feat: add pgvector backend + namespace-isolation conformance contract
Adds a second external storage backend (Postgres/pgvector) alongside Qdrant to prove the BaseBackend/BaseCollection contract generalizes across substrates (SQL + JSONB containment filters + pgvector `<=>` ranking vs Qdrant's REST/dict model), and addresses the review feedback on PR #1679. Backend (mempalace/backends/pgvector.py): - table-per-(namespace, palace, collection) isolation; advertises supports_namespace_isolation - JSONB filter pushdown for the containment subset, local-exact fallback for $or/$contains/comparisons/where_document - BM25 lexical search; marker-based mismatch protection - optional psycopg dependency (lazy import), in-memory fake for CI, live test gated on MEMPALACE_PGVECTOR_LIVE_URL - registered in registry/__init__/pyproject entry point + [pgvector] extra; MEMPALACE_PGVECTOR_DSN / MEMPALACE_PGVECTOR_NAMESPACE config; README docs Isolation contract (RFC 001): - PalaceRef/BaseBackend document the per-id MUST and the cross-namespace MUST, gated on the new supports_namespace_isolation capability token - runnable conformance suite (tests/_backend_conformance.py, tests/test_backend_conformance.py); qdrant + pgvector run it via their fakes Marker fail-loud guard: - qdrant and pgvector now refuse get_collection when local_path is None instead of silently opening a remote collection with no mismatch protection Review fixes: - palace._open_collection_or_explain handles unknown-backend KeyError as a CLI state message instead of an escaping stack trace - dedup.py docstring no longer claims "No API calls" unconditionally (false for remote backends)
This commit is contained in:
Igor Lins e Silva
@@ -72,8 +72,11 @@ pip install mempalace
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## Storage backends
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ChromaDB is the default. For the pluggable-backend preview, MemPalace also
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ships `sqlite_exact` for local exact-vector correctness checks and `qdrant`
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for an opt-in Qdrant service backend.
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ships `sqlite_exact` for local exact-vector correctness checks, and two opt-in
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external service backends — `qdrant` (REST) and `pgvector` (Postgres). The two
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external backends exercise the storage contract on different substrates (a
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REST/dict store and a SQL/JSONB store), so it is not accidentally shaped around
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one vendor.
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```bash
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# local no-service backend
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@@ -82,14 +85,25 @@ mempalace mine ~/projects/myapp --backend sqlite_exact
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# Qdrant backend, defaulting to http://localhost:6333
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MEMPALACE_QDRANT_URL=http://localhost:6333 \
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mempalace mine ~/projects/myapp --backend qdrant
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# Postgres + pgvector backend, defaulting to postgresql://localhost:5432/mempalace
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# needs the optional driver: pip install mempalace[pgvector]
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# and the `vector` extension available on the server
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MEMPALACE_PGVECTOR_DSN=postgresql://localhost:5432/mempalace \
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mempalace mine ~/projects/myapp --backend pgvector
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```
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Qdrant can also be configured with `MEMPALACE_QDRANT_API_KEY`,
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`MEMPALACE_QDRANT_NAMESPACE`, and `MEMPALACE_QDRANT_TIMEOUT`.
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When `MEMPALACE_QDRANT_URL` points anywhere other than your own local or
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trusted self-hosted service, MemPalace will send and store verbatim drawer
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text and metadata there. That is an explicit opt-in backend choice, never
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the default.
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`MEMPALACE_QDRANT_NAMESPACE`, and `MEMPALACE_QDRANT_TIMEOUT`; pgvector with
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`MEMPALACE_PGVECTOR_NAMESPACE`. Both external backends isolate tenants by
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namespace (advertised via the `supports_namespace_isolation` capability) and
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write a local marker (`qdrant_backend.json` / `pgvector_backend.json`) to guard
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against silently opening a palace against the wrong server.
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When `MEMPALACE_QDRANT_URL` or `MEMPALACE_PGVECTOR_DSN` points anywhere other
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than your own local or trusted self-hosted service, MemPalace will send and
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store verbatim drawer text and metadata there. That is an explicit opt-in
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backend choice, never the default.
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## Quickstart
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@@ -34,6 +34,7 @@ from .base import (
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UnsupportedFilterError,
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)
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from .chroma import ChromaBackend, ChromaCollection
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from .pgvector import PgVectorBackend, PgVectorCollection
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from .qdrant import QdrantBackend, QdrantCollection
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from .sqlite_exact import SQLiteExactBackend, SQLiteExactCollection
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from .registry import (
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@@ -65,6 +66,8 @@ __all__ = [
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"LexicalResult",
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"PalaceNotFoundError",
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"PalaceRef",
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"PgVectorBackend",
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"PgVectorCollection",
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"QdrantBackend",
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"QdrantCollection",
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"QueryResult",
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@@ -86,6 +86,29 @@ class PalaceRef:
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``id`` is always present and is the key backends use to cache handles.
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``local_path`` is populated for filesystem-rooted palaces.
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``namespace`` is used by server-mode backends for tenant / prefix routing.
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Isolation contract (RFC 001 §2.1, conformance: ``tests/test_backend_conformance.py``)
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-----------------------------------------------------------------------------------
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``id`` is the *required* isolation key. Within a single backend instance:
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A record written for one ``PalaceRef.id`` MUST NOT be returned,
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modified, or deleted by an operation issued for a different
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``PalaceRef.id``. Cross-palace access is a spec violation.
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``namespace`` is *additional* partitioning, honored only by backends that
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advertise the ``supports_namespace_isolation`` capability. For those
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backends the same guarantee extends to namespaces:
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A record written under one ``namespace`` MUST NOT be returned,
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modified, or deleted by an operation issued under a different
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``namespace`` within the same backend instance. Cross-namespace
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access is a spec violation.
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Backends that do not advertise ``supports_namespace_isolation`` (e.g.
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``sqlite_exact``, whose isolation is the on-disk path alone) MAY ignore
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``namespace`` entirely; callers MUST NOT rely on it for tenant isolation
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on such backends. Any conforming backend can self-check both guarantees by
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running the shared assertions in ``tests/_backend_conformance.py``.
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"""
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id: str
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@@ -345,6 +368,14 @@ class BaseBackend(ABC):
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Instances are lightweight on construction — no I/O, no network. All
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connection work is deferred to ``get_collection``. Instances are thread-
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safe for concurrent ``get_collection`` calls across different palaces.
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Every backend MUST satisfy the per-``PalaceRef.id`` isolation guarantee in
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:class:`PalaceRef`. Backends that additionally isolate by
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``PalaceRef.namespace`` (multi-tenant / hosted deployments) MUST advertise
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the ``supports_namespace_isolation`` capability token; doing so is a
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promise to satisfy the cross-namespace guarantee and to pass the namespace
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arm of the conformance suite. Backends without the token MAY ignore
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``namespace``.
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"""
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name: ClassVar[str]
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File diff suppressed because it is too large
Load Diff
@@ -1081,6 +1081,7 @@ class QdrantBackend(BaseBackend):
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"supports_embeddings_out",
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"supports_metadata_filters",
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"supports_lexical_search",
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"supports_namespace_isolation",
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"server_mode",
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}
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)
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@@ -1221,6 +1222,18 @@ class QdrantBackend(BaseBackend):
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self._validate_marker_target(palace, config)
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elif not create:
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raise PalaceNotFoundError(marker_path)
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else:
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# The qdrant marker is this backend's only mismatch-protection
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# anchor, and it lives next to the palace on local disk. With no
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# local_path (the pure-remote / hosted mode) we can neither write
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# nor validate it, so opening would silently drop protection
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# against URL/namespace drift. Refuse loudly instead. A remote
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# marker store for pure-remote palaces is tracked as a follow-up.
