Resume Feature Implementation

components/review_dashboard_page.py

@@ -362,20 +362,18 @@ class ReviewDashboardPage:
                     Annotation.annotator_id == target_annotator_obj.id
                 ).count()
 
-                # Calculate how many items to load initially to include the resume index
-                INITIAL_BATCH_SIZE = 5  # Minimum batch size
-                if resume_index >= 0:
-                    # Load enough items to include the resume index, but at least INITIAL_BATCH_SIZE
-                    items_to_load = max(INITIAL_BATCH_SIZE, resume_index + 1)
-                    # Cap it to avoid loading too many items at once
-                    items_to_load = min(items_to_load, 20)
-                else:
-                    # No unreviewed items found, load standard batch from the end
-                    items_to_load = INITIAL_BATCH_SIZE
+                # Calculate loading strategy based on resume logic
+                INITIAL_BATCH_SIZE = 10  # Standard batch size
+                CONTEXT_ITEMS = 1  # Number of reviewed items to include for context
+                load_offset = 0  # Initialize load_offset
                 
-                # Load items based on resume logic
                 if resume_index >= 0:
-                    # Load from the beginning to include the resume index
+                    # Load items starting from around the first unreviewed annotation
+                    # Include some context (already reviewed items) before the unreviewed one
+                    load_offset = max(0, resume_index - CONTEXT_ITEMS)
+                    items_to_load = INITIAL_BATCH_SIZE
+                    
+                    # Load items starting from the calculated offset
                     query = db.query(
                         Annotation,
                         TTSData.filename,
@@ -384,9 +382,12 @@ class ReviewDashboardPage:
                         TTSData, Annotation.tts_data_id == TTSData.id
                     ).filter(
                         Annotation.annotator_id == target_annotator_obj.id
-                    ).order_by(Annotation.id).limit(items_to_load)
+                    ).order_by(Annotation.id).offset(load_offset).limit(items_to_load)
+                    
+                    log.info(f"Resume mode: Loading {items_to_load} items starting from offset {load_offset} (first unreviewed at global index {resume_index})")
                 else:
-                    # All items reviewed, load from the end
+                    # No unreviewed items found, load standard batch from the end
+                    load_offset = max(0, total_count - INITIAL_BATCH_SIZE)
                     query = db.query(
                         Annotation,
                         TTSData.filename,
@@ -395,14 +396,12 @@ class ReviewDashboardPage:
                         TTSData, Annotation.tts_data_id == TTSData.id
                     ).filter(
                         Annotation.annotator_id == target_annotator_obj.id
-                    ).order_by(Annotation.id.desc()).limit(items_to_load)
+                    ).order_by(Annotation.id).offset(load_offset).limit(INITIAL_BATCH_SIZE)
+                    
+                    log.info(f"All reviewed mode: Loading {INITIAL_BATCH_SIZE} items from offset {load_offset}")
 
                 results = query.all()
                 
-                # If we loaded from the end (all reviewed), reverse the results to maintain chronological order
-                if resume_index < 0:
-                    results = list(reversed(results))
-                
                 log.info(f"Loaded {len(results)} annotations out of {total_count} total for target annotator ID {target_annotator_obj.id}")
 
                 # Process items with minimal data - validation status will be loaded on-demand
@@ -427,15 +426,22 @@ class ReviewDashboardPage:
                 # --- Calculate initial index based on resume logic ---
                 initial_idx = 0
                 if items:
-                    if resume_index >= 0 and resume_index < len(items):
-                        # Resume from the first unreviewed item
-                        initial_idx = resume_index
-                        log.info(f"User '{username}' resuming at first unreviewed item, index: {initial_idx} (annotation ID: {items[initial_idx]['annotation_id']})")
+                    if resume_index >= 0:
+                        # Calculate the local index within loaded items
+                        # The first unreviewed annotation should be at: resume_index - load_offset
+                        local_resume_index = resume_index - load_offset
+                        if 0 <= local_resume_index < len(items):
+                            initial_idx = local_resume_index
+                            log.info(f"User '{username}' resuming at first unreviewed item, local index: {initial_idx} (global index: {resume_index}, annotation ID: {items[initial_idx]['annotation_id']})")
+                        else:
+                            # Fallback to first item if calculation is off
+                            initial_idx = 0
+                            log.warning(f"Resume index calculation off, starting at first loaded item. Local index: {local_resume_index}, loaded items: {len(items)}")
                     else:
-                        # All items reviewed or no unreviewed items in current batch, start from the last item
+                        # All items reviewed, start from the last item
                         initial_idx = len(items) - 1 if items else 0
                         if items:
-                            log.info(f"User '{username}' has all loaded items reviewed, starting at last item index: {initial_idx} (annotation ID: {items[initial_idx]['annotation_id']})")
+                            log.info(f"User '{username}' has all items reviewed, starting at last item index: {initial_idx} (annotation ID: {items[initial_idx]['annotation_id']})")
                 else:
                     log.info(f"User '{username}' has no items assigned, starting at index 0.")