From 1d9e8d67382d17b3498324d471d69e6e1e590bf0 Mon Sep 17 00:00:00 2001 From: Cheney Zhang Date: Tue, 14 Jul 2026 01:07:14 +0000 Subject: [PATCH] Add Milvus memory backend Signed-off-by: Cheney Zhang --- README.md | 15 +- README_zh.md | 15 +- pyproject.toml | 3 + src/rath/config/credentials.py | 3 +- src/rath/config/schema.py | 19 +- src/rath/memory/__init__.py | 5 + src/rath/memory/abc.py | 19 +- src/rath/memory/adapters/milvus.py | 877 ++++++++++++++++++ tests/config/test_credentials_split.py | 26 +- tests/config/test_memory_from_config.py | 27 + tests/config/test_schema.py | 26 + tests/memory/conformance/conftest.py | 15 +- tests/memory/milvus_backend/__init__.py | 1 + .../milvus_backend/test_milvus_memory.py | 370 ++++++++ .../unit/test_no_backend_crossimport.py | 2 + uv.lock | 635 +++++++++++-- 16 files changed, 1961 insertions(+), 97 deletions(-) create mode 100644 src/rath/memory/adapters/milvus.py create mode 100644 tests/memory/milvus_backend/__init__.py create mode 100644 tests/memory/milvus_backend/test_milvus_memory.py diff --git a/README.md b/README.md index 83ad6c4..872ea84 100644 --- a/README.md +++ b/README.md @@ -259,7 +259,7 @@ The `local` backend is always available and runs file, command, and code tools a Memory is a persistent plane parallel to sandbox execution. It is not a tool result and not just prompt text; it is state that can be attached to an agent, recalled before a run, and committed after a run. -The base install includes a zero-dependency local memory backend. It stores data under `.openrath/memory/`, supports lexical BM25 recall without an LLM, and can use embeddings when an embedding provider is configured. OpenViking is available as an optional backend for users who want a richer external memory service. +The base install includes a zero-dependency local memory backend. It stores data under `.openrath/memory/`, supports lexical BM25 recall without an LLM, and can use embeddings when an embedding provider is configured. OpenViking is available as an optional backend for users who want a richer external memory service. Milvus is available as an optional vector memory backend for semantic recall on Milvus Lite, Milvus server, or Zilliz Cloud. ```python with flow.Agent("You remember useful facts.", model="gpt-5.5", memory="local") as agent: @@ -267,6 +267,18 @@ with flow.Agent("You remember useful facts.", model="gpt-5.5", memory="local") a hits = agent.recall_memory("preferred programming language") ``` +Milvus defaults to local Milvus Lite (`./milvus.db`) and uses the existing +OpenAI-compatible embedding settings: + +```python +# pip install "openrath[milvus]" +# Optional: export MILVUS_URI=http://localhost:19530 or a Zilliz Cloud URI. +# Optional for cloud: export MILVUS_TOKEN=... +with flow.Agent("You remember useful facts.", model="gpt-5.5", memory="milvus") as agent: + agent.remember_memory("The user evaluates vector databases.") + hits = agent.recall_memory("vector database preference") +``` + Agent memory APIs are intentionally discoverable: - `memory=` binds a store at construction time. @@ -326,6 +338,7 @@ Optional sandbox and memory integrations: ```bash pip install "openrath[opensandbox]" pip install "openrath[openviking]" +pip install "openrath[milvus]" ``` For source development: diff --git a/README_zh.md b/README_zh.md index 5e42b89..34f311d 100644 --- a/README_zh.md +++ b/README_zh.md @@ -253,7 +253,7 @@ session = Session.from_user_message("List files").to("local", spec="./") Memory 是与 sandbox 执行平行持久平面。它不是 tool result，也不只是 prompt 文本；它是可以绑定到 Agent、在运行前 recall、在运行后 commit 的状态。 -基础安装包含一个零依赖的本地 memory 后端。它将数据存储在 `.openrath/memory/` 下，无需 LLM 即可支持 lexical BM25 recall，并在配置了 embedding 提供程序时可以使用 embeddings。OpenViking 作为可选后端，为需要更丰富外部 memory 服务的用户提供。 +基础安装包含一个零依赖的本地 memory 后端。它将数据存储在 `.openrath/memory/` 下，无需 LLM 即可支持 lexical BM25 recall，并在配置了 embedding 提供程序时可以使用 embeddings。OpenViking 作为可选后端，为需要更丰富外部 memory 服务的用户提供。Milvus 也作为可选向量 memory 后端提供，可用于 Milvus Lite、Milvus server 或 Zilliz Cloud 上的语义 recall。 ```python with flow.Agent("You remember useful facts.", model="gpt-5.5", memory="local") as agent: @@ -261,6 +261,18 @@ with flow.Agent("You remember useful facts.", model="gpt-5.5", memory="local") a hits = agent.recall_memory("preferred programming language") ``` +Milvus 默认使用本地 Milvus Lite（`./milvus.db`），并复用现有的 +OpenAI-compatible embedding 配置： + +```python +# pip install "openrath[milvus]" +# Optional: export MILVUS_URI=http://localhost:19530 or a Zilliz Cloud URI. +# Optional for cloud: export MILVUS_TOKEN=... +with flow.Agent("You remember useful facts.", model="gpt-5.5", memory="milvus") as agent: + agent.remember_memory("The user evaluates vector databases.") + hits = agent.recall_memory("vector database preference") +``` + Agent memory API 有意设计得易于发现： - `memory=` 在构造时绑定 store。 @@ -320,6 +332,7 @@ pip install openrath ```bash pip install "openrath[opensandbox]" pip install "openrath[openviking]" +pip install "openrath[milvus]" ``` 源码开发： diff --git a/pyproject.toml b/pyproject.toml index 250a14d..93a56df 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -68,6 +68,9 @@ otel = [ s3 = [ "boto3>=1.40,<2", ] +milvus = [ + "pymilvus[milvus-lite]>=3.0.0", +] [tool.ruff] line-length = 88 diff --git a/src/rath/config/credentials.py b/src/rath/config/credentials.py index 4c71c21..71d2027 100644 --- a/src/rath/config/credentials.py +++ b/src/rath/config/credentials.py @@ -13,6 +13,7 @@ Secret layout in ``credentials.json``:: {"version": 1, "llm": {"providers": {"": ""}}, + "memory": {"providers": {"": ""}}, "backend": {"providers": {"": ""}}} Only sections that hold a ``providers`` mapping with an ``api_key`` field are @@ -34,7 +35,7 @@ CREDENTIALS_FILENAME = "credentials.json" # Config sections whose ``providers[*].api_key`` is a secret to externalize. -SECRET_SECTIONS: tuple[str, ...] = ("llm", "backend") +SECRET_SECTIONS: tuple[str, ...] = ("llm", "memory", "backend") def split_secrets(payload: dict[str, Any]) -> tuple[dict[str, Any], dict[str, Any]]: diff --git a/src/rath/config/schema.py b/src/rath/config/schema.py index 8e13ef7..0125f2c 100644 --- a/src/rath/config/schema.py +++ b/src/rath/config/schema.py @@ -90,19 +90,26 @@ class MCPConfig(BaseModel): class MemoryProviderConfig(BaseModel): - """One named entry under ``memory.providers`` (local backend only). + """One named entry under ``memory.providers``. ``embedding_provider`` and ``chat_provider`` name entries under - ``llm.providers`` used by :class:`~rath.memory.adapters.local.LocalMemoryBackend` - for vector search and commit-time memo extraction respectively. - OpenViking connection settings stay on ``MemoryStoreSpec.options`` or - environment variables — they are not modeled here. + ``llm.providers`` used by memory backends for vector search and + commit-time memo extraction respectively. ``api_key`` is externalized to + ``credentials.json`` on save and is mapped to backend-specific secret + fields such as the Milvus token at open time. """ - backend_kind: Literal["local"] = "local" + backend_kind: Literal["local", "milvus"] = "local" path: str | None = None embedding_provider: str | None = None chat_provider: str | None = None + uri: str | None = None + api_key: str | None = None + db_name: str | None = None + collection_name: str | None = None + embedding_model: str | None = None + embedding_dimensions: int | None = None + max_scan: int | None = None model_config = ConfigDict(extra="allow") diff --git a/src/rath/memory/__init__.py b/src/rath/memory/__init__.py index 1f6e111..032703a 100644 --- a/src/rath/memory/__init__.py +++ b/src/rath/memory/__init__.py @@ -66,6 +66,11 @@ except ImportError: # pragma: no cover — optional ``openviking`` extra pass +try: + from rath.memory.adapters import milvus as _milvus # noqa: F401 +except ImportError: # pragma: no cover — optional ``milvus`` extra + pass + # The local backend has zero runtime dependencies; pin it as the default # so ``rath.memory.current()`` works out of the box. _set_default("local") diff --git a/src/rath/memory/abc.py b/src/rath/memory/abc.py index 7c579d0..6ac9b7b 100644 --- a/src/rath/memory/abc.py +++ b/src/rath/memory/abc.py @@ -52,9 +52,8 @@ def from_config( """Build a :class:`MemoryStoreSpec` from ``~/.openrath/config.json``. Looks up ``name`` (or ``memory.default_provider`` when ``name=None``) - under ``memory.providers``. Only **local** presets are modeled in - config today; OpenViking stores should be built explicitly via - :class:`MemoryStoreSpec` kwargs / ``options``. + under ``memory.providers``. OpenViking stores should be built + explicitly via :class:`MemoryStoreSpec` kwargs / ``options``. Lazy-imports :mod:`rath.config` so ``import rath.memory`` never touches the filesystem. @@ -72,6 +71,20 @@ def from_config( options["embedding_provider"] = entry.embedding_provider if entry.chat_provider is not None: options["chat_provider"] = entry.chat_provider + if entry.uri is not None: + options["uri"] = entry.uri + if entry.api_key is not None: + options["token"] = entry.api_key + if entry.db_name is not None: + options["db_name"] = entry.db_name + if entry.collection_name is not None: + options["collection_name"] = entry.collection_name + if entry.embedding_model is not None: + options["embedding_model"] = entry.embedding_model + if entry.embedding_dimensions is not None: + options["embedding_dimensions"] = entry.embedding_dimensions + if entry.max_scan is not None: + options["max_scan"] = entry.max_scan base = cls( options=MappingProxyType(options) if options else None, ) diff --git a/src/rath/memory/adapters/milvus.py b/src/rath/memory/adapters/milvus.py new file mode 100644 index 0000000..245a4d1 --- /dev/null +++ b/src/rath/memory/adapters/milvus.py @@ -0,0 +1,877 @@ +"""Milvus memory backend adapter (optional ``openrath[milvus]`` extra). + +The adapter stores OpenRath memory entries in a Milvus collection and uses +OpenRath's embedding client for vector search. It defaults to Milvus Lite via +``./milvus.db`` and can be pointed at Milvus server or Zilliz Cloud by passing +``uri`` / ``token`` options, or by setting ``MILVUS_URI`` / ``MILVUS_TOKEN``. +""" + +from __future__ import annotations + +import importlib +import math +import os +import re +import time +import uuid +from dataclasses import dataclass +from typing import Any + +from pymilvus import DataType, MilvusClient # type: ignore[import-untyped] + +try: # pragma: no cover - optional across pymilvus versions + _MilvusException = getattr( + importlib.import_module("pymilvus.exceptions"), + "MilvusException", + ) +except ImportError: # pragma: no cover + _MilvusException = Exception + +from rath.memory.abc import MemoryBackend, MemoryStore, MemoryStoreSpec +from rath.memory.capabilities import MemoryCapabilities, ScopeModel +from rath.memory.errors import ( + MemoryBackendError, + MemoryStoreClosed, + UnsupportedMemoryOp, +) +from rath.memory.op_types import ( + MemoryOp, + MemoryOpFind, + MemoryOpList, + MemoryOpRead, + MemoryOpSearch, + MemoryOpTree, + MemoryOpWrite, +) +from rath.memory.registry import register +from rath.memory.results import ( + MemoryEntry, + MemoryExecutionFailure, + MemoryFindResult, + MemoryHit, + MemoryListResult, + MemoryReadResult, + MemoryResult, + MemoryWriteResult, +) +from rath.memory.uri import ( + MEMORY_URI_PREFIX, + MEMORY_URI_ROOT, + memory_uri_prefix, + to_public_uri, +) + +__all__ = ["MilvusMemoryBackend"] + + +_CAPABILITIES = MemoryCapabilities( + scope_model=ScopeModel.HYBRID, + supports_write=True, + supports_read=True, + supports_list=True, + supports_tree=True, + supports_vector_search=True, + supports_intent_search=False, + supports_resource_ingest=False, + supports_session_commit=False, + supports_l0_l1_l2=False, +) + +_SUPPORTED_OPS: frozenset[type[MemoryOp]] = frozenset( + { + MemoryOpWrite, + MemoryOpRead, + MemoryOpList, + MemoryOpTree, + MemoryOpFind, + MemoryOpSearch, + } +) + +_VALID_SCOPES: frozenset[str] = frozenset({"user", "agent", "session", "resources"}) +_COLLECTION_RE = re.compile(r"^[A-Za-z_][A-Za-z0-9_]{0,254}$") + +_DEFAULT_URI = "./milvus.db" +_DEFAULT_COLLECTION = "openrath_memory" +_DEFAULT_MAX_SCAN = 16384 + +_URI_FIELD = "uri" +_VECTOR_FIELD = "vector" +_CONTENT_FIELD = "content" +_SCOPE_FIELD = "scope" +_PATH_FIELD = "path" +_NAME_FIELD = "name" +_PARENT_URI_FIELD = "parent_uri" +_CREATED_AT_FIELD = "created_at" +_UPDATED_AT_FIELD = "updated_at" +_METADATA_FIELD = "metadata" + +_MAX_URI_LENGTH = 2048 +_MAX_PATH_LENGTH = 2048 +_MAX_NAME_LENGTH = 512 +_MAX_CONTENT_LENGTH = 65535 + + +@dataclass(frozen=True, slots=True) +class _ParsedURI: + uri: str + scope: str + path: str + + +@dataclass +class _MilvusHandle: + """Internal binding between a store handle and a Milvus client.""" + + client: MilvusClient + uri: str + collection_name: str + options: dict[str, Any] + drop_on_close: bool = False + max_scan: int = _DEFAULT_MAX_SCAN + embedding_client: Any | None = None + embedding_init_failed: bool = False + dimension: int | None = None + collection_ready: bool = False + schema_checked: bool = False + + +@register("milvus") +class MilvusMemoryBackend(MemoryBackend): + """Milvus-backed memory backend using :class:`pymilvus.MilvusClient`.""" + + def __init__(self) -> None: + self._handles: dict[str, _MilvusHandle] = {} + + @classmethod + def is_available(cls) -> bool: + return True + + @classmethod + def capabilities(cls) -> MemoryCapabilities: + return _CAPABILITIES + + @classmethod + def supported_ops(cls) -> frozenset[type[MemoryOp]]: + return _SUPPORTED_OPS + + def store_count(self) -> int: + return len(self._handles) + + def open(self, spec: MemoryStoreSpec | None = None) -> MemoryStore: + spec = spec or MemoryStoreSpec() + options = dict(spec.options or {}) + uri = _string_option(options, "uri", "MILVUS_URI", default=_DEFAULT_URI) + token = _string_option( + options, "token", "MILVUS_TOKEN", default=options.get("api_key") + ) + db_name = _string_option(options, "db_name", "MILVUS_DB_NAME") + collection_name = _string_option( + options, + "collection_name", + "MILVUS_COLLECTION_NAME", + default=os.environ.get("MILVUS_COLLECTION") or _DEFAULT_COLLECTION, + ) + if not _COLLECTION_RE.fullmatch(collection_name): + raise MemoryBackendError( + "Milvus collection_name must start with a letter or underscore " + "and contain only letters, digits, and underscores" + ) + + client_kwargs: dict[str, Any] = {"uri": uri} + if token: + client_kwargs["token"] = token + if db_name: + client_kwargs["db_name"] = db_name + try: + client = MilvusClient(**client_kwargs) + except Exception as exc: # noqa: BLE001 + raise MemoryBackendError( + f"failed to open Milvus client for {uri!r}: {exc}" + ) from exc + + handle = uuid.uuid4().hex + self._handles[handle] = _MilvusHandle( + client=client, + uri=uri, + collection_name=collection_name, + options=options, + drop_on_close=_bool_option(options, "drop_on_close", default=False), + max_scan=_int_option(options, "max_scan", default=_DEFAULT_MAX_SCAN), + ) + return MemoryStore(backend=self, handle=handle, spec=spec) + + def close(self, store: MemoryStore) -> None: + if store.closed: + return + bound = self._handles.pop(store.handle, None) + if bound is not None: + if bound.drop_on_close: + try: + if bound.client.has_collection( + collection_name=bound.collection_name + ): + bound.client.drop_collection( + collection_name=bound.collection_name + ) + except Exception: # noqa: BLE001 + pass + close = getattr(bound.client, "close", None) + if close is not None: + try: + close() + except Exception: # noqa: BLE001 + pass + store.closed = True + + def dispatch(self, store: MemoryStore, op: MemoryOp) -> MemoryResult: + if store.closed: + raise MemoryStoreClosed(store.handle) + if type(op) not in _SUPPORTED_OPS: + raise UnsupportedMemoryOp(op_type=type(op), backend_name="milvus") + bound = self._handles[store.handle] + try: + if isinstance(op, MemoryOpWrite): + return self._dispatch_write(bound, op) + if isinstance(op, MemoryOpRead): + return self._dispatch_read(bound, op) + if isinstance(op, MemoryOpList): + return self._dispatch_list(bound, op) + if isinstance(op, MemoryOpTree): + return self._dispatch_tree(bound, op) + if isinstance(op, MemoryOpFind): + return self._dispatch_find(bound, op) + if isinstance(op, MemoryOpSearch): + return self._dispatch_find( + bound, + MemoryOpFind( + query=op.query, + target_uri=op.target_uri, + top_k=op.top_k, + ), + ) + except MemoryStoreClosed: + raise + except Exception as exc: # noqa: BLE001 + return _failure_from(exc) + raise AssertionError(f"unreachable dispatch branch for {type(op).