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raise BackendError(
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"qdrant backend requires a local palace path to anchor mismatch "
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"protection; pure-remote palaces (local_path=None) are not "
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"supported yet"
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)
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remote_collection = self._remote_collection_name(
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palace=palace,
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collection_name=collection_name,
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@@ -207,6 +207,7 @@ def resolve_backend_for_palace(
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def _register_builtins() -> None:
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"""Register chroma as the in-tree default."""
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from .chroma import ChromaBackend
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from .pgvector import PgVectorBackend
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from .qdrant import QdrantBackend
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from .sqlite_exact import SQLiteExactBackend
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@@ -217,6 +218,8 @@ def _register_builtins() -> None:
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_registry["qdrant"] = QdrantBackend
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if "sqlite_exact" not in _registry:
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_registry["sqlite_exact"] = SQLiteExactBackend
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if "pgvector" not in _registry:
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_registry["pgvector"] = PgVectorBackend
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_register_builtins()
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@@ -383,6 +383,30 @@ class MempalaceConfig:
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timeout = 10.0
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return timeout if timeout > 0 else 10.0
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@property
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def pgvector_dsn(self):
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"""Postgres DSN for the opt-in ``pgvector`` backend.
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Defaults to a localhost DSN so selecting pgvector never silently sends
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memory to a remote database. Point at a LAN or cloud Postgres via config
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or ``MEMPALACE_PGVECTOR_DSN`` only when deliberately chosen.
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"""
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env_val = os.environ.get("MEMPALACE_PGVECTOR_DSN")
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if env_val:
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return env_val.strip()
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return str(
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self._file_config.get("pgvector_dsn", "postgresql://localhost:5432/mempalace")
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).strip()
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@property
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def pgvector_namespace(self):
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"""Optional pgvector table namespace/prefix for multi-tenant isolation."""
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env_val = os.environ.get("MEMPALACE_PGVECTOR_NAMESPACE")
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if env_val:
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return env_val.strip()
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value = self._file_config.get("pgvector_namespace")
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return str(value).strip() if value else None
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@property
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def people_map(self):
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"""Mapping of name variants to canonical names."""
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+3
-1
@@ -7,7 +7,9 @@ accumulate. This module finds drawers from the same source_file that
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are too similar (cosine distance < threshold), keeps the longest/richest
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version, and deletes the rest.
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No API calls — uses the configured local vector backend's similarity search.
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Uses the configured storage backend's similarity search. With the default
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local backends (Chroma, sqlite_exact) this stays on-machine with no external
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calls; with a remote backend (e.g. Qdrant) it issues queries to that backend.
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Usage (standalone):
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python -m mempalace.dedup # dedup all
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@@ -185,6 +185,8 @@ def _backend_artifact_label(backend_name: Optional[str]) -> str:
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return "chroma.sqlite3"
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if backend_name == "qdrant":
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return "qdrant_backend.json"
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if backend_name == "pgvector":
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return "pgvector_backend.json"
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if backend_name == "sqlite_exact":
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return "sqlite_exact.sqlite3"
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return "backend database"
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@@ -239,6 +241,14 @@ def _open_collection_or_explain(
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emit(f"\n Backend mismatch at {palace_path}: {e}")
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emit(" Select the matching backend or use a fresh palace directory.")
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return None
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except KeyError as e:
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# Unknown backend name (e.g. a typo in MEMPALACE_BACKEND/--backend):
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# resolve_backend_name -> get_backend_class raises KeyError carrying the
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# available-backend list. Surface it as a CLI state message rather than
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# letting it escape as a stack trace.
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emit(f"\n Unknown backend selected for {palace_path}: {e.args[0] if e.args else e}")
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emit(" Set --backend or MEMPALACE_BACKEND to a registered backend.")
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return None
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detected = detect_backend_for_path(palace_path)
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if detected is None:
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emit(
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@@ -60,6 +60,7 @@ mempalace-mcp = "mempalace.mcp_server:main"
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[project.entry-points."mempalace.backends"]
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chroma = "mempalace.backends.chroma:ChromaBackend"
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pgvector = "mempalace.backends.pgvector:PgVectorBackend"
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qdrant = "mempalace.backends.qdrant:QdrantBackend"
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sqlite_exact = "mempalace.backends.sqlite_exact:SQLiteExactBackend"
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@@ -94,6 +95,11 @@ dev = [
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"mypy>=1.0",
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]
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spellcheck = ["autocorrect>=2.0"]
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# Opt-in Postgres + pgvector backend. Only the psycopg driver is needed on the
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# client; the server must have the `vector` extension available. Selected via
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# MEMPALACE_BACKEND=pgvector / --backend pgvector; never required for the
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# default (Chroma) install.
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pgvector = ["psycopg[binary]>=3.1"]
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# Hardware acceleration for the ONNX embedding model. Install exactly one:
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# pip install mempalace[gpu] — NVIDIA CUDA
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# pip install mempalace[dml] — DirectML (Windows AMD/Intel/NVIDIA)
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@@ -0,0 +1,61 @@
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"""Shared backend isolation conformance assertions (RFC 001 isolation contract).
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Any backend's test module can import these to prove the isolation guarantees
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declared on :class:`mempalace.backends.PalaceRef`:
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* per-``PalaceRef.id`` isolation — required of every backend;
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* per-``PalaceRef.namespace`` isolation — required of backends advertising the
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``supports_namespace_isolation`` capability.
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This module is intentionally not a ``test_*`` file: it ships assertions, not
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test cases, so pytest does not collect it directly.
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"""
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_PROBE_ID = "conformance-isolation-probe"
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_PROBE_DOC = "partition isolation probe document"
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_PROBE_EMBEDDING = [1.0, 0.0, 0.0, 0.0]
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def assert_partition_isolation(backend, writer, other, *, embedding=None):
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"""Assert ``writer`` and ``other`` are isolated partitions of ``backend``.
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A record written to ``writer`` MUST NOT be returned, modified, or deleted
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through ``other`` (query / get / count / delete), and ``writer`` MUST still
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hold it afterwards. ``writer`` and ``other`` are two collections that the
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isolation contract says must not see each other — distinct palace ids (the
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universal guarantee) or distinct namespaces (the namespace guarantee).
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Embeddings are supplied only for backends that require explicit vectors, so
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the same assertion works for text-embedding backends (Chroma) and
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explicit-vector backends (qdrant, sqlite_exact) alike.
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"""
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explicit = "requires_explicit_embeddings" in backend.capabilities
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vector = list(embedding if embedding is not None else _PROBE_EMBEDDING)
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baseline_other = other.count()
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add_kwargs = {
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"ids": [_PROBE_ID],
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"documents": [_PROBE_DOC],
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"metadatas": [{"wing": "conformance"}],
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}
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if explicit:
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add_kwargs["embeddings"] = [vector]
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writer.add(**add_kwargs)
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if explicit:
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leaked = other.query(query_embeddings=[vector], n_results=10)
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else:
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leaked = other.query(query_texts=[_PROBE_DOC], n_results=10)
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hit_ids = leaked.ids[0] if leaked.ids else []
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assert _PROBE_ID not in hit_ids, "query() leaked a record across the isolation boundary"
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assert other.get(ids=[_PROBE_ID]).ids == [], (
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"get() leaked a record across the isolation boundary"
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)
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assert other.count() == baseline_other, "count() leaked a record across the isolation boundary"
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# A delete issued against the other partition MUST NOT touch writer's record.
