f"task_{worker_id}")
+            if pooled:
+                results.append((worker_id, pooled))
+                time.sleep(0.1)  # Simulate work
+                pool.release(pooled)
+
+        threads = [threading.Thread(target=worker, args=(i,)) for i in range(4)]
+        for t in threads:
+            t.start()
+        for t in threads:
+            t.join()
+
+        # All workers should have acquired a service
+        assert len(results) == 4
+
+        pool.shutdown()
+
+
+class TestGetServicePool:
+    """Tests for get_service_pool helper function"""
+
+    def setup_method(self):
+        """Reset singleton before each test"""
+        shutdown_service_pool()
+        OCRServicePool._instance = None
+
+    def teardown_method(self):
+        """Cleanup after each test"""
+        shutdown_service_pool()
+        OCRServicePool._instance = None
+
+    def test_get_service_pool_creates_singleton(self):
+        """Test that get_service_pool creates a singleton"""
+        pool1 = get_service_pool()
+        pool2 = get_service_pool()
+        assert pool1 is pool2
+        shutdown_service_pool()
+
+    def test_shutdown_service_pool(self):
+        """Test shutdown_service_pool cleans up"""
+        pool = get_service_pool()
+        shutdown_service_pool()
+
+        # Should be able to create new pool
+        new_pool = get_service_pool()
+        assert new_pool._initialized is True
+        shutdown_service_pool()
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])

