Perf: dedupe table_exists() lookups, atomic insert counter, fewer connections in update_llm_index()

test_migration_never_delegates_to_current_schema_helpers never actually ran
the migration (missing check_and_run_migrations() call) and its source-text
assertion was tautological (the "or DROP TABLE in source" clause was always
true). Now runs the real migration and asserts spy call counts instead:
DocumentChunksTable.create/DocumentMetaTable.create are each called exactly
3 times (construction, rebuild temp file, post-swap reopen -- all via
_open_connection, never from inside apply()), and _create_vec_table is
never called from the migration path.

test_drop_table_clears_modified_times asserted via get_modified_times(),
which short-circuits on table_exists() -- checking only the vec0 table that
drop_table() drops first -- so the assertion held even if
DocumentMetaTable.delete_all() were never called. Now asserts directly
against document_meta and document_chunks row counts.

docker/rootfs/etc/s6-overlay/s6-rc.d/init-llmindex-migrate/run

@@ -0,0 +1,12 @@
+#!/command/with-contenv /usr/bin/bash
+# shellcheck shell=bash
+
+declare -r log_prefix="[init-llmindex-migrate]"
+
+echo "${log_prefix} Checking for pending LLM index migrations..."
+cd "${PAPERLESS_SRC_DIR}"
+if [[ -n "${USER_IS_NON_ROOT}" ]]; then
+	python3 manage.py document_llmindex migrate
+else
+	s6-setuidgid paperless python3 manage.py document_llmindex migrate
+fi

docker/rootfs/etc/s6-overlay/s6-rc.d/init-llmindex-migrate/type

@@ -0,0 +1 @@
+oneshot

docker/rootfs/etc/s6-overlay/s6-rc.d/init-llmindex-migrate/up

@@ -0,0 +1 @@
+/etc/s6-overlay/s6-rc.d/init-llmindex-migrate/run

docs/administration.md

@@ -212,6 +212,16 @@ following:
     This is a no-op if the index is already up to date, so it is safe to
     run on every upgrade.
 
+5.  Migrate the LLM index if needed.
+
+    ```shell-session
+    cd src
+    python3 manage.py document_llmindex migrate
+    ```
+
+    This is a no-op if the index schema is already current, so it is safe
+    to run on every upgrade.
+
 ### Database Upgrades
 
 Paperless-ngx is compatible with Django-supported versions of PostgreSQL and MariaDB and it is generally
@@ -532,7 +542,7 @@ index is updated automatically on the schedule set by
 can manage it manually:
 
 ```
-document_llmindex {rebuild,update,compact}
+document_llmindex {rebuild,update,compact,migrate}
 ```
 
 Specify `rebuild` to build the index from scratch from all documents in the database. Use

src/documents/management/commands/document_llmindex.py

@@ -3,6 +3,7 @@ from typing import Any
 from documents.management.commands.base import PaperlessCommand
 from documents.tasks import llmindex_index
 from paperless_ai.indexing import llm_index_compact
+from paperless_ai.indexing import llm_index_migrate
 
 
 class Command(PaperlessCommand):
@@ -13,12 +14,18 @@ class Command(PaperlessCommand):
 
     def add_arguments(self, parser: Any) -> None:
         super().add_arguments(parser)
-        parser.add_argument("command", choices=["rebuild", "update", "compact"])
+        parser.add_argument(
+            "command",
+            choices=["rebuild", "update", "compact", "migrate"],
+        )
 
     def handle(self, *args: Any, **options: Any) -> None:
         if options["command"] == "compact":
             llm_index_compact()
             return
+        if options["command"] == "migrate":
+            llm_index_migrate()
+            return
         llmindex_index(
             rebuild=options["command"] == "rebuild",
             iter_wrapper=lambda docs: self.track(

src/documents/tests/management/test_management_document_llmindex.py

@@ -9,6 +9,7 @@ if TYPE_CHECKING:
 
 _COMPACT = "documents.management.commands.document_llmindex.llm_index_compact"
 _INDEX = "documents.management.commands.document_llmindex.llmindex_index"
+_MIGRATE = "documents.management.commands.document_llmindex.llm_index_migrate"
 
 
 class TestDocumentLlmindexCommand:
@@ -17,6 +18,11 @@ class TestDocumentLlmindexCommand:
         call_command("document_llmindex", "compact")
         mock_compact.assert_called_once_with()
 
+    def test_migrate_calls_llm_index_migrate(self, mocker: MockerFixture) -> None:
+        mock_migrate = mocker.patch(_MIGRATE)
+        call_command("document_llmindex", "migrate")
+        mock_migrate.assert_called_once_with()
+
     def test_rebuild_calls_llmindex_index_with_rebuild_true(
         self,
         mocker: MockerFixture,

src/paperless_ai/indexing.py

@@ -144,6 +144,24 @@ def _exclude_readers():
         lock.close()
 
 
+def _with_exclusive_access(operation: str, fn):
+    """Run ``fn()`` with exclusive index access (see ``_exclude_readers()``),
+    for compaction/migration file swaps that must not run while readers are
+    active. Returns ``fn()``'s result, or None (after logging) if active
+    readers do not drain within ``LLM_INDEX_COMPACTION_LOCK_TIMEOUT`` --
+    callers skip the operation this run; it retries next time.
+    """
+    try:
+        with _exclude_readers():
+            return fn()
+    except Timeout:
+        logger.info(
+            "Skipping LLM index %s: index readers are active; will retry next run.",
+            operation,
+        )
+        return None
+
+
 @contextmanager
 def write_store(embed_model_name: str | None = None):
     """Acquire the write lock and yield the vector store.
@@ -168,6 +186,21 @@ def write_store(embed_model_name: str | None = None):
         yield store
 
 
+def _check_and_run_migrations(store: "PaperlessSqliteVecVectorStore") -> bool:
+    """Run any pending structural migrations, returning True if a pending
+    re-embed migration needs the caller to force a rebuild -- never
+    triggered automatically here. Safe to call before any write, including
+    delete()/upsert_document(): has_pending_migration() (see its docstring)
+    keeps this a no-op, with no exclusive access taken, once the store is
+    current.
+    """
+    if not store.has_pending_migration():
+        return False
+    return bool(
+        _with_exclusive_access("migration check", store.check_and_run_migrations),
+    )
+
+
 def _safe_related_name(document: Document, field: str) -> str | None:
     """
     Returns the ``name`` of a related object (correspondent, document_type,
@@ -339,15 +372,7 @@ def update_llm_index(
     happens, since a rebuild always covers the whole library regardless.
     """
     with write_store() as store:
-        try:
+        needs_reembed = _check_and_run_migrations(store)
-            with _exclude_readers():
-                needs_reembed = store.check_and_run_migrations()
-        except Timeout:
-            logger.info(
-                "Skipping LLM index migration check: index readers are active; "
-                "will retry next run.",
-            )
-            needs_reembed = False
         if needs_reembed:
             logger.warning(
                 "LLM index migration requires re-embedding; forcing rebuild.",
@@ -368,12 +393,11 @@ def update_llm_index(
     config = AIConfig()
     model_name = get_configured_model_name(config)
 
-    if not rebuild and llm_index_exists():
+    if not rebuild:
         with read_store() as store:
-            config_mismatch = store.config_mismatch(model_name)
+            if store.table_exists() and store.config_mismatch(model_name):
-        if config_mismatch:
+                logger.warning("Embedding model changed; forcing LLM index rebuild.")
-            logger.warning("Embedding model changed; forcing LLM index rebuild.")
+                rebuild = True
-            rebuild = True
 
     if no_documents:
         logger.warning("No documents found to index.")
@@ -412,14 +436,7 @@ def update_llm_index(
                 else "No changes detected in LLM index."
             )
 
-        try:
+        _with_exclusive_access("compaction", store.compact)
-            with _exclude_readers():
-                store.compact()
-        except Timeout:
-            logger.info(
-                "Skipping LLM index compaction: index readers are active; "
-                "will retry next run.",
-            )
     return msg
 
 
@@ -434,25 +451,60 @@ def llm_index_add_or_update_document(document: Document):
         _embed_nodes(new_nodes, get_embedding_model(config))
 
     with write_store(embed_model_name=get_configured_model_name(config)) as store:
+        needs_reembed = _check_and_run_migrations(store)
+        if needs_reembed:
+            logger.warning(
+                "Skipping incremental LLM index update for document %s: the "
+                "index requires re-embedding first. Run 'document_llmindex "
+                "rebuild' to resolve.",
+                document.id,
+            )
+            return
         store.upsert_document(str(document.id), new_nodes)
 
 
+def llm_index_migrate() -> None:
+    """Apply any pending LLM index schema migrations, with no reindex.
+
+    Intended to run unconditionally on every startup (see the
+    init-llmindex-migrate container step and the bare-metal upgrade docs):
+    has_pending_migration() short-circuits to a metadata-only read once the
+    store is current, so a healthy install pays almost nothing here. Only
+    ever applies structural migrations -- a pending re-embed migration is
+    left for the explicit, deliberate rebuild path (``document_llmindex
+    update``/``rebuild``) to resolve, since re-embedding can be slow and,
+    for a metered embedding backend, cost money.
+    """
+    if not AIConfig().llm_index_enabled:
+        return
+    with write_store() as store:
+        needs_reembed = _check_and_run_migrations(store)
+    if needs_reembed:
+        logger.warning(
+            "LLM index requires re-embedding, which this automatic migration "
+            "check will not do on its own -- it can be slow and, for a "
+            "metered embedding backend, cost money. Run "
+            "'document_llmindex rebuild' manually when ready.",
+        )
+
+
 def llm_index_compact() -> None:
     """Compact the index immediately, rebuilding the table to reclaim space."""
     with write_store() as store:
-        try:
+        _with_exclusive_access("compaction", lambda: store.compact(force=True))
-            with _exclude_readers():
-                store.compact(force=True)
-        except Timeout:
-            logger.info(
-                "Skipping LLM index compaction: index readers are active; "
-                "will retry next run.",
-            )
 
 
 def llm_index_remove_document(document: Document):
     """Remove a document's chunks from the LLM index."""
     with write_store() as store:
+        if _check_and_run_migrations(store):
+            logger.warning(
+                "Skipping removal of document %s from the LLM index: the "
+                "index requires re-embedding first. Run 'document_llmindex "
+                "rebuild' to resolve.",
+                document.id,
+            )
+            return
         store.delete(str(document.id))
 
 

src/paperless_ai/migrations/__init__.py

@@ -0,0 +1,60 @@
+"""Schema migrations for the sqlite-vec vector store.
+
+Each migration lives in its own module here, named ``mNNNN_description.py``
+(e.g. ``m0001_v1_to_v2.py`` -- a leading digit isn't a valid Python
+identifier, hence the ``m`` prefix, unlike Django's own numbered migrations,
+which load via a dynamic ``importlib.import_module()`` call rather than a
+static import statement), and registers itself into ``MIGRATIONS`` at import
+time. ``vector_store.py`` imports those modules at the bottom of the file,
+purely for that registration side effect, after ``PaperlessSqliteVecVectorStore``
+is fully defined -- migrations need it to implement ``apply()`` (see
+``Migration`` below).
+
+To add a new migration: add a new ``mNNNN_description.py`` module here that
+imports ``PaperlessSqliteVecVectorStore`` from ``paperless_ai.vector_store``,
+defines its ``apply()``, and appends a ``Migration`` to ``MIGRATIONS``; then
+import that module at the bottom of ``vector_store.py`` and bump
+``SCHEMA_VERSION`` there. A migration must freeze its own historical DDL for
+any side table its target version depends on (``DROP TABLE IF EXISTS`` +
+its own literal ``CREATE TABLE``/``CREATE INDEX`` statements) rather than
+delegating to any "current schema" helper -- see ``m0001_v1_to_v2.py`` for
+why and the worked example.
+"""
+
+import sqlite3
+from collections.abc import Callable
+from dataclasses import dataclass
+from dataclasses import field
+from typing import Literal
+
+
+@dataclass
+class Migration:
+    """A schema migration for the sqlite-vec vector store.
+
+    kind="structural": rows are copied into a new-schema file with no
+    re-embedding needed.  Supply ``apply(src_conn, dst_conn, dim)``, which
+    must create every table its target schema needs in ``dst_conn`` and copy
+    ``src_conn``'s rows and relevant ``index_meta`` keys into it.
+    ``schema_version`` is written by the migration runner after ``apply``
+    returns, not by ``apply`` itself.
+
+    kind="re-embed": the new schema requires fresh embeddings.
+    ``check_and_run_migrations()`` returns True when it encounters one of
+    these so the caller can force a full rebuild (which recreates the table
+    at the current SCHEMA_VERSION).
+    """
+
+    from_version: int
+    to_version: int
+    kind: Literal["structural", "re-embed"]
+    description: str
+    apply: Callable[[sqlite3.Connection, sqlite3.Connection, int], None] | None = field(
+        default=None,
+        repr=False,
+    )
+
+
+# Registry of all schema migrations in order, populated by each migration
+# module's import-time registration (see the module docstring above).
+MIGRATIONS: list[Migration] = []