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other.delete(ids=[_PROBE_ID])
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survivor = writer.get(ids=[_PROBE_ID])
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assert survivor.ids == [_PROBE_ID], "delete() crossed the isolation boundary"
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@@ -0,0 +1,43 @@
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"""Backend isolation conformance suite (RFC 001 isolation contract).
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Runs the shared isolation assertions from ``_backend_conformance`` against the
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built-in local backends. Server-mode backends (qdrant) run the same assertions
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under their own fake/live client in ``test_qdrant_backend.py``.
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"""
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import pytest
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from _backend_conformance import assert_partition_isolation
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from mempalace.backends import PalaceRef
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from mempalace.backends.chroma import ChromaBackend
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from mempalace.backends.sqlite_exact import SQLiteExactBackend
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_LOCAL_BACKENDS = [
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pytest.param(ChromaBackend, id="chroma"),
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pytest.param(SQLiteExactBackend, id="sqlite_exact"),
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]
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@pytest.mark.parametrize("backend_cls", _LOCAL_BACKENDS)
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def test_cross_palace_isolation(backend_cls, tmp_path):
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"""One backend instance must isolate two distinct palaces (PalaceRef.id)."""
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backend = backend_cls()
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try:
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cols = []
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for label in ("alpha", "beta"):
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path = tmp_path / label
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ref = PalaceRef(id=str(path), local_path=str(path))
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cols.append(
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backend.get_collection(palace=ref, collection_name="mempalace_drawers", create=True)
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)
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assert_partition_isolation(backend, cols[0], cols[1])
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finally:
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backend.close()
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def test_local_backends_do_not_claim_namespace_isolation():
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"""Local backends isolate by on-disk path, not namespace; they must not
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advertise the namespace-isolation capability (RFC 001 isolation contract)."""
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assert "supports_namespace_isolation" not in ChromaBackend.capabilities
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assert "supports_namespace_isolation" not in SQLiteExactBackend.capabilities
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@@ -61,6 +61,21 @@ def test_open_collection_or_explain_state_c_no_collection(tmp_path):
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assert any("mempalace mine" in line for line in lines)
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def test_open_collection_or_explain_unknown_backend(tmp_path, monkeypatch):
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"""An unknown backend name (typo in MEMPALACE_BACKEND/--backend) must
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surface as a CLI state message, not an escaping KeyError stack trace."""
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emit, lines = _capture()
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palace = tmp_path / "palace"
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palace.mkdir()
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monkeypatch.setenv("MEMPALACE_BACKEND", "does_not_exist")
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result = _open_collection_or_explain(str(palace), out=emit)
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assert result is None
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assert any("Unknown backend selected" in line for line in lines)
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assert any("does_not_exist" in line for line in lines)
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def test_open_collection_or_explain_state_d_healthy(tmp_path):
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"""State D: healthy palace — returns the opened collection silently."""
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emit, lines = _capture()
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@@ -0,0 +1,490 @@
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import os
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||||
import pytest
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||||
|
||||
from _backend_conformance import assert_partition_isolation
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|
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from mempalace.backends import (
|
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BackendError,
|
||||
BackendMismatchError,
|
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CollectionNotInitializedError,
|
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DimensionMismatchError,
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PalaceRef,
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||||
available_backends,
|
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)
|
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from mempalace.backends.pgvector import (
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PgVectorBackend,
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||||
_matches_where,
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||||
_vector_distance,
|
||||
_as_vector_array,
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||||
)
|
||||
|
||||
|
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class _FakePgVectorClient:
|
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"""In-memory stand-in for the psycopg-backed client.
|
||||
|
||||
Stores rows per table so the same-instance/different-table isolation the
|
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real backend gets from Postgres is exercised deterministically in CI. The
|
||||
real client pushes filters/ranking to SQL; this fake applies the same
|
||||
Python filter + cosine ranking the local-fallback path uses.
|
||||
"""
|
||||
|
||||
instances: list = []
|
||||
|
||||
def __init__(self, _config):
|
||||
self.tables: dict = {}
|
||||
self.query_calls: list = []
|
||||
_FakePgVectorClient.instances.append(self)
|
||||
|
||||
def ping(self):
|
||||
return None
|
||||
|
||||
def ensure_extension(self):
|
||||
return None
|
||||
|
||||
def table_exists(self, table):
|
||||
return table in self.tables
|
||||
|
||||
def table_dimension(self, table):
|
||||
return self.tables.get(table, {}).get("dimension")
|
||||
|
||||
def create_table(self, table, dimension):
|
||||
self.tables.setdefault(table, {"dimension": dimension, "rows": {}})
|
||||
|
||||
def upsert_rows(self, table, rows):
|
||||
store = self.tables.setdefault(
|
||||
table,
|
||||
{"dimension": len(rows[0]["embedding"]) if rows else 0, "rows": {}},
|
||||
)
|
||||
for row in rows:
|
||||
store["rows"][row["id"]] = dict(row)
|
||||
|
||||
def _filtered(self, table, where):
|
||||
rows = list(self.tables.get(table, {"rows": {}})["rows"].values())
|
||||
return [row for row in rows if _matches_where(row.get("metadata") or {}, where)]
|
||||
|
||||
def query_rows(self, table, *, vector, limit, where, with_embedding):
|
||||
self.query_calls.append(where)
|
||||
q = _as_vector_array(vector)
|
||||
scored = []
|
||||
for row in self._filtered(table, where):
|
||||
distance = _vector_distance(q, row.get("embedding"))
|
||||
if distance is not None:
|
||||
scored.append((distance, row))
|
||||
scored.sort(key=lambda item: item[0])
|
||||
out = []
|
||||
for distance, row in scored[:limit]:
|
||||
item = {
|
||||
"id": row["id"],
|
||||
"document": row["document"],
|
||||
"metadata": row.get("metadata") or {},
|
||||
"embedding": row.get("embedding") if with_embedding else None,
|
||||
"distance": distance,
|
||||
}
|
||||
out.append(item)
|
||||
return out
|
||||
|
||||
def scroll_rows(self, table, *, where=None, with_embedding=False):
|
||||
out = []
|
||||
for row in self._filtered(table, where):
|
||||
out.append(
|
||||
{
|
||||
"id": row["id"],
|
||||
"document": row["document"],
|
||||
"metadata": row.get("metadata") or {},
|
||||
"embedding": row.get("embedding") if with_embedding else None,
|
||||
"distance": None,
|
||||
}
|
||||
)
|
||||
return out
|
||||
|
||||
def delete_rows(self, table, *, ids=None, where=None):
|
||||
rows = self.tables.get(table, {"rows": {}})["rows"]
|
||||
if ids is not None:
|
||||
for doc_id in ids:
|
||||
rows.pop(doc_id, None)
|
||||
return
|
||||
for doc_id, row in list(rows.items()):
|
||||
if _matches_where(row.get("metadata") or {}, where):
|
||||
rows.pop(doc_id, None)
|
||||
|
||||
def count_rows(self, table):
|
||||
return len(self.tables.get(table, {"rows": {}})["rows"])
|
||||
|
||||
def drop_table(self, table):
|
||||
self.tables.pop(table, None)
|
||||
|
||||
def close(self):
|
||||
return None
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def fake_pgvector(monkeypatch):
|
||||
import mempalace.backends.pgvector as pgvector
|
||||
|
||||
_FakePgVectorClient.instances.clear()
|
||||
monkeypatch.setattr(pgvector, "_PgVectorClient", _FakePgVectorClient)
|
||||
monkeypatch.delenv("MEMPALACE_PGVECTOR_DSN", raising=False)
|
||||
monkeypatch.delenv("MEMPALACE_PGVECTOR_NAMESPACE", raising=False)
|
||||
return _FakePgVectorClient
|
||||
|
||||
|
||||
def _collection(tmp_path, name="drawers"):
|
||||
backend = PgVectorBackend()
|
||||
palace = PalaceRef(id=str(tmp_path), local_path=str(tmp_path))
|
||||
return backend, backend.get_collection(palace=palace, collection_name=name, create=True)
|
||||
|
||||
|
||||
def test_registry_exposes_pgvector():
|
||||
assert "pgvector" in available_backends()
|
||||
|
||||
|
||||
def test_pgvector_add_query_filters_lexical_and_marker(tmp_path, fake_pgvector):
|
||||
backend, col = _collection(tmp_path)
|
||||
assert not os.path.isfile(tmp_path / "pgvector_backend.json")
|
||||
|
||||
col.add(
|
||||
ids=["a", "b", "c"],
|
||||
documents=[
|
||||
"alpha backend note",
|
||||
"rareterm pgvector backend note",
|
||||
"frontend design note",
|
||||
],
|
||||
metadatas=[
|
||||
{"wing": "project", "room": "backend", "rank": 1},
|
||||
{"wing": "project", "room": "backend", "rank": 3},
|
||||
{"wing": "project", "room": "frontend", "rank": 2},
|
||||
],
|
||||
embeddings=[[1, 0], [0.9, 0.1], [0, 1]],
|
||||
)
|
||||
|
||||
assert PgVectorBackend.detect(str(tmp_path))
|
||||
assert os.path.isfile(tmp_path / "pgvector_backend.json")