frontend/package-lock.json

@@ -8,6 +8,7 @@
       "name": "frontend",
       "version": "0.0.0",
       "dependencies": {
+        "@radix-ui/react-select": "^2.2.6",
         "@tanstack/react-query": "^5.90.7",
         "axios": "^1.13.2",
         "class-variance-authority": "^0.7.0",
@@ -87,7 +88,6 @@
       "integrity": "sha512-e7jT4DxYvIDLk1ZHmU/m/mB19rex9sv0c2ftBtjSBv+kVM/902eh0fINUzD7UwLLNR+jU585GxUJ8/EBfAM5fw==",
       "dev": true,
       "license": "MIT",
-      "peer": true,
       "dependencies": {
         "@babel/code-frame": "^7.27.1",
         "@babel/generator": "^7.28.5",
@@ -947,6 +947,44 @@
         "node": "^18.18.0 || ^20.9.0 || >=21.1.0"
       }
     },
+    "node_modules/@floating-ui/core": {
+      "version": "1.7.3",
+      "resolved": "https://registry.npmjs.org/@floating-ui/core/-/core-1.7.3.tgz",
+      "integrity": "sha512-sGnvb5dmrJaKEZ+LDIpguvdX3bDlEllmv4/ClQ9awcmCZrlx5jQyyMWFM5kBI+EyNOCDDiKk8il0zeuX3Zlg/w==",
+      "license": "MIT",
+      "dependencies": {
+        "@floating-ui/utils": "^0.2.10"
+      }
+    },
+    "node_modules/@floating-ui/dom": {
+      "version": "1.7.4",
+      "resolved": "https://registry.npmjs.org/@floating-ui/dom/-/dom-1.7.4.tgz",
+      "integrity": "sha512-OOchDgh4F2CchOX94cRVqhvy7b3AFb+/rQXyswmzmGakRfkMgoWVjfnLWkRirfLEfuD4ysVW16eXzwt3jHIzKA==",
+      "license": "MIT",
+      "dependencies": {
+        "@floating-ui/core": "^1.7.3",
+        "@floating-ui/utils": "^0.2.10"
+      }
+    },
+    "node_modules/@floating-ui/react-dom": {
+      "version": "2.1.6",
+      "resolved": "https://registry.npmjs.org/@floating-ui/react-dom/-/react-dom-2.1.6.tgz",
+      "integrity": "sha512-4JX6rEatQEvlmgU80wZyq9RT96HZJa88q8hp0pBd+LrczeDI4o6uA2M+uvxngVHo4Ihr8uibXxH6+70zhAFrVw==",
+      "license": "MIT",
+      "dependencies": {
+        "@floating-ui/dom": "^1.7.4"
+      },
+      "peerDependencies": {
+        "react": ">=16.8.0",
+        "react-dom": ">=16.8.0"
+      }
+    },
+    "node_modules/@floating-ui/utils": {
+      "version": "0.2.10",
+      "resolved": "https://registry.npmjs.org/@floating-ui/utils/-/utils-0.2.10.tgz",
+      "integrity": "sha512-aGTxbpbg8/b5JfU1HXSrbH3wXZuLPJcNEcZQFMxLs3oSzgtVu6nFPkbbGGUvBcUjKV2YyB9Wxxabo+HEH9tcRQ==",
+      "license": "MIT"
+    },
     "node_modules/@humanfs/core": {
       "version": "0.19.1",
       "resolved": "https://registry.npmjs.org/@humanfs/core/-/core-0.19.1.tgz",
@@ -1272,6 +1310,502 @@
         "node": ">= 8"
       }
     },
+    "node_modules/@radix-ui/number": {
+      "version": "1.1.1",
+      "resolved": "https://registry.npmjs.org/@radix-ui/number/-/number-1.1.1.tgz",
+      "integrity": "sha512-MkKCwxlXTgz6CFoJx3pCwn07GKp36+aZyu/u2Ln2VrA5DcdyCZkASEDBTd8x5whTQQL5CiYf4prXKLcgQdv29g==",
+      "license": "MIT"
+    },
+    "node_modules/@radix-ui/primitive": {
+      "version": "1.1.3",
+      "resolved": "https://registry.npmjs.org/@radix-ui/primitive/-/primitive-1.1.3.tgz",
+      "integrity": "sha512-JTF99U/6XIjCBo0wqkU5sK10glYe27MRRsfwoiq5zzOEZLHU3A3KCMa5X/azekYRCJ0HlwI0crAXS/5dEHTzDg==",
+      "license": "MIT"
+    },
+    "node_modules/@radix-ui/react-arrow": {
+      "version": "1.1.7",
+      "resolved": "https://registry.npmjs.org/@radix-ui/react-arrow/-/react-arrow-1.1.7.tgz",
+      "integrity": "sha512-F+M1tLhO+mlQaOWspE8Wstg+z6PwxwRd8oQ8IXceWz92kfAmalTRf0EjrouQeo7QssEPfCn05B4Ihs1K9WQ/7w==",
+      "license": "MIT",
+      "dependencies": {
+        "@radix-ui/react-primitive": "2.1.3"
+      },
+      "peerDependencies": {
+        "@types/react": "*",
+        "@types/react-dom": "*",
+        "react": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc",
+        "react-dom": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc"
+      },
+      "peerDependenciesMeta": {
+        "@types/react": {
+          "optional": true
+        },
+        "@types/react-dom": {
+          "optional": true
+        }
+      }
+    },
+    "node_modules/@radix-ui/react-collection": {
+      "version": "1.1.7",
+      "resolved": "https://registry.npmjs.org/@radix-ui/react-collection/-/react-collection-1.1.7.tgz",
+      "integrity": "sha512-Fh9rGN0MoI4ZFUNyfFVNU4y9LUz93u9/0K+yLgA2bwRojxM8JU1DyvvMBabnZPBgMWREAJvU2jjVzq+LrFUglw==",
+      "license": "MIT",
+      "dependencies": {
+        "@radix-ui/react-compose-refs": "1.1.2",
+        "@radix-ui/react-context": "1.1.2",
+        "@radix-ui/react-primitive": "2.1.3",
+        "@radix-ui/react-slot": "1.2.3"
+      },
+      "peerDependencies": {
+        "@types/react": "*",
+        "@types/react-dom": "*",
+        "react": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc",
+        "react-dom": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc"
+      },
+      "peerDependenciesMeta": {
+        "@types/react": {
+          "optional": true
+        },
+        "@types/react-dom": {
+          "optional": true
+        }
+      }
+    },
+    "node_modules/@radix-ui/react-compose-refs": {
+      "version": "1.1.2",
+      "resolved": "https://registry.npmjs.org/@radix-ui/react-compose-refs/-/react-compose-refs-1.1.2.tgz",
+      "integrity": "sha512-z4eqJvfiNnFMHIIvXP3CY57y2WJs5g2v3X0zm9mEJkrkNv4rDxu+sg9Jh8EkXyeqBkB7SOcboo9dMVqhyrACIg==",
+      "license": "MIT",
+      "peerDependencies": {
+        "@types/react": "*",
+        "react": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc"
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@@ -2067,7 +2599,6 @@
       "integrity": "sha512-tK3GPFWbirvNgsNKto+UmB/cRtn6TZfyw0D6IKrW55n6Vbs7KJoZtI//kpTKzE/DUmmnAFD8/Ca46s7Obs92/w==",
       "dev": true,
       "license": "MIT",
-      "peer": true,
       "dependencies": {
         "@typescript-eslint/scope-manager": "8.46.4",
         "@typescript-eslint/types": "8.46.4",
@@ -2326,7 +2857,6 @@
       "integrity": "sha512-NZyJarBfL7nWwIq+FDL6Zp/yHEhePMNnnJ0y3qfieCrmNvYct8uvtiV41UvlSe6apAfk0fY1FbWx+NwfmpvtTg==",
       "dev": true,
       "license": "MIT",
-      "peer": true,
       "bin": {
         "acorn": "bin/acorn"
       },
@@ -2384,6 +2914,18 @@
       "dev": true,
       "license": "Python-2.0"
     },
+    "node_modules/aria-hidden": {
+      "version": "1.2.6",
+      "resolved": "https://registry.npmjs.org/aria-hidden/-/aria-hidden-1.2.6.tgz",
+      "integrity": "sha512-ik3ZgC9dY/lYVVM++OISsaYDeg1tb0VtP5uL3ouh1koGOaUMDPpbFIei4JkFimWUFPn90sbMNMXQAIVOlnYKJA==",
+      "license": "MIT",
+      "dependencies": {
+        "tslib": "^2.0.0"
+      },
+      "engines": {
+        "node": ">=10"
+      }
+    },
     "node_modules/asynckit": {
       "version": "0.4.0",
       "resolved": "https://registry.npmjs.org/asynckit/-/asynckit-0.4.0.tgz",
@@ -2519,7 +3061,6 @@
         }
       ],
       "license": "MIT",
-      "peer": true,
       "dependencies": {
         "baseline-browser-mapping": "^2.8.25",
         "caniuse-lite": "^1.0.30001754",
@@ -2817,6 +3358,12 @@
         "node": ">=8"
       }
     },
+    "node_modules/detect-node-es": {
+      "version": "1.1.0",
+      "resolved": "https://registry.npmjs.org/detect-node-es/-/detect-node-es-1.1.0.tgz",
+      "integrity": "sha512-ypdmJU/TbBby2Dxibuv7ZLW3Bs1QEmM7nHjEANfohJLvE0XVujisn1qPJcZxg+qDucsr+bP6fLD1rPS3AhJ7EQ==",
+      "license": "MIT"
+    },
     "node_modules/devlop": {
       "version": "1.1.0",
       "resolved": "https://registry.npmjs.org/devlop/-/devlop-1.1.0.tgz",
@@ -2981,7 +3528,6 @@
       "integrity": "sha512-BhHmn2yNOFA9H9JmmIVKJmd288g9hrVRDkdoIgRCRuSySRUHH7r/DI6aAXW9T1WwUuY3DFgrcaqB+deURBLR5g==",
       "dev": true,
       "license": "MIT",
-      "peer": true,
       "dependencies": {
         "@eslint-community/eslint-utils": "^4.8.0",
         "@eslint-community/regexpp": "^4.12.1",
@@ -3414,6 +3960,15 @@
         "url": "https://github.com/sponsors/ljharb"
       }
     },
+    "node_modules/get-nonce": {
+      "version": "1.0.1",
+      "resolved": "https://registry.npmjs.org/get-nonce/-/get-nonce-1.0.1.tgz",
+      "integrity": "sha512-FJhYRoDaiatfEkUK8HKlicmu/3SGFD51q3itKDGoSTysQJBnfOcxU5GxnhE1E6soB76MbT0MBtnKJuXyAx+96Q==",
+      "license": "MIT",
+      "engines": {
+        "node": ">=6"
+      }
+    },
     "node_modules/get-proto": {
       "version": "1.0.1",
       "resolved": "https://registry.npmjs.org/get-proto/-/get-proto-1.0.1.tgz",
@@ -3606,7 +4161,6 @@
         }
       ],
       "license": "MIT",
-      "peer": true,
       "dependencies": {
         "@babel/runtime": "^7.27.6"
       },
@@ -5096,7 +5650,6 @@
         }
       ],
       "license": "MIT",
-      "peer": true,
       "dependencies": {
         "nanoid": "^3.3.11",
         "picocolors": "^1.1.1",
@@ -5186,7 +5739,6 @@
       "resolved": "https://registry.npmjs.org/react/-/react-19.2.0.tgz",
       "integrity": "sha512-tmbWg6W31tQLeB5cdIBOicJDJRR2KzXsV7uSK9iNfLWQ5bIZfxuPEHp7M8wiHyHnn0DD1i7w3Zmin0FtkrwoCQ==",
       "license": "MIT",
-      "peer": true,
       "engines": {
         "node": ">=0.10.0"
       }
@@ -5196,7 +5748,6 @@
       "resolved": "https://registry.npmjs.org/react-dom/-/react-dom-19.2.0.tgz",
       "integrity": "sha512-UlbRu4cAiGaIewkPyiRGJk0imDN2T3JjieT6spoL2UeSf5od4n5LB/mQ4ejmxhCFT1tYe8IvaFulzynWovsEFQ==",
       "license": "MIT",
-      "peer": true,
       "dependencies": {
         "scheduler": "^0.27.0"
       },
@@ -5332,6 +5883,53 @@
         "node": ">=0.10.0"
       }
     },
+    "node_modules/react-remove-scroll": {
+      "version": "2.7.1",
+      "resolved": "https://registry.npmjs.org/react-remove-scroll/-/react-remove-scroll-2.7.1.tgz",
+      "integrity": "sha512-HpMh8+oahmIdOuS5aFKKY6Pyog+FNaZV/XyJOq7b4YFwsFHe5yYfdbIalI4k3vU2nSDql7YskmUseHsRrJqIPA==",
+      "license": "MIT",
+      "dependencies": {
+        "react-remove-scroll-bar": "^2.3.7",
+        "react-style-singleton": "^2.2.3",
+        "tslib": "^2.1.0",
+        "use-callback-ref": "^1.3.3",
+        "use-sidecar": "^1.1.3"
+      },
+      "engines": {
+        "node": ">=10"
+      },
+      "peerDependencies": {
+        "@types/react": "*",
+        "react": "^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0 || ^19.0.0-rc"
+      },
+      "peerDependenciesMeta": {
+        "@types/react": {
+          "optional": true
+        }
+      }
+    },
+    "node_modules/react-remove-scroll-bar": {
+      "version": "2.3.8",
+      "resolved": "https://registry.npmjs.org/react-remove-scroll-bar/-/react-remove-scroll-bar-2.3.8.tgz",
+      "integrity": "sha512-9r+yi9+mgU33AKcj6IbT9oRCO78WriSj6t/cF8DWBZJ9aOGPOTEDvdUDz1FwKim7QXWwmHqtdHnRJfhAxEG46Q==",
+      "license": "MIT",
+      "dependencies": {
+        "react-style-singleton": "^2.2.2",
+        "tslib": "^2.0.0"
+      },
+      "engines": {
+        "node": ">=10"
+      },
+      "peerDependencies": {
+        "@types/react": "*",
+        "react": "^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0"
+      },
+      "peerDependenciesMeta": {
+        "@types/react": {
+          "optional": true
+        }
+      }
+    },
     "node_modules/react-router": {
       "version": "7.9.6",
       "resolved": "https://registry.npmjs.org/react-router/-/react-router-7.9.6.tgz",
@@ -5370,6 +5968,28 @@
         "react-dom": ">=18"
       }
     },
+    "node_modules/react-style-singleton": {
+      "version": "2.2.3",
+      "resolved": "https://registry.npmjs.org/react-style-singleton/-/react-style-singleton-2.2.3.tgz",
+      "integrity": "sha512-b6jSvxvVnyptAiLjbkWLE/lOnR4lfTtDAl+eUC7RZy+QQWc6wRzIV2CE6xBuMmDxc2qIihtDCZD5NPOFl7fRBQ==",
+      "license": "MIT",
+      "dependencies": {
+        "get-nonce": "^1.0.0",
+        "tslib": "^2.0.0"
+      },
+      "engines": {
+        "node": ">=10"
+      },
+      "peerDependencies": {
+        "@types/react": "*",
+        "react": "^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0 || ^19.0.0-rc"
+      },
+      "peerDependenciesMeta": {
+        "@types/react": {
+          "optional": true
+        }
+      }
+    },
     "node_modules/remark-parse": {
       "version": "11.0.0",
       "resolved": "https://registry.npmjs.org/remark-parse/-/remark-parse-11.0.0.tgz",
@@ -5691,7 +6311,6 @@
       "integrity": "sha512-5gTmgEY/sqK6gFXLIsQNH19lWb4ebPDLA4SdLP7dsWkIXHWlG66oPuVvXSGFPppYZz8ZDZq0dYYrbHfBCVUb1Q==",
       "dev": true,
       "license": "MIT",
-      "peer": true,
       "engines": {
         "node": ">=12"
       },
@@ -5770,7 +6389,6 @@
       "integrity": "sha512-jl1vZzPDinLr9eUt3J/t7V6FgNEw9QjvBPdysz9KfQDD41fQrC2Y4vKQdiaUpFT4bXlb1RHhLpp8wtm6M5TgSw==",
       "devOptional": true,
       "license": "Apache-2.0",
-      "peer": true,
       "bin": {
         "tsc": "bin/tsc",
         "tsserver": "bin/tsserver"
@@ -5938,6 +6556,49 @@
         "punycode": "^2.1.0"
       }
     },
+    "node_modules/use-callback-ref": {
+      "version": "1.3.3",
+      "resolved": "https://registry.npmjs.org/use-callback-ref/-/use-callback-ref-1.3.3.tgz",
+      "integrity": "sha512-jQL3lRnocaFtu3V00JToYz/4QkNWswxijDaCVNZRiRTO3HQDLsdu1ZtmIUvV4yPp+rvWm5j0y0TG/S61cuijTg==",
+      "license": "MIT",
+      "dependencies": {
+        "tslib": "^2.0.0"
+      },
+      "engines": {
+        "node": ">=10"
+      },
+      "peerDependencies": {
+        "@types/react": "*",
+        "react": "^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0 || ^19.0.0-rc"
+      },
+      "peerDependenciesMeta": {
+        "@types/react": {
+          "optional": true
+        }
+      }
+    },
+    "node_modules/use-sidecar": {
+      "version": "1.1.3",
+      "resolved": "https://registry.npmjs.org/use-sidecar/-/use-sidecar-1.1.3.tgz",
+      "integrity": "sha512-Fedw0aZvkhynoPYlA5WXrMCAMm+nSWdZt6lzJQ7Ok8S6Q+VsHmHpRWndVRJ8Be0ZbkfPc5LRYH+5XrzXcEeLRQ==",
+      "license": "MIT",
+      "dependencies": {
+        "detect-node-es": "^1.1.0",
+        "tslib": "^2.0.0"
+      },
+      "engines": {
+        "node": ">=10"
+      },
+      "peerDependencies": {
+        "@types/react": "*",
+        "react": "^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0 || ^19.0.0-rc"
+      },
+      "peerDependenciesMeta": {
+        "@types/react": {
+          "optional": true
+        }
+      }
+    },
     "node_modules/use-sync-external-store": {
       "version": "1.6.0",
       "resolved": "https://registry.npmjs.org/use-sync-external-store/-/use-sync-external-store-1.6.0.tgz",
@@ -5981,7 +6642,6 @@
       "integrity": "sha512-BxAKBWmIbrDgrokdGZH1IgkIk/5mMHDreLDmCJ0qpyJaAteP8NvMhkwr/ZCQNqNH97bw/dANTE9PDzqwJghfMQ==",
       "dev": true,
       "license": "MIT",
-      "peer": true,
       "dependencies": {
         "esbuild": "^0.25.0",
         "fdir": "^6.5.0",
@@ -6075,7 +6735,6 @@
       "integrity": "sha512-5gTmgEY/sqK6gFXLIsQNH19lWb4ebPDLA4SdLP7dsWkIXHWlG66oPuVvXSGFPppYZz8ZDZq0dYYrbHfBCVUb1Q==",
       "dev": true,
       "license": "MIT",
-      "peer": true,
       "engines": {
         "node": ">=12"
       },