src/paperless_ai/migrations/m0001_v1_to_v2.py

@@ -0,0 +1,118 @@
+import sqlite3
+
+from paperless_ai.migrations import MIGRATIONS
+from paperless_ai.migrations import Migration
+from paperless_ai.tables import ChunkRow
+from paperless_ai.tables import DocumentChunksTable
+from paperless_ai.tables import DocumentMetaRow
+from paperless_ai.tables import DocumentMetaTable
+from paperless_ai.tables import IndexMetaTable
+from paperless_ai.vector_store import COMPACT_BATCH_SIZE
+from paperless_ai.vector_store import DEFAULT_TABLE_NAME
+
+# v1's vec0 shape has never changed since it first shipped and is the ONLY
+# real upgrade path -- no store has ever existed at any intermediate
+# version, so this migration goes straight from that shipped shape to the
+# final v2 target in one pass.
+_V1_SELECT = (
+    "SELECT id, document_id, modified, node_content, embedding FROM "
+    + DEFAULT_TABLE_NAME
+)
+
+
+def _migrate_v1_to_v2(
+    src_conn: sqlite3.Connection,
+    dst_conn: sqlite3.Connection,
+    dim: int,
+) -> None:
+    """v1 -> v2: document_id TEXT -> INTEGER, modified moves out of vec0
+    into document_meta, document_chunks added for O(1) per-document delete.
+
+    Freezes its own v2-shaped vec0/document_chunks/document_meta DDL inline,
+    rather than delegating to the gateway "create table" helpers or the
+    store's own vec0-table builder (all of which always reflect the
+    *current* schema): a later schema version changing any of these tables'
+    shape must not silently change what this migration produces for someone
+    upgrading straight from v1.
+    _open_connection() already created document_chunks/document_meta on
+    dst_conn (reflecting current HEAD) as a side effect of opening it for
+    this migration's rebuild -- DROP them first so this migration's own
+    frozen CREATE TABLE isn't a silent no-op against that. Safe here because
+    dst_conn is a freshly opened, empty rebuild file with nothing written
+    yet.
+    """
+    dst_conn.execute(  # nosemgrep: python.sqlalchemy.security.sqlalchemy-execute-raw-query.sqlalchemy-execute-raw-query
+        "CREATE VIRTUAL TABLE "
+        + DEFAULT_TABLE_NAME
+        + " USING vec0("
+        + "id TEXT PRIMARY KEY,"
+        + " document_id INTEGER,"
+        + " +node_content TEXT,"
+        + " embedding float["
+        + str(int(dim))
+        + "] distance_metric=cosine"
+        + ")",
+    )
+    dst_conn.execute("DROP TABLE IF EXISTS document_chunks")
+    dst_conn.execute(
+        "CREATE TABLE document_chunks "
+        "(chunk_id TEXT PRIMARY KEY, document_id INTEGER NOT NULL)",
+    )
+    dst_conn.execute(
+        "CREATE INDEX idx_document_chunks_document_id ON document_chunks (document_id)",
+    )
+    dst_conn.execute("DROP TABLE IF EXISTS document_meta")
+    dst_conn.execute(
+        "CREATE TABLE document_meta "
+        "(document_id INTEGER PRIMARY KEY, modified TEXT NOT NULL)",
+    )
+
+    IndexMetaTable.set_dim(dst_conn, dim)
+    embed_model = IndexMetaTable.get_embed_model(src_conn)
+    if embed_model is not None:
+        IndexMetaTable.set_embed_model(dst_conn, embed_model)
+
+    dst_conn.execute("BEGIN IMMEDIATE")
+    src_cursor = src_conn.execute(_V1_SELECT)
+    live = 0
+    while batch := src_cursor.fetchmany(COMPACT_BATCH_SIZE):
+        vec0_rows = []
+        chunk_rows = []
+        meta_by_document: dict[int, str] = {}
+        for r in batch:
+            document_id = int(r["document_id"])
+            vec0_rows.append(
+                (r["id"], document_id, r["node_content"], bytes(r["embedding"])),
+            )
+            chunk_rows.append(ChunkRow(r["id"], document_id))
+            meta_by_document[document_id] = str(r["modified"] or "")
+        dst_conn.executemany(
+            "INSERT INTO "
+            + DEFAULT_TABLE_NAME
+            + " (id, document_id, node_content, embedding) VALUES (?, ?, ?, ?)",
+            vec0_rows,
+        )
+        DocumentChunksTable.insert_many(dst_conn, chunk_rows)
+        DocumentMetaTable.upsert_many(
+            dst_conn,
+            (DocumentMetaRow(doc_id, mod) for doc_id, mod in meta_by_document.items()),
+        )
+        live += len(batch)
+    # This migration only ever copies live rows (like compact()), so the
+    # cumulative counter resets to match -- the new file has no bloat yet.
+    IndexMetaTable.reset_total_inserts(dst_conn, live)
+    dst_conn.execute("COMMIT")
+
+
+MIGRATIONS.append(
+    Migration(
+        from_version=1,
+        to_version=2,
+        kind="structural",
+        description=(
+            "document_id TEXT -> INTEGER; move modified into document_meta; "
+            "add document_chunks for O(1) per-document delete"
+        ),
+        apply=_migrate_v1_to_v2,
+    ),
+)

src/paperless_ai/tables.py

@@ -0,0 +1,242 @@
+"""Thin gateways over the plain relational side tables that sit alongside the
+vec0 table. Each method takes the sqlite3.Connection to operate on
+explicitly, rather than owning one -- the store swaps connections during
+compact()/migration, and migrations always work across two connections
+(src_conn, dst_conn) at once.
+
+PRECONDITION: Callers must set conn.row_factory = sqlite3.Row before passing a
+connection to any of these gateways' read methods. The read methods across all
+three classes (DocumentChunksTable.chunk_ids_for_document, IndexMetaTable._get,
+DocumentMetaTable.all_modified_times, DocumentMetaTable.copy_all) use
+row["column_name"] dictionary-style indexing, which requires sqlite3.Row as the
+row factory -- without it, sqlite3.Row is not set, rows are returned as plain
+tuples, and tuple indices must be integers, raising TypeError.
+"""
+
+import sqlite3
+from collections.abc import Iterable
+from typing import NamedTuple
+
+
+class ChunkRow(NamedTuple):
+    chunk_id: str
+    document_id: int
+
+
+class DocumentMetaRow(NamedTuple):
+    document_id: int
+    modified: str
+
+
+class DocumentChunksTable:
+    """chunk_id -> document_id, indexed by document_id. Gives O(1)
+    per-document chunk lookup that vec0's own document_id metadata column
+    cannot (see PaperlessSqliteVecVectorStore._delete_chunks_by_document_id).
+    """
+
+    @staticmethod
+    def create(conn: sqlite3.Connection) -> None:
+        conn.execute(
+            "CREATE TABLE IF NOT EXISTS document_chunks "
+            "(chunk_id TEXT PRIMARY KEY, document_id INTEGER NOT NULL)",
+        )
+        conn.execute(
+            "CREATE INDEX IF NOT EXISTS idx_document_chunks_document_id "
+            "ON document_chunks (document_id)",
+        )
+
+    @staticmethod
+    def insert_many(conn: sqlite3.Connection, rows: Iterable[ChunkRow]) -> None:
+        """rows must already be batch-bounded by the caller (e.g. vec0's own
+        fetchmany() loop) -- this never reads, so it can't itself introduce
+        an unbounded scan, but a whole-table iterable defeats the point."""
+        conn.executemany(
+            "INSERT INTO document_chunks (chunk_id, document_id) VALUES (?, ?)",
+            rows,
+        )
+
+    @staticmethod
+    def chunk_ids_for_document(
+        conn: sqlite3.Connection,
+        document_id: int,
+    ) -> list[str]:
+        return [
+            row["chunk_id"]
+            for row in conn.execute(
+                "SELECT chunk_id FROM document_chunks WHERE document_id = ?",
+                (document_id,),
+            ).fetchall()
+        ]
+
+    @staticmethod
+    def delete_for_document(conn: sqlite3.Connection, document_id: int) -> None:
+        conn.execute(
+            "DELETE FROM document_chunks WHERE document_id = ?",
+            (document_id,),
+        )
+
+    @staticmethod
+    def delete_all(conn: sqlite3.Connection) -> None:
+        conn.execute("DELETE FROM document_chunks")
+
+    @staticmethod
+    def count(conn: sqlite3.Connection) -> int:
+        """Cheap stand-in for vec0's own row count -- see compact()."""
+        return conn.execute("SELECT count(*) FROM document_chunks").fetchone()[0]
+
+
+class DocumentMetaTable:
+    """document_id -> modified, one row per document. Lives outside vec0
+    because vec0 only inlines TEXT metadata up to 12 bytes and `modified`
+    (an ISO timestamp) is always longer.
+    """
+
+    @staticmethod
+    def create(conn: sqlite3.Connection) -> None:
+        conn.execute(
+            "CREATE TABLE IF NOT EXISTS document_meta "
+            "(document_id INTEGER PRIMARY KEY, modified TEXT NOT NULL)",
+        )
+
+    @staticmethod
+    def upsert_many(
+        conn: sqlite3.Connection,
+        rows: Iterable[DocumentMetaRow],
+    ) -> None:
+        conn.executemany(
+            "INSERT INTO document_meta (document_id, modified) VALUES (?, ?) "
+            "ON CONFLICT(document_id) DO UPDATE SET modified = excluded.modified",
+            rows,
+        )
+
+    @staticmethod
+    def delete_for_document(conn: sqlite3.Connection, document_id: int) -> None:
+        conn.execute(
+            "DELETE FROM document_meta WHERE document_id = ?",
+            (document_id,),
+        )
+
+    @staticmethod
+    def delete_all(conn: sqlite3.Connection) -> None:
+        conn.execute("DELETE FROM document_meta")
+
+    @staticmethod
+    def copy_all(
+        src_conn: sqlite3.Connection,
+        dst_conn: sqlite3.Connection,
+        batch_size: int,
+    ) -> None:
+        """Stream document_meta from src_conn into dst_conn in bounded
+        batches. The *only* sanctioned way to move this table across
+        connections (compact()/migrations) -- an unbounded fetchall here
+        would defeat the same OOM-avoidance the vec0 row copy already relies
+        on. batch_size has no default: forces the call site to think about
+        it (pass COMPACT_BATCH_SIZE)."""
+        cursor = src_conn.execute(
+            "SELECT document_id, modified FROM document_meta",
+        )
+        while batch := cursor.fetchmany(batch_size):
+            DocumentMetaTable.upsert_many(
+                dst_conn,
+                (DocumentMetaRow(r["document_id"], r["modified"]) for r in batch),
+            )
+
+    @staticmethod
+    def all_modified_times(conn: sqlite3.Connection) -> dict[str, str]:
+        """Full document_id -> modified map, for get_modified_times()'s
+        public API only. One unbounded read by design (existing behavior).
+        Never use this for cross-connection copying; see copy_all()."""
+        return {
+            str(row["document_id"]): str(row["modified"] or "")
+            for row in conn.execute(
+                "SELECT document_id, modified FROM document_meta",
+            )
+        }
+
+
+class IndexMetaTable:
+    """Typed accessors over index_meta's key/value rows -- replaces
+    PaperlessSqliteVecVectorStore._meta_get_on/_meta_set_on, which returned
+    untyped str | None regardless of whether the key held an int (dim,
+    schema_version, total_inserts) or a string (embed_model).
+    """
+
+    @staticmethod
+    def create(conn: sqlite3.Connection) -> None:
+        conn.execute(
+            "CREATE TABLE IF NOT EXISTS index_meta (key TEXT PRIMARY KEY, value TEXT)",
+        )
+
+    @staticmethod
+    def _get(conn: sqlite3.Connection, key: str) -> str | None:
+        row = conn.execute(
+            "SELECT value FROM index_meta WHERE key = ?",
+            (key,),
+        ).fetchone()
+        return row["value"] if row else None
+
+    @staticmethod
+    def _set(conn: sqlite3.Connection, key: str, value: str) -> None:
+        conn.execute(
+            "INSERT INTO index_meta (key, value) VALUES (?, ?) "
+            "ON CONFLICT(key) DO UPDATE SET value = excluded.value",
+            (key, value),
+        )
+
+    @staticmethod
+    def get_dim(conn: sqlite3.Connection) -> int | None:
+        value = IndexMetaTable._get(conn, "dim")
+        return int(value) if value is not None else None
+
+    @staticmethod
+    def set_dim(conn: sqlite3.Connection, dim: int) -> None:
+        IndexMetaTable._set(conn, "dim", str(dim))
+
+    @staticmethod
+    def get_embed_model(conn: sqlite3.Connection) -> str | None:
+        return IndexMetaTable._get(conn, "embed_model")
+
+    @staticmethod
+    def set_embed_model(conn: sqlite3.Connection, name: str) -> None:
+        IndexMetaTable._set(conn, "embed_model", name)
+
+    @staticmethod
+    def get_schema_version(conn: sqlite3.Connection) -> int | None:
+        value = IndexMetaTable._get(conn, "schema_version")
+        return int(value) if value is not None else None
+
+    @staticmethod
+    def set_schema_version(conn: sqlite3.Connection, version: int) -> None:
+        IndexMetaTable._set(conn, "schema_version", str(version))
+
+    @staticmethod
+    def get_total_inserts(conn: sqlite3.Connection) -> int:
+        value = IndexMetaTable._get(conn, "total_inserts")
+        return int(value) if value is not None else 0
+
+    @staticmethod
+    def increment_total_inserts(conn: sqlite3.Connection, count: int) -> None:
+        """Atomically add ``count`` to the stored counter in one statement
+        (INSERT .. ON CONFLICT DO UPDATE with arithmetic), instead of a
+        separate read-then-write -- called once per add()/upsert_document(),
+        so halving the statement count here is a real, if small, per-call
+        saving. index_meta.value has TEXT affinity, so the incremented
+        result is stored as its text representation -- get_total_inserts()
+        already expects that (int(value)), so this is not a behavior
+        change, only fewer statements.
+        """
+        conn.execute(
+            "INSERT INTO index_meta (key, value) VALUES ('total_inserts', ?) "
+            "ON CONFLICT(key) DO UPDATE SET value = "
+            "CAST(index_meta.value AS INTEGER) + CAST(excluded.value AS INTEGER)",
+            (str(count),),
+        )
+
+    @staticmethod
+    def reset_total_inserts(conn: sqlite3.Connection, count: int) -> None:
+        """Set total_inserts to an absolute value -- distinct from
+        increment_total_inserts(): used by compact()'s rebuild and by
+        m0001_v1_to_v2 after copying live rows into a fresh file, where
+        total_inserts must become exactly the live row count, not add to
+        whatever the source file's counter held."""
+        IndexMetaTable._set(conn, "total_inserts", str(count))

src/paperless_ai/tests/test_ai_indexing.py

@@ -1,3 +1,4 @@
+import logging
 from pathlib import Path
 from unittest.mock import MagicMock
 from unittest.mock import patch
@@ -252,6 +253,45 @@ def test_update_llm_index_rebuilds_on_model_name_change(
         assert store.stored_model_name() == "model-b"
 