__name__}") + + def _dispatch_write(self, bound: _MilvusHandle, op: MemoryOpWrite) -> MemoryResult: + parsed = _parse_memory_uri(op.uri) + if isinstance(parsed, MemoryExecutionFailure): + return parsed + if op.mode not in ("replace", "write"): + return MemoryExecutionFailure( + kind="unsupported", + message=f"unsupported write mode: {op.mode!r}", + ) + if len(parsed.uri) > _MAX_URI_LENGTH or len(parsed.path) > _MAX_PATH_LENGTH: + return MemoryExecutionFailure( + kind="invalid_uri", + message="memory URI is too long for the Milvus schema", + ) + if len(op.content) > _MAX_CONTENT_LENGTH: + return MemoryExecutionFailure( + kind="unsupported", + message=( + "memory content exceeds the Milvus VARCHAR limit of " + f"{_MAX_CONTENT_LENGTH} characters" + ), + ) + + vector = _embedding_vector(bound, op.content) + if isinstance(vector, MemoryExecutionFailure): + return vector + ready = _ensure_collection(bound, len(vector)) + if isinstance(ready, MemoryExecutionFailure): + return ready + + now = int(time.time() * 1000) + name = _name_for_path(parsed) + record: dict[str, Any] = { + _URI_FIELD: parsed.uri, + _VECTOR_FIELD: vector, + _CONTENT_FIELD: op.content, + _SCOPE_FIELD: parsed.scope, + _PATH_FIELD: parsed.path, + _NAME_FIELD: name, + _PARENT_URI_FIELD: _parent_uri(parsed), + _CREATED_AT_FIELD: now, + _UPDATED_AT_FIELD: now, + _METADATA_FIELD: dict(op.metadata or {}), + } + bound.client.upsert(collection_name=bound.collection_name, data=[record]) + return MemoryWriteResult( + uri=parsed.uri, + bytes_written=len(op.content.encode("utf-8")), + ) + + def _dispatch_read(self, bound: _MilvusHandle, op: MemoryOpRead) -> MemoryResult: + parsed = _parse_memory_uri(op.uri) + if isinstance(parsed, MemoryExecutionFailure): + return parsed + if not _has_collection(bound): + return MemoryExecutionFailure( + kind="not_found", + message=f"no memory at {parsed.uri}", + ) + row = _fetch_one(bound, parsed.uri) + if row is None: + return MemoryExecutionFailure( + kind="not_found", + message=f"no memory at {parsed.uri}", + ) + text = str(row.get(_CONTENT_FIELD) or "") + data: str | bytes = text if op.encoding is not None else text.encode("utf-8") + return MemoryReadResult(uri=parsed.uri, data=data, level=op.level) + + def _dispatch_list(self, bound: _MilvusHandle, op: MemoryOpList) -> MemoryResult: + parsed = _parse_memory_uri(op.uri) + if isinstance(parsed, MemoryExecutionFailure): + return parsed + if not _has_collection(bound): + return MemoryListResult(entries=()) + rows = _fetch_rows(bound) + return MemoryListResult(entries=_list_entries(rows, parsed)) + + def _dispatch_tree(self, bound: _MilvusHandle, op: MemoryOpTree) -> MemoryResult: + parsed = _parse_memory_uri(op.uri) + if isinstance(parsed, MemoryExecutionFailure): + return parsed + if not _has_collection(bound): + return MemoryListResult(entries=()) + rows = _fetch_rows(bound) + return MemoryListResult(entries=_tree_entries(rows, parsed, max_depth=op.depth)) + + def _dispatch_find(self, bound: _MilvusHandle, op: MemoryOpFind) -> MemoryResult: + if op.top_k <= 0: + return MemoryFindResult(hits=()) + target: _ParsedURI | None = None + if op.target_uri: + parsed = _parse_memory_uri(op.target_uri) + if isinstance(parsed, MemoryExecutionFailure): + return parsed + target = parsed + + if not _has_collection(bound): + return MemoryFindResult(hits=()) + vector = _embedding_vector(bound, op.query) + if isinstance(vector, MemoryExecutionFailure): + return vector + ready = _ensure_collection(bound, len(vector), create=False) + if isinstance(ready, MemoryExecutionFailure): + return ready + + expr = None + if target is not None: + expr = f"{_SCOPE_FIELD} == {_quote_expr_string(target.scope)}" + limit = min(bound.max_scan, max(op.top_k * 16, op.top_k)) + raw = bound.client.search( + collection_name=bound.collection_name, + data=[vector], + anns_field=_VECTOR_FIELD, + limit=limit, + filter=expr, + output_fields=[ + _URI_FIELD, + _CONTENT_FIELD, + _SCOPE_FIELD, + _PATH_FIELD, + ], + search_params={"metric_type": "IP"}, + ) + hits: list[MemoryHit] = [] + for raw_hit in _iter_search_hits(raw): + entity = raw_hit.get("entity") or raw_hit + uri = str(entity.get(_URI_FIELD) or raw_hit.get("id") or "") + content = str(entity.get(_CONTENT_FIELD) or "") + scope = str(entity.get(_SCOPE_FIELD) or "") + path = str(entity.get(_PATH_FIELD) or "") + if target is not None and not _matches_target(scope, path, target): + continue + score = float(raw_hit.get("distance", raw_hit.get("score", 0.0)) or 0.0) + hits.append( + MemoryHit( + uri=uri, + score=score, + snippet=_snippet(content), + level=None, + ) + ) + if len(hits) >= op.top_k: + break + return MemoryFindResult(hits=tuple(hits)) + + +def _ensure_collection( + bound: _MilvusHandle, dimension: int, *, create: bool = True +) -> MemoryExecutionFailure | None: + if dimension <= 0: + return MemoryExecutionFailure( + kind="internal", + message="embedding provider returned an empty vector", + ) + if _has_collection(bound): + if not bound.schema_checked: + failure = _validate_collection_schema(bound, expected_dim=dimension) + if failure is not None: + return failure + bound.schema_checked = True + bound.dimension = dimension + bound.collection_ready = True + return None + if not create: + return MemoryExecutionFailure( + kind="not_found", + message=f"Milvus