fix: Savepoint leak in embedding pipeline, atomic fail_job, RRF dedup

Three correctness fixes found during peer code review:

Embedding pipeline savepoint leak (HIGH severity):
The SAVEPOINT embed_page / RELEASE embed_page pattern had ~10 `?`
propagation points between them. Any error from record_embedding_error,
clear_document_embeddings, or store_embedding would exit the function
without rolling back, leaving the SQLite connection in a broken
transactional state and causing cascading failures for the rest of the
session. Fixed by extracting page processing into `embed_page()` and
wrapping with explicit rollback-on-error handling.

Dependent queue fail_job race (MEDIUM severity):
fail_job performed a SELECT followed by a separate UPDATE on the
attempts counter without a transaction. Under concurrent lock
reclamation, the attempts value could be read stale. Replaced with a
single atomic UPDATE that increments attempts and computes exponential
backoff entirely in SQL, also halving DB round-trips. Added explicit
error when the job no longer exists.

RRF duplicate document score inflation (MEDIUM severity):
If a retriever returned the same document_id multiple times, the RRF
score accumulated multiple rank contributions while the rank only
recorded the first occurrence. Moved the score accumulation inside the
`if is_none` guard so only the first occurrence per list contributes.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

src/search/rrf.rs

@@ -33,8 +33,10 @@ pub fn rank_rrf(vector_results: &[(i64, f64)], fts_results: &[(i64, f64)]) -> Ve
     for (i, &(doc_id, _)) in vector_results.iter().enumerate() {
         let rank = i + 1; // 1-indexed
         let entry = scores.entry(doc_id).or_insert((0.0, None, None));
-        entry.0 += 1.0 / (RRF_K + rank as f64);
+        // Only count the first occurrence per list to prevent duplicates
+        // from inflating the score.
         if entry.1.is_none() {
+            entry.0 += 1.0 / (RRF_K + rank as f64);
             entry.1 = Some(rank);
         }
     }
@@ -42,8 +44,8 @@ pub fn rank_rrf(vector_results: &[(i64, f64)], fts_results: &[(i64, f64)]) -> Ve
     for (i, &(doc_id, _)) in fts_results.iter().enumerate() {
         let rank = i + 1; // 1-indexed
         let entry = scores.entry(doc_id).or_insert((0.0, None, None));
-        entry.0 += 1.0 / (RRF_K + rank as f64);
         if entry.2.is_none() {
+            entry.0 += 1.0 / (RRF_K + rank as f64);
             entry.2 = Some(rank);
         }
     }