 
+@pytest.mark.django_db
+def test_update_llm_index_merges_exists_and_config_mismatch_reads(
+    temp_llm_index_dir: Path,
+    real_document: Document,
+    mock_embed_model: FakeEmbedding,
+) -> None:
+    # Build an initial index so the second call's table_exists()/
+    # config_mismatch() checks have something real to check against.
+    with patch("documents.models.Document.objects.all") as mock_all:
+        mock_queryset = MagicMock()
+        mock_queryset.exists.return_value = True
+        mock_queryset.__iter__.return_value = iter([real_document])
+        mock_queryset.select_related.return_value = mock_queryset
+        mock_queryset.prefetch_related.return_value = mock_queryset
+        mock_all.return_value = mock_queryset
+        indexing.update_llm_index(rebuild=True)
+
+    with patch("documents.models.Document.objects.all") as mock_all:
+        mock_queryset = MagicMock()
+        mock_queryset.exists.return_value = True
+        mock_queryset.__iter__.return_value = iter([real_document])
+        mock_queryset.select_related.return_value = mock_queryset
+        mock_queryset.prefetch_related.return_value = mock_queryset
+        mock_all.return_value = mock_queryset
+        with patch(
+            "paperless_ai.indexing.read_store",
+            wraps=indexing.read_store,
+        ) as read_store_spy:
+            indexing.update_llm_index(rebuild=False)
+
+    # Documents exist, so the fast-exit check's `no_documents and ...`
+    # short-circuits before ever calling llm_index_exists() -- the only
+    # read_store() call left in this path is the merged table_exists()/
+    # config_mismatch() check. Before this task's fix, that merged check
+    # was two separate read_store() calls (one inside llm_index_exists(),
+    # one for config_mismatch() right after) -- so this asserts 1, not 2.
+    assert read_store_spy.call_count == 1
+
+
 @pytest.mark.django_db
 def test_update_llm_index_partial_update(
     temp_llm_index_dir: Path,
@@ -737,6 +777,7 @@ class TestLlmIndexLocking:
         mocker: pytest_mock.MockerFixture,
     ) -> None:
         mock_store = MagicMock()
+        mock_store.has_pending_migration.return_value = False
         mocker.patch(
             "paperless_ai.indexing.write_store",
             return_value=mocker.MagicMock(
@@ -757,12 +798,45 @@ class TestLlmIndexLocking:
 
         mock_store.upsert_document.assert_called_once()
 
+    def test_add_or_update_document_skips_write_when_reembed_pending(
+        self,
+        temp_llm_index_dir: Path,
+        mock_embed_model: FakeEmbedding,
+        mocker: pytest_mock.MockerFixture,
+    ) -> None:
+        """A pending re-embed migration must block the incremental write,
+        not let it proceed against a schema that just changed underneath it.
+        """
+        mock_store = MagicMock()
+        mock_store.has_pending_migration.return_value = True
+        mock_store.check_and_run_migrations.return_value = True
+        mocker.patch(
+            "paperless_ai.indexing.write_store",
+            return_value=mocker.MagicMock(
+                __enter__=mocker.MagicMock(return_value=mock_store),
+                __exit__=mocker.MagicMock(return_value=False),
+            ),
+        )
+        mock_node = MagicMock()
+        mock_node.get_content.return_value = "fake node text"
+        mocker.patch(
+            "paperless_ai.indexing.build_document_node",
+            return_value=[mock_node],
+        )
+
+        doc = MagicMock(spec=Document)
+        doc.id = 1
+        indexing.llm_index_add_or_update_document(doc)
+
+        mock_store.upsert_document.assert_not_called()
+
     def test_remove_document_uses_write_store(
         self,
         temp_llm_index_dir: Path,
         mocker: pytest_mock.MockerFixture,
     ) -> None:
         mock_store = MagicMock()
+        mock_store.has_pending_migration.return_value = False
         mocker.patch(
             "paperless_ai.indexing.write_store",
             return_value=mocker.MagicMock(
@@ -777,6 +851,31 @@ class TestLlmIndexLocking:
 
         mock_store.delete.assert_called_once_with("1")
 
+    def test_remove_document_skips_write_when_reembed_pending(
+        self,
+        temp_llm_index_dir: Path,
+        mocker: pytest_mock.MockerFixture,
+    ) -> None:
+        """A pending re-embed migration must block the delete too, for the
+        same consistency reason as the incremental-update path.
+        """
+        mock_store = MagicMock()
+        mock_store.has_pending_migration.return_value = True
+        mock_store.check_and_run_migrations.return_value = True
+        mocker.patch(
+            "paperless_ai.indexing.write_store",
+            return_value=mocker.MagicMock(
+                __enter__=mocker.MagicMock(return_value=mock_store),
+                __exit__=mocker.MagicMock(return_value=False),
+            ),
+        )
+
+        doc = MagicMock(spec=Document)
+        doc.id = 1
+        indexing.llm_index_remove_document(doc)
+
+        mock_store.delete.assert_not_called()
+
     def test_update_llm_index_rebuild_uses_write_store(
         self,
         temp_llm_index_dir: Path,
@@ -849,6 +948,76 @@ class TestVectorStoreIndexing:
             assert rows >= 1
 
 
+class TestLlmIndexMigrate:
+    def test_noop_when_ai_disabled(self, mocker: pytest_mock.MockerFixture) -> None:
+        """
+        GIVEN:
+            - AI/LLM index support is disabled in configuration
+        WHEN:
+            - llm_index_migrate() is called
+        THEN:
+            - No store is opened and no migration check runs
+        """
+        mocker.patch(
+            "paperless_ai.indexing.AIConfig",
+            return_value=mocker.Mock(llm_index_enabled=False),
+        )
+        write_store_mock = mocker.patch("paperless_ai.indexing.write_store")
+        indexing.llm_index_migrate()
+        write_store_mock.assert_not_called()
+
+    def test_runs_pending_migration_when_enabled(
+        self,
+        mocker: pytest_mock.MockerFixture,
+    ) -> None:
+        """
+        GIVEN:
+            - AI/LLM index support is enabled
+        WHEN:
+            - llm_index_migrate() is called
+        THEN:
+            - The store is opened for write and a migration check runs
+        """
+        mocker.patch(
+            "paperless_ai.indexing.AIConfig",
+            return_value=mocker.Mock(llm_index_enabled=True),
+        )
+        store_mock = mocker.MagicMock()
+        store_mock.has_pending_migration.return_value = False
+        write_store_cm = mocker.patch("paperless_ai.indexing.write_store")
+        write_store_cm.return_value.__enter__.return_value = store_mock
+        indexing.llm_index_migrate()
+        store_mock.has_pending_migration.assert_called_once()
+
+    def test_logs_warning_when_reembed_needed(
+        self,
+        mocker: pytest_mock.MockerFixture,
+        caplog: pytest.LogCaptureFixture,
+    ) -> None:
+        """
+        GIVEN:
+            - AI/LLM index support is enabled
+            - A pending migration requires re-embedding
+        WHEN:
+            - llm_index_migrate() is called
+        THEN:
+            - A warning directs the operator to run a manual rebuild, since
+              this automatic check must never re-embed on its own
+        """
+        mocker.patch(
+            "paperless_ai.indexing.AIConfig",
+            return_value=mocker.Mock(llm_index_enabled=True),
+        )
+        store_mock = mocker.MagicMock()
+        store_mock.has_pending_migration.return_value = True
+        store_mock.check_and_run_migrations.return_value = True
+        write_store_cm = mocker.patch("paperless_ai.indexing.write_store")
+        write_store_cm.return_value.__enter__.return_value = store_mock
+        with caplog.at_level(logging.WARNING, logger="paperless_ai.indexing"):
+            indexing.llm_index_migrate()
+        assert "requires re-embedding" in caplog.text
+
+
 @pytest.mark.django_db
 class TestQuerySimilarDocuments:
     def test_query_similar_documents_respects_allowed_ids(

src/paperless_ai/tests/test_tables.py

@@ -0,0 +1,340 @@
+import sqlite3
+from collections.abc import Generator
+
+import pytest
+from pytest_mock import MockerFixture
+
+from paperless_ai.tables import ChunkRow
+from paperless_ai.tables import DocumentChunksTable
+from paperless_ai.tables import DocumentMetaRow
+from paperless_ai.tables import DocumentMetaTable
+from paperless_ai.tables import IndexMetaTable
+
+
+@pytest.fixture
+def conn() -> Generator[sqlite3.Connection, None, None]:
+    connection = sqlite3.connect(":memory:")
+    connection.row_factory = sqlite3.Row
+    try:
+        yield connection
+    finally:
+        connection.close()
+
+
+class TestDocumentChunksTable:
+    def test_create_is_idempotent(self, conn: sqlite3.Connection) -> None:
+        """
+        GIVEN:
+            - A bare sqlite3 connection
+        WHEN:
+            - create() is called, a row is inserted, then create() is called again
+        THEN:
+            - No error is raised and the row survives uncorrupted
+        """
+        DocumentChunksTable.create(conn)
+        DocumentChunksTable.insert_many(conn, [ChunkRow("c1", 1)])
+        DocumentChunksTable.create(conn)
+        assert DocumentChunksTable.chunk_ids_for_document(conn, 1) == ["c1"]
+
+    def test_insert_many_then_lookup_by_document_id(
+        self,
+        conn: sqlite3.Connection,
+    ) -> None:
+        """
+        GIVEN:
+            - An empty document_chunks table
+        WHEN:
+            - Two chunks for document 1 and one for document 2 are inserted
+        THEN:
+            - chunk_ids_for_document returns exactly the matching chunk ids
+        """
+        DocumentChunksTable.create(conn)
+        DocumentChunksTable.insert_many(
+            conn,
+            [ChunkRow("c1", 1), ChunkRow("c2", 1), ChunkRow("c3", 2)],
+        )
+        assert sorted(DocumentChunksTable.chunk_ids_for_document(conn, 1)) == [
+            "c1",
+            "c2",
+        ]
+        assert DocumentChunksTable.chunk_ids_for_document(conn, 2) == ["c3"]
+        assert DocumentChunksTable.chunk_ids_for_document(conn, 999) == []
+
+    def test_delete_for_document_removes_only_that_document(
+        self,
+        conn: sqlite3.Connection,
+    ) -> None:
+        """
+        GIVEN:
+            - Chunks for two different documents
+        WHEN:
+            - delete_for_document() is called for one of them
+        THEN:
+            - Only that document's chunks are removed
+        """
+        DocumentChunksTable.create(conn)
+        DocumentChunksTable.insert_many(
+            conn,
+            [ChunkRow("c1", 1), ChunkRow("c2", 2)],
+        )
+        DocumentChunksTable.delete_for_document(conn, 1)
+        assert DocumentChunksTable.chunk_ids_for_document(conn, 1) == []
+        assert DocumentChunksTable.chunk_ids_for_document(conn, 2) == ["c2"]
+
+    def test_delete_all_clears_every_row(self, conn: sqlite3.Connection) -> None:
+        """
+        GIVEN:
+            - Chunks for multiple documents
+        WHEN:
+            - delete_all() is called
+        THEN:
+            - count() returns 0
+        """
+        DocumentChunksTable.create(conn)
+        DocumentChunksTable.insert_many(
+            conn,
+            [ChunkRow("c1", 1), ChunkRow("c2", 2)],
+        )
+        DocumentChunksTable.delete_all(conn)
+        assert DocumentChunksTable.count(conn) == 0
+
+    def test_count_reflects_live_rows(self, conn: sqlite3.Connection) -> None:
+        """
+        GIVEN:
+            - An empty document_chunks table
+        WHEN:
+            - Rows are inserted then one document's rows are deleted
+        THEN:
+            - count() reflects the remaining row count
+        """
+        DocumentChunksTable.create(conn)
+        DocumentChunksTable.insert_many(
+            conn,
+            [ChunkRow("c1", 1), ChunkRow("c2", 1), ChunkRow("c3", 2)],
+        )
+        assert DocumentChunksTable.count(conn) == 3
+        DocumentChunksTable.delete_for_document(conn, 1)
+        assert DocumentChunksTable.count(conn) == 1
+
+
+class TestDocumentMetaTable:
+    def test_upsert_many_then_all_modified_times(
+        self,
+        conn: sqlite3.Connection,
+    ) -> None:
+        """
+        GIVEN:
+            - An empty document_meta table
+        WHEN:
+            - Two documents' modified timestamps are upserted
+        THEN:
+            - all_modified_times() returns both, keyed by str(document_id)
+        """
+        DocumentMetaTable.create(conn)
+        DocumentMetaTable.upsert_many(
+            conn,
+            [
+                DocumentMetaRow(1, "2026-01-01T00:00:00"),
+                DocumentMetaRow(2, "2026-02-02T00:00:00"),
+            ],
+        )
+        assert DocumentMetaTable.all_modified_times(conn) == {
+            "1": "2026-01-01T00:00:00",
+            "2": "2026-02-02T00:00:00",
+        }
+
+    def test_upsert_many_overwrites_existing_value(
+        self,
+        conn: sqlite3.Connection,
+    ) -> None:
+        """
+        GIVEN:
+            - A document_meta row for document 1
+        WHEN:
+            - upsert_many() is called again with a new modified value for
+              the same document_id
+        THEN:
+            - The stored value is replaced, not duplicated
+        """
+        DocumentMetaTable.create(conn)
+        DocumentMetaTable.upsert_many(conn, [DocumentMetaRow(1, "old")])
+        DocumentMetaTable.upsert_many(conn, [DocumentMetaRow(1, "new")])
+        assert DocumentMetaTable.all_modified_times(conn) == {"1": "new"}
+
+    def test_delete_for_document_removes_only_that_row(
+        self,
+        conn: sqlite3.Connection,
+    ) -> None:
+        """
+        GIVEN:
+            - document_meta rows for two documents
+        WHEN:
+            - delete_for_document() is called for one of them
+        THEN:
+            - Only that document's row is removed
+        """
+        DocumentMetaTable.create(conn)
+        DocumentMetaTable.upsert_many(
+            conn,
+            [DocumentMetaRow(1, "a"), DocumentMetaRow(2, "b")],
+        )
+        DocumentMetaTable.delete_for_document(conn, 1)
+        assert DocumentMetaTable.all_modified_times(conn) == {"2": "b"}
+
+    def test_delete_all_clears_every_row(self, conn: sqlite3.Connection) -> None:
+        """
+        GIVEN:
+            - document_meta rows for multiple documents
+        WHEN:
+            - delete_all() is called
+        THEN:
+            - all_modified_times() returns an empty dict
+        """
+        DocumentMetaTable.create(conn)
+        DocumentMetaTable.upsert_many(
+            conn,
+            [DocumentMetaRow(1, "a"), DocumentMetaRow(2, "b")],
+        )
+        DocumentMetaTable.delete_all(conn)
+        assert DocumentMetaTable.all_modified_times(conn) == {}
+
+    def test_copy_all_streams_every_row_to_destination(
+        self,
+        conn: sqlite3.Connection,
+    ) -> None:
+        """
+        GIVEN:
+            - A source connection with document_meta rows for 5 documents
+            - A separate, empty destination connection
+        WHEN:
+            - copy_all() is called with a batch size smaller than the row
+              count, forcing multiple fetchmany() cycles
+        THEN:
+            - Every row is present on the destination connection
+        """
+        DocumentMetaTable.create(conn)
+        DocumentMetaTable.upsert_many(
+            conn,
+            [DocumentMetaRow(i, f"modified-{i}") for i in range(5)],
+        )
+        dst_conn = sqlite3.connect(":memory:")
+        dst_conn.row_factory = sqlite3.Row
+        try:
+            DocumentMetaTable.create(dst_conn)
+            DocumentMetaTable.copy_all(conn, dst_conn, batch_size=2)
+            assert DocumentMetaTable.all_modified_times(dst_conn) == {
+                str(i): f"modified-{i}" for i in range(5)
+            }
+        finally:
+            dst_conn.close()
+
+
+class TestIndexMetaTable:
+    @pytest.mark.parametrize(
+        ("setter_name", "getter_name", "value"),
+        [
+            ("set_dim", "get_dim", 384),
+            ("set_embed_model", "get_embed_model", "model-a"),
+            ("set_schema_version", "get_schema_version", 2),
+        ],
+    )
+    def test_typed_accessor_roundtrip(
+        self,
+        conn: sqlite3.Connection,
+        setter_name: str,
+        getter_name: str,
+        value: int | str,
+    ) -> None:
+        """
+        GIVEN:
+            - An empty index_meta table
+        WHEN:
+            - A typed accessor's setter is called then the getter is read back
+        THEN:
+            - The same value is returned, correctly typed (int or str)
+        """
+        IndexMetaTable.create(conn)
+        getter = getattr(IndexMetaTable, getter_name)
+        setter = getattr(IndexMetaTable, setter_name)
+        assert getter(conn) is None
+        setter(conn, value)
+        assert getter(conn) == value
+
+    def test_total_inserts_starts_at_zero(self, conn: sqlite3.Connection) -> None:
+        """
+        GIVEN:
+            - An empty index_meta table
+        WHEN:
+            - get_total_inserts() is read before anything is set
+        THEN:
+            - 0 is returned
+        """
+        IndexMetaTable.create(conn)
+        assert IndexMetaTable.get_total_inserts(conn) == 0
+
+    def test_increment_total_inserts_accumulates(
+        self,
+        conn: sqlite3.Connection,
+    ) -> None:
+        """
+        GIVEN:
+            - An empty index_meta table
+        WHEN:
+            - increment_total_inserts() is called twice
+        THEN:
+            - get_total_inserts() returns the running sum
+        """
+        IndexMetaTable.create(conn)
+        IndexMetaTable.increment_total_inserts(conn, 5)
+        IndexMetaTable.increment_total_inserts(conn, 3)
+        assert IndexMetaTable.get_total_inserts(conn) == 8
+
+    def test_increment_total_inserts_is_a_single_statement(
+        self,
+        mocker: MockerFixture,
+    ) -> None:
+        """
+        GIVEN:
+            - An empty index_meta table
+        WHEN:
+            - increment_total_inserts() is called
+        THEN:
+            - Exactly one conn.execute() call is made (a single INSERT ...
+              ON CONFLICT DO UPDATE, not a separate read then write)
+        """
+
+        # sqlite3.Connection is an immutable C extension type with no
+        # instance __dict__, so mocker.spy(conn, "execute") can't shadow
+        # "execute" on a plain connection ("attribute 'execute' is
+        # read-only"). A trivial Python subclass gets a normal instance
+        # __dict__, making the instance spyable while still being a real,
+        # usable sqlite3.Connection.
+        class _SpyableConnection(sqlite3.Connection):
+            pass
+
+        conn = sqlite3.connect(":memory:", factory=_SpyableConnection)
+        try:
+            conn.row_factory = sqlite3.Row
+            IndexMetaTable.create(conn)
+            execute_spy = mocker.spy(conn, "execute")
+            IndexMetaTable.increment_total_inserts(conn, 5)
+            assert execute_spy.call_count == 1
+        finally:
+            conn.close()
+
+    def test_reset_total_inserts_sets_absolute_value(
+        self,
+        conn: sqlite3.Connection,
+    ) -> None:
+        """
+        GIVEN:
+            - A total_inserts counter already at a high value
+        WHEN:
+            - reset_total_inserts() is called with a lower value
+        THEN:
+            - get_total_inserts() returns exactly that value, not a sum
+        """
+        IndexMetaTable.create(conn)
+        IndexMetaTable.increment_total_inserts(conn, 100)
+        IndexMetaTable.reset_total_inserts(conn, 7)
+        assert IndexMetaTable.get_total_inserts(conn) == 7