collection {bound.collection_name!r} does not exist", + ) + + schema = bound.client.create_schema(auto_id=False, enable_dynamic_field=True) + schema.add_field( + field_name=_URI_FIELD, + datatype=DataType.VARCHAR, + is_primary=True, + max_length=_MAX_URI_LENGTH, + ) + schema.add_field( + field_name=_VECTOR_FIELD, + datatype=DataType.FLOAT_VECTOR, + dim=dimension, + ) + schema.add_field( + field_name=_CONTENT_FIELD, + datatype=DataType.VARCHAR, + max_length=_MAX_CONTENT_LENGTH, + ) + schema.add_field( + field_name=_SCOPE_FIELD, + datatype=DataType.VARCHAR, + max_length=64, + ) + schema.add_field( + field_name=_PATH_FIELD, + datatype=DataType.VARCHAR, + max_length=_MAX_PATH_LENGTH, + ) + schema.add_field( + field_name=_NAME_FIELD, + datatype=DataType.VARCHAR, + max_length=_MAX_NAME_LENGTH, + ) + schema.add_field( + field_name=_PARENT_URI_FIELD, + datatype=DataType.VARCHAR, + max_length=_MAX_URI_LENGTH, + ) + schema.add_field(field_name=_CREATED_AT_FIELD, datatype=DataType.INT64) + schema.add_field(field_name=_UPDATED_AT_FIELD, datatype=DataType.INT64) + schema.add_field(field_name=_METADATA_FIELD, datatype=DataType.JSON) + + index_params = bound.client.prepare_index_params() + index_params.add_index( + field_name=_VECTOR_FIELD, + index_type="AUTOINDEX", + metric_type="IP", + ) + bound.client.create_collection( + collection_name=bound.collection_name, + schema=schema, + index_params=index_params, + ) + bound.dimension = dimension + bound.collection_ready = True + bound.schema_checked = True + return None + + +def _validate_collection_schema( + bound: _MilvusHandle, *, expected_dim: int +) -> MemoryExecutionFailure | None: + try: + desc = bound.client.describe_collection(collection_name=bound.collection_name) + except Exception as exc: # noqa: BLE001 + return _failure_from(exc) + fields = _schema_fields(desc) + names = {_field_name(field) for field in fields} + missing = {_URI_FIELD, _VECTOR_FIELD, _CONTENT_FIELD} - names + if missing: + return MemoryExecutionFailure( + kind="internal", + message=( + f"Milvus collection {bound.collection_name!r} is missing required " + f"fields: {sorted(missing)}" + ), + ) + actual_dim = _vector_dim(fields) + if actual_dim is not None and actual_dim != expected_dim: + return MemoryExecutionFailure( + kind="internal", + message=( + f"Milvus collection {bound.collection_name!r} has vector " + f"dimension {actual_dim}, but the embedding provider returned " + f"dimension {expected_dim}" + ), + ) + return None + + +def _schema_fields(desc: Any) -> list[Any]: + if isinstance(desc, dict): + fields = desc.get("fields") + if isinstance(fields, list): + return fields + schema = desc.get("schema") + if isinstance(schema, dict) and isinstance(schema.get("fields"), list): + return list(schema["fields"]) + schema = getattr(desc, "schema", None) + fields = getattr(schema, "fields", None) + if isinstance(fields, list): + return fields + return [] + + +def _field_name(field: Any) -> str: + if isinstance(field, dict): + return str(field.get("name") or field.get("field_name") or "") + return str(getattr(field, "name", "") or getattr(field, "field_name", "")) + + +def _vector_dim(fields: list[Any]) -> int | None: + for field in fields: + if _field_name(field) != _VECTOR_FIELD: + continue + if isinstance(field, dict): + params = field.get("params") + if isinstance(params, dict) and params.get("dim") is not None: + return int(params["dim"]) + if field.get("dim") is not None: + return int(field["dim"]) + params = getattr(field, "params", None) + if isinstance(params, dict) and params.get("dim") is not None: + return int(params["dim"]) + dim = getattr(field, "dim", None) + if dim is not None: + return int(dim) + return None + + +def _has_collection(bound: _MilvusHandle) -> bool: + return bool(bound.client.has_collection(collection_name=bound.collection_name)) + + +def _fetch_one(bound: _MilvusHandle, uri: str) -> dict[str, Any] | None: + rows = bound.client.query( + collection_name=bound.collection_name, + filter=f"{_URI_FIELD} == {_quote_expr_string(uri)}", + output_fields=[ + _URI_FIELD, + _CONTENT_FIELD, + _SCOPE_FIELD, + _PATH_FIELD, + _NAME_FIELD, + _PARENT_URI_FIELD, + ], + limit=1, + ) + if not rows: + return None + return dict(rows[0]) + + +def _fetch_rows(bound: _MilvusHandle) -> list[dict[str, Any]]: + rows = bound.client.query( + collection_name=bound.collection_name, + filter=f"{_SCOPE_FIELD} != {_quote_expr_string('')}", + output_fields=[ + _URI_FIELD, + _CONTENT_FIELD, + _SCOPE_FIELD, + _PATH_FIELD, + _NAME_FIELD, + _PARENT_URI_FIELD, + ], + limit=bound.max_scan, + ) + return [dict(row) for row in rows] + + +def _embedding_vector( + bound: _MilvusHandle, text: str +) -> list[float] | MemoryExecutionFailure: + client = _maybe_embedding_client(bound) + if client is None: + return MemoryExecutionFailure( + kind="internal", + message=( + "Milvus memory requires an embedding provider; pass " + "MemoryStoreSpec(options={'embedding': client}) or configure " + "OPENAI_API_KEY / llm.embedding_provider" + ), + ) + try: + raw = client.embed_one(text) + except Exception as exc: # noqa: BLE001 + return MemoryExecutionFailure( + kind="transport", + message=f"embedding request failed: {exc}", + detail=type(exc).