frontend/package.json

@@ -10,6 +10,7 @@
     "preview": "vite preview"
   },
   "dependencies": {
+    "@radix-ui/react-select": "^2.2.6",
     "@tanstack/react-query": "^5.90.7",
     "axios": "^1.13.2",
     "class-variance-authority": "^0.7.0",

frontend/src/components/PDFViewer.tsx

@@ -1,11 +1,17 @@
-import { useState, useMemo } from 'react'
-import { Document, Page } from 'react-pdf'
+import { useState, useCallback, useMemo, useRef, useEffect } from 'react'
+import { Document, Page, pdfjs } from 'react-pdf'
+import type { PDFDocumentProxy } from 'pdfjs-dist'
 import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card'
 import { Button } from '@/components/ui/button'
-import { ChevronLeft, ChevronRight, ZoomIn, ZoomOut } from 'lucide-react'
+import { ChevronLeft, ChevronRight, ZoomIn, ZoomOut, Loader2 } from 'lucide-react'
 import 'react-pdf/dist/Page/AnnotationLayer.css'
 import 'react-pdf/dist/Page/TextLayer.css'
 
+// Configure standard font data URL for proper font rendering
+const pdfOptions = {
+  standardFontDataUrl: `https://unpkg.com/pdfjs-dist@${pdfjs.version}/standard_fonts/`,
+}
+
 interface PDFViewerProps {
   title?: string
   pdfUrl: string
@@ -17,41 +23,56 @@ export default function PDFViewer({ title, pdfUrl, className, httpHeaders }: PDF
   const [numPages, setNumPages] = useState<number>(0)
   const [pageNumber, setPageNumber] = useState<number>(1)
   const [scale, setScale] = useState<number>(1.0)
-  const [loading, setLoading] = useState<boolean>(true)
+  const [documentLoaded, setDocumentLoaded] = useState<boolean>(false)
   const [error, setError] = useState<string | null>(null)
 
-  // Memoize the file prop to prevent unnecessary reloads
+  // Store PDF document reference
+  const pdfDocRef = useRef<PDFDocumentProxy | null>(null)
+
+  // Memoize file config to prevent unnecessary reloads
   const fileConfig = useMemo(() => {
     return httpHeaders ? { url: pdfUrl, httpHeaders } : pdfUrl
   }, [pdfUrl, httpHeaders])
 
-  const onDocumentLoadSuccess = ({ numPages }: { numPages: number }) => {
-    setNumPages(numPages)
-    setLoading(false)
+  // Reset state when URL changes
+  useEffect(() => {
+    setDocumentLoaded(false)
     setError(null)
-  }
+    setNumPages(0)
+    setPageNumber(1)
+    pdfDocRef.current = null
+  }, [pdfUrl])
 
-  const onDocumentLoadError = (error: Error) => {
-    console.error('Error loading PDF:', error)
-    setError('Failed to load PDF. Please try again later.')
-    setLoading(false)
-  }
+  const onDocumentLoadSuccess = useCallback((pdf: { numPages: number }) => {
+    pdfDocRef.current = pdf as unknown as PDFDocumentProxy
+    setNumPages(pdf.numPages)
+    setPageNumber(1)
+    setDocumentLoaded(true)
+    setError(null)
+  }, [])
 
-  const goToPreviousPage = () => {
+  const onDocumentLoadError = useCallback((err: Error) => {
+    console.error('Error loading PDF:', err)
+    setError('無法載入 PDF 檔案。請稍後再試。')
+    setDocumentLoaded(false)
+    pdfDocRef.current = null
+  }, [])
+
+  const goToPreviousPage = useCallback(() => {
     setPageNumber((prev) => Math.max(prev - 1, 1))
-  }
+  }, [])
 
-  const goToNextPage = () => {
+  const goToNextPage = useCallback(() => {
     setPageNumber((prev) => Math.min(prev + 1, numPages))
-  }
+  }, [numPages])
 
-  const zoomIn = () => {
+  const zoomIn = useCallback(() => {
     setScale((prev) => Math.min(prev + 0.2, 3.0))
-  }
+  }, [])
 
-  const zoomOut = () => {
+  const zoomOut = useCallback(() => {
     setScale((prev) => Math.max(prev - 0.2, 0.5))
-  }
+  }, [])
 
   return (
     <Card className={className}>
@@ -69,18 +90,18 @@ export default function PDFViewer({ title, pdfUrl, className, httpHeaders }: PDF
               variant="outline"
               size="sm"
               onClick={goToPreviousPage}
-              disabled={pageNumber <= 1 || loading}
+              disabled={pageNumber <= 1 || !documentLoaded}
             >
               <ChevronLeft className="h-4 w-4" />
             </Button>
             <span className="text-sm whitespace-nowrap">
-              Page {pageNumber} of {numPages || '...'}
+              第 {pageNumber} 頁 / 共 {numPages || '...'} 頁
             </span>
             <Button
               variant="outline"
               size="sm"
               onClick={goToNextPage}
-              disabled={pageNumber >= numPages || loading}
+              disabled={pageNumber >= numPages || !documentLoaded}
             >
               <ChevronRight className="h-4 w-4" />
             </Button>
@@ -92,7 +113,7 @@ export default function PDFViewer({ title, pdfUrl, className, httpHeaders }: PDF
               variant="outline"
               size="sm"
               onClick={zoomOut}
-              disabled={scale <= 0.5 || loading}
+              disabled={scale <= 0.5 || !documentLoaded}
             >
               <ZoomOut className="h-4 w-4" />
             </Button>
@@ -103,7 +124,7 @@ export default function PDFViewer({ title, pdfUrl, className, httpHeaders }: PDF
               variant="outline"
               size="sm"
               onClick={zoomIn}
-              disabled={scale >= 3.0 || loading}
+              disabled={scale >= 3.0 || !documentLoaded}
             >
               <ZoomIn className="h-4 w-4" />
             </Button>
@@ -113,39 +134,48 @@ export default function PDFViewer({ title, pdfUrl, className, httpHeaders }: PDF
         {/* PDF Document */}
         <div className="border rounded-md bg-muted/10 overflow-auto max-h-[800px]">
           <div className="flex justify-center p-4">
-            {loading && (
-              <div className="flex items-center justify-center min-h-[400px]">
-                <div className="animate-spin rounded-full h-12 w-12 border-b-2 border-primary"></div>
-              </div>
-            )}
-
-            {error && (
+            {error ? (
               <div className="flex items-center justify-center min-h-[400px]">
                 <div className="text-center">
-                  <p className="text-destructive font-semibold mb-2">Error</p>
+                  <p className="text-destructive font-semibold mb-2">錯誤</p>
                   <p className="text-sm text-muted-foreground">{error}</p>
                 </div>
               </div>
-            )}
-
-            {!error && (
+            ) : (
               <Document
+                key={pdfUrl}
                 file={fileConfig}
+                options={pdfOptions}
                 onLoadSuccess={onDocumentLoadSuccess}
                 onLoadError={onDocumentLoadError}
                 loading={
                   <div className="flex items-center justify-center min-h-[400px]">
-                    <div className="animate-spin rounded-full h-12 w-12 border-b-2 border-primary"></div>
+                    <div className="text-center">
+                      <Loader2 className="w-12 h-12 animate-spin text-primary mx-auto mb-4" />
+                      <p className="text-muted-foreground">載入 PDF 中...</p>
+                    </div>
                   </div>
                 }
               >
-                <Page
-                  pageNumber={pageNumber}
-                  scale={scale}
-                  renderTextLayer={true}
-                  renderAnnotationLayer={true}
-                  className="shadow-lg"
-                />
+                {documentLoaded && (
+                  <Page
+                    pageNumber={pageNumber}
+                    scale={scale}
+                    renderTextLayer={true}
+                    renderAnnotationLayer={true}
+                    className="shadow-lg"
+                    loading={
+                      <div className="flex items-center justify-center min-h-[400px]">
+                        <Loader2 className="w-8 h-8 animate-spin text-primary" />
+                      </div>
+                    }
+                    error={
+                      <div className="text-center p-4 text-destructive">
+                        無法載入第 {pageNumber} 頁
+                      </div>
+                    }
+                  />
+                )}
               </Document>
             )}
           </div>

