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Code Issues 1 Pull Requests 2 Actions Packages Projects Releases Wiki Activity
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4 Commits
Author SHA1 Message Date
Richie ceb2dbb2b3 refactor(ebook-search): simplify search and phrase matching
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2026-07-15 15:25:11 -04:00
Richie 6bf77299e8 Refactor logging statements to use f-strings for improved readability and consistency across the codebase. This change enhances the clarity of log messages by directly embedding variable values, making it easier to trace and debug application behavior.
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pytest / pytest (pull_request) Successful in 28s
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test ebook search / test-ebook-search (pull_request) Failing after 35s
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2026-07-12 19:34:19 -04:00
Richie bfb3463fd0 feat(ebook): migrate to async DB/HTTP and parallelize phrase pipeline 
Convert the ebook-search web app to async end to end and add concurrency
to the protected-phrase extraction and judging pipeline so large books no
longer block the event loop or the UI.

ORM / infra:
- Add get_async_postgres_engine and factor shared URL/connect_args building
  into build_postgres_url (reused by the sync and async engine builders)
- Add async FastAPI session helpers (get_async_db, AsyncDbSession) with
  expire_on_commit=False to avoid implicit IO under asyncio

App:
- Use AsyncEngine/AsyncSession throughout routes, search, ingest, embeddings,
  answer, rerank and LLM calls; convert handlers to async
- Share a single httpx.AsyncClient in app state for LLM requests; size the
  connection pool for concurrent phrase-judging workers
- Add judge_tasks: run per-book judging as tracked background tasks so a
  book already being judged isn't double-queued

Protected phrases:
- Add a process pool (pool.py) and worker-count config
  (extraction/judge book/phrase workers) to parallelize candidate generation
  and judging
- Split admin actions into all/missing variants for generation and judging

Config:
- Add protected_phrase_extraction_workers, phrase_judge_book_workers,
  phrase_judge_phrase_workers
 2026-07-12 17:51:06 -04:00
Richie bcb8b7b169 Add models and database persistence for protected phrase extraction 
- Introduced dataclasses for phrase candidates, judgments, and matches in `models.py`.
- Implemented database operations for candidate and protected phrases in `store.py`, including loading, saving, and deleting phrases.
- Enhanced text normalization functions in `text_normalization.py` with detailed docstrings.
- Refactored search functionality to utilize new models and methods for detecting protected phrases.
 2026-07-12 17:49:52 -04:00