fix(protected-phrases): isolate phrase generation per book

Run full-book candidate generation inside worker-owned sessions so each book commits independently during backfills. Abort recalculation when a book has no indexed chapters to preserve existing phrase data, and update admin/UI tests for the new generation flow.

python/ebook_search/protected_phrases/pool.py

@@ -9,21 +9,11 @@ or server threads.
 
 from __future__ import annotations
 
-import asyncio
 import logging
 import multiprocessing
 import os
 from concurrent.futures import ProcessPoolExecutor
 from threading import Lock
-from typing import TYPE_CHECKING
-
-from python.ebook_search.protected_phrases.extraction import extract_phrase_candidates_for_book
-
-if TYPE_CHECKING:
-    from collections.abc import Mapping, Sequence
-
-    from python.ebook_search.config import EbookSearchConfig
-    from python.ebook_search.protected_phrases.models import PhraseCandidate
 
 logger = logging.getLogger(__name__)
 
@@ -66,36 +56,3 @@ def shutdown_extraction_pool() -> None:
             _extraction_pool.pool.shutdown(wait=False, cancel_futures=True)
             _extraction_pool.pool = None
             logger.info("ebook_phrase_extraction_pool_shutdown")
-
-
-async def extract_phrase_candidates_in_pool(
-    book_text: str,
-    chapters: Sequence[str],
-    config: EbookSearchConfig,
-    *,
-    metadata: Mapping[str, object] | None,
-) -> list[PhraseCandidate]:
-    """Run book phrase extraction in a worker process and await the result.
-
-    Only the CPU-bound extraction runs in the worker; the caller keeps all database work in the
-    request process. The spaCy pipeline is not supported here because it is not picklable, so
-    this always runs the non-spaCy extraction path.
-
-    Args:
-        book_text (str): Full book text used for extraction.
-        chapters (Sequence[str]): Chapter-like text blocks used for frequency counts.
-        config (EbookSearchConfig): Runtime phrase-tuning settings.
-        metadata (Mapping[str, object] | None): Optional book metadata used as a candidate source.
-
-    Returns:
-        list[PhraseCandidate]: Scored candidates sorted best-first and capped per book.
-    """
-    pool = get_extraction_pool(config.protected_phrase_extraction_workers)
-    future = pool.submit(
-        extract_phrase_candidates_for_book,
-        book_text,
-        list(chapters),
-        config,
-        metadata=dict(metadata) if metadata is not None else None,
-    )
-    return await asyncio.wrap_future(future)