frontend/src/components/TaskNotFound.tsx

@@ -0,0 +1,46 @@
+import { useNavigate } from 'react-router-dom'
+import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card'
+import { Button } from '@/components/ui/button'
+import { Trash2 } from 'lucide-react'
+
+interface TaskNotFoundProps {
+  taskId: string | null
+  onClearAndUpload: () => void
+}
+
+export default function TaskNotFound({ taskId, onClearAndUpload }: TaskNotFoundProps) {
+  const navigate = useNavigate()
+
+  const handleClick = () => {
+    onClearAndUpload()
+    navigate('/upload')
+  }
+
+  return (
+    <div className="flex items-center justify-center min-h-[60vh]">
+      <Card className="max-w-md text-center">
+        <CardHeader>
+          <div className="flex justify-center mb-4">
+            <div className="w-16 h-16 bg-destructive/10 rounded-full flex items-center justify-center">
+              <Trash2 className="w-8 h-8 text-destructive" />
+            </div>
+          </div>
+          <CardTitle className="text-xl">任務已刪除</CardTitle>
+        </CardHeader>
+        <CardContent className="space-y-4">
+          <p className="text-muted-foreground">
+            此任務已被刪除或不存在。請上傳新檔案以建立新任務。
+          </p>
+          {taskId && (
+            <p className="text-xs text-muted-foreground font-mono">
+              任務 ID: {taskId}
+            </p>
+          )}
+          <Button onClick={handleClick} size="lg">
+            前往上傳頁面
+          </Button>
+        </CardContent>
+      </Card>
+    </div>
+  )
+}

frontend/src/components/ui/select.tsx

@@ -1,12 +1,14 @@
 import * as React from 'react'
+import * as SelectPrimitive from '@radix-ui/react-select'
 import { cn } from '@/lib/utils'
-import { ChevronDown } from 'lucide-react'
+import { Check, ChevronDown, ChevronUp } from 'lucide-react'
 
-export interface SelectProps extends React.SelectHTMLAttributes<HTMLSelectElement> {
+// Simple native select for backwards compatibility
+export interface NativeSelectProps extends React.SelectHTMLAttributes<HTMLSelectElement> {
   options: Array<{ value: string; label: string }>
 }
 
-const Select = React.forwardRef<HTMLSelectElement, SelectProps>(
+const NativeSelect = React.forwardRef<HTMLSelectElement, NativeSelectProps>(
   ({ className, options, ...props }, ref) => {
     return (
       <div className="relative">
@@ -33,6 +35,168 @@ const Select = React.forwardRef<HTMLSelectElement, SelectProps>(
     )
   }
 )
-Select.displayName = 'Select'
+NativeSelect.displayName = 'NativeSelect'
 
-export { Select }
+const Select = SelectPrimitive.Root
+
+const SelectGroup = SelectPrimitive.Group
+
+const SelectValue = SelectPrimitive.Value
+
+const SelectTrigger = React.forwardRef<
+  React.ComponentRef<typeof SelectPrimitive.Trigger>,
+  React.ComponentPropsWithoutRef<typeof SelectPrimitive.Trigger>
+>(({ className, children, ...props }, ref) => (
+  <SelectPrimitive.Trigger
+    ref={ref}
+    className={cn(
+      'flex h-10 w-full items-center justify-between rounded-lg border border-border bg-background px-3 py-2 text-sm',
+      'ring-offset-background placeholder:text-muted-foreground',
+      'focus:outline-none focus:ring-2 focus:ring-primary/20 focus:border-primary',
+      'disabled:cursor-not-allowed disabled:opacity-50',
+      '[&>span]:line-clamp-1',
+      className
+    )}
+    {...props}
+  >
+    {children}
+    <SelectPrimitive.Icon asChild>
+      <ChevronDown className="h-4 w-4 opacity-50" />
+    </SelectPrimitive.Icon>
+  </SelectPrimitive.Trigger>
+))
+SelectTrigger.displayName = SelectPrimitive.Trigger.displayName
+
+const SelectScrollUpButton = React.forwardRef<
+  React.ComponentRef<typeof SelectPrimitive.ScrollUpButton>,
+  React.ComponentPropsWithoutRef<typeof SelectPrimitive.ScrollUpButton>
+>(({ className, ...props }, ref) => (
+  <SelectPrimitive.ScrollUpButton
+    ref={ref}
+    className={cn(
+      'flex cursor-default items-center justify-center py-1',
+      className
+    )}
+    {...props}
+  >
+    <ChevronUp className="h-4 w-4" />
+  </SelectPrimitive.ScrollUpButton>
+))
+SelectScrollUpButton.displayName = SelectPrimitive.ScrollUpButton.displayName
+
+const SelectScrollDownButton = React.forwardRef<
+  React.ComponentRef<typeof SelectPrimitive.ScrollDownButton>,
+  React.ComponentPropsWithoutRef<typeof SelectPrimitive.ScrollDownButton>
+>(({ className, ...props }, ref) => (
+  <SelectPrimitive.ScrollDownButton
+    ref={ref}
+    className={cn(
+      'flex cursor-default items-center justify-center py-1',
+      className
+    )}
+    {...props}
+  >
+    <ChevronDown className="h-4 w-4" />
+  </SelectPrimitive.ScrollDownButton>
+))
+SelectScrollDownButton.displayName = SelectPrimitive.ScrollDownButton.displayName
+
+const SelectContent = React.forwardRef<
+  React.ComponentRef<typeof SelectPrimitive.Content>,
+  React.ComponentPropsWithoutRef<typeof SelectPrimitive.Content>
+>(({ className, children, position = 'popper', ...props }, ref) => (
+  <SelectPrimitive.Portal>
+    <SelectPrimitive.Content
+      ref={ref}
+      className={cn(
+        'relative z-50 max-h-96 min-w-[8rem] overflow-hidden rounded-lg border border-border bg-popover text-popover-foreground shadow-md',
+        'data-[state=open]:animate-in data-[state=closed]:animate-out',
+        'data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0',
+        'data-[state=closed]:zoom-out-95 data-[state=open]:zoom-in-95',
+        'data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2',
+        'data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2',
+        position === 'popper' &&
+          'data-[side=bottom]:translate-y-1 data-[side=left]:-translate-x-1 data-[side=right]:translate-x-1 data-[side=top]:-translate-y-1',
+        className
+      )}
+      position={position}
+      {...props}
+    >
+      <SelectScrollUpButton />
+      <SelectPrimitive.Viewport
+        className={cn(
+          'p-1',
+          position === 'popper' &&
+            'h-[var(--radix-select-trigger-height)] w-full min-w-[var(--radix-select-trigger-width)]'
+        )}
+      >
+        {children}
+      </SelectPrimitive.Viewport>
+      <SelectScrollDownButton />
+    </SelectPrimitive.Content>
+  </SelectPrimitive.Portal>
+))
+SelectContent.displayName = SelectPrimitive.Content.displayName
+
+const SelectLabel = React.forwardRef<
+  React.ComponentRef<typeof SelectPrimitive.Label>,
+  React.ComponentPropsWithoutRef<typeof SelectPrimitive.Label>
+>(({ className, ...props }, ref) => (
+  <SelectPrimitive.Label
+    ref={ref}
+    className={cn('py-1.5 pl-8 pr-2 text-sm font-semibold', className)}
+    {...props}
+  />
+))
+SelectLabel.displayName = SelectPrimitive.Label.displayName
+
+const SelectItem = React.forwardRef<
+  React.ComponentRef<typeof SelectPrimitive.Item>,
+  React.ComponentPropsWithoutRef<typeof SelectPrimitive.Item>
+>(({ className, children, ...props }, ref) => (
+  <SelectPrimitive.Item
+    ref={ref}
+    className={cn(
+      'relative flex w-full cursor-default select-none items-center rounded-md py-1.5 pl-8 pr-2 text-sm outline-none',
+      'focus:bg-accent focus:text-accent-foreground',
+      'data-[disabled]:pointer-events-none data-[disabled]:opacity-50',
+      className
+    )}
+    {...props}
+  >
+    <span className="absolute left-2 flex h-3.5 w-3.5 items-center justify-center">
+      <SelectPrimitive.ItemIndicator>
+        <Check className="h-4 w-4" />
+      </SelectPrimitive.ItemIndicator>
+    </span>
+
+    <SelectPrimitive.ItemText>{children}</SelectPrimitive.ItemText>
+  </SelectPrimitive.Item>
+))
+SelectItem.displayName = SelectPrimitive.Item.displayName
+
+const SelectSeparator = React.forwardRef<
+  React.ComponentRef<typeof SelectPrimitive.Separator>,
+  React.ComponentPropsWithoutRef<typeof SelectPrimitive.Separator>
+>(({ className, ...props }, ref) => (
+  <SelectPrimitive.Separator
+    ref={ref}
+    className={cn('-mx-1 my-1 h-px bg-muted', className)}
+    {...props}
+  />
+))
+SelectSeparator.displayName = SelectPrimitive.Separator.displayName
+
+export {
+  Select,
+  SelectGroup,
+  SelectValue,
+  SelectTrigger,
+  SelectContent,
+  SelectLabel,
+  SelectItem,
+  SelectSeparator,
+  SelectScrollUpButton,
+  SelectScrollDownButton,
+  NativeSelect,
+}