|
||||
assert col.count() == 3
|
||||
|
||||
# Equality filter is pushed down (no local fallback); $in stays pushdown.
|
||||
result = col.query(
|
||||
query_embeddings=[[1, 0]],
|
||||
n_results=3,
|
||||
where={"wing": "project"},
|
||||
include=["documents", "metadatas", "distances", "embeddings"],
|
||||
)
|
||||
assert result.ids[0][0] == "a"
|
||||
assert set(result.ids[0]) == {"a", "b", "c"}
|
||||
assert result.embeddings[0][0] == pytest.approx([1.0, 0.0])
|
||||
|
||||
hits = col.lexical_search(query="rareterm backend", n_results=2, where={"wing": "project"}).hits
|
||||
assert [hit.id for hit in hits] == ["b", "a"]
|
||||
|
||||
backend.close_palace(str(tmp_path))
|
||||
with pytest.raises(Exception):
|
||||
col.count()
|
||||
|
||||
|
||||
def test_pgvector_requires_explicit_embeddings(tmp_path, fake_pgvector):
|
||||
_backend, col = _collection(tmp_path)
|
||||
with pytest.raises(ValueError, match="explicit embeddings"):
|
||||
col.add(ids=["a"], documents=["no vector"], metadatas=[{}])
|
||||
|
||||
|
||||
def test_pgvector_marker_not_written_when_first_write_fails(tmp_path, fake_pgvector, monkeypatch):
|
||||
_backend, col = _collection(tmp_path)
|
||||
fake_client = fake_pgvector.instances[0]
|
||||
|
||||
def fail_upsert(*_args, **_kwargs):
|
||||
raise RuntimeError("pg unavailable")
|
||||
|
||||
monkeypatch.setattr(fake_client, "upsert_rows", fail_upsert)
|
||||
|
||||
with pytest.raises(RuntimeError):
|
||||
col.upsert(ids=["a"], documents=["one"], metadatas=[{}], embeddings=[[1, 0]])
|
||||
|
||||
assert not os.path.isfile(tmp_path / "pgvector_backend.json")
|
||||
|
||||
|
||||
def test_pgvector_dimension_mismatch(tmp_path, fake_pgvector):
|
||||
_backend, col = _collection(tmp_path)
|
||||
col.upsert(ids=["a"], documents=["one"], metadatas=[{}], embeddings=[[1, 0]])
|
||||
with pytest.raises(DimensionMismatchError):
|
||||
col.upsert(ids=["b"], documents=["two"], metadatas=[{}], embeddings=[[1, 0, 0]])
|
||||
|
||||
|
||||
def test_pgvector_add_rejects_duplicate_ids_in_same_batch(tmp_path, fake_pgvector):
|
||||
_backend, col = _collection(tmp_path)
|
||||
with pytest.raises(ValueError, match="unique"):
|
||||
col.add(
|
||||
ids=["a", "a"], documents=["x", "y"], metadatas=[{}, {}], embeddings=[[1, 0], [0, 1]]
|
||||
)
|
||||
|
||||
|
||||
def test_pgvector_complex_filters_use_local_fallback(tmp_path, fake_pgvector):
|
||||
_backend, col = _collection(tmp_path)
|
||||
col.add(
|
||||
ids=["a", "b", "c"],
|
||||
documents=["alpha", "beta", "gamma"],
|
||||
metadatas=[
|
||||
{"wing": "x", "rank": 1, "tags": "core,vector"},
|
||||
{"wing": "y", "rank": 3, "tags": "sqlite,exact"},
|
||||
{"wing": "z", "rank": 2, "tags": "old"},
|
||||
],
|
||||
embeddings=[[1, 0], [0.9, 0.1], [0, 1]],
|
||||
)
|
||||
|
||||
# $or, $contains and comparisons must route to the local exact path and
|
||||
# still return the correct rows.
|
||||
or_hits = col.get(where={"$or": [{"wing": "x"}, {"wing": "z"}]})
|
||||
assert set(or_hits.ids) == {"a", "c"}
|
||||
|
||||
contains = col.get(where={"tags": {"$contains": "sqlite"}})
|
||||
assert contains.ids == ["b"]
|
||||
|
||||
ranked = col.query(query_embeddings=[[1, 0]], n_results=3, where={"rank": {"$gte": 2}})
|
||||
assert set(ranked.ids[0]) == {"b", "c"}
|
||||
|
||||
|
||||
def test_pgvector_marker_participates_in_backend_mismatch(tmp_path, fake_pgvector):
|
||||
from mempalace.palace import resolve_backend_name
|
||||
|
||||
_backend, col = _collection(tmp_path)
|
||||
col.upsert(ids=["a"], documents=["one"], metadatas=[{}], embeddings=[[1, 0]])
|
||||
|
||||
assert resolve_backend_name(str(tmp_path)) == "pgvector"
|
||||
with pytest.raises(BackendMismatchError):
|
||||
resolve_backend_name(str(tmp_path), explicit="qdrant")
|
||||
|
||||
|
||||
def test_pgvector_marker_rejects_target_change(tmp_path, fake_pgvector, monkeypatch):
|
||||
_backend, col = _collection(tmp_path)
|
||||
col.upsert(ids=["a"], documents=["one"], metadatas=[{}], embeddings=[[1, 0]])
|
||||
|
||||
backend2 = PgVectorBackend()
|
||||
palace = PalaceRef(id=str(tmp_path), local_path=str(tmp_path))
|
||||
with pytest.raises(BackendMismatchError):
|
||||
backend2.get_collection(
|
||||
palace=palace,
|
||||
collection_name="drawers",
|
||||
create=True,
|
||||
options={"dsn": "postgresql://other-host:5432/other"},
|
||||
)
|
||||
|
||||
|
||||
def test_pgvector_rejects_pure_remote_palace(tmp_path, fake_pgvector):
|
||||
"""No local_path means the marker (the only mismatch-protection anchor)
|
||||
cannot be written or validated, so the backend refuses rather than silently
|
||||
opening an unprotected table (RFC 001 isolation contract, PR #1679)."""