src/paperless_ai/tests/test_vector_store.py

@@ -8,21 +8,23 @@ from llama_index.core.vector_stores.types import FilterOperator
 from llama_index.core.vector_stores.types import MetadataFilter
 from llama_index.core.vector_stores.types import MetadataFilters
 from llama_index.core.vector_stores.types import VectorStoreQuery
+from pytest_mock import MockerFixture
 
+from paperless_ai.migrations import MIGRATIONS
+from paperless_ai.migrations import Migration
 from paperless_ai.vector_store import DB_FILENAME
 from paperless_ai.vector_store import DEFAULT_TABLE_NAME
-from paperless_ai.vector_store import MIGRATIONS
 from paperless_ai.vector_store import SCHEMA_VERSION
-from paperless_ai.vector_store import Migration
 from paperless_ai.vector_store import PaperlessSqliteVecVectorStore
 from paperless_ai.vector_store import _build_where
+from paperless_ai.vector_store import _pack
 
 DIM = 16
 
 
 def make_node(
     node_id: str,
-    document_id: str,
+    document_id: int,
     *,
     modified: str = "2026-06-10T00:00:00",
     seed: float = 0.0,
@@ -59,13 +61,13 @@ def _query(
     )
 
 
-def _eq_filter(key: str, value: str):
+def _eq_filter(key: str, value: int):
     return MetadataFilters(
         filters=[MetadataFilter(key=key, operator=FilterOperator.EQ, value=value)],
     )
 
 
-def _in_filter(document_ids: list[str]):
+def _in_filter(document_ids: list[int]):
     return MetadataFilters(
         filters=[
             MetadataFilter(
@@ -77,7 +79,7 @@ def _in_filter(document_ids: list[str]):
     )
 
 
-def _ne_filter(document_id: str):
+def _ne_filter(document_id: int):
     return MetadataFilters(
         filters=[
             MetadataFilter(
@@ -91,11 +93,11 @@ def _ne_filter(document_id: str):
 
 class TestCrud:
     def test_add_then_query_returns_node(self, store) -> None:
-        node = make_node("n1", "1")
+        node = make_node("n1", 1)
         assert store.add([node]) == ["n1"]
         result = _query(store, node.embedding, top_k=1)
         assert result.ids == ["n1"]
-        assert result.nodes[0].metadata["document_id"] == "1"
+        assert result.nodes[0].metadata["document_id"] == 1
         # cosine distance of the identical vector is 0 -> similarity 1
         assert result.similarities[0] == pytest.approx(1.0)
 
@@ -108,58 +110,58 @@ class TestCrud:
         assert not store.table_exists()
 
     def test_delete_removes_all_chunks_of_document(self, store) -> None:
-        store.add([make_node("a1", "1"), make_node("a2", "1"), make_node("b1", "2")])
+        store.add([make_node("a1", 1), make_node("a2", 1), make_node("b1", 2)])
-        store.delete("1")
+        store.delete(1)
         result = _query(store, [0.0] * DIM, top_k=10)
         assert result.ids == ["b1"]
 
     def test_query_with_in_filter_scopes_results(self, store) -> None:
         store.add(
             [
-                make_node("a1", "1", seed=0.0),
+                make_node("a1", 1, seed=0.0),
-                make_node("b1", "2", seed=1.0),
+                make_node("b1", 2, seed=1.0),
-                make_node("c1", "3", seed=2.0),
+                make_node("c1", 3, seed=2.0),
             ],
         )
-        result = _query(store, [0.0] * DIM, top_k=10, filters=_in_filter(["2", "3"]))
+        result = _query(store, [0.0] * DIM, top_k=10, filters=_in_filter([2, 3]))
         assert sorted(result.ids) == ["b1", "c1"]
 
     def test_query_respects_top_k_with_filter(self, store) -> None:
         # k semantics: global top-k even with IN filters (document_id is a
         # metadata column, not a partition key -- see design doc).
         store.add(
-            [make_node(f"n{i}", str(i % 4), seed=float(i)) for i in range(12)],
+            [make_node(f"n{i}", i % 4, seed=float(i)) for i in range(12)],
         )
         result = _query(
             store,
             [0.0] * DIM,
             top_k=3,
-            filters=_in_filter(["0", "1", "2", "3"]),
+            filters=_in_filter([0, 1, 2, 3]),
         )
         assert len(result.ids) == 3
         assert result.similarities == sorted(result.similarities, reverse=True)
 
     def test_get_nodes_filter_and_empty_paths(self, store) -> None:
-        assert store.get_nodes(filters=_in_filter(["1"])) == []  # no table yet
+        assert store.get_nodes(filters=_in_filter([1])) == []  # no table yet
-        store.add([make_node("a1", "1"), make_node("b1", "2")])
+        store.add([make_node("a1", 1), make_node("b1", 2)])
-        nodes = store.get_nodes(filters=_in_filter(["1"]))
+        nodes = store.get_nodes(filters=_in_filter([1]))
         assert [n.node_id for n in nodes] == ["a1"]
         assert nodes[0].embedding is not None
-        assert store.get_nodes(filters=_in_filter(["999"])) == []
+        assert store.get_nodes(filters=_in_filter([999])) == []
 
     def test_query_with_eq_filter_scopes_results(self, store) -> None:
         store.add(
             [
-                make_node("a1", "1", seed=0.0),
+                make_node("a1", 1, seed=0.0),
-                make_node("b1", "2", seed=1.0),
+                make_node("b1", 2, seed=1.0),
-                make_node("c1", "3", seed=2.0),
+                make_node("c1", 3, seed=2.0),
             ],
         )
         result = _query(
             store,
             [0.0] * DIM,
             top_k=10,
-            filters=_eq_filter("document_id", "2"),
+            filters=_eq_filter("document_id", 2),
         )
         assert result.ids == ["b1"]
 
@@ -168,7 +170,7 @@ class TestCrud:
             store.get_nodes(node_ids=["x"])
 
     def test_fresh_instance_sees_existing_table(self, store, tmp_path: Path) -> None:
-        store.add([make_node("a1", "1")])
+        store.add([make_node("a1", 1)])
         with PaperlessSqliteVecVectorStore(uri=str(tmp_path)) as reopened:
             assert reopened.table_exists()
             assert reopened.vector_dim() == DIM
@@ -176,23 +178,98 @@ class TestCrud:
 
     def test_table_exists_and_drop(self, store) -> None:
         assert not store.table_exists()
-        store.add([make_node("a1", "1")])
+        store.add([make_node("a1", 1)])
         assert store.table_exists()
         store.drop_table()
         assert not store.table_exists()
         assert store.vector_dim() is None
 
+    def test_document_id_stored_as_integer_in_vec0(
+        self,
+        store: PaperlessSqliteVecVectorStore,
+    ) -> None:
+        """
+        GIVEN:
+            - An empty vector store
+        WHEN:
+            - A node is added with an int document_id
+        THEN:
+            - vec0's own document_id column holds an INTEGER, not TEXT
+        """
+        store.add([make_node("a1", 1)])
+        row = store.client.execute(
+            "SELECT document_id FROM documents WHERE id = 'a1'",
+        ).fetchone()
+        assert isinstance(row["document_id"], int)
+
+    def test_drop_table_clears_modified_times(
+        self,
+        store: PaperlessSqliteVecVectorStore,
+    ) -> None:
+        """
+        GIVEN:
+            - A store with a tracked document's modified time
+        WHEN:
+            - drop_table() is called
+        THEN:
+            - document_meta and document_chunks are both cleared directly
+              (asserted against the tables themselves, not via
+              get_modified_times()/table_exists() -- those short-circuit on
+              the vec0 table being gone, which drop_table() does first, so
+              they would pass even if DocumentMetaTable.delete_all()/
+              DocumentChunksTable.delete_all() were never called)
+        """
+        store.add([make_node("a1", 1)])
+        store.drop_table()
+        assert (
+            store.client.execute(
+                "SELECT count(*) FROM document_meta",
+            ).fetchone()[0]
+            == 0
+        )
+        assert (
+            store.client.execute(
+                "SELECT count(*) FROM document_chunks",
+            ).fetchone()[0]
+            == 0
+        )
+
+    def test_upsert_document_checks_table_exists_once(
+        self,
+        store: PaperlessSqliteVecVectorStore,
+        mocker: MockerFixture,
+    ) -> None:
+        """
+        GIVEN:
+            - An existing store with one document already indexed
+        WHEN:
+            - upsert_document() replaces that document's chunks
+        THEN:
+            - table_exists() is queried at most once per call, not twice
+              (previously: once via _ensure_table(), once via the separate
+              `if self.table_exists():` delete-chunks guard)
+        """
+        store.add([make_node("a1", 1)])
+        # store is a pydantic model, whose __setattr__/__delattr__ reject
+        # arbitrary instance attributes ("object has no attribute
+        # 'table_exists'"), so mocker.spy(store, "table_exists") can't
+        # shadow the method on the instance. Spying on the class works
+        # (bound method lookup on the instance still resolves through it).
+        exists_spy = mocker.spy(PaperlessSqliteVecVectorStore, "table_exists")
+        store.upsert_document(1, [make_node("a2", 1)])
+        assert exists_spy.call_count == 1
+
 