frontend/src/hooks/useTaskValidation.ts

@@ -0,0 +1,64 @@
+import { useEffect, useState } from 'react'
+import { useQuery } from '@tanstack/react-query'
+import { useUploadStore } from '@/store/uploadStore'
+import { apiClientV2 } from '@/services/apiV2'
+import type { TaskDetail } from '@/types/apiV2'
+
+interface UseTaskValidationResult {
+  taskId: string | null
+  taskDetail: TaskDetail | undefined
+  isLoading: boolean
+  isNotFound: boolean
+  clearAndReset: () => void
+}
+
+/**
+ * Hook for validating task existence and handling deleted tasks gracefully.
+ * Shows loading state first, then either returns task data or marks as not found.
+ */
+export function useTaskValidation(options?: {
+  refetchInterval?: number | false | ((query: any) => number | false)
+}): UseTaskValidationResult {
+  const { batchId, clearUpload } = useUploadStore()
+  const taskId = batchId ? String(batchId) : null
+
+  const [isNotFound, setIsNotFound] = useState(false)
+
+  const { data: taskDetail, isLoading, error, isFetching } = useQuery({
+    queryKey: ['taskDetail', taskId],
+    queryFn: () => apiClientV2.getTask(taskId!),
+    enabled: !!taskId && !isNotFound,
+    retry: (failureCount, error: any) => {
+      // Don't retry on 404
+      if (error?.response?.status === 404) {
+        return false
+      }
+      return failureCount < 2
+    },
+    refetchInterval: options?.refetchInterval ?? false,
+    // Disable stale time to ensure we check fresh data
+    staleTime: 0,
+  })
+
+  // Handle 404 error - mark as not found immediately
+  useEffect(() => {
+    if (error && (error as any)?.response?.status === 404) {
+      setIsNotFound(true)
+    }
+  }, [error])
+
+  // Clear state and store
+  const clearAndReset = () => {
+    clearUpload()
+    setIsNotFound(false)
+  }
+
+  return {
+    taskId,
+    taskDetail,
+    // Show loading if we have a taskId and are still fetching (but not if already marked as not found)
+    isLoading: !!taskId && !isNotFound && (isLoading || isFetching) && !taskDetail,
+    isNotFound,
+    clearAndReset,
+  }
+}

frontend/src/main.tsx

@@ -1,4 +1,3 @@
-import { StrictMode } from 'react'
 import { createRoot } from 'react-dom/client'
 import { BrowserRouter } from 'react-router-dom'
 import { QueryClient, QueryClientProvider } from '@tanstack/react-query'
@@ -10,8 +9,8 @@ import App from './App.tsx'
 
 // Configure PDF.js worker for react-pdf
 import { pdfjs } from 'react-pdf'
-// Use the worker from react-pdf's bundled pdfjs-dist
-pdfjs.GlobalWorkerOptions.workerSrc = `//unpkg.com/pdfjs-dist@${pdfjs.version}/build/pdf.worker.min.mjs`
+// Use CDN for the worker (most reliable for Vite)
+pdfjs.GlobalWorkerOptions.workerSrc = `https://unpkg.com/pdfjs-dist@${pdfjs.version}/build/pdf.worker.min.mjs`
 
 // Create React Query client
 const queryClient = new QueryClient({
@@ -24,16 +23,16 @@ const queryClient = new QueryClient({
   },
 })
 
+// Note: StrictMode disabled due to react-pdf incompatibility
+// StrictMode's double-invocation causes PDF worker race conditions
 createRoot(document.getElementById('root')!).render(
-  <StrictMode>
-    <QueryClientProvider client={queryClient}>
-      <I18nextProvider i18n={i18n}>
-        <ToastProvider>
-          <BrowserRouter>
-            <App />
-          </BrowserRouter>
-        </ToastProvider>
-      </I18nextProvider>
-    </QueryClientProvider>
-  </StrictMode>,
+  <QueryClientProvider client={queryClient}>
+    <I18nextProvider i18n={i18n}>
+      <ToastProvider>
+        <BrowserRouter>
+          <App />
+        </BrowserRouter>
+      </ToastProvider>
+    </I18nextProvider>
+  </QueryClientProvider>,
 )

frontend/src/pages/ProcessingPage.tsx

@@ -1,26 +1,35 @@
-import { useEffect, useState } from 'react'
+import { useState, useEffect } from 'react'
 import { useNavigate } from 'react-router-dom'
 import { useTranslation } from 'react-i18next'
-import { useQuery, useMutation } from '@tanstack/react-query'
+import { useMutation } from '@tanstack/react-query'
 import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card'
 import { Progress } from '@/components/ui/progress'
 import { Button } from '@/components/ui/button'
 import { Badge } from '@/components/ui/badge'
 import { useToast } from '@/components/ui/toast'
-import { useUploadStore } from '@/store/uploadStore'
 import { apiClientV2 } from '@/services/apiV2'
 import { Play, CheckCircle, FileText, AlertCircle, Clock, Activity, Loader2 } from 'lucide-react'
 import PPStructureParams from '@/components/PPStructureParams'
+import TaskNotFound from '@/components/TaskNotFound'
+import { useTaskValidation } from '@/hooks/useTaskValidation'
 import type { PPStructureV3Params, ProcessingOptions } from '@/types/apiV2'
 
 export default function ProcessingPage() {
   const { t } = useTranslation()
   const navigate = useNavigate()
   const { toast } = useToast()
-  const { batchId } = useUploadStore()
 
-  // In V2, batchId is actually a task_id (string)
-  const taskId = batchId ? String(batchId) : null
+  // Use shared hook for task validation
+  const { taskId, taskDetail, isLoading: isValidating, isNotFound, clearAndReset } = useTaskValidation({
+    refetchInterval: (query) => {
+      const data = query.state.data
+      if (!data) return 2000
+      if (data.status === 'completed' || data.status === 'failed') {
+        return false
+      }
+      return 2000
+    },
+  })
 
   // PP-StructureV3 parameters state
   const [ppStructureParams, setPpStructureParams] = useState<PPStructureV3Params>({})
@@ -56,22 +65,6 @@ export default function ProcessingPage() {
     },
   })
 
-  // Poll task status
-  const { data: taskDetail } = useQuery({
-    queryKey: ['taskDetail', taskId],
-    queryFn: () => apiClientV2.getTask(taskId!),
-    enabled: !!taskId,
-    refetchInterval: (query) => {
-      const data = query.state.data
-      if (!data) return 2000
-      // Stop polling if completed or failed
-      if (data.status === 'completed' || data.status === 'failed') {
-        return false
-      }
-      return 2000 // Poll every 2 seconds
-    },
-  })
-
   // Auto-redirect when completed
   useEffect(() => {
     if (taskDetail?.status === 'completed') {
@@ -115,6 +108,23 @@ export default function ProcessingPage() {
     }
   }
 
+  // Show loading while validating task
+  if (isValidating) {
+    return (
+      <div className="flex items-center justify-center min-h-[60vh]">
+        <div className="text-center">
+          <Loader2 className="w-12 h-12 animate-spin text-primary mx-auto mb-4" />
+          <p className="text-muted-foreground">載入任務資訊...</p>
+        </div>
+      </div>
+    )
+  }
+
+  // Show message when task was deleted
+  if (isNotFound) {
+    return <TaskNotFound taskId={taskId} onClearAndUpload={clearAndReset} />
+  }
+
   // Show helpful message when no task is selected
   if (!taskId) {
     return (

frontend/src/pages/ResultsPage.tsx

@@ -1,29 +1,23 @@
+import { useMemo } from 'react'
 import { useNavigate } from 'react-router-dom'
 import { useTranslation } from 'react-i18next'
-import { useQuery } from '@tanstack/react-query'
 import { Button } from '@/components/ui/button'
 import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card'
 import PDFViewer from '@/components/PDFViewer'
 import { useToast } from '@/components/ui/toast'
-import { useUploadStore } from '@/store/uploadStore'
 import { apiClientV2 } from '@/services/apiV2'
 import { FileText, Download, AlertCircle, TrendingUp, Clock, Layers, FileJson, Loader2 } from 'lucide-react'
 import { Badge } from '@/components/ui/badge'
+import TaskNotFound from '@/components/TaskNotFound'
+import { useTaskValidation } from '@/hooks/useTaskValidation'
 
 export default function ResultsPage() {
   const { t } = useTranslation()
   const navigate = useNavigate()
   const { toast } = useToast()
-  const { batchId } = useUploadStore()
 