|
||||
backend = PgVectorBackend()
|
||||
palace = PalaceRef(id="tenant-remote", local_path=None, namespace="tenant-remote")
|
||||
with pytest.raises(BackendError, match="local palace path"):
|
||||
backend.get_collection(palace=palace, collection_name="drawers", create=True)
|
||||
|
||||
|
||||
def test_pgvector_missing_table_after_marker_is_not_initialized(tmp_path, fake_pgvector):
|
||||
_backend, col = _collection(tmp_path)
|
||||
col.upsert(ids=["a"], documents=["one"], metadatas=[{}], embeddings=[[1, 0]])
|
||||
fake_pgvector.instances[0].drop_table(col._table)
|
||||
|
||||
assert col.health().ok is False
|
||||
with pytest.raises(CollectionNotInitializedError):
|
||||
col.count()
|
||||
|
||||
|
||||
def test_pgvector_cross_palace_isolation_conformance(tmp_path, fake_pgvector):
|
||||
"""Shared per-PalaceRef.id isolation conformance (RFC 001 isolation contract)."""
|
||||
backend = PgVectorBackend()
|
||||
cols = []
|
||||
for label in ("alpha", "beta"):
|
||||
path = tmp_path / label
|
||||
ref = PalaceRef(id=str(path), local_path=str(path))
|
||||
cols.append(backend.get_collection(palace=ref, collection_name="drawers", create=True))
|
||||
# Same backend + same DSN → same client instance, distinct tables.
|
||||
assert cols[0]._table != cols[1]._table
|
||||
assert_partition_isolation(backend, cols[0], cols[1], embedding=[1.0, 0.0])
|
||||
|
||||
|
||||
def test_pgvector_namespace_isolation_conformance(tmp_path, fake_pgvector):
|
||||
"""Shared per-PalaceRef.namespace isolation conformance — pgvector advertises
|
||||
``supports_namespace_isolation`` (RFC 001 isolation contract)."""
|
||||
assert "supports_namespace_isolation" in PgVectorBackend.capabilities
|
||||
backend = PgVectorBackend()
|
||||
ref_a = PalaceRef(
|
||||
id=str(tmp_path / "tenant-a"),
|
||||
local_path=str(tmp_path / "tenant-a"),
|
||||
namespace="tenant-a",
|
||||
)
|
||||
ref_b = PalaceRef(
|
||||
id=str(tmp_path / "tenant-b"),
|
||||
local_path=str(tmp_path / "tenant-b"),
|
||||
namespace="tenant-b",
|
||||
)
|
||||
col_a = backend.get_collection(palace=ref_a, collection_name="drawers", create=True)
|
||||
col_b = backend.get_collection(palace=ref_b, collection_name="drawers", create=True)
|
||||
# Mechanism: the namespace partitions the table name.
|
||||
assert col_a._table != col_b._table
|
||||
assert "tenant_a" in col_a._table and "tenant_b" in col_b._table
|
||||
# Behaviour: a record under one namespace is invisible under the other.
|
||||
assert_partition_isolation(backend, col_a, col_b, embedding=[1.0, 0.0])
|
||||
|
||||
|
||||
def test_pgvector_update_merges_documents_and_metadata(tmp_path, fake_pgvector):
|
||||
_backend, col = _collection(tmp_path)
|
||||
col.add(
|
||||
ids=["a", "b"],
|
||||
documents=["alpha", "beta"],
|
||||
metadatas=[{"wing": "x", "rank": 1}, {"wing": "y", "rank": 2}],
|
||||
embeddings=[[1, 0], [0, 1]],
|
||||
)
|
||||
col.update(ids=["a"], documents=["alpha-2"], metadatas=[{"rank": 9}])
|
||||
got = col.get(ids=["a"], include=["documents", "metadatas"])
|
||||
assert got.documents == ["alpha-2"]
|
||||
# merge keeps the untouched key and overrides the updated one.
|
||||
assert got.metadatas[0] == {"wing": "x", "rank": 9}
|
||||
# untouched row is unchanged.
|
||||
assert col.get(ids=["b"]).ids == ["b"]
|
||||
with pytest.raises(ValueError, match="at least one"):
|
||||
col.update(ids=["a"])
|
||||
|
||||
|
||||
def test_pgvector_get_limit_offset_and_embeddings(tmp_path, fake_pgvector):
|
||||
_backend, col = _collection(tmp_path)
|
||||
col.add(
|
||||
ids=["a", "b", "c"],
|
||||
documents=["alpha", "beta", "gamma"],
|
||||
metadatas=[{"wing": "x"}, {"wing": "x"}, {"wing": "x"}],
|
||||
embeddings=[[1, 0], [0, 1], [0.5, 0.5]],
|
||||
)
|
||||
page = col.get(where={"wing": "x"}, limit=1, offset=1, include=["documents", "embeddings"])
|
||||
assert len(page.ids) == 1
|
||||
assert page.embeddings is not None and len(page.embeddings[0]) == 2
|
||||
|
||||
|
||||
def test_pgvector_delete_by_where_pushdown_and_local(tmp_path, fake_pgvector):
|
||||
_backend, col = _collection(tmp_path)
|
||||
col.add(
|
||||
ids=["a", "b", "c"],
|
||||
documents=["alpha", "beta", "gamma"],
|
||||
metadatas=[{"wing": "x"}, {"wing": "y"}, {"wing": "z"}],
|
||||
embeddings=[[1, 0], [0, 1], [0.5, 0.5]],
|
||||
)
|
||||
# pushdown equality delete
|
||||
col.delete(where={"wing": "y"})
|
||||
assert set(col.get().ids) == {"a", "c"}
|
||||
# local-fallback delete ($or routes through the exact path)
|
||||
col.delete(where={"$or": [{"wing": "x"}, {"wing": "z"}]})
|
||||
assert col.count() == 0
|
||||
|
||||
|
||||
def test_pgvector_query_dimension_mismatch_against_known_dim(tmp_path, fake_pgvector):
|
||||
_backend, col = _collection(tmp_path)
|
||||
col.add(ids=["a"], documents=["alpha"], metadatas=[{}], embeddings=[[1, 0]])
|
||||
with pytest.raises(DimensionMismatchError):
|
||||
col.query(query_embeddings=[[1, 0, 0]], n_results=1)
|
||||
|
||||
|
||||
def test_pgvector_get_collection_positional_and_palace_path_forms(tmp_path, fake_pgvector):
|
||||
backend = PgVectorBackend()
|
||||
col = backend.get_collection(str(tmp_path / "p1"), "drawers", create=True)
|
||||
col.upsert(ids=["a"], documents=["one"], metadatas=[{}], embeddings=[[1, 0]])
|
||||
assert col.count() == 1
|
||||
col2 = backend.get_collection(
|
||||
palace_path=str(tmp_path / "p2"), collection_name="drawers", create=True
|
||||
)
|
||||
col2.upsert(ids=["b"], documents=["two"], metadatas=[{}], embeddings=[[1, 0]])
|
||||
assert col2.count() == 1
|
||||
assert col._table != col2._table
|
||||
|
||||
|
||||
def test_pgvector_health_and_delete_collection(tmp_path, fake_pgvector):
|
||||
backend = PgVectorBackend()
|
||||
palace = PalaceRef(id=str(tmp_path), local_path=str(tmp_path))
|
||||
col = backend.get_collection(palace=palace, collection_name="drawers", create=True)
|
||||