 class TestBuildWhere:
     def test_ne_filter_translates_to_not_equal_clause(self) -> None:
-        where, params = _build_where(_ne_filter("1"))
+        where, params = _build_where(_ne_filter(1))
         assert where == "(document_id != ?)"
-        assert params == ["1"]
+        assert params == [1]
 
     def test_query_with_ne_filter_excludes_matching_document(self, store) -> None:
-        store.add([make_node("a1", "1"), make_node("b1", "2")])
+        store.add([make_node("a1", 1), make_node("b1", 2)])
         assert sorted(
-            _query(store, [0.0] * DIM, top_k=5, filters=_ne_filter("1")).ids,
+            _query(store, [0.0] * DIM, top_k=5, filters=_ne_filter(1)).ids,
         ) == [
             "b1",
         ]
@@ -206,7 +283,7 @@ class TestBuildWhere:
                 MetadataFilter(
                     key="document_id",
                     operator=FilterOperator.EQ,
-                    value="1",
+                    value=1,
                 ),
             ],
         )
@@ -215,13 +292,13 @@ class TestBuildWhere:
         assert params == []
 
     def test_query_with_untranslatable_filter_returns_no_rows(self, store) -> None:
-        store.add([make_node("a1", "1"), make_node("b1", "2")])
+        store.add([make_node("a1", 1), make_node("b1", 2)])
         nested = MetadataFilters(
             filters=[
                 MetadataFilter(
                     key="document_id",
                     operator=FilterOperator.EQ,
-                    value="1",
+                    value=1,
                 ),
             ],
         )
@@ -234,19 +311,19 @@ class TestBuildWhere:
 class TestUpsert:
     def test_upsert_replaces_and_prunes_stale_chunks(self, store) -> None:
         store.add(
-            [make_node("d1c1", "1"), make_node("d1c2", "1"), make_node("d2c1", "2")],
+            [make_node("d1c1", 1), make_node("d1c2", 1), make_node("d2c1", 2)],
         )
-        store.upsert_document("1", [make_node("d1new", "1")])
+        store.upsert_document(1, [make_node("d1new", 1)])
         result = _query(store, [0.0] * DIM, top_k=10)
         assert sorted(result.ids) == ["d1new", "d2c1"]
 
     def test_upsert_creates_table_when_missing(self, store) -> None:
-        store.upsert_document("1", [make_node("a1", "1")])
+        store.upsert_document(1, [make_node("a1", 1)])
         assert _query(store, [0.0] * DIM, top_k=1).ids == ["a1"]
 
     def test_upsert_empty_nodes_removes_document(self, store) -> None:
-        store.add([make_node("a1", "1"), make_node("b1", "2")])
+        store.add([make_node("a1", 1), make_node("b1", 2)])
-        store.upsert_document("1", [])
+        store.upsert_document(1, [])
         assert _query(store, [0.0] * DIM, top_k=10).ids == ["b1"]
 
     def test_upsert_is_atomic_for_concurrent_readers(
@@ -255,16 +332,16 @@ class TestUpsert:
         tmp_path: Path,
     ) -> None:
         """A second connection must never observe document 1 half-replaced."""
-        store.add([make_node("a1", "1"), make_node("a2", "1")])
+        store.add([make_node("a1", 1), make_node("a2", 1)])
         with PaperlessSqliteVecVectorStore(uri=str(tmp_path)) as reader:
-            store.upsert_document("1", [make_node("a3", "1")])
+            store.upsert_document(1, [make_node("a3", 1)])
-            ids = [n.node_id for n in reader.get_nodes(filters=_in_filter(["1"]))]
+            ids = [n.node_id for n in reader.get_nodes(filters=_in_filter([1]))]
             assert ids == ["a3"]
 
 
 class TestMetadataCoercion:
     def test_none_metadata_values_become_empty_strings(self, store) -> None:
-        node = make_node("a1", "1")
+        node = make_node("a1", 1)
         node.metadata["modified"] = None
         store.add([node])  # must not raise (vec0 rejects NULL metadata)
         assert store.get_modified_times() == {"1": ""}
@@ -283,7 +360,7 @@ class TestModelNameTracking:
             uri=str(tmp_path),
             embed_model_name="model-a",
         ) as store:
-            store.add([make_node("a1", "1")])
+            store.add([make_node("a1", 1)])
             assert store.stored_model_name() == "model-a"
         with PaperlessSqliteVecVectorStore(uri=str(tmp_path)) as reopened:
             assert reopened.stored_model_name() == "model-a"
@@ -294,7 +371,7 @@ class TestModelNameTracking:
             embed_model_name="model-a",
         ) as store:
             assert not store.config_mismatch("anything")  # no table yet
-            store.add([make_node("a1", "1")])
+            store.add([make_node("a1", 1)])
             assert not store.config_mismatch("model-a")
             assert store.config_mismatch("model-b")
 
@@ -303,7 +380,7 @@ class TestModelNameTracking:
         tmp_path: Path,
     ) -> None:
         with PaperlessSqliteVecVectorStore(uri=str(tmp_path)) as store:  # no model name
-            store.add([make_node("a1", "1")])
+            store.add([make_node("a1", 1)])
             assert not store.config_mismatch("model-a")
 
 
@@ -314,9 +391,9 @@ class TestGetModifiedTimes:
     def test_returns_one_entry_per_document(self, store) -> None:
         store.add(
             [
-                make_node("a1", "1", modified="2026-01-01T00:00:00"),
+                make_node("a1", 1, modified="2026-01-01T00:00:00"),
-                make_node("a2", "1", modified="2026-01-01T00:00:00"),
+                make_node("a2", 1, modified="2026-01-01T00:00:00"),
-                make_node("b1", "2", modified="2026-02-02T00:00:00"),
+                make_node("b1", 2, modified="2026-02-02T00:00:00"),
             ],
         )
         assert store.get_modified_times() == {
@@ -341,37 +418,35 @@ class TestCompact:
     def _churn(self, store, cycles: int) -> None:
         for i in range(cycles):
             store.upsert_document(
-                "1",
+                1,
-                [make_node(f"gen{i}-{j}", "1", seed=float(j)) for j in range(20)],
+                [make_node(f"gen{i}-{j}", 1, seed=float(j)) for j in range(20)],
             )
 
     def test_compact_noop_below_threshold(self, store) -> None:
-        store.add([make_node("a1", "1")])
+        store.add([make_node("a1", 1)])
         store.compact()
         assert _query(store, [0.0] * DIM, top_k=1).ids == ["a1"]
 
     def test_force_compact_preserves_rows_and_metadata(self, store) -> None:
-        store.add([make_node("a1", "1"), make_node("b1", "2", seed=3.0)])
+        store.add([make_node("a1", 1), make_node("b1", 2, seed=3.0)])
         self._churn(store, 5)
         before = {
-            n.node_id: n.metadata
+            n.node_id: n.metadata for n in store.get_nodes(filters=_in_filter([1, 2]))
-            for n in store.get_nodes(filters=_in_filter(["1", "2"]))
         }
         store.compact(force=True)
         after = {
-            n.node_id: n.metadata
+            n.node_id: n.metadata for n in store.get_nodes(filters=_in_filter([1, 2]))
-            for n in store.get_nodes(filters=_in_filter(["1", "2"]))
         }
         assert after == before
         assert self._bloat_ratio(store) == pytest.approx(1.0)
         # store remains fully usable after the rebuild; use a seed far from all
         # existing nodes (gen4-0..gen4-19 have seeds 0..19) so cosine KNN is
         # unambiguous at top_k=1.
-        store.upsert_document("3", [make_node("c1", "3", seed=100.0)])
+        store.upsert_document(3, [make_node("c1", 3, seed=100.0)])
         assert "c1" in _query(store, [100.0] * DIM, top_k=1).ids
 
     def test_auto_compact_triggers_on_churn(self, store) -> None:
-        store.add([make_node(f"s{j}", "1", seed=float(j)) for j in range(20)])
+        store.add([make_node(f"s{j}", 1, seed=float(j)) for j in range(20)])
         self._churn(store, 5)
         assert self._bloat_ratio(store) > 2
         store.compact()
@@ -393,7 +468,7 @@ class TestCompact:
         but a concurrent reader keeps -wal/-shm alive, so the cleanup must
         unlink them explicitly (as the structural-migration path does).
         """
-        store.add([make_node("a1", "1")])
+        store.add([make_node("a1", 1)])
         compact_path = str(tmp_path / DB_FILENAME) + ".compact"
         held: list[sqlite3.Connection] = []
 
@@ -429,16 +504,40 @@ class TestCompact:
         regression in the streaming loop (dropped tail, off-by-one) surfaces.
         """
         monkeypatch.setattr("paperless_ai.vector_store.COMPACT_BATCH_SIZE", 3)
-        store.add([make_node(f"n{i}", "1", seed=float(i)) for i in range(10)])
+        store.add([make_node(f"n{i}", 1, seed=float(i)) for i in range(10)])
         store.compact(force=True)
-        ids = {n.node_id for n in store.get_nodes(filters=_in_filter(["1"]))}
+        ids = {n.node_id for n in store.get_nodes(filters=_in_filter([1]))}
         assert ids == {f"n{i}" for i in range(10)}
         assert self._bloat_ratio(store) == pytest.approx(1.0)
 
+    def test_force_compact_preserves_modified_times(
+        self,
+        store: PaperlessSqliteVecVectorStore,
+    ) -> None:
+        """
+        GIVEN:
+            - A store with documents whose modified times are tracked
+        WHEN:
+            - compact(force=True) rebuilds the database file
+        THEN:
+            - get_modified_times() still returns every document's value
+              (document_meta must be copied across the file-swap, not just
+              the vec0 rows)
+        """
+        store.add(
+            [
+                make_node("a1", 1, modified="2026-01-01T00:00:00"),
+                make_node("b1", 2, modified="2026-02-02T00:00:00"),
+            ],
+        )
+        before = store.get_modified_times()
+        store.compact(force=True)
+        assert store.get_modified_times() == before
+
 
 class TestDbFile:
     def test_single_db_file_in_index_dir(self, store, tmp_path: Path) -> None:
-        store.add([make_node("a1", "1")])
+        store.add([make_node("a1", 1)])
         assert (tmp_path / DB_FILENAME).exists()
 
     def test_wal_mode_enabled(self, store) -> None:
@@ -448,7 +547,16 @@ class TestDbFile:
 
 
 class TestMigrations:
-    """Tests for the schema migration machinery."""
+    """Tests for the schema migration machinery.
+
+    These tests exercise check_and_run_migrations()'s generic dispatch logic
+    (structural vs. re-embed, version-boundary stopping) using ad hoc test
+    migrations layered on top of SCHEMA_VERSION -- distinct from
+    TestV1ToV2Migration, which exercises the real, frozen m0001_v1_to_v2
+    migration. Test migrations use version numbers starting at
+    SCHEMA_VERSION (2) and above so they never collide with the real
+    from_version=1/to_version=2 migration already registered in MIGRATIONS.
+    """
 
     def _schema_version(self, store: PaperlessSqliteVecVectorStore) -> int | None:
         row = store.client.execute(
@@ -457,21 +565,21 @@ class TestMigrations:
         return int(row[0]) if row else None
 
     def test_new_table_records_schema_version(self, store) -> None:
-        store.add([make_node("a1", "1")])
+        store.add([make_node("a1", 1)])
         assert self._schema_version(store) == SCHEMA_VERSION
 
     def test_check_migrations_no_table_returns_false(self, store) -> None:
         assert store.check_and_run_migrations() is False
 
     def test_check_migrations_current_version_returns_false(self, store) -> None:
-        store.add([make_node("a1", "1")])
+        store.add([make_node("a1", 1)])
         assert store.check_and_run_migrations() is False
 
     def test_reembed_migration_returns_true(self, store, tmp_path: Path) -> None:
-        store.add([make_node("a1", "1")])
+        store.add([make_node("a1", 1)])
         migration = Migration(
-            from_version=1,
+            from_version=SCHEMA_VERSION,
-            to_version=2,
+            to_version=SCHEMA_VERSION + 1,
             kind="re-embed",
             description="test re-embed",
         )
@@ -480,7 +588,7 @@ class TestMigrations:
             from paperless_ai import vector_store as vs_mod
 
             original = vs_mod.SCHEMA_VERSION
-            vs_mod.SCHEMA_VERSION = 2
+            vs_mod.SCHEMA_VERSION = SCHEMA_VERSION + 1
             result = store.check_and_run_migrations()
         finally:
             MIGRATIONS.remove(migration)
@@ -492,7 +600,7 @@ class TestMigrations:
         store,
         tmp_path: Path,
     ) -> None:
-        store.add([make_node("a1", "1"), make_node("b1", "2")])
+        store.add([make_node("a1", 1), make_node("b1", 2)])
 
         def apply(
             src: sqlite3.Connection,
@@ -511,7 +619,7 @@ class TestMigrations:
                 (str(dim),),
             )
             rows = src.execute(
-                "SELECT id, document_id, modified, node_content, embedding "
+                "SELECT id, document_id, node_content, embedding "
                 f"FROM {DEFAULT_TABLE_NAME}",
             ).fetchall()
             dst.execute("BEGIN IMMEDIATE")
@@ -522,8 +630,8 @@ class TestMigrations:
                 [
                     (
                         r["id"],
-                        r["document_id"],
+                        str(r["document_id"]),
-                        r["modified"],
+                        "",
                         r["node_content"],
                         bytes(r["embedding"]),
                     )
@@ -538,8 +646,8 @@ class TestMigrations:
             dst.execute("COMMIT")
 
         migration = Migration(
-            from_version=1,
+            from_version=SCHEMA_VERSION,
-            to_version=2,
+            to_version=SCHEMA_VERSION + 1,
             kind="structural",
             description="test structural",
             apply=apply,
@@ -549,28 +657,29 @@ class TestMigrations:
             from paperless_ai import vector_store as vs_mod
 