-  // In V2, batchId is actually a task_id (string)
-  const taskId = batchId ? String(batchId) : null
-
-  // Get task details
-  const { data: taskDetail, isLoading } = useQuery({
-    queryKey: ['taskDetail', taskId],
-    queryFn: () => apiClientV2.getTask(taskId!),
-    enabled: !!taskId,
+  // Use shared hook for task validation
+  const { taskId, taskDetail, isLoading, isNotFound, clearAndReset } = useTaskValidation({
     refetchInterval: (query) => {
       const data = query.state.data
       if (!data) return 2000
@@ -34,6 +28,19 @@ export default function ResultsPage() {
     },
   })
 
+  // Construct PDF URL for preview - memoize to prevent unnecessary reloads
+  // Must be called unconditionally before any early returns (React hooks rule)
+  const API_BASE_URL = import.meta.env.VITE_API_BASE_URL || 'http://localhost:8000'
+  const pdfUrl = useMemo(() => {
+    return taskId ? `${API_BASE_URL}/api/v2/tasks/${taskId}/download/pdf` : ''
+  }, [taskId, API_BASE_URL])
+
+  // Get auth token for PDF preview - memoize to prevent new object reference each render
+  const pdfHttpHeaders = useMemo(() => {
+    const authToken = localStorage.getItem('auth_token_v2')
+    return authToken ? { Authorization: `Bearer ${authToken}` } : undefined
+  }, [])
+
   const handleDownloadPDF = async () => {
     if (!taskId) return
     try {
@@ -101,6 +108,23 @@ export default function ResultsPage() {
     }
   }
 
+  // Show loading while validating task
+  if (isLoading) {
+    return (
+      <div className="flex items-center justify-center min-h-[60vh]">
+        <div className="text-center">
+          <Loader2 className="w-12 h-12 animate-spin text-primary mx-auto mb-4" />
+          <p className="text-muted-foreground">載入任務結果...</p>
+        </div>
+      </div>
+    )
+  }
+
+  // Show message when task was deleted
+  if (isNotFound) {
+    return <TaskNotFound taskId={taskId} onClearAndUpload={clearAndReset} />
+  }
+
   // Show helpful message when no task is selected
   if (!taskId) {
     return (
@@ -127,17 +151,7 @@ export default function ResultsPage() {
     )
   }
 
-  if (isLoading) {
-    return (
-      <div className="flex items-center justify-center min-h-[60vh]">
-        <div className="text-center">
-          <Loader2 className="w-12 h-12 animate-spin text-primary mx-auto mb-4" />
-          <p className="text-muted-foreground">載入任務結果...</p>
-        </div>
-      </div>
-    )
-  }
-
+  // Fallback for no task detail (shouldn't happen with proper validation)
   if (!taskDetail) {
     return (
       <div className="flex items-center justify-center min-h-[60vh]">
@@ -157,14 +171,6 @@ export default function ResultsPage() {
 
   const isCompleted = taskDetail.status === 'completed'
 
-  // Construct PDF URL for preview
-  const API_BASE_URL = import.meta.env.VITE_API_BASE_URL || 'http://localhost:8000'
-  const pdfUrl = taskId ? `${API_BASE_URL}/api/v2/tasks/${taskId}/download/pdf` : ''
-
-  // Get auth token for PDF preview
-  const authToken = localStorage.getItem('auth_token_v2')
-  const pdfHttpHeaders = authToken ? { Authorization: `Bearer ${authToken}` } : undefined
-
   return (
     <div className="space-y-6">
       {/* Page Header */}

frontend/src/pages/TaskDetailPage.tsx

@@ -1,3 +1,4 @@
+import { useMemo } from 'react'
 import { useParams, useNavigate } from 'react-router-dom'
 import { useTranslation } from 'react-i18next'
 import { useQuery } from '@tanstack/react-query'
@@ -65,6 +66,19 @@ export default function TaskDetailPage() {
     retry: false,
   })
 
+  // Construct PDF URL for preview - memoize to prevent unnecessary reloads
+  // Must be called unconditionally before any early returns (React hooks rule)
+  const API_BASE_URL = import.meta.env.VITE_API_BASE_URL || 'http://localhost:8000'
+  const pdfUrl = useMemo(() => {
+    return taskId ? `${API_BASE_URL}/api/v2/tasks/${taskId}/download/pdf` : ''
+  }, [taskId, API_BASE_URL])
+
+  // Get auth token for PDF preview - memoize to prevent new object reference each render
+  const pdfHttpHeaders = useMemo(() => {
+    const authToken = localStorage.getItem('auth_token_v2')
+    return authToken ? { Authorization: `Bearer ${authToken}` } : undefined
+  }, [])
+
   const getTrackBadge = (track?: ProcessingTrack) => {
     if (!track) return null
     switch (track) {
@@ -218,14 +232,6 @@ export default function TaskDetailPage() {
   const isProcessing = taskDetail.status === 'processing'
   const isFailed = taskDetail.status === 'failed'
 
-  // Construct PDF URL for preview
-  const API_BASE_URL = import.meta.env.VITE_API_BASE_URL || 'http://localhost:8000'
-  const pdfUrl = taskId ? `${API_BASE_URL}/api/v2/tasks/${taskId}/download/pdf` : ''
-
-  // Get auth token for PDF preview
-  const authToken = localStorage.getItem('auth_token_v2')
-  const pdfHttpHeaders = authToken ? { Authorization: `Bearer ${authToken}` } : undefined
-
   return (
     <div className="space-y-6">
       {/* Page Header */}

frontend/src/pages/TaskHistoryPage.tsx

@@ -28,7 +28,7 @@ import {
   TableHeader,
   TableRow,
 } from '@/components/ui/table'
-import { Select } from '@/components/ui/select'
+import { NativeSelect } from '@/components/ui/select'
 import { Card, CardContent, CardDescription, CardHeader, CardTitle } from '@/components/ui/card'
 
 export default function TaskHistoryPage() {
@@ -112,6 +112,43 @@ export default function TaskHistoryPage() {
     }
   }
 
+  // Delete all tasks
+  const handleDeleteAll = async () => {
+    if (tasks.length === 0) {
+      alert('沒有可刪除的任務')
+      return
+    }
+
+    if (!confirm(`確定要刪除所有 ${total} 個任務嗎？此操作無法復原！`)) return
+
+    try {
+      setLoading(true)
+      // Delete tasks one by one
+      for (const task of tasks) {
+        await apiClientV2.deleteTask(task.task_id)
+      }
+      // If there are more pages, keep fetching and deleting
+      let hasMoreTasks = hasMore
+      while (hasMoreTasks) {
+        const response = await apiClientV2.listTasks({ page: 1, page_size: 100 })
+        if (response.tasks.length === 0) break
+        for (const task of response.tasks) {
+          await apiClientV2.deleteTask(task.task_id)
+        }
+        hasMoreTasks = response.has_more
+      }
+      fetchTasks()
+      fetchStats()
+      alert('所有任務已刪除')
+    } catch (err: any) {
+      alert(err.response?.data?.detail || '刪除任務失敗')
+      fetchTasks()
+      fetchStats()
+    } finally {
+      setLoading(false)
+    }
+  }
+
   // View task details
   const handleViewDetails = (taskId: string) => {
     navigate(`/tasks/${taskId}`)
@@ -220,10 +257,16 @@ export default function TaskHistoryPage() {
           <h1 className="text-3xl font-bold text-gray-900">任務歷史</h1>
           <p className="text-gray-600 mt-1">查看和管理您的 OCR 任務</p>
         </div>
-        <Button onClick={() => fetchTasks()} variant="outline">
-          <RefreshCw className="w-4 h-4 mr-2" />
-          刷新
-        </Button>
+        <div className="flex gap-2">
+          <Button onClick={() => fetchTasks()} variant="outline">
+            <RefreshCw className="w-4 h-4 mr-2" />
+            刷新
+          </Button>
+          <Button onClick={handleDeleteAll} variant="destructive" disabled={loading || tasks.length === 0}>
+            <Trash2 className="w-4 h-4 mr-2" />
+            刪除全部
+          </Button>
+        </div>
       </div>
 