col.upsert(ids=["a"], documents=["one"], metadatas=[{}], embeddings=[[1, 0]])
|
||||
assert col.health().ok is True
|
||||
assert backend.health(palace).ok is True
|
||||
backend.delete_collection(str(tmp_path), "drawers")
|
||||
assert col.health().ok is False
|
||||
|
||||
|
||||
def test_pgvector_close_marks_backend_closed(tmp_path, fake_pgvector):
|
||||
backend = PgVectorBackend()
|
||||
palace = PalaceRef(id=str(tmp_path), local_path=str(tmp_path))
|
||||
col = backend.get_collection(palace=palace, collection_name="drawers", create=True)
|
||||
col.upsert(ids=["a"], documents=["one"], metadatas=[{}], embeddings=[[1, 0]])
|
||||
backend.close()
|
||||
with pytest.raises(BackendError):
|
||||
backend.get_collection(palace=palace, collection_name="drawers", create=True)
|
||||
|
||||
|
||||
def test_pgvector_marker_unreadable_raises_mismatch(tmp_path, fake_pgvector):
|
||||
_backend, col = _collection(tmp_path)
|
||||
col.upsert(ids=["a"], documents=["one"], metadatas=[{}], embeddings=[[1, 0]])
|
||||
marker = tmp_path / "pgvector_backend.json"
|
||||
marker.write_text("{ not json", encoding="utf-8")
|
||||
backend2 = PgVectorBackend()
|
||||
palace = PalaceRef(id=str(tmp_path), local_path=str(tmp_path))
|
||||
with pytest.raises(BackendMismatchError):
|
||||
backend2.get_collection(palace=palace, collection_name="drawers", create=True)
|
||||
|
||||
|
||||
def test_pgvector_dsn_resolved_from_env(tmp_path, fake_pgvector, monkeypatch):
|
||||
from mempalace.backends.pgvector import _PgVectorConfig
|
||||
|
||||
monkeypatch.setenv("MEMPALACE_PGVECTOR_DSN", "postgresql://example:5432/memdb")
|
||||
monkeypatch.setenv("MEMPALACE_PGVECTOR_NAMESPACE", "team-a")
|
||||
config = _PgVectorConfig.from_options()
|
||||
assert config.dsn == "postgresql://example:5432/memdb"
|
||||
assert config.namespace == "team-a"
|
||||
|
||||
|
||||
def test_palace_wrapper_embeds_for_pgvector(tmp_path, monkeypatch, fake_pgvector):
|
||||
import mempalace.backends.embedding_wrapper as embedding_wrapper
|
||||
from mempalace import palace
|
||||
|
||||
monkeypatch.setattr(
|
||||
embedding_wrapper, "_embed_texts", lambda texts: [[1.0, 0.0] for _ in texts]
|
||||
)
|
||||
monkeypatch.setenv("MEMPALACE_BACKEND_EXPLICIT", "pgvector")
|
||||
monkeypatch.setenv("MEMPALACE_BACKEND", "pgvector")
|
||||
|
||||
col = palace.get_collection(str(tmp_path), "mempalace_drawers", create=True)
|
||||
col.add(documents=["wrapped pgvector document"], ids=["wrapped"], metadatas=[{"wing": "w"}])
|
||||
result = col.query(query_texts=["wrapped"], n_results=1)
|
||||
assert result.ids == [["wrapped"]]
|
||||
|
||||
|
||||
def test_pgvector_live_roundtrip_when_enabled(tmp_path):
|
||||
live_url = os.environ.get("MEMPALACE_PGVECTOR_LIVE_URL")
|
||||
if not live_url:
|
||||
pytest.skip("set MEMPALACE_PGVECTOR_LIVE_URL to run live Postgres pgvector test")
|
||||
|
||||
backend = PgVectorBackend()
|
||||
palace = PalaceRef(id=str(tmp_path), local_path=str(tmp_path), namespace="livetest")
|
||||
col = backend.get_collection(
|
||||
palace=palace,
|
||||
collection_name="drawers",
|
||||
create=True,
|
||||
options={"dsn": live_url},
|
||||
)
|
||||
try:
|
||||
col.upsert(
|
||||
ids=["live-a", "live-b"],
|
||||
documents=["rareterm live pgvector backend", "other live document"],
|
||||
metadatas=[{"wing": "live", "rank": 2}, {"wing": "other", "rank": 1}],
|
||||
embeddings=[[1.0, 0.0], [0.0, 1.0]],
|
||||
)
|
||||
assert PgVectorBackend.detect(str(tmp_path))
|
||||
assert col.count() == 2
|
||||
|
||||
result = col.query(query_embeddings=[[1.0, 0.0]], n_results=2, where={"wing": "live"})
|
||||
assert result.ids == [["live-a"]]
|
||||
|
||||
hits = col.lexical_search(query="rareterm", n_results=1).hits
|
||||
assert hits and hits[0].id == "live-a"
|
||||
|
||||
col.delete(ids=["live-a"])
|
||||
assert col.get(ids=["live-a"]).ids == []
|
||||
finally:
|
||||
try:
|
||||
backend.delete_collection(str(tmp_path), "drawers")
|
||||
except Exception:
|
||||
pass
|
||||
backend.close()
|
||||
@@ -4,6 +4,8 @@ import uuid
|
||||
import numpy as np
|
||||
import pytest
|
||||
|
||||
from _backend_conformance import assert_partition_isolation
|
||||
|
||||
from mempalace.backends import (
|
||||
BackendError,
|
||||
BackendMismatchError,
|
||||
@@ -436,6 +438,51 @@ def test_palace_wrapper_embeds_for_qdrant(tmp_path, monkeypatch, fake_qdrant):
|
||||
assert result.ids == [["wrapped"]]
|
||||
|
||||
|
||||
def test_qdrant_rejects_pure_remote_palace(tmp_path, fake_qdrant):
|
||||
"""No local_path means the marker (the only mismatch-protection anchor)
|
||||
cannot be written or validated, so the backend must refuse rather than
|
||||
silently open an unprotected remote collection (RFC 001 isolation contract, PR #1679)."""
|
||||
backend = QdrantBackend()
|
||||
palace = PalaceRef(id="tenant-remote", local_path=None, namespace="tenant-remote")
|
||||
with pytest.raises(BackendError, match="local palace path"):
|
||||
backend.get_collection(palace=palace, collection_name="drawers", create=True)
|
||||
|
||||
|
||||
def test_qdrant_cross_palace_isolation_conformance(tmp_path, fake_qdrant):
|
||||
"""Shared per-PalaceRef.id isolation conformance (RFC 001 isolation contract)."""
|
||||
backend = QdrantBackend()
|
||||
cols = []
|
||||
for label in ("alpha", "beta"):
|
||||
path = tmp_path / label
|
||||
ref = PalaceRef(id=str(path), local_path=str(path))
|
||||
cols.append(backend.get_collection(palace=ref, collection_name="drawers", create=True))
|
||||
assert_partition_isolation(backend, cols[0], cols[1], embedding=[1.0, 0.0])
|
||||
|
||||
|
||||
def test_qdrant_namespace_isolation_conformance(tmp_path, fake_qdrant):
|
||||
"""Shared per-PalaceRef.namespace isolation conformance — qdrant advertises
|
||||
``supports_namespace_isolation`` so it must satisfy the cross-namespace MUST
|
||||
(RFC 001 isolation contract)."""