             original = vs_mod.SCHEMA_VERSION
-            vs_mod.SCHEMA_VERSION = 2
+            vs_mod.SCHEMA_VERSION = SCHEMA_VERSION + 1
             result = store.check_and_run_migrations()
         finally:
             MIGRATIONS.remove(migration)
             vs_mod.SCHEMA_VERSION = original
 
         assert result is False
-        assert self._schema_version(store) == 2
+        assert self._schema_version(store) == SCHEMA_VERSION + 1
         ids = {n.node_id for n in store.get_nodes()}
         assert ids == {"a1", "b1"}
 
     def test_compact_preserves_schema_version(self, store) -> None:
-        store.add([make_node("a1", "1")])
+        store.add([make_node("a1", 1)])
         assert self._schema_version(store) == SCHEMA_VERSION
         store.compact(force=True)
         assert self._schema_version(store) == SCHEMA_VERSION
 
     def test_stop_at_reembed_boundary(self, store) -> None:
-        # Registry: structural v2, re-embed v3, structural v4.
+        # Registry: structural v(N+1), re-embed v(N+2), structural v(N+3),
-        # Only v2 should apply; the re-embed boundary must stop execution
+        # where N = SCHEMA_VERSION. Only v(N+1) should apply; the re-embed
-        # before v4 runs, and the stored version must stay at 2.
+        # boundary must stop execution before v(N+3) runs, and the stored
-        store.add([make_node("a1", "1"), make_node("b1", "2")])
+        # version must stay at N+1.
+        store.add([make_node("a1", 1), make_node("b1", 2)])
 
         def copy_apply(
             src: sqlite3.Connection,
@@ -589,7 +698,7 @@ class TestMigrations:
                 (str(dim),),
             )
             rows = src.execute(
-                "SELECT id, document_id, modified, node_content, embedding "
+                "SELECT id, document_id, node_content, embedding "
                 f"FROM {DEFAULT_TABLE_NAME}",
             ).fetchall()
             dst.execute("BEGIN IMMEDIATE")
@@ -600,8 +709,8 @@ class TestMigrations:
                 [
                     (
                         r["id"],
-                        r["document_id"],
+                        str(r["document_id"]),
-                        r["modified"],
+                        "",
                         r["node_content"],
                         bytes(r["embedding"]),
                     )
@@ -612,23 +721,23 @@ class TestMigrations:
 
         migrations = [
             Migration(
-                from_version=1,
+                from_version=SCHEMA_VERSION,
-                to_version=2,
+                to_version=SCHEMA_VERSION + 1,
                 kind="structural",
-                description="v2 structural",
+                description="v(N+1) structural",
                 apply=copy_apply,
             ),
             Migration(
-                from_version=2,
+                from_version=SCHEMA_VERSION + 1,
-                to_version=3,
+                to_version=SCHEMA_VERSION + 2,
                 kind="re-embed",
-                description="v3 re-embed boundary",
+                description="v(N+2) re-embed boundary",
             ),
             Migration(
-                from_version=3,
+                from_version=SCHEMA_VERSION + 2,
-                to_version=4,
+                to_version=SCHEMA_VERSION + 3,
                 kind="structural",
-                description="v4 structural - must not run",
+                description="v(N+3) structural - must not run",
                 apply=copy_apply,
             ),
         ]
@@ -637,7 +746,7 @@ class TestMigrations:
             from paperless_ai import vector_store as vs_mod
 
             original = vs_mod.SCHEMA_VERSION
-            vs_mod.SCHEMA_VERSION = 4
+            vs_mod.SCHEMA_VERSION = SCHEMA_VERSION + 3
             result = store.check_and_run_migrations()
         finally:
             for m in migrations:
@@ -645,4 +754,237 @@ class TestMigrations:
             vs_mod.SCHEMA_VERSION = original
 
         assert result is True
-        assert self._schema_version(store) == 2
+        assert self._schema_version(store) == SCHEMA_VERSION + 1
+
+    def test_has_pending_migration_false_when_no_table(
+        self,
+        store: PaperlessSqliteVecVectorStore,
+    ) -> None:
+        """
+        GIVEN:
+            - A vector store with no table created yet
+        WHEN:
+            - has_pending_migration() is checked
+        THEN:
+            - False is returned (nothing to migrate before anything exists)
+        """
+        assert store.has_pending_migration() is False
+
+    def test_has_pending_migration_false_at_current_version(
+        self,
+        store: PaperlessSqliteVecVectorStore,
+    ) -> None:
+        """
+        GIVEN:
+            - A store at the current SCHEMA_VERSION
+        WHEN:
+            - has_pending_migration() is checked
+        THEN:
+            - False is returned
+        """
+        store.add([make_node("a1", 1)])
+        assert store.has_pending_migration() is False
+
+    def test_has_pending_migration_true_when_behind(
+        self,
+        store: PaperlessSqliteVecVectorStore,
+    ) -> None:
+        """
+        GIVEN:
+            - A store whose schema_version has been forced behind SCHEMA_VERSION
+        WHEN:
+            - has_pending_migration() is checked
+        THEN:
+            - True is returned
+        """
+        store.add([make_node("a1", 1)])
+        store.client.execute(
+            "UPDATE index_meta SET value = '0' WHERE key = 'schema_version'",
+        )
+        assert store.has_pending_migration() is True
+
+
+class TestV1ToV2Migration:
+    """m0001_v1_to_v2 migrates a real, historically-shaped v1 store. The
+    fixture below is a literal, hardcoded v1 DDL string -- NOT derived from
+    any current code -- so this test keeps testing the actual historical
+    shape even if vector_store.py's "current" schema changes again later.
+    """
+
+    def _build_v1_store(self, db_path: str, dim: int) -> None:
+        conn = sqlite3.connect(db_path)
+        conn.row_factory = sqlite3.Row
+        conn.enable_load_extension(True)  # noqa: FBT003
+        import sqlite_vec
+
+        sqlite_vec.load(conn)
+        conn.enable_load_extension(False)  # noqa: FBT003
+        conn.execute("PRAGMA journal_mode=WAL")
+        conn.execute("PRAGMA synchronous=NORMAL")
+        conn.execute(
+            "CREATE TABLE IF NOT EXISTS index_meta (key TEXT PRIMARY KEY, value TEXT)",
+        )
+        conn.execute(  # nosemgrep
+            "CREATE VIRTUAL TABLE documents USING vec0("
+            "id TEXT PRIMARY KEY, document_id TEXT, modified TEXT,"
+            f" +node_content TEXT, embedding float[{dim}] distance_metric=cosine"
+            ")",
+        )
+        conn.execute(
+            "INSERT INTO index_meta (key, value) VALUES ('dim', ?)",
+            (str(dim),),
+        )
+        conn.execute(
+            "INSERT INTO index_meta (key, value) VALUES ('schema_version', '1')",
+        )
+        conn.execute(
+            "INSERT INTO index_meta (key, value) VALUES ('embed_model', 'model-a')",
+        )
+        rows = [
+            ("c1", "1", "2026-01-01T00:00:00", '{"text": "a"}', _pack([0.1] * dim)),
+            ("c2", "1", "2026-01-01T00:00:00", '{"text": "b"}', _pack([0.2] * dim)),
+            ("c3", "2", "2026-02-02T00:00:00", '{"text": "c"}', _pack([0.3] * dim)),
+        ]
+        conn.executemany(
+            "INSERT INTO documents (id, document_id, modified, node_content, embedding)"
+            " VALUES (?, ?, ?, ?, ?)",
+            rows,
+        )
+        conn.execute(
+            "INSERT INTO index_meta (key, value) VALUES ('total_inserts', '3')",
+        )
+        conn.commit()
+        conn.close()
+
+    def test_migration_converts_v1_store_to_v2(self, tmp_path: Path) -> None:
+        """
+        GIVEN:
+            - A real v1-shaped store (TEXT document_id, modified inline in
+              vec0, no document_chunks/document_meta) built from a literal,
+              hardcoded historical DDL
+        WHEN:
+            - A PaperlessSqliteVecVectorStore is opened against it
+        THEN:
+            - schema_version becomes 2, document_id values become int,
+              document_chunks/document_meta are backfilled once per chunk/
+              document respectively, and dim/embed_model survive
+        """
+        db_dir = tmp_path
+        self._build_v1_store(str(db_dir / DB_FILENAME), dim=16)
+        with PaperlessSqliteVecVectorStore(uri=str(db_dir)) as store:
+            assert store.check_and_run_migrations() is False
+            row = store.client.execute(
+                "SELECT value FROM index_meta WHERE key = 'schema_version'",
+            ).fetchone()
+            assert int(row["value"]) == 2
+            doc_id_row = store.client.execute(
+                "SELECT document_id FROM documents WHERE id = 'c1'",
+            ).fetchone()
+            assert isinstance(doc_id_row["document_id"], int)
+            assert doc_id_row["document_id"] == 1
+            chunk_ids = sorted(
+                r["chunk_id"]
+                for r in store.client.execute(
+                    "SELECT chunk_id FROM document_chunks",
+                ).fetchall()
+            )
+            assert chunk_ids == ["c1", "c2", "c3"]
+            assert store.get_modified_times() == {
+                "1": "2026-01-01T00:00:00",
+                "2": "2026-02-02T00:00:00",
+            }
+            assert store.stored_model_name() == "model-a"
+            assert store.vector_dim() == 16
+
+    def test_migration_raises_on_malformed_document_id(
+        self,
+        tmp_path: Path,
+    ) -> None:
+        """
+        GIVEN:
+            - A v1-shaped store with a corrupted, non-integer document_id
+              value on one row
+        WHEN:
+            - The migration runs
+        THEN:
+            - A ValueError is raised (fail loudly, no silent data loss) --
+              this matches the rest of vector_store.py, which has no
+              precedent for silently skipping malformed rows
+        """
+        db_dir = tmp_path
+        self._build_v1_store(str(db_dir / DB_FILENAME), dim=16)
+        import sqlite_vec
+
+        conn = sqlite3.connect(str(db_dir / DB_FILENAME))
+        conn.enable_load_extension(True)  # noqa: FBT003
+        sqlite_vec.load(conn)
+        conn.enable_load_extension(False)  # noqa: FBT003
+        conn.execute(
+            "UPDATE documents SET document_id = 'not-an-int' WHERE id = 'c1'",
+        )
+        conn.commit()
+        conn.close()
+        with (
+            pytest.raises(ValueError),
+            PaperlessSqliteVecVectorStore(uri=str(db_dir)) as store,
+        ):
+            store.check_and_run_migrations()
+
+    def test_migration_never_delegates_to_current_schema_helpers(
+        self,
+        tmp_path: Path,
+        mocker: MockerFixture,
+    ) -> None:
+        """
+        GIVEN:
+            - A real v1-shaped store
+        WHEN:
+            - The migration runs, with DocumentChunksTable.create/
+              DocumentMetaTable.create/_create_vec_table spied on
+        THEN:
+            - None of those "current schema" helpers are ever called during
+              the migration -- it must freeze its own historical DDL, per
+              the DDL-freezing rule (see spec), so a future schema bump
+              can't silently corrupt this migration's output
+        """
+        db_dir = tmp_path
+        self._build_v1_store(str(db_dir / DB_FILENAME), dim=16)
+        from paperless_ai.tables import DocumentChunksTable
+        from paperless_ai.tables import DocumentMetaTable
+
+        chunks_create_spy = mocker.spy(DocumentChunksTable, "create")
+        meta_create_spy = mocker.spy(DocumentMetaTable, "create")
+        vec_table_spy = mocker.spy(
+            PaperlessSqliteVecVectorStore,
+            "_create_vec_table",
+        )
+        with PaperlessSqliteVecVectorStore(uri=str(db_dir)) as store:
+            store.check_and_run_migrations()
+        # _open_connection() legitimately calls create() three times across
+        # a structural migration: once for the store's own live connection
+        # (construction), once for the migration's temp rebuild file
+        # (_rebuild_file), and once more when _swap_in_compact() reopens the
+        # swapped-in file as self._conn. What matters is that
+        # m0001_v1_to_v2's apply() itself never calls these directly, which
+        # a source-text check alone can't prove (it can't tell "mentioned in
+        # a comment" from "actually called", and is trivially evadable by
+        # importing a symbol under an alias). Asserting the exact call count
+        # instead: exactly 3 calls to each create() (all from
+        # _open_connection, never a 4th from inside apply()), and zero calls
+        # to _create_vec_table (neither _open_connection nor apply() calls
+        # it -- apply() freezes its own literal CREATE VIRTUAL TABLE DDL
+        # instead).
+        assert chunks_create_spy.call_count == 3
+        assert meta_create_spy.call_count == 3
+        assert vec_table_spy.call_count == 0
+        # Cheap secondary signal, kept alongside the spy assertions above
+        # (not in place of them): the migration module's source should never
+        # even mention these "current schema" helpers by name.
+        import inspect
+
+        from paperless_ai.migrations import m0001_v1_to_v2
+
+        source = inspect.getsource(m0001_v1_to_v2)
+        assert "DocumentChunksTable.create" not in source
+        assert "DocumentMetaTable.create" not in source
+        assert "_create_vec_table(" not in source

src/paperless_ai/vector_store.py

@@ -2,16 +2,13 @@ import json
 import logging
 import sqlite3
 import struct
-from collections.abc import Callable
 from collections.abc import Iterator
 from collections.abc import Sequence
 from contextlib import contextmanager
-from dataclasses import dataclass
-from dataclasses import field
 from pathlib import Path
 from types import TracebackType
 from typing import Any
-from typing import Literal
+from typing import NamedTuple
 
 import sqlite_vec
 from llama_index.core.bridge.pydantic import PrivateAttr
@@ -26,6 +23,14 @@ from llama_index.core.vector_stores.types import VectorStoreQueryResult
 from llama_index.core.vector_stores.utils import metadata_dict_to_node
 from llama_index.core.vector_stores.utils import node_to_metadata_dict
 
+from paperless_ai.migrations import MIGRATIONS
+from paperless_ai.migrations import Migration
+from paperless_ai.tables import ChunkRow
+from paperless_ai.tables import DocumentChunksTable
+from paperless_ai.tables import DocumentMetaRow
+from paperless_ai.tables import DocumentMetaTable
+from paperless_ai.tables import IndexMetaTable
+
 logger = logging.getLogger("paperless_ai.vector_store")
 