       {/* Statistics */}
@@ -288,7 +331,7 @@ export default function TaskHistoryPage() {
           <div className="grid grid-cols-1 md:grid-cols-4 gap-4">
             <div>
               <label className="block text-sm font-medium text-gray-700 mb-2">狀態</label>
-              <Select
+              <NativeSelect
                 value={statusFilter}
                 onChange={(e) => {
                   setStatusFilter(e.target.value as any)

openspec/changes/enhance-memory-management/design.md

@@ -415,4 +415,173 @@ async def test_concurrent_load():
 ### Phase 4: Hardening (Week 4)
 - Stress testing
 - Performance tuning
-- Documentation and monitoring
+- Documentation and monitoring
+
+## Configuration Settings Reference
+
+All memory management settings are defined in `backend/app/core/config.py` under the `Settings` class.
+
+### Memory Thresholds
+
+| Setting | Type | Default | Description |
+|---------|------|---------|-------------|
+| `memory_warning_threshold` | float | 0.80 | GPU memory usage ratio (0-1) to trigger warning alerts |
+| `memory_critical_threshold` | float | 0.95 | GPU memory ratio to start throttling operations |
+| `memory_emergency_threshold` | float | 0.98 | GPU memory ratio to trigger emergency cleanup |
+
+### Memory Monitoring
+
+| Setting | Type | Default | Description |
+|---------|------|---------|-------------|
+| `memory_check_interval_seconds` | int | 30 | Background check interval for memory monitoring |
+| `enable_memory_alerts` | bool | True | Enable/disable memory threshold alerts |
+| `gpu_memory_limit_mb` | int | 6144 | Maximum GPU memory to use (MB) |
+| `gpu_memory_reserve_mb` | int | 512 | Memory reserved for CUDA overhead |
+
+### Model Lifecycle Management
+
+| Setting | Type | Default | Description |
+|---------|------|---------|-------------|
+| `enable_model_lifecycle_management` | bool | True | Use ModelManager for model lifecycle |
+| `model_idle_timeout_seconds` | int | 300 | Unload models after idle time |
+| `pp_structure_idle_timeout_seconds` | int | 300 | Unload PP-StructureV3 after idle |
+| `structure_model_memory_mb` | int | 2000 | Estimated memory for PP-StructureV3 |
+| `ocr_model_memory_mb` | int | 500 | Estimated memory per OCR language model |
+| `enable_lazy_model_loading` | bool | True | Load models on demand |
+| `auto_unload_unused_models` | bool | True | Auto-unload unused language models |
+
+### Service Pool Configuration
+
+| Setting | Type | Default | Description |
+|---------|------|---------|-------------|
+| `enable_service_pool` | bool | True | Use OCRServicePool |
+| `max_services_per_device` | int | 1 | Max OCRService instances per GPU |
+| `max_total_services` | int | 2 | Max total OCRService instances |
+| `service_acquire_timeout_seconds` | float | 300.0 | Timeout for acquiring service from pool |
+| `max_queue_size` | int | 50 | Max pending tasks per device queue |
+
+### Concurrency Control
+
+| Setting | Type | Default | Description |
+|---------|------|---------|-------------|
+| `max_concurrent_predictions` | int | 2 | Max concurrent PP-StructureV3 predictions |
+| `max_concurrent_pages` | int | 2 | Max pages processed concurrently |
+| `inference_batch_size` | int | 1 | Batch size for inference |
+| `enable_batch_processing` | bool | True | Enable batch processing for large docs |
+
+### Recovery Settings
+
+| Setting | Type | Default | Description |
+|---------|------|---------|-------------|
+| `enable_cpu_fallback` | bool | True | Fall back to CPU when GPU memory low |
+| `enable_emergency_cleanup` | bool | True | Auto-cleanup on memory pressure |
+| `enable_worker_restart` | bool | False | Restart workers on OOM (requires supervisor) |
+
+### Feature Flags
+
+| Setting | Type | Default | Description |
+|---------|------|---------|-------------|
+| `enable_chart_recognition` | bool | True | Enable chart/diagram recognition |
+| `enable_formula_recognition` | bool | True | Enable math formula recognition |
+| `enable_table_recognition` | bool | True | Enable table structure recognition |
+| `enable_seal_recognition` | bool | True | Enable seal/stamp recognition |
+| `enable_text_recognition` | bool | True | Enable general text recognition |
+| `enable_memory_optimization` | bool | True | Enable memory optimizations |
+
+### Environment Variable Override
+
+All settings can be overridden via environment variables. The format is uppercase with underscores:
+
+```bash
+# Example .env file
+MEMORY_WARNING_THRESHOLD=0.75
+MEMORY_CRITICAL_THRESHOLD=0.90
+MAX_CONCURRENT_PREDICTIONS=1
+GPU_MEMORY_LIMIT_MB=4096
+ENABLE_CPU_FALLBACK=true
+```
+
+### Recommended Configurations
+
+#### RTX 4060 8GB (Default)
+```bash
+GPU_MEMORY_LIMIT_MB=6144
+MAX_CONCURRENT_PREDICTIONS=2
+MAX_CONCURRENT_PAGES=2
+INFERENCE_BATCH_SIZE=1
+```
+
+#### RTX 3090 24GB
+```bash
+GPU_MEMORY_LIMIT_MB=20480
+MAX_CONCURRENT_PREDICTIONS=4
+MAX_CONCURRENT_PAGES=4
+INFERENCE_BATCH_SIZE=2
+```
+
+#### CPU-Only Mode
+```bash
+FORCE_CPU_MODE=true
+MAX_CONCURRENT_PREDICTIONS=1
+ENABLE_CPU_FALLBACK=false
+```
+
+## Prometheus Metrics
+
+The system exports Prometheus-format metrics via the `PrometheusMetrics` class. Available metrics:
+
+### GPU Metrics
+- `tool_ocr_memory_gpu_total_bytes` - Total GPU memory
+- `tool_ocr_memory_gpu_used_bytes` - Used GPU memory
+- `tool_ocr_memory_gpu_free_bytes` - Free GPU memory
+- `tool_ocr_memory_gpu_utilization_ratio` - GPU utilization (0-1)
+
+### Model Metrics
+- `tool_ocr_memory_models_loaded_total` - Number of loaded models
+- `tool_ocr_memory_models_memory_bytes` - Total memory used by models
+- `tool_ocr_memory_model_ref_count{model_id}` - Reference count per model
+
+### Prediction Metrics
+- `tool_ocr_memory_predictions_active` - Currently active predictions
+- `tool_ocr_memory_predictions_queue_depth` - Predictions waiting in queue
+- `tool_ocr_memory_predictions_total` - Total predictions processed (counter)
+- `tool_ocr_memory_predictions_timeouts_total` - Total prediction timeouts (counter)
+
+### Pool Metrics
+- `tool_ocr_memory_pool_services_total` - Total services in pool
+- `tool_ocr_memory_pool_services_available` - Available services
+- `tool_ocr_memory_pool_services_in_use` - Services in use
+- `tool_ocr_memory_pool_acquisitions_total` - Total acquisitions (counter)
+
+### Recovery Metrics
+- `tool_ocr_memory_recovery_count_total` - Total recovery attempts
+- `tool_ocr_memory_recovery_in_cooldown` - In cooldown (0/1)
+- `tool_ocr_memory_recovery_cooldown_remaining_seconds` - Remaining cooldown
+
+## Memory Dump API
+
+The `MemoryDumper` class provides debugging capabilities:
+
+```python
+from app.services.memory_manager import get_memory_dumper
+
+dumper = get_memory_dumper()
+
+# Create a memory dump
+dump = dumper.create_dump(include_python_objects=True)
+
+# Get dump as dictionary for JSON serialization
+dump_dict = dumper.to_dict(dump)
+
+# Compare two dumps to detect memory growth
+comparison = dumper.compare_dumps(dump1, dump2)
+```
+
+Memory dumps include:
+- GPU/CPU memory usage
+- Loaded models and reference counts
+- Active predictions and queue state
+- Service pool statistics
+- Recovery manager state
+- Python GC statistics
+- Large Python objects (optional)

openspec/changes/enhance-memory-management/tasks.md

@@ -3,123 +3,123 @@
 ## Section 1: Model Lifecycle Management (Priority: Critical)
 
 ### 1.1 Create ModelManager class
-- [ ] Design ModelManager interface with load/unload/get methods
-- [ ] Implement reference counting for model instances
-- [ ] Add idle timeout tracking with configurable thresholds
-- [ ] Create teardown() method for explicit cleanup
-- [ ] Add logging for model lifecycle events
+- [x] Design ModelManager interface with load/unload/get methods
+- [x] Implement reference counting for model instances
+- [x] Add idle timeout tracking with configurable thresholds
+- [x] Create teardown() method for explicit cleanup
+- [x] Add logging for model lifecycle events
 
 ### 1.2 Integrate PP-StructureV3 with ModelManager
-- [ ] Remove permanent exemption from unloading (lines 255-267)
-- [ ] Wrap PP-StructureV3 in managed model wrapper
-- [ ] Implement lazy loading on first access
-- [ ] Add unload capability with cache clearing
-- [ ] Test model reload after unload
+- [x] Remove permanent exemption from unloading (lines 255-267)
+- [x] Wrap PP-StructureV3 in managed model wrapper
+- [x] Implement lazy loading on first access
+- [x] Add unload capability with cache clearing
+- [x] Test model reload after unload
 
 ## Section 2: Service Singleton Pattern (Priority: Critical)
 
 ### 2.1 Create OCRServicePool
-- [ ] Design pool interface with acquire/release methods
-- [ ] Implement per-device instance management
-- [ ] Add queue-based task distribution
-- [ ] Implement concurrency limits via semaphores
-- [ ] Add health check for pooled instances
+- [x] Design pool interface with acquire/release methods
+- [x] Implement per-device instance management
+- [x] Add queue-based task distribution
+- [x] Implement concurrency limits via semaphores
+- [x] Add health check for pooled instances
 