|
||||
assert "supports_namespace_isolation" in QdrantBackend.capabilities
|
||||
backend = QdrantBackend()
|
||||
ref_a = PalaceRef(
|
||||
id=str(tmp_path / "tenant-a"),
|
||||
local_path=str(tmp_path / "tenant-a"),
|
||||
namespace="tenant-a",
|
||||
)
|
||||
ref_b = PalaceRef(
|
||||
id=str(tmp_path / "tenant-b"),
|
||||
local_path=str(tmp_path / "tenant-b"),
|
||||
namespace="tenant-b",
|
||||
)
|
||||
col_a = backend.get_collection(palace=ref_a, collection_name="drawers", create=True)
|
||||
col_b = backend.get_collection(palace=ref_b, collection_name="drawers", create=True)
|
||||
# Mechanism: the namespace partitions the remote collection name.
|
||||
assert col_a._remote_collection != col_b._remote_collection
|
||||
# Behaviour: a record under one namespace is invisible under the other.
|
||||
assert_partition_isolation(backend, col_a, col_b, embedding=[1.0, 0.0])
|
||||
|
||||
|
||||
def test_qdrant_live_rest_roundtrip_when_enabled(tmp_path):
|
||||
live_url = os.environ.get("MEMPALACE_QDRANT_LIVE_URL")
|
||||
if not live_url:
|
||||
|
||||
@@ -1999,6 +1999,10 @@ gpu = [
|
||||
{ name = "onnxruntime-gpu", version = "1.24.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version == '3.10.*'" },
|
||||
{ name = "onnxruntime-gpu", version = "1.25.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" },
|
||||
]
|
||||
pgvector = [
|
||||
{ name = "psycopg", version = "3.2.13", source = { registry = "https://pypi.org/simple" }, extra = ["binary"], marker = "python_full_version < '3.10'" },
|
||||
{ name = "psycopg", version = "3.3.4", source = { registry = "https://pypi.org/simple" }, extra = ["binary"], marker = "python_full_version >= '3.10'" },
|
||||
]
|
||||
spellcheck = [
|
||||
{ name = "autocorrect" },
|
||||
]
|
||||
@@ -2032,6 +2036,7 @@ requires-dist = [
|
||||
{ name = "onnxruntime-gpu", marker = "extra == 'gpu'", specifier = ">=1.16" },
|
||||
{ name = "pre-commit", marker = "extra == 'dev'", specifier = ">=3.0" },
|
||||
{ name = "psutil", marker = "extra == 'dev'", specifier = ">=5.9" },
|
||||
{ name = "psycopg", extras = ["binary"], marker = "extra == 'pgvector'", specifier = ">=3.1" },
|
||||
{ name = "pytest", marker = "extra == 'dev'", specifier = ">=7.0" },
|
||||
{ name = "pytest-cov", marker = "extra == 'dev'", specifier = ">=4.0" },
|
||||
{ name = "python-dateutil", specifier = ">=2.8" },
|
||||
@@ -2041,7 +2046,7 @@ requires-dist = [
|
||||
{ name = "tokenizers", specifier = ">=0.15" },
|
||||
{ name = "tomli", marker = "python_full_version < '3.11'", specifier = ">=2.0.0" },
|
||||
]
|
||||
provides-extras = ["dev", "spellcheck", "gpu", "dml", "coreml", "multilingual", "extract"]
|
||||
provides-extras = ["dev", "spellcheck", "pgvector", "gpu", "dml", "coreml", "multilingual", "extract"]
|
||||
|
||||
[package.metadata.requires-dev]
|
||||
dev = [
|
||||
@@ -3704,6 +3709,199 @@ wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/8c/c7/7bb2e321574b10df20cbde462a94e2b71d05f9bbda251ef27d104668306a/psutil-7.2.2-cp37-abi3-win_arm64.whl", hash = "sha256:8c233660f575a5a89e6d4cb65d9f938126312bca76d8fe087b947b3a1aaac9ee", size = 134617, upload-time = "2026-01-28T18:15:36.514Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "psycopg"
|
||||
version = "3.2.13"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
resolution-markers = [
|
||||
"python_full_version < '3.10'",
|
||||
]
|
||||
dependencies = [
|
||||
{ name = "typing-extensions", marker = "python_full_version < '3.10'" },
|
||||
{ name = "tzdata", marker = "python_full_version < '3.10' and sys_platform == 'win32'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/44/05/d4a05988f15fcf90e0088c735b1f2fc04a30b7fc65461d6ec278f5f2f17a/psycopg-3.2.13.tar.gz", hash = "sha256:309adaeda61d44556046ec9a83a93f42bbe5310120b1995f3af49ab6d9f13c1d", size = 160626, upload-time = "2025-11-21T22:34:32.328Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/a9/14/f2724bd1986158a348316e86fdd0837a838b14a711df3f00e47fba597447/psycopg-3.2.13-py3-none-any.whl", hash = "sha256:a481374514f2da627157f767a9336705ebefe93ea7a0522a6cbacba165da179a", size = 206797, upload-time = "2025-11-21T22:29:39.733Z" },
|
||||
]
|
||||
|
||||
[package.optional-dependencies]
|
||||
binary = [
|
||||
{ name = "psycopg-binary", version = "3.2.13", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.10' and implementation_name != 'pypy'" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "psycopg"
|
||||
version = "3.3.4"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
resolution-markers = [
|
||||
"python_full_version >= '3.15' and sys_platform == 'win32'",
|
||||
"python_full_version >= '3.15' and sys_platform != 'win32'",
|
||||
"python_full_version == '3.14.*' and sys_platform == 'win32'",
|
||||
"python_full_version == '3.14.*' and sys_platform != 'win32'",
|
||||
"python_full_version == '3.13.*' and sys_platform == 'win32'",
|
||||
"python_full_version == '3.13.*' and sys_platform != 'win32'",
|
||||
"python_full_version == '3.12.*' and sys_platform == 'win32'",
|
||||
"python_full_version == '3.12.*' and sys_platform != 'win32'",
|
||||
"python_full_version == '3.11.*' and sys_platform == 'win32'",
|
||||
"python_full_version == '3.11.*' and sys_platform != 'win32'",
|
||||
"python_full_version == '3.10.*' and sys_platform == 'win32'",
|
||||
"python_full_version == '3.10.*' and sys_platform != 'win32'",
|
||||
]
|
||||
dependencies = [
|
||||
{ name = "typing-extensions", marker = "python_full_version >= '3.10' and python_full_version < '3.13'" },
|
||||
{ name = "tzdata", marker = "python_full_version >= '3.10' and sys_platform == 'win32'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/db/2f/cb91e5502ec9de1de6f1b76cfbf69531932725361168bb06963620c77e2e/psycopg-3.3.4.tar.gz", hash = "sha256:e21207764952cff81b6b8bdacad9a3939f2793367fdac2987b3aac36a651b5bc", size = 165799, upload-time = "2026-05-01T23:31:55.179Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/5c/e0/7b3dee031daae7743609ce3c746565d4a3ed7c2c186479eb48e34e838c64/psycopg-3.3.4-py3-none-any.whl", hash = "sha256:b6bbc25ccf05c8fad3b061d9db2ef0909a555171b84b07f29458a447253d679a", size = 213001, upload-time = "2026-05-01T23:20:50.816Z" },
|
||||
]
|
||||
|
||||
[package.optional-dependencies]
|
||||
binary = [
|
||||
{ name = "psycopg-binary", version = "3.3.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.10' and implementation_name != 'pypy'" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "psycopg-binary"
|
||||
version = "3.2.13"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
resolution-markers = [
|
||||