 DB_FILENAME = "llmindex.db"
@@ -34,7 +39,7 @@ DEFAULT_TABLE_NAME = "documents"
 # Current schema version. Written to index_meta at table creation and bumped
 # whenever a Migration is added to MIGRATIONS. check_and_run_migrations() uses
 # this to decide which migrations to run on an existing store.
-SCHEMA_VERSION = 1
+SCHEMA_VERSION = 2
 
 # compact(): rebuild when the cumulative rowid count exceeds this multiple of
 # the live row count. DELETEs on vec0 tables never reclaim space (upstream
@@ -49,40 +54,23 @@ COMPACT_BATCH_SIZE = 500
 
 # Filterable vec0 metadata columns. _build_where() only ever receives filter
 # keys we construct ourselves, but allowlisting keeps SQL identifiers safe by
-# construction.
+# construction. "modified" is not here: it is never filtered on, and as of
-_FILTER_COLUMNS = frozenset({"document_id", "modified"})
+# schema v2 it isn't even a vec0 column anymore (see document_meta).
+_FILTER_COLUMNS = frozenset({"document_id"})
 
 
-@dataclass
+class _Row(NamedTuple):
-class Migration:
+    """One node, ready to write. ``modified`` is not a vec0 column (see
-    """A schema migration for the sqlite-vec vector store.
+    document_meta) -- it rides along here because every row-producing call
-
+    site needs both the vec0 insert values and the document_meta upsert
-    kind="structural": rows are copied into a new-schema file with no
+    value from the same node.
-    re-embedding needed.  Supply ``apply(src_conn, dst_conn, dim)`` which
-    must create the vec0 table in ``dst_conn``, copy all rows from
-    ``src_conn``, and write ``dim`` / ``embed_model`` / ``total_inserts`` to
-    ``dst_conn``'s ``index_meta``.  ``schema_version`` is written by the
-    migration runner after ``apply`` returns.
-
-    kind="re-embed": the new schema requires fresh embeddings.
-    ``check_and_run_migrations()`` returns True when it encounters one of
-    these so the caller can force a full rebuild (which recreates the table
-    at the current SCHEMA_VERSION).
     """
 
-    from_version: int
+    chunk_id: str
-    to_version: int
+    document_id: int
-    kind: Literal["structural", "re-embed"]
+    modified: str
-    description: str
+    node_content: str
-    apply: Callable[[sqlite3.Connection, sqlite3.Connection, int], None] | None = field(
+    embedding: bytes
-        default=None,
-        repr=False,
-    )
-
-
-# Registry of all schema migrations in order. Empty at v1 -- this is the
-# baseline. Add entries here (and bump SCHEMA_VERSION) when the schema changes.
-MIGRATIONS: list[Migration] = []
 
 
 def _pack(embedding: Sequence[float]) -> bytes:
@@ -93,14 +81,30 @@ def _unpack(blob: bytes) -> list[float]:
     return list(struct.unpack(f"{len(blob) // 4}f", blob))
 
 
-def _build_where(filters: MetadataFilters | None) -> tuple[str, list[str]]:
+_INSERT = (
-    """Translate the EQ / IN / NE filters we use into a parameterized SQL clause
+    "INSERT INTO "
-    on vec0 metadata columns. Returns ("", []) when there is nothing to filter.
+    + DEFAULT_TABLE_NAME
+    + " (id, document_id, node_content, embedding) VALUES (?, ?, ?, ?)"
+)
+
+
+def _vec0_params(rows: list[_Row]) -> list[tuple[str, int, str, bytes]]:
+    """``rows``, minus the ``modified`` field vec0 no longer stores."""
+    return [(r.chunk_id, r.document_id, r.node_content, r.embedding) for r in rows]
+
+
+def _build_where(filters: MetadataFilters | None) -> tuple[str, list[int]]:
+    """Translate the EQ / IN / NE filters we use into a parameterized SQL
+    clause on vec0 metadata columns. Returns ("", []) when there is nothing
+    to filter. document_id is vec0's only filterable column and is INTEGER;
+    every value is coerced via int() here so callers (which today still pass
+    strings in places, e.g. indexing.py's MetadataFilter construction) don't
+    have to be individually correct -- vec0 doesn't coerce types itself.
     """
     if filters is None or not filters.filters:
         return "", []
     clauses: list[str] = []
-    params: list[str] = []
+    params: list[int] = []
     for f in filters.filters:
         # filters.filters is Union[MetadataFilter, ExactMatchFilter, MetadataFilters];
         # we only build MetadataFilter entries, so skip anything else at runtime.
@@ -109,7 +113,7 @@ def _build_where(filters: MetadataFilters | None) -> tuple[str, list[str]]:
         if f.key not in _FILTER_COLUMNS:  # pragma: no cover - we build the keys
             raise NotImplementedError(f"Unsupported filter column: {f.key}")
         if f.operator == FilterOperator.IN:
-            values = [str(v) for v in f.value]  # type: ignore[union-attr]  # value is list when operator is IN
+            values = [int(v) for v in f.value]  # type: ignore[union-attr]
             if not values:  # pragma: no cover
                 clauses.append("1 = 0")
                 continue
@@ -118,10 +122,10 @@ def _build_where(filters: MetadataFilters | None) -> tuple[str, list[str]]:
             params.extend(values)
         elif f.operator == FilterOperator.EQ:
             clauses.append(f"{f.key} = ?")
-            params.append(str(f.value))
+            params.append(int(f.value))
         elif f.operator == FilterOperator.NE:
             clauses.append(f"{f.key} != ?")
-            params.append(str(f.value))
+            params.append(int(f.value))
         else:  # pragma: no cover - we only ever build EQ/IN/NE filters
             raise NotImplementedError(f"Unsupported filter operator: {f.operator}")
     if not clauses:
@@ -186,9 +190,21 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
         conn.enable_load_extension(False)  # noqa: FBT003
         conn.execute("PRAGMA journal_mode=WAL")
         conn.execute("PRAGMA synchronous=NORMAL")
-        conn.execute(
+        IndexMetaTable.create(conn)
-            "CREATE TABLE IF NOT EXISTS index_meta (key TEXT PRIMARY KEY, value TEXT)",
+        # vec0 metadata columns only get an efficient lookup path inside a
-        )
+        # KNN (MATCH) query; a plain `WHERE document_id = ?` is a full table
+        # scan regardless of index size. This plain, indexed table is how
+        # delete()/upsert_document() find a document's chunk ids without
+        # that scan.
+        DocumentChunksTable.create(conn)
+        # modified used to be a vec0 metadata column, but vec0 only inlines
+        # TEXT metadata up to 12 bytes -- an ISO timestamp is always longer,
+        # so every read recompiled and stepped a fresh SQL statement per row.
+        # It was never filtered on inside a KNN query either, so it never
+        # needed to be a vec0 column at all. One row per document here (not
+        # per chunk, like document_chunks), since every chunk of a document
+        # shares the same modified value -- see get_modified_times().
+        DocumentMetaTable.create(conn)
         return conn
 
     @property
@@ -223,24 +239,6 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
         else:
             self._conn.execute("COMMIT")
 
-    def _meta_get(self, key: str) -> str | None:
-        row = self._conn.execute(
-            "SELECT value FROM index_meta WHERE key = ?",
-            (key,),
-        ).fetchone()
-        return row["value"] if row else None
-
-    @staticmethod
-    def _meta_set_on(conn: sqlite3.Connection, key: str, value: str) -> None:
-        conn.execute(
-            "INSERT INTO index_meta (key, value) VALUES (?, ?) "
-            "ON CONFLICT(key) DO UPDATE SET value = excluded.value",
-            (key, value),
-        )
-
-    def _meta_set(self, key: str, value: str) -> None:
-        self._meta_set_on(self._conn, key, value)
-
     def table_exists(self) -> bool:
         return (
             self._conn.execute(
@@ -253,18 +251,19 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
     def vector_dim(self) -> int | None:
         if not self.table_exists():
             return None
-        value = self._meta_get("dim")
+        return IndexMetaTable.get_dim(self._conn)
-        return int(value) if value else None
 
     def drop_table(self) -> None:
         self._conn.execute("DROP TABLE IF EXISTS " + DEFAULT_TABLE_NAME)
         self._conn.execute("DELETE FROM index_meta")
+        DocumentChunksTable.delete_all(self._conn)
+        DocumentMetaTable.delete_all(self._conn)
 
     def stored_model_name(self) -> str | None:
         """Return the embedding model name recorded at table creation, or None."""
         if not self.table_exists():
             return None
-        return self._meta_get("embed_model")
+        return IndexMetaTable.get_embed_model(self._conn)
 
     def config_mismatch(self, model_name: str) -> bool:
         """True when the stored model name differs from ``model_name``.
@@ -282,14 +281,17 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
         # document_id is deliberately a metadata column, NOT a partition key:
         # partition keys change KNN `k` to per-partition semantics under IN
         # filters (asg017/sqlite-vec#142); metadata columns give a correct
-        # global top-k.
+        # global top-k. INTEGER (not TEXT, as in schema v1): EQ/NE/IN
+        # comparisons become a native i64 array compare instead of per-row
+        # strncmp against a 16-byte text view, and this drops the unused
+        # metadatatext shadow table TEXT columns carry. modified is not a
+        # column here at all as of v2 -- see document_meta.
         conn.execute(  # nosemgrep: python.sqlalchemy.security.sqlalchemy-execute-raw-query.sqlalchemy-execute-raw-query
             "CREATE VIRTUAL TABLE "
             + DEFAULT_TABLE_NAME
             + " USING vec0("
             + "id TEXT PRIMARY KEY,"
-            + " document_id TEXT,"
+            + " document_id INTEGER,"
-            + " modified TEXT,"
             + " +node_content TEXT,"
             + " embedding float["
             + str(int(dim))
@@ -299,37 +301,70 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
 
     def _create_table(self, dim: int) -> None:
         self._create_vec_table(self._conn, dim)
-        self._meta_set("dim", str(dim))
+        IndexMetaTable.set_dim(self._conn, dim)
-        self._meta_set("schema_version", str(SCHEMA_VERSION))
+        IndexMetaTable.set_schema_version(self._conn, SCHEMA_VERSION)
         if self._embed_model_name:
-            self._meta_set("embed_model", self._embed_model_name)
+            IndexMetaTable.set_embed_model(self._conn, self._embed_model_name)
 
-    def _ensure_table(self, dim: int) -> None:
+    def _ensure_table(self, dim: int, *, table_exists: bool) -> None:
-        if not self.table_exists():
+        if not table_exists:
             self._create_table(dim)
 
-    def _row(self, node: BaseNode) -> tuple[str, str, str, str, bytes]:
+    def _row(self, node: BaseNode) -> _Row:
         meta = node_to_metadata_dict(
             node,
             remove_text=False,
             flat_metadata=self.flat_metadata,
         )
-        # vec0 metadata columns reject NULL (asg017/sqlite-vec#141): coerce
-        # every value to a string, with "" as the absent sentinel.
         document_id = node.ref_doc_id or node.metadata.get("document_id")
-        return (
+        return _Row(
-            node.node_id,
+            chunk_id=node.node_id,
-            str(document_id or ""),
+            document_id=int(document_id),
-            str(node.metadata.get("modified") or ""),
+            modified=str(node.metadata.get("modified") or ""),
-            json.dumps(meta),
+            node_content=json.dumps(meta),
-            _pack(node.get_embedding()),
+            embedding=_pack(node.get_embedding()),
         )
 
-    _INSERT = (
+    def _index_chunks(self, rows: list[_Row]) -> None:
-        "INSERT INTO "
+        """Record each row's (chunk_id, document_id) in document_chunks, and
-        + DEFAULT_TABLE_NAME
+        each row's (document_id, modified) in document_meta -- deduped
-        + " (id, document_id, modified, node_content, embedding) VALUES (?, ?, ?, ?, ?)"
+        within the batch, since every chunk of a document shares the same
-    )
+        modified value -- kept in lockstep with every insert into the vec0
+        table.
+        """
+        DocumentChunksTable.insert_many(
+            self._conn,
+            (ChunkRow(r.chunk_id, r.document_id) for r in rows),
+        )
+        modified_by_document = {r.document_id: r.modified for r in rows}
+        DocumentMetaTable.upsert_many(
+            self._conn,
+            (
+                DocumentMetaRow(doc_id, mod)
+                for doc_id, mod in modified_by_document.items()
+            ),
+        )
+
+    def _delete_chunks_by_document_id(self, document_id: int) -> None:
+        """Delete all of a document's chunks via point-deletes on `id`.
+
+        vec0 has no efficient lookup on the document_id metadata column
+        outside a KNN query, so a plain `DELETE ... WHERE document_id = ?`
+        is a full table scan regardless of index size. Looking the chunk
+        ids up in document_chunks first (a real indexed lookup) and
+        deleting each by its `id` primary key instead turns that scan into
+        a handful of O(1) point deletes.
+        """
+        chunk_ids = DocumentChunksTable.chunk_ids_for_document(
+            self._conn,
+            document_id,
+        )
+        self._conn.executemany(
+            "DELETE FROM " + DEFAULT_TABLE_NAME + " WHERE id = ?",
+            [(chunk_id,) for chunk_id in chunk_ids],
+        )
+        DocumentChunksTable.delete_for_document(self._conn, document_id)
+        DocumentMetaTable.delete_for_document(self._conn, document_id)
 
     def _increment_total_inserts(self, count: int) -> None:
         """Increment the cumulative insert counter stored in index_meta.
@@ -339,48 +374,56 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
         live_rows exceeds COMPACT_BLOAT_RATIO the table has accumulated
         enough deleted-but-not-freed rows to warrant a rebuild.
         """
-        current = int(self._meta_get("total_inserts") or "0")
+        IndexMetaTable.increment_total_inserts(self._conn, count)
-        self._meta_set("total_inserts", str(current + count))
 
     def add(self, nodes: Sequence[BaseNode], **add_kwargs: Any) -> list[str]:
         if not nodes:
             return []
         rows = [self._row(node) for node in nodes]
         with self._transaction():
-            self._ensure_table(len(nodes[0].get_embedding()))
+            self._ensure_table(
-            self._conn.executemany(self._INSERT, rows)
+                len(nodes[0].get_embedding()),
+                table_exists=self.table_exists(),
+            )
+            self._conn.executemany(_INSERT, _vec0_params(rows))
+            self._index_chunks(rows)
             self._increment_total_inserts(len(rows))
         return [node.node_id for node in nodes]
 
-    def upsert_document(self, document_id: str, nodes: list[BaseNode]) -> list[str]:
+    def upsert_document(
+        self,
+        document_id: int | str,
+        nodes: list[BaseNode],
+    ) -> list[str]:
         """Atomically replace all stored chunks of ``document_id`` with ``nodes``.
 