__name__, + ) + vector = [float(x) for x in raw] + if not vector: + return MemoryExecutionFailure( + kind="internal", + message="embedding provider returned an empty vector", + ) + return _normalize(vector) + + +def _maybe_embedding_client(bound: _MilvusHandle) -> Any | None: + if bound.embedding_init_failed: + return None + if bound.embedding_client is not None: + return bound.embedding_client + pre = bound.options.get("embedding") + if pre is not None and hasattr(pre, "embed") and hasattr(pre, "embed_one"): + bound.embedding_client = pre + return pre + + name = bound.options.get("embedding_provider") + overrides: dict[str, Any] = {} + model = bound.options.get("embedding_model") + if model: + overrides["model"] = str(model) + dimensions = bound.options.get("embedding_dimensions") + if dimensions is not None: + overrides["dimensions"] = int(dimensions) + try: + from rath.llm.embedding import EmbeddingProvider, RathOpenAIEmbeddingClient + + provider = EmbeddingProvider.from_config( + str(name) if name else None, **overrides + ) + bound.embedding_client = RathOpenAIEmbeddingClient(provider) + return bound.embedding_client + except Exception: # noqa: BLE001 + bound.embedding_init_failed = True + return None + + +def _parse_memory_uri(uri: str) -> _ParsedURI | MemoryExecutionFailure: + prefix = memory_uri_prefix(uri) + if prefix is None: + return MemoryExecutionFailure( + kind="invalid_uri", + message=f"URI must start with {MEMORY_URI_PREFIX!r}: {uri!r}", + ) + public = to_public_uri(uri).rstrip("/") + if public.rstrip("/") == MEMORY_URI_ROOT.rstrip("/"): + return MemoryExecutionFailure( + kind="invalid_uri", + message="URI has empty path after scheme", + ) + if not public.startswith(MEMORY_URI_PREFIX): + return MemoryExecutionFailure( + kind="invalid_uri", + message=f"URI must start with {MEMORY_URI_PREFIX!r}: {uri!r}", + ) + tail = public[len(MEMORY_URI_PREFIX) :] + if not tail: + return MemoryExecutionFailure( + kind="invalid_uri", + message="URI has empty path after scheme", + ) + parts = tail.split("/") + scope = parts[0] + if scope not in _VALID_SCOPES: + return MemoryExecutionFailure( + kind="invalid_uri", + message=f"unknown scope {scope!r}; must be one of {sorted(_VALID_SCOPES)}", + ) + rest = parts[1:] + for seg in rest: + if seg in ("", ".", ".."): + return MemoryExecutionFailure( + kind="invalid_uri", + message=f"forbidden path segment in {uri!r}", + ) + path = "/".join(rest) + normalized = f"{MEMORY_URI_PREFIX}{scope}" + if path: + normalized = f"{normalized}/{path}" + return _ParsedURI(uri=normalized, scope=scope, path=path) + + +def _parent_uri(parsed: _ParsedURI) -> str: + if not parsed.path: + return MEMORY_URI_ROOT + parent = parsed.path.rsplit("/", 1)[0] if "/" in parsed.path else "" + if not parent: + return f"{MEMORY_URI_PREFIX}{parsed.scope}" + return f"{MEMORY_URI_PREFIX}{parsed.scope}/{parent}" + + +def _name_for_path(parsed: _ParsedURI) -> str: + if not parsed.path: + return parsed.scope + name = parsed.path.rsplit("/", 1)[-1] + if len(name) > _MAX_NAME_LENGTH: + return name[:_MAX_NAME_LENGTH] + return name + + +def _list_entries( + rows: list[dict[str, Any]], base: _ParsedURI +) -> tuple[MemoryEntry, ...]: + merged: dict[str, MemoryEntry] = {} + for row in rows: + item = _entry_under_base(row, base, max_depth=0) + if item is None: + continue + existing = merged.get(item.uri) + if existing is None or (item.is_dir and not existing.is_dir): + merged[item.uri] = item + return tuple(sorted(merged.values(), key=lambda entry: entry.uri)) + + +def _tree_entries( + rows: list[dict[str, Any]], base: _ParsedURI, *, max_depth: int +) -> tuple[MemoryEntry, ...]: + merged: dict[str, MemoryEntry] = {} + for row in rows: + for depth in range(max(0, max_depth) + 1): + item = _entry_under_base(row, base, max_depth=depth) + if item is None: + continue + existing = merged.get(item.uri) + if existing is None or (item.is_dir and not existing.is_dir): + merged[item.uri] = item + return tuple(sorted(merged.values(), key=lambda entry: entry.uri)) + + +def _entry_under_base( + row: dict[str, Any], base: _ParsedURI, *, max_depth: int +) -> MemoryEntry | None: + scope = str(row.get(_SCOPE_FIELD) or "") + path = str(row.get(_PATH_FIELD) or "") + if scope != base.scope: + return None + if not _matches_target(scope, path, base): + return None + rest = _relative_path(path, base.path) + if not rest: + return None + parts = rest.split("/") + if max_depth >= len(parts): + return None + shown = parts[: max_depth + 1] + is_leaf = len(shown) == len(parts) + child_path = "/".join(part for part in (base.path, *shown) if part) + child_uri = f"{MEMORY_URI_PREFIX}{scope}/{child_path}" if child_path else base.uri + name = shown[-1] + size = len(str(row.get(_CONTENT_FIELD) or "").encode("utf-8")) if is_leaf else None + return MemoryEntry(name=name, uri=child_uri, is_dir=not is_leaf, size=size) + + +def _relative_path(path: str, prefix: str) -> str: + if not prefix: + return path + if path == prefix: + return "" + return path[len(prefix) + 1 :] if path.startswith(prefix + "/") else "" + + +def _matches_target(scope: str, path: str, target: _ParsedURI) -> bool: + if scope != target.scope: + return False + if not target.path: + return True + return path == target.path or path.startswith(target.path + "/") + + +def _iter_search_hits(raw: Any) -> list[dict[str, Any]]: + if not raw: + return [] + first = raw[0] if isinstance(raw, list) else raw + if isinstance(first, list): + return [dict(item) for item in first] + return [dict(item) for item in raw] + + +def _normalize(vector: list[float]) -> list[float]: + norm = math.sqrt(sum(x * x for x in vector)) + if norm == 0.0: + return vector + return [x / norm for x in