Guard against deleting a knowledge base while its documents are still indexing (pause/await before delete)

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### 1. Is this request related to a challenge you're experiencing?

Follow-up to #38518. That issue has two halves:

1. **Non-robust cleanup** — being fixed in #38519 (delete in per-step-committed batches so a failure no longer rolls back the whole cleanup and orphans everything).
2. **No guard against deleting a dataset while its documents are still indexing** — this request.

`DatasetService.delete_dataset` (`api/services/dataset_service.py`, ~L1308) sends the `dataset_was_deleted` signal and does `db.session.delete(dataset)` immediately, with **no check for or cancellation of in-flight indexing**. When a dataset is deleted mid-indexing, the running pipeline keeps executing and fails repeatedly with `KnowledgeIndexNodeError: Dataset not found.` (`core/rag/index_processor/index_processor.py` `index_and_clean`), and it can keep writing rows that race with the cleanup task — the root cause behind the orphaned data in #38518. Even with #38519 making cleanup robust, avoiding the race in the first place is the correct defensive posture.

### 2. Describe the feature you'd like to see

Before deleting a dataset, pause and await any in-flight indexing for its documents, then delete.

A concrete shape (suggested on #38518): reuse the existing **per-document pause mechanism** — `Document.is_paused` (set e.g. in `controllers/console/datasets/datasets_document.py`) which makes `indexing_runner` raise `DocumentIsPausedError` at its stage checkpoints. `delete_dataset` could:

1. Find all documents of the dataset in an active indexing state (`IndexingStatus` `WAITING` / `PARSING` / `CLEANING` / `SPLITTING` / `INDEXING`, see `models/enums.py`).
2. Set their pause flag (Redis + DB) and wait for the running tasks to acknowledge/stop at the next checkpoint (with a bounded timeout).
3. Proceed with deletion + cleanup once no document is actively indexing.

This closes the race without having to revoke Celery tasks directly. An alternative (simpler but less friendly) is to **reject** deletion with a clear error while indexing is active, letting the user stop/finish it first.

### 3. How will this feature improve your workflow?

Deleting a knowledge base while it is still indexing (easy to do on large ingests) no longer races the cleanup and leaves tens of GB of orphaned `document_segments` / `child_chunks` / `embedding_vector_index_*` behind — which is exactly what we hit in production (#38518).

### Related

- #38518 (parent report), #38519 (cleanup-robustness fix)
- #37773 (related document-vs-dataset segment race), #38117 (infinite loop in `_delete_records` during dataset deletion)

Start with DatasetService.delete_dataset in api/services/dataset_service.py, then read Document.is_paused, indexing_runner, and IndexingStatus in models/enums.py. Trace how pause state is set in controllers/console/datasets/datasets_document.py and how index_processor.py acknowledges it. Done means deletion no longer races active indexing, with bounded waiting or a clear rejection and cleanup proceeding safely.

Written by the indexing model from the issue text.