Add per-request AI logging, DB batch queue, WS entity updates, and UI polish

- log_thread.py: thread-safe ContextVar bridge so executor threads can log
  individual LLM calls and archive searches back to the event loop
- ai_log.py: init_thread_logging(), notify_entity_update(); WS now pushes
  entity_update messages when book data changes after any plugin or batch run
- batch.py: replace batch_pending.json with batch_queue SQLite table;
  run_batch_consumer() reads queue dynamically so new books can be added
  while batch is running; add_to_queue() deduplicates
- migrate.py: fix _migrate_v1 (clear-on-startup bug); add _migrate_v2 for
  batch_queue table
- _client.py / archive.py / identification.py: wrap each LLM API call and
  archive search with log_thread start/finish entries
- api.py: POST /api/batch returns {already_running, added}; notify_entity_update
  after identify pipeline
- models.default.yaml: strengthen ai_identify confidence-scoring instructions;
  warn against placeholder data
- detail-render.js: book log entries show clickable ID + spine thumbnail;
  book spine/title images open full-screen popup
- events.js: batch-start handles already_running+added; open-img-popup action
- init.js: entity_update WS handler; image popup close listeners
- overlays.css / index.html: full-screen image popup overlay
- eslint.config.js: add new globals; fix no-redeclare/no-unused-vars for
  multi-file global architecture; all lint errors resolved

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

config/models.default.yaml

@@ -42,9 +42,33 @@ models:
     credentials: openrouter
     model: "google/gemini-flash-1.5"
     prompt: |
-      # ${RAW_TEXT}      — text read from the book spine (multi-line)
-      # ${OUTPUT_FORMAT} — JSON schema injected by BookIdentifierPlugin
-      The following text was read from a book spine:
+      # ${RAW_TEXT}           — text read from the book spine (multi-line)
+      # ${ARCHIVE_RESULTS}    — JSON array of candidate records from library archives
+      # ${OUTPUT_FORMAT}      — JSON schema injected by BookIdentifierPlugin
+      Text read from the book spine:
       ${RAW_TEXT}
-      Identify this book. Search for it if needed. Return ONLY valid JSON, no explanation:
+
+      Archive search results (may be empty):
+      ${ARCHIVE_RESULTS}
+
+      Your task:
+      1. Search the web for this book if needed to find additional information.
+      2. Combine the spine text, archive results, and your web search into identification candidates.
+      3. Collapse candidates that are clearly the same book (same title + author + year + publisher) into one entry, listing all contributing sources.
+      4. Rank candidates by confidence (highest first). Assign a score 0.0-1.0.
+      5. Remove any candidates you believe are irrelevant or clearly wrong.
+
+      IMPORTANT — confidence scoring rules:
+      - The score must reflect how well the found information matches the spine text and recognized data.
+      - If the only available evidence is a title with no author, year, publisher, or corroborating archive results, the score must not exceed 0.5.
+      - Base confidence on: quality of spine text match, number of matching fields, archive result corroboration, and completeness of the identified record.
+      - A record with title + author + year that appears in multiple archive sources warrants a high score; a record with only a guessed title warrants a low score.
+
+      IMPORTANT — output format rules:
+      - The JSON schema below is a format specification only. Do NOT use it as a source of example data.
+      - Do NOT return placeholder values such as "The Great Gatsby", "Unknown Author", "Example Publisher", or any other generic example text unless that exact text literally appears on the spine.
+      - Return only real books that could plausibly match what is shown on this spine.
+      - If you cannot identify the book with reasonable confidence, return an empty array [].
+
+      Return ONLY valid JSON matching the schema below, no explanation:
       ${OUTPUT_FORMAT}