 ### 2.2 Refactor task router
-- [ ] Replace OCRService() instantiation with pool.acquire()
-- [ ] Add proper release in finally blocks
-- [ ] Handle pool exhaustion gracefully
-- [ ] Add metrics for pool utilization
-- [ ] Update error handling for pooled services
+- [x] Replace OCRService() instantiation with pool.acquire()
+- [x] Add proper release in finally blocks
+- [x] Handle pool exhaustion gracefully
+- [x] Add metrics for pool utilization
+- [x] Update error handling for pooled services
 
 ## Section 3: Enhanced Memory Monitoring (Priority: High)
 
 ### 3.1 Create MemoryGuard class
-- [ ] Implement paddle.device.cuda memory queries
-- [ ] Add pynvml integration as fallback
-- [ ] Add torch memory query support
-- [ ] Create configurable threshold system
-- [ ] Implement memory prediction for operations
+- [x] Implement paddle.device.cuda memory queries
+- [x] Add pynvml integration as fallback
+- [x] Add torch memory query support
+- [x] Create configurable threshold system
+- [x] Implement memory prediction for operations
 
 ### 3.2 Integrate memory checks
-- [ ] Replace existing check_gpu_memory implementation
-- [ ] Add pre-operation memory checks
-- [ ] Implement CPU fallback when memory low
-- [ ] Add memory usage logging
-- [ ] Create memory pressure alerts
+- [x] Replace existing check_gpu_memory implementation
+- [x] Add pre-operation memory checks
+- [x] Implement CPU fallback when memory low
+- [x] Add memory usage logging
+- [x] Create memory pressure alerts
 
 ## Section 4: Concurrency Control (Priority: High)
 
 ### 4.1 Implement prediction semaphores
-- [ ] Add semaphore for PP-StructureV3.predict
-- [ ] Configure max concurrent predictions
-- [ ] Add queue for waiting predictions
-- [ ] Implement timeout handling
-- [ ] Add metrics for queue depth
+- [x] Add semaphore for PP-StructureV3.predict
+- [x] Configure max concurrent predictions
+- [x] Add queue for waiting predictions
+- [x] Implement timeout handling
+- [x] Add metrics for queue depth
 
 ### 4.2 Add selective processing
-- [ ] Create config for disabling chart/formula/table
-- [ ] Implement batch processing for large documents
-- [ ] Add progressive loading for multi-page docs
-- [ ] Create priority queue for operations
-- [ ] Test memory savings with selective processing
+- [x] Create config for disabling chart/formula/table
+- [x] Implement batch processing for large documents
+- [x] Add progressive loading for multi-page docs
+- [x] Create priority queue for operations
+- [x] Test memory savings with selective processing
 
 ## Section 5: Active Memory Management (Priority: Medium)
 
 ### 5.1 Create memory monitor thread
-- [ ] Implement background monitoring loop
-- [ ] Add periodic memory metrics collection
-- [ ] Create threshold-based triggers
-- [ ] Implement automatic cache clearing
-- [ ] Add LRU-based model unloading
+- [x] Implement background monitoring loop
+- [x] Add periodic memory metrics collection
+- [x] Create threshold-based triggers
+- [x] Implement automatic cache clearing
+- [x] Add LRU-based model unloading
 
 ### 5.2 Add recovery mechanisms
-- [ ] Implement emergency memory release
-- [ ] Add worker process restart capability
-- [ ] Create memory dump for debugging
-- [ ] Add cooldown period after recovery
-- [ ] Test recovery under various scenarios
+- [x] Implement emergency memory release
+- [x] Add worker process restart capability (RecoveryManager)
+- [x] Create memory dump for debugging
+- [x] Add cooldown period after recovery
+- [x] Test recovery under various scenarios
 
 ## Section 6: Cleanup Hooks (Priority: Medium)
 
 ### 6.1 Implement shutdown handlers
-- [ ] Add FastAPI shutdown event handler
-- [ ] Create signal handlers (SIGTERM, SIGINT)
-- [ ] Implement graceful model unloading
-- [ ] Add connection draining
-- [ ] Test shutdown sequence
+- [x] Add FastAPI shutdown event handler
+- [x] Create signal handlers (SIGTERM, SIGINT)
+- [x] Implement graceful model unloading
+- [x] Add connection draining
+- [x] Test shutdown sequence
 
 ### 6.2 Add task cleanup
-- [ ] Wrap background tasks with cleanup
-- [ ] Add success/failure callbacks
-- [ ] Implement resource release on completion
-- [ ] Add cleanup verification logging
-- [ ] Test cleanup in error scenarios
+- [x] Wrap background tasks with cleanup
+- [x] Add success/failure callbacks
+- [x] Implement resource release on completion
+- [x] Add cleanup verification logging
+- [x] Test cleanup in error scenarios
 
 ## Section 7: Configuration & Settings (Priority: Low)
 
 ### 7.1 Add memory settings to config
-- [ ] Define memory threshold parameters
-- [ ] Add model timeout settings
-- [ ] Configure pool sizes
-- [ ] Add feature flags for new behavior
-- [ ] Document all settings
+- [x] Define memory threshold parameters
+- [x] Add model timeout settings
+- [x] Configure pool sizes
+- [x] Add feature flags for new behavior
+- [x] Document all settings
 
 ### 7.2 Create monitoring dashboard
-- [ ] Add memory metrics endpoint
-- [ ] Create pool status endpoint
-- [ ] Add model lifecycle stats
-- [ ] Implement health check endpoint
-- [ ] Add Prometheus metrics export
+- [x] Add memory metrics endpoint
+- [x] Create pool status endpoint
+- [x] Add model lifecycle stats
+- [x] Implement health check endpoint
+- [x] Add Prometheus metrics export
 
 ## Section 8: Testing & Documentation (Priority: High)
 
 ### 8.1 Create comprehensive tests
-- [ ] Unit tests for ModelManager
-- [ ] Integration tests for OCRServicePool
-- [ ] Memory leak detection tests
-- [ ] Stress tests with concurrent requests
-- [ ] Performance benchmarks
+- [x] Unit tests for ModelManager
+- [x] Integration tests for OCRServicePool
+- [x] Memory leak detection tests
+- [x] Stress tests with concurrent requests
+- [x] Performance benchmarks
 
 ### 8.2 Documentation
 - [ ] Document memory management architecture
@@ -131,5 +131,46 @@
 ---
 
 **Total Tasks**: 58
-**Estimated Effort**: 3-4 weeks
-**Critical Path**: Sections 1-2 must be completed first as they form the foundation
+**Completed**: 53
+**Remaining**: 5 (Section 8.2 Documentation only)
+**Progress**: ~91%
+
+**Critical Path Status**: Sections 1-8.1 are completed (foundation, memory monitoring, prediction semaphores, batch processing, recovery, signal handlers, configuration, Prometheus metrics, and comprehensive tests in place)
+
+## Implementation Summary
+
+### Files Created
+- `backend/app/services/memory_manager.py` - ModelManager, MemoryGuard, MemoryConfig, PredictionSemaphore, BatchProcessor, ProgressiveLoader, PriorityOperationQueue, RecoveryManager
+- `backend/app/services/service_pool.py` - OCRServicePool, PoolConfig
+- `backend/tests/services/test_memory_manager.py` - Unit tests for memory management (57 tests)
+- `backend/tests/services/test_service_pool.py` - Unit tests for service pool (18 tests)
+- `backend/tests/services/test_ocr_memory_integration.py` - Integration tests for memory check patterns (10 tests)
+
+### Files Modified
+- `backend/app/core/config.py` - Added memory management configuration settings
+- `backend/app/services/ocr_service.py` - Removed PP-StructureV3 exemption, added unload capability, integrated MemoryGuard for pre-operation checks and CPU fallback, added PredictionSemaphore for concurrent prediction control
+- `backend/app/services/pp_structure_enhanced.py` - Added PredictionSemaphore control for predict calls
+- `backend/app/routers/tasks.py` - Refactored to use service pool
+- `backend/app/main.py` - Added startup/shutdown handlers, signal handlers (SIGTERM/SIGINT), connection draining, recovery manager shutdown
+
+### New Classes Added (Section 4.2-8)
+- `BatchProcessor` - Memory-aware batch processing for large documents with priority support
+- `ProgressiveLoader` - Progressive page loading with lookahead and automatic cleanup
+- `PriorityOperationQueue` - Priority queue with timeout and cancellation support
+- `RecoveryManager` - Memory recovery with cooldown period and attempt limits
+- `MemoryDumper` - Memory dump creation for debugging with history and comparison
+- `PrometheusMetrics` - Prometheus-format metrics export for monitoring
+- Signal handlers for graceful shutdown (SIGTERM, SIGINT)
+- Connection draining for clean shutdown
+
+### New Test Classes Added (Section 8.1)
+- `TestModelReloadAfterUnload` - Tests for model reload after unload
+- `TestSelectiveProcessingMemorySavings` - Tests for memory savings with selective processing
+- `TestRecoveryScenarios` - Tests for recovery under various scenarios
+- `TestShutdownSequence` - Tests for shutdown sequence
+- `TestCleanupInErrorScenarios` - Tests for cleanup in error scenarios
+- `TestMemoryLeakDetection` - Tests for memory leak detection
+- `TestStressConcurrentRequests` - Stress tests with concurrent requests
+- `TestPerformanceBenchmarks` - Performance benchmark tests
+- `TestMemoryDumper` - Tests for MemoryDumper class
+- `TestPrometheusMetrics` - Tests for PrometheusMetrics class