rename(547): the server is grimoire — package, image, DB defaults, backups

Step 2 of the Scribe -> Grimoire rename.

- src/scribe -> src/grimoire, and every import, patch target, module path,
  hypercorn entry point and `python -m grimoire.restore` with it; pyproject,
  uv.lock and the frontend package are named grimoire.
- Image git.fabledsword.com/bvandeusen/fabledgrimoire; CI's Postgres service
  runs as grimoire / grimoire_test.
- Compose files default the DB user, database and (prod) volume to grimoire,
  each overridable from .env, so an install created as Scribe keeps its data
  by setting POSTGRES_USER, POSTGRES_DB and PGDATA_VOLUME.
- Backups are written as grimoire-<ts>.tar with format grimoire-backup-tar.
  Archives named scribe-* with the scribe-backup-tar manifest still restore
  and are still counted at the destination (folder and S3), with tests.
- Exports, the MCP auth realm, the ASGI scope key and the persistent logger
  carry the new name.

Kept on purpose: the secret-sealing key label stays "scribe.secrets.v1",
because every stored secret was derived under it.

Plugin identity (plugin name, hooks, env vars, .scribe marker, skills) is
step 3.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

tests/test_integration_milestone_search.py

@@ -11,12 +11,12 @@ from unittest.mock import AsyncMock, patch
 import pytest
 import pytest_asyncio
 
-from scribe.models import async_session
-from scribe.models.embedding import EMBEDDING_DIM, MilestoneEmbedding
-from scribe.models.milestone import Milestone
-from scribe.models.project import Project
-from scribe.services import dedup as dedup_svc
-from scribe.services.embeddings import CHUNKER_VERSION, EMBEDDING_MODEL, semantic_search_milestones
+from grimoire.models import async_session
+from grimoire.models.embedding import EMBEDDING_DIM, MilestoneEmbedding
+from grimoire.models.milestone import Milestone
+from grimoire.models.project import Project
+from grimoire.services import dedup as dedup_svc
+from grimoire.services.embeddings import CHUNKER_VERSION, EMBEDDING_MODEL, semantic_search_milestones
 from tests.helpers import ensure_user
 
 pytestmark = [pytest.mark.integration, pytest.mark.usefixtures("_dispose_engine", "_no_embedding")]
@@ -56,7 +56,7 @@ async def roadmap():
 
 
 async def _found(user_id, **kw) -> list[int]:
-    with patch("scribe.services.embeddings.get_embedding", AsyncMock(return_value=NEAR)):
+    with patch("grimoire.services.embeddings.get_embedding", AsyncMock(return_value=NEAR)):
         hits = await semantic_search_milestones(user_id, "book metadata and providers",
                                                 threshold=0.5, limit=10, **kw)
     return [m.id for _s, m in hits]
@@ -89,7 +89,7 @@ LONG = "Resolve works and editions against the metadata providers. " * 5
 
 
 async def _gate(roadmap, title, text="", project=None):
-    with patch("scribe.services.embeddings.get_embedding", AsyncMock(return_value=NEAR)):
+    with patch("grimoire.services.embeddings.get_embedding", AsyncMock(return_value=NEAR)):
         return await dedup_svc.plan_gate(
             roadmap["owner"], project or roadmap["mine"], title, text,
         )