"python_full_version < '3.10'",
|
||||
]
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/8f/16/325f72b7ebdb906bd6cca6c0caea5b8fd7092c4686237c5669fe3f3cc7f2/psycopg_binary-3.2.13-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:9e25eb65494955c0dabdcd7097b004cbd70b982cf3cbc7186c2e854f788677a9", size = 4013642, upload-time = "2025-11-21T22:29:43.39Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/4a/a6/f7616dfcab942d5ad6fb5ce8364148e22a4cd817340ac368b6a6bd17559d/psycopg_binary-3.2.13-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:732b25c2d932ca0655ea2588563eae831dc0842c93c69be4754a5b0e9760b38d", size = 4076666, upload-time = "2025-11-21T22:29:51.33Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/4d/f7/cddf75c43c967c9262afe6863275fdd2e5f877d98c379f5c3a21b6fa419d/psycopg_binary-3.2.13-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:7350d9cc4e35529c4548ddda34a1c17f28d3f3a8f792c25cd67e8a04952ed415", size = 4639390, upload-time = "2025-11-21T22:29:57.614Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/9f/b9/f86f2e6413ac024b3a759fd446cc90c325a0d7403dce533bd419e1c41164/psycopg_binary-3.2.13-cp310-cp310-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:090c22795969ee1ace17322b1718769694607d942cef084c6fb4493adfa57da0", size = 4737745, upload-time = "2025-11-21T22:30:01.814Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/19/aa/1a17c7176875d7e0a848710d87f13fdd3cc08724fa6bfcc43c72846f22b9/psycopg_binary-3.2.13-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:9ac329532f36342ff99fc1aefdbb531563bec03c7bc3ae934c8347a7a61339df", size = 4419762, upload-time = "2025-11-21T22:30:05.401Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/a3/9b/5c7f8c90a3504c45ceadffa1f1f4b2fc8ce9e04494cf67d27dfa265e5681/psycopg_binary-3.2.13-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:1db11a7e618d58cfb937c409c7d279a84cbb31d32a7efc63f1e5f426f3613793", size = 3878529, upload-time = "2025-11-21T22:30:09.493Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/ea/37/37e7152e6b0813e68361768d1baf0e40d8ed0ac8091471641c2c88e0cec6/psycopg_binary-3.2.13-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:5f5081b2cbb0358bb3625109d41b57411bf9d9c29762a867e38c06d974b245ee", size = 3560767, upload-time = "2025-11-21T22:30:13.88Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/f7/b2/929d8e15b8797486d160b797ce84a4d0251a9361f7f31e9b01b439608e3b/psycopg_binary-3.2.13-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:5d466ac3a3738647ff2405397946870dc363e33282ced151e7ea74f622947c06", size = 3604456, upload-time = "2025-11-21T22:30:18.392Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/c7/74/4d4e7481bc717bbe3de689c4d40439d4e1be07df989da2c38140298cbae5/psycopg_binary-3.2.13-cp310-cp310-win_amd64.whl", hash = "sha256:087acf2b24787ae206718136c1f51bc90cda68b02c3819b0556f418e3565f2c3", size = 2910871, upload-time = "2025-11-21T22:30:22.24Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/06/f5/fc70804a999167daf5b876107b99e8fe91c3f785a31753c0e3e7b93446ba/psycopg_binary-3.2.13-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:9cfe87749d010dfd34534ba8c71aa0674db9a3fce65232c98989f77c742c9ce7", size = 4013844, upload-time = "2025-11-21T22:30:25.985Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/07/87/857639681f5dfcd567aaf199fe4e5b026a105b0462a604f4fb7eda0735d8/psycopg_binary-3.2.13-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:8db77fac1dfe3f69c982db92a51fd78e1354fa8f523a6781a636123e5c7ffcde", size = 4077002, upload-time = "2025-11-21T22:30:29.539Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/7c/1d/2cb7af6a31429b9022455c966d8408a2b5a19acd3de7610402381518e8f7/psycopg_binary-3.2.13-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:cbbac4cd5b0e14b91ad8244268ca3fc2f527d1a337b489af57d7669c9d2e1a24", size = 4637181, upload-time = "2025-11-21T22:30:34.126Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/28/bd/ffde1ac7e6ab75646c253fbe0378772fb6f0229af8a05cd9862ee8aad0f0/psycopg_binary-3.2.13-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:a146f0a59a7e3ca92996f8133b1d5e5922e668f7c656b4a9201e702f4cf25896", size = 4737775, upload-time = "2025-11-21T22:30:38.408Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/c2/74/3702732d01639c97943d56ec26860357dfacda0b5a708e82e794d07f499c/psycopg_binary-3.2.13-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:27150515de5f709e4142429db6fd36a1d01f0b8b17d915b5f7bb095364465398", size = 4421537, upload-time = "2025-11-21T22:30:42.696Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/f2/8c/915a899857c2211196aa7f1749ba85bed421afaf72f185a0eb91e64ba550/psycopg_binary-3.2.13-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:9942255705255367d94368941e3a913b0daf74b47d191471dbe4dc0de9fbc769", size = 3877500, upload-time = "2025-11-21T22:30:47.064Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/36/d9/46060c183413bf62d47df98d7e3b30ab561639bcb583c3796cca30dafa43/psycopg_binary-3.2.13-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:75ebc8335f48c339ec24f4c371595f6b7043147fe6d18e619c8564428ab8adaf", size = 3560186, upload-time = "2025-11-21T22:30:54.522Z" },
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{ url = "https://files.pythonhosted.org/packages/fd/a0/c8f43cee36386f7bc891ab41a9d31ea07cf9826038e732da79f26b1e5f34/psycopg_binary-3.3.4-cp314-cp314-musllinux_1_2_ppc64le.whl", hash = "sha256:df1d567fc430f6df15c9fcf67d87685fc49bdb325adc0db5af1adfb2f44eb5c9", size = 4210256, upload-time = "2026-05-01T23:31:33.884Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/4e/2c/c1547871be3790676e8868b38655496422f94f0978dfb66b74bdba2f1676/psycopg_binary-3.3.4-cp314-cp314-musllinux_1_2_riscv64.whl", hash = "sha256:6b9016b1714da4dd5ecaaa75b82098aa5a0b87854ce9b092e21c27c4ae23e014", size = 3946204, upload-time = "2026-05-01T23:31:39.626Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/c4/b1/f6670f00fa7ea601584623f6c11602ab92117d83eaff885e0210f6de7418/psycopg_binary-3.3.4-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:47c656a8a7ba6eb0cff1801a4caaa9c8bdc12d03080e273aff1c8ac39971a77e", size = 4255811, upload-time = "2026-05-01T23:31:44.986Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/eb/e6/5fff07a70d1f945ed90ae131c3bd76cab32beff7c58c6db15ad5820b6d1f/psycopg_binary-3.3.4-cp314-cp314-win_amd64.whl", hash = "sha256:c37e024c07308cd06cf3ec51bfd0e7f6157585a4d84d1bce4a7f5f7913719bf8", size = 3666849, upload-time = "2026-05-01T23:31:51.165Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "pybase64"
|
||||
version = "1.4.3"
|
||||
|
||||
Reference in New Issue
Block a user