feat: Add Playbook Manager, Saved Searches, and Timeline View components

- Implemented PlaybookManager for creating and managing investigation playbooks with templates.
- Added SavedSearches component for managing bookmarked queries and recurring scans.
- Introduced TimelineView for visualizing forensic event timelines with zoomable charts.
- Enhanced backend processing with auto-queued jobs for dataset uploads and improved database concurrency.
- Updated frontend components for better user experience and performance optimizations.
- Documented changes in update log for future reference.

_optimize_scanner_keyset.py

@@ -0,0 +1,61 @@
+from pathlib import Path
+p=Path(r'd:/Projects/Dev/ThreatHunt/backend/app/services/scanner.py')
+t=p.read_text(encoding='utf-8')
+start=t.index('    async def _scan_datasets(')
+end=t.index('    async def _scan_hunts', start)
+new_func='''    async def _scan_datasets(
+        self, patterns: dict, result: ScanResult, dataset_ids: list[str] | None
+    ) -> None:
+        """Scan dataset rows in batches using keyset pagination (no OFFSET)."""
+        ds_q = select(Dataset.id, Dataset.name)
+        if dataset_ids:
+            ds_q = ds_q.where(Dataset.id.in_(dataset_ids))
+        ds_result = await self.db.execute(ds_q)
+        ds_map = {r[0]: r[1] for r in ds_result.fetchall()}
+
+        if not ds_map:
+            return
+
+        import asyncio
+
+        for ds_id, ds_name in ds_map.items():
+            last_id = 0
+            while True:
+                rows_result = await self.db.execute(
+                    select(DatasetRow)
+                    .where(DatasetRow.dataset_id == ds_id)
+                    .where(DatasetRow.id > last_id)
+                    .order_by(DatasetRow.id)
+                    .limit(BATCH_SIZE)
+                )
+                rows = rows_result.scalars().all()
+                if not rows:
+                    break
+
+                for row in rows:
+                    result.rows_scanned += 1
+                    data = row.data or {}
+                    for col_name, cell_value in data.items():
+                        if cell_value is None:
+                            continue
+                        text = str(cell_value)
+                        self._match_text(
+                            text,
+                            patterns,
+                            "dataset_row",
+                            row.id,
+                            col_name,
+                            result.hits,
+                            row_index=row.row_index,
+                            dataset_name=ds_name,
+                        )
+
+                last_id = rows[-1].id
+                await asyncio.sleep(0)
+                if len(rows) < BATCH_SIZE:
+                    break
+
+'''
+out=t[:start]+new_func+t[end:]
+p.write_text(out,encoding='utf-8')
+print('optimized scanner _scan_datasets to keyset pagination')