Drop the JSON vector column, and fix what was hiding behind it

Migration 38 left memories.embedding in place so a rollback could still find
the vectors. Production has since been verified reading from embedding_blob,
so migration 42 drops it: 4 MB of a 99.6 MB database holding nothing anyone
reads.

Removing it surfaced a live bug. Changing your embedding model is supposed to
throw the bank's vectors away and let the post-turn pass rebuild them, because
two models' vectors are not comparable. The settings route did that by nulling
memories.embedding -- correct until 38 moved the vectors, after which it
cleared the dead column and left the blob intact with `embedded` still true.
_embed_pending filters on `embedded IS FALSE`, so it never saw those rows and
the bank went on ranking against the old model's vectors permanently.

Nothing would have reported it. cosine returns 0.0 on a width mismatch, so a
different-width model scores every memory zero and retrieval returns whichever
rows happen to sort first; a same-width model scores plausible garbage.

The bulk clear now sets both columns. It stays a bulk UPDATE rather than going
through set_vector -- loading the rows is the cost that whole path exists to
avoid -- so set_vector's docstring now names it as the one caller that
legitimately writes those columns by hand. No cache invalidation is added:
clearing `embedded` drops the rows out of the catalogue query, and set_vector
evicts each entry as the re-embed puts it back.

test_embedding_blob.py now rebuilds the pre-38 schema by hand where it tests
the backfill, since create_all no longer produces the column it converts from,
and asserts 42 removes it at the end of a full bootstrap -- 38 reads that
column and 42 drops it, so an upgrade that reordered them would arrive with an
empty bank.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_017Dvvqn9ZDR4ixeFPHNbww7

backend/app/memorybank.py

@@ -86,13 +86,15 @@ def set_vector(memory: models.Memory, vector: list[float] | None) -> None:
     """Store (or clear) a memory's embedding.
 
     Every column that describes the vector moves together: `embedding_blob` is
-    what the ranking reads, `embedded` is the flag everything else reads, and
-    the JSON `embedding` stays correct behind both until the follow-up
-    migration drops it. Going through one function is what keeps them in step —
-    and it is also the only place a stored vector can change, which is what
-    makes the cache below safe to invalidate here and nowhere else.
+    what the ranking reads and `embedded` is the flag everything else reads.
+    Going through one function is what keeps them in step — and it is also the
+    only place a stored vector can change, which is what makes the cache below
+    safe to invalidate here and nowhere else.
+
+    The one caller that legitimately cannot come through here is the bulk
+    clear in `routers/settings.py` when the embedding model changes. It has to
+    set the same two columns by hand; see the note there.
     """
-    memory.embedding = vector
     memory.embedding_blob = None if vector is None else vectors.pack(vector)
     memory.embedded = vector is not None
     cached = _vector_cache.get(memory.adventure_id)