         One transaction deletes the document's existing rows and inserts the
-        new set (vec0's INSERT OR REPLACE is broken upstream, #259, so
+        new set (vec0's INSERT OR REPLACE is broken upstream, so delete+insert
-        delete+insert it is). WAL readers in other processes see either the
+        it is). WAL readers in other processes see either the old or the new
-        old or the new chunk set, never a partial state.
+        chunk set, never a partial state.
         """
+        doc_id = int(document_id)
         rows = [self._row(node) for node in nodes]
         with self._transaction():
-            if nodes:
+            table_exists = self.table_exists()
-                self._ensure_table(len(nodes[0].get_embedding()))
+            if nodes and not table_exists:
-            if self.table_exists():
+                self._ensure_table(
-                self._conn.execute(
+                    len(nodes[0].get_embedding()),
-                    "DELETE FROM " + DEFAULT_TABLE_NAME + " WHERE document_id = ?",
+                    table_exists=False,
-                    (str(document_id),),
                 )
+                table_exists = True
+            if table_exists:
+                self._delete_chunks_by_document_id(doc_id)
             if rows:
-                self._conn.executemany(self._INSERT, rows)
+                self._conn.executemany(_INSERT, _vec0_params(rows))
+                self._index_chunks(rows)
                 self._increment_total_inserts(len(rows))
         return [node.node_id for node in nodes]
 
-    def delete(self, ref_doc_id: str, **delete_kwargs: Any) -> None:
+    def delete(self, ref_doc_id: int | str, **delete_kwargs: Any) -> None:
         if self.table_exists():
             with self._transaction():
-                self._conn.execute(
+                self._delete_chunks_by_document_id(int(ref_doc_id))
-                    "DELETE FROM " + DEFAULT_TABLE_NAME + " WHERE document_id = ?",
-                    (str(ref_doc_id),),
-                )
 
     def _rows_to_nodes(self, rows: list[sqlite3.Row]) -> list[BaseNode]:
         nodes: list[BaseNode] = []
@@ -450,41 +493,60 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
     def get_modified_times(self) -> dict[str, str]:
         """Return {document_id: stored_modified_isoformat} for all indexed documents.
 
-        All chunks of a document share the same ``modified`` value, so the
+        document_meta already has exactly one row per document (not per
-        first row seen per document is sufficient.
+        chunk, unlike the vec0 table), so no dedup is needed here.
         """
         if not self.table_exists():
             return {}
-        result: dict[str, str] = {}
+        return DocumentMetaTable.all_modified_times(self._conn)
-        for row in self._conn.execute(
+
-            "SELECT document_id, modified FROM " + DEFAULT_TABLE_NAME,
+    @property
-        ):
+    def _db_path(self) -> str:
-            doc_id = str(row["document_id"])
+        return str(Path(self._uri) / DB_FILENAME)
-            if doc_id not in result:
+
-                result[doc_id] = str(row["modified"] or "")
+    @contextmanager
-        return result
+    def _rebuild_file(self) -> Iterator[sqlite3.Connection]:
+        """Open a fresh temp database file for a file-swap rebuild (compact
+        or structural migration), yielding its connection for the caller to
+        populate.
+
+        On success, swaps the temp file in as the live database (closing
+        this store's current connection first -- see _swap_in_compact()).
+        On any exception, discards the temp file, including its -wal/-shm,
+        instead, and this store's own connection is left untouched.
+        """
+        compact_path = self._db_path + ".compact"
+        new_conn = self._open_connection(compact_path)
+        try:
+            yield new_conn
+        except BaseException:
+            new_conn.close()
+            for suffix in ["", "-wal", "-shm"]:
+                Path(compact_path + suffix).unlink(missing_ok=True)
+            raise
+        else:
+            new_conn.close()
+            self._swap_in_compact(compact_path, self._db_path)
 
     def compact(self, *, force: bool = False) -> None:
         """Rebuild the database file to reclaim space left behind by DELETEs.
 
         vec0 DELETE only invalidates rows; the vector data stays in the file
-        forever (asg017/sqlite-vec#54), and per-document re-indexing is a
+        forever, and per-document re-indexing is a delete+insert. The
-        delete+insert. The cumulative insert counter in ``index_meta`` tracks
+        cumulative insert counter in ``index_meta`` tracks total rows ever
-        total rows ever written; when that exceeds ``COMPACT_BLOAT_RATIO`` x
+        written; when that exceeds ``COMPACT_BLOAT_RATIO`` x the live row
-        the live row count (or when forced), live rows are copied into a fresh
+        count (or when forced), live rows are copied into a fresh database
-        database file and swapped in via ``os.replace``.
+        file and swapped in via ``os.replace``.
 
         Note: ``ALTER TABLE ... RENAME TO`` on vec0 virtual tables does NOT
-        rename the shadow tables (sqlite-vec upstream limitation), so
+        rename the shadow tables (sqlite-vec upstream limitation), so an
-        an in-place rename-based rebuild is not safe.  The file-swap approach
+        in-place rename-based rebuild is not safe. The file-swap approach is
-        is the maintainer-endorsed workaround (asg017/sqlite-vec#205).
+        the maintainer-endorsed workaround.
         """
         if not self.table_exists():
             return
-        live = self._conn.execute(
+        live = DocumentChunksTable.count(self._conn)
-            "SELECT count(*) FROM " + DEFAULT_TABLE_NAME,
+        total = IndexMetaTable.get_total_inserts(self._conn) or live
-        ).fetchone()[0]
-        total = int(self._meta_get("total_inserts") or str(live))
         if not force and total <= max(live, 1) * COMPACT_BLOAT_RATIO:
             return
         dim = self.vector_dim()
@@ -496,50 +558,62 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
             live,
             total,
         )
-        db_path = str(Path(self._uri) / DB_FILENAME)
+        with self._rebuild_file() as new_conn:
-        compact_path = db_path + ".compact"
+            self._rebuild_into(self._conn, new_conn, dim)
 
-        # Copy all live rows into a fresh database file.
+    @staticmethod
-        new_conn = self._open_connection(compact_path)
+    def _rebuild_into(
-        try:
+        src_conn: sqlite3.Connection,
-            self._create_vec_table(new_conn, dim)
+        dst_conn: sqlite3.Connection,
-            self._meta_set_on(new_conn, "dim", str(dim))
+        dim: int,
-            for key in ("embed_model", "schema_version"):
+    ) -> int:
-                value = self._meta_get(key)
+        """Create the vec0 table in ``dst_conn``, copy dim/embed_model from
-                if value is not None:
+        ``src_conn``, and stream every live vec0 row, document_chunks row,
-                    self._meta_set_on(new_conn, key, value)
+        and document_meta row across. Returns the number of vec0 rows
-            src_cursor = self._conn.execute(
+        copied. Used by compact() only -- m0001_v1_to_v2 freezes its own
-                "SELECT id, document_id, modified, node_content, embedding "
+        copy loop instead of calling this, since this always reflects the
-                "FROM " + DEFAULT_TABLE_NAME,
+        *current* schema (see the migration DDL-freezing rule in the spec).
+        """
+        PaperlessSqliteVecVectorStore._create_vec_table(dst_conn, dim)
+        dim_value = IndexMetaTable.get_dim(src_conn)
+        if dim_value is not None:
+            IndexMetaTable.set_dim(dst_conn, dim_value)
+        embed_model = IndexMetaTable.get_embed_model(src_conn)
+        if embed_model is not None:
+            IndexMetaTable.set_embed_model(dst_conn, embed_model)
+        schema_version = IndexMetaTable.get_schema_version(src_conn)
+        if schema_version is not None:
+            IndexMetaTable.set_schema_version(dst_conn, schema_version)
+
+        dst_conn.execute("BEGIN IMMEDIATE")
+        src_cursor = src_conn.execute(
+            "SELECT id, document_id, node_content, embedding FROM "
+            + DEFAULT_TABLE_NAME,
+        )
+        copied = 0
+        while batch := src_cursor.fetchmany(COMPACT_BATCH_SIZE):
+            dst_conn.executemany(
+                _INSERT,
+                [
+                    (
+                        r["id"],
+                        r["document_id"],
+                        r["node_content"],
+                        bytes(r["embedding"]),
+                    )
+                    for r in batch
+                ],
             )
-            new_conn.execute("BEGIN IMMEDIATE")
+            DocumentChunksTable.insert_many(
-            # Stream rows from the source cursor in batches instead of
+                dst_conn,
-            # materializing the whole table in memory, so a large index does
+                (ChunkRow(r["id"], r["document_id"]) for r in batch),
-            # not cause an OOM during routine maintenance compactions.
+            )
-            while batch := src_cursor.fetchmany(COMPACT_BATCH_SIZE):
+            copied += len(batch)
-                new_conn.executemany(
+        DocumentMetaTable.copy_all(src_conn, dst_conn, COMPACT_BATCH_SIZE)
-                    self._INSERT,
+        # Reset the cumulative counter: after a rebuild, total_inserts == live.
-                    [
+        IndexMetaTable.reset_total_inserts(dst_conn, copied)
-                        (
+        dst_conn.execute("COMMIT")
-                            r["id"],
+        return copied
-                            r["document_id"],
-                            r["modified"],
-                            r["node_content"],
-                            bytes(r["embedding"]),
-                        )
-                        for r in batch
-                    ],
-                )
-            # Reset the cumulative counter: after compact, total_inserts == live.
-            self._meta_set_on(new_conn, "total_inserts", str(live))
-            new_conn.execute("COMMIT")
-        except BaseException:
-            new_conn.close()
-            for p in [compact_path, compact_path + "-wal", compact_path + "-shm"]:
-                Path(p).unlink(missing_ok=True)
-            raise
-        new_conn.close()
-        self._swap_in_compact(compact_path, db_path)
 
     def _swap_in_compact(self, compact_path: str, db_path: str) -> None:
         """Atomically replace the live database with the compacted copy."""
@@ -551,6 +625,31 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
         Path(compact_path).replace(db_path)
         self._conn = self._open_connection(db_path)
 
+    def _stored_schema_version(self) -> int | None:
+        """The schema_version recorded in index_meta, or None if no table
+        exists. A missing key (a store predating version tracking) is
+        treated as SCHEMA_VERSION -- i.e. already current -- since no
+        migration in MIGRATIONS targets a version before tracking began.
+        """
+        if not self.table_exists():
+            return None
+        raw_version = IndexMetaTable.get_schema_version(self._conn)
+        return raw_version if raw_version is not None else SCHEMA_VERSION
+
+    def has_pending_migration(self) -> bool:
+        """Cheaply check whether a migration is pending, with no exclusive
+        access needed -- just a metadata read under the connection callers
+        already hold via the write FileLock.
+
+        Callers should only pay for check_and_run_migrations()'s exclusive
+        access (a structural migration's file swap must not run while
+        readers are active) when this returns True, so that the common
+        case -- already at SCHEMA_VERSION -- never contends with readers
+        or a concurrent compaction.
+        """
+        current = self._stored_schema_version()
+        return current is not None and current < SCHEMA_VERSION
+
     def check_and_run_migrations(self) -> bool:
         """Apply any pending schema migrations to the store.
 
@@ -559,15 +658,13 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
         this method returns True when one is encountered so the caller can
         force a full rebuild (which recreates the table at SCHEMA_VERSION).
 
-        Must be called under the write FileLock.  No-op when the table does
+        Must be called under the write FileLock, with readers excluded (see
-        not exist or is already at SCHEMA_VERSION.
+        has_pending_migration() for a cheap pre-check that avoids paying for
+        that exclusion in the common case).  No-op when the table does not
+        exist or is already at SCHEMA_VERSION.
         """
-        if not self.table_exists():
+        current = self._stored_schema_version()
-            return False
+        if current is None or current >= SCHEMA_VERSION:
-
-        raw = self._meta_get("schema_version")
-        current = int(raw) if raw is not None else SCHEMA_VERSION
-        if current >= SCHEMA_VERSION:
             return False
 
         pending = sorted(
@@ -579,7 +676,7 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
             if migration.kind == "re-embed":
                 logger.warning(
                     "LLM index schema v%d -> v%d requires re-embedding (%s); "
-                    "forcing full rebuild.",
+                    "the caller must force a rebuild.",
                     migration.from_version,
                     migration.to_version,
                     migration.description,
@@ -601,16 +698,12 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
         dim = self.vector_dim()
         if dim is None:  # pragma: no cover
             raise RuntimeError("Cannot migrate: no stored vector dimension")
-        db_path = str(Path(self._uri) / DB_FILENAME)
+        with self._rebuild_file() as new_conn:
-        compact_path = db_path + ".compact"
-        new_conn = self._open_connection(compact_path)
-        try:
             migration.apply(self._conn, new_conn, dim)
-            self._meta_set_on(new_conn, "schema_version", str(migration.to_version))
+            IndexMetaTable.set_schema_version(new_conn, migration.to_version)
-        except BaseException:  # pragma: no cover
+
-            new_conn.close()
+
-            for p in [compact_path, compact_path + "-wal", compact_path + "-shm"]:
+# Registers m0001_v1_to_v2 into MIGRATIONS; must be at the bottom (needs
-                Path(p).unlink(missing_ok=True)
+# PaperlessSqliteVecVectorStore fully defined) -- see
-            raise
+# paperless_ai/migrations/__init__.py for the full procedure.
-        new_conn.close()
+from paperless_ai.migrations import m0001_v1_to_v2  # noqa: E402, F401
-        self._swap_in_compact(compact_path, db_path)