vector] + + +def _snippet(body: str, *, max_chars: int = 200) -> str: + stripped = body.strip() + if len(stripped) <= max_chars: + return stripped + return stripped[:max_chars].rstrip() + "..." + + +def _quote_expr_string(value: str) -> str: + escaped = value.replace("\\", "\\\\").replace('"', '\\"') + return f'"{escaped}"' + + +def _string_option( + options: dict[str, Any], + key: str, + env_key: str, + *, + default: str | None = None, +) -> str: + value = options.get(key) + if value is None: + value = os.environ.get(env_key) + if value is None: + value = default + return "" if value is None else str(value) + + +def _bool_option(options: dict[str, Any], key: str, *, default: bool) -> bool: + value = options.get(key) + if value is None: + return default + if isinstance(value, bool): + return value + return str(value).strip().lower() in {"1", "true", "yes", "on"} + + +def _int_option(options: dict[str, Any], key: str, *, default: int) -> int: + value = options.get(key) + if value is None: + return default + try: + parsed = int(value) + except (TypeError, ValueError): + return default + return parsed if parsed > 0 else default + + +def _failure_from(exc: BaseException) -> MemoryExecutionFailure: + if isinstance(exc, TimeoutError): + return MemoryExecutionFailure( + kind="timeout", + message=str(exc), + detail=type(exc).__name__, + ) + if isinstance(exc, ConnectionError): + return MemoryExecutionFailure( + kind="transport", + message=str(exc), + detail=type(exc).__name__, + ) + if isinstance(exc, _MilvusException): + return MemoryExecutionFailure( + kind="transport", + message=str(exc), + detail=type(exc).__name__, + ) + return MemoryExecutionFailure( + kind="internal", + message=str(exc), + detail=type(exc).__name__, + ) diff --git a/tests/config/test_credentials_split.py b/tests/config/test_credentials_split.py index c488336..4fc67b0 100644 --- a/tests/config/test_credentials_split.py +++ b/tests/config/test_credentials_split.py @@ -21,7 +21,7 @@ import pytest from rath.config.paths import resolve_config_dir, resolve_config_path -from rath.config.schema import LLMProviderConfig +from rath.config.schema import LLMProviderConfig, MemoryProviderConfig from rath.config.store import ConfigStore @@ -70,6 +70,30 @@ def test_load_remerges_secret(_isolate_openrath_home: Path) -> None: assert reloaded.get_llm_provider("main").api_key == "sk-remerge" +def test_memory_provider_api_key_split_and_remerged( + _isolate_openrath_home: Path, +) -> None: + store = ConfigStore(path=resolve_config_path()) + store.config.memory.providers["milvus-main"] = MemoryProviderConfig( + backend_kind="milvus", + uri="https://example.api.gcp-us-west1.zillizcloud.com", + api_key="sk-memory-secret", + ) + store.save() + + config_raw = json.loads(resolve_config_path().read_text(encoding="utf-8")) + entry = config_raw["memory"]["providers"]["milvus-main"] + assert entry["backend_kind"] == "milvus" + assert entry.get("api_key") in (None, "") + + creds_raw = json.loads(_credentials_path().read_text(encoding="utf-8")) + assert creds_raw["memory"]["providers"]["milvus-main"] == "sk-memory-secret" + + ConfigStore._cache.clear() + reloaded = ConfigStore.load() + assert reloaded.get_memory_provider("milvus-main").api_key == "sk-memory-secret" + + @pytest.mark.skipif(sys.platform.startswith("win"), reason="POSIX perms only") def test_credentials_file_is_0600(_isolate_openrath_home: Path) -> None: store = ConfigStore(path=resolve_config_path()) diff --git a/tests/config/test_memory_from_config.py b/tests/config/test_memory_from_config.py index e81a1d5..440f08b 100644 --- a/tests/config/test_memory_from_config.py +++ b/tests/config/test_memory_from_config.py @@ -40,6 +40,33 @@ def test_named_memory_provider_round_trips_into_spec(tmp_path: Path) -> None: assert spec.options["chat_provider"] == "chat-main" +def test_named_milvus_provider_round_trips_into_spec(tmp_path: Path) -> None: + store = _build_store_with( + tmp_path, + main=MemoryProviderConfig( + backend_kind="milvus", + uri="http://localhost:19530", + api_key="milvus-token", + db_name="default", + collection_name="openrath_memory", + embedding_provider="embed-main", + embedding_model="text-embedding-3-small", + embedding_dimensions=512, + max_scan=2048, + ), + ) + spec = MemoryStoreSpec.from_config("main", store=store) + assert spec.options is not None + assert spec.options["uri"] == "http://localhost:19530" + assert spec.options["token"] == "milvus-token" + assert spec.options["db_name"] == "default" + assert spec.options["collection_name"] == "openrath_memory" + assert spec.options["embedding_provider"] == "embed-main" + assert spec.options["embedding_model"] == "text-embedding-3-small" + assert spec.options["embedding_dimensions"] == 512 + assert spec.options["max_scan"] == 2048 + + def test_default_memory_provider_used_when_name_omitted(tmp_path: Path) -> None: cfg_path = tmp_path / "config.json" store = ConfigStore(path=cfg_path) diff --git a/tests/config/test_schema.py b/tests/config/test_schema.py index f46d3cc..6f4d73b 100644 --- a/tests/config/test_schema.py +++ b/tests/config/test_schema.py @@ -88,6 +88,32 @@ def test_memory_config_accepts_local_provider() -> None: assert entry.chat_provider == "chat" +def test_memory_config_accepts_milvus_provider() -> None: + c = MemoryConfig( + default_provider="milvus-main", + providers={ + "milvus-main": MemoryProviderConfig( + backend_kind="milvus", + uri="https://example.api.gcp-us-west1.zillizcloud.com", + api_key="sk-milvus", + db_name="default", + collection_name="openrath_memory", + embedding_provider="embed", + embedding_model="text-embedding-3-small", + embedding_dimensions=256, + max_scan=4096, + ), + }, + ) + entry = c.providers["milvus-main"] + assert entry.backend_kind == "milvus" + assert entry.uri == "https://example.api.gcp-us-west1.zillizcloud.com" + assert entry.api_key == "sk-milvus" + assert entry.collection_name == "openrath_memory" + assert entry.embedding_dimensions == 256 + assert entry.max_scan == 4096 + + def test_legacy_config_without_memory_section_loads_defaults() -> None: legacy = { "version": 1, diff --git a/tests/memory/conformance/conftest.py b/tests/memory/conformance/conftest.py index ee9c94a..c7520f9 100644 --- a/tests/memory/conformance/conftest.py +++ b/tests/memory/conformance/conftest.py @@ -20,13 +20,24 @@ from rath.memory import MemoryStore, MemoryStoreSpec from rath.memory.abc import MemoryBackend +from rath.memory.adapters.local import LocalMemoryBackend from rath.memory.registry import get as get_backend -from rath.memory.registry import list_names +from rath.memory.registry import get_class, list_names, set_default _OV_URL = os.environ.get("OPEN_VIKING_URL", "http://127.0.0.1:1933") _OV_CONF = Path.home() / ".openviking" / "ov.conf" +def _ensure_local_registered() -> None: + try: + get_class("local") + except Exception: # noqa: BLE001 - tests may clear the process registry + import rath.memory.registry as reg + + reg._REGISTRY["local"] = LocalMemoryBackend + set_default("local") + + def _openviking_ready() -> bool: if "openviking" not in list_names(): return False @@ -52,6 +63,7 @@ def _openviking_ready() -> bool: def _available_backends() -> list[str]: + _ensure_local_registered() out = ["local"] if _openviking_ready(): out.append("openviking") @@ -69,6 +81,7 @@ def _isolate_openrath_home( @pytest.fixture(params=_available_backends()) def conformant_backend(request: pytest.FixtureRequest) -> Iterator[MemoryBackend]: + _ensure_local_registered() name = request.param b = get_backend(name) yield b diff --git a/tests/memory/milvus_backend/__init__.py b/tests/memory/milvus_backend/__init__.py new file mode 100644 index 0000000..42068ba --- /dev/null +++ b/tests/memory/milvus_backend/__init__.py @@ -0,0 +1 @@ +"""Milvus memory backend tests.""" diff --git a/tests/memory/milvus_backend/test_milvus_memory.py b/tests/memory/milvus_backend/test_milvus_memory.py new file mode 100644 index 0000000..ff9d2cb --- /dev/null +++ b/tests/memory/milvus_backend/test_milvus_memory.py @@ -0,0 +1,370 @@ +"""Milvus-backed memory adapter tests against real Milvus Lite.""" + +from __future__ import annotations + +import os +import uuid +from collections.abc import Iterator +from pathlib import Path + +import pytest + +pytest.importorskip("pymilvus") + +from rath.memory import MemoryStore, MemoryStoreSpec +from rath.memory.adapters.milvus import MilvusMemoryBackend +from rath.memory.op_types import ( + MemoryOpFind, + MemoryOpList, + MemoryOpRead, + MemoryOpSearch, + MemoryOpTree, + MemoryOpWrite, +) +from rath.memory.results import ( + MemoryExecutionFailure, + MemoryFindResult, + MemoryListResult, + MemoryReadResult, + MemoryWriteResult, +) + + +class _FakeEmbeddingProvider: + model = "fake-embedding-3d" + + +class _FakeEmbedding: + provider = _FakeEmbeddingProvider() + + def embed( + self, texts: tuple[str, ...] | list[str] + ) -> tuple[tuple[float, ...], ...]: + return tuple(self.embed_one(text) for text in texts) + + def embed_one(self, text: str) -> tuple[float, ...]: + lowered = text.lower() + if any(token in lowered for token in ("dark", "night", "eyes", "theme")): + return (1.0, 0.0, 0.0) + if any(token in lowered for token in ("coffee", "espresso")): + return (0.0, 1.0, 0.0) + return (0.0, 0.0, 1.0) + + +class _FakeEmbedding2D: + provider = _FakeEmbeddingProvider() + + def embed( + self, texts: tuple[str, ...] | list[str] + ) -> tuple[tuple[float, ...], ...]: + return tuple(self.embed_one(text) for text in texts) + + def embed_one(self, text: str) -> tuple[float, ...]: + return (1.0, 0.0) + + +@pytest.fixture +def backend() -> MilvusMemoryBackend: + return MilvusMemoryBackend() + + +def _collection_name() -> str: + return f"openrath_test_{uuid.uuid4().hex}" + + +def _store_options(tmp_path: Path, **overrides: object) -> dict[str, object]: + options: dict[str, object] = { + "uri": str(tmp_path / "milvus.db"), + "collection_name": _collection_name(), + "embedding": _FakeEmbedding(), + "drop_on_close": True, + } + options.update(overrides) + return options + + +@pytest.fixture +def store(backend: MilvusMemoryBackend, tmp_path: Path) -> Iterator[MemoryStore]: + s = backend.open(MemoryStoreSpec(options=_store_options(tmp_path))) + try: + yield s + finally: + if not s.closed: + backend.close(s) + + +def _write( + backend: MilvusMemoryBackend, + store: MemoryStore, + uri: str, + content: str, +) -> None: + res = backend.dispatch(store, MemoryOpWrite(uri=uri, content=content)) + assert isinstance(res, MemoryWriteResult) + + +def test_write_read_list_tree_and_find( + backend: MilvusMemoryBackend, + store: MemoryStore, +) -> None: + _write( + backend, + store, + "memory://user/memories/preferences/dark_theme", + "The user enables a dark colour theme for late-night coding.", + ) + _write( + backend, + store, + "memory://user/memories/preferences/coffee", + "The user drinks espresso before standup.", + ) + _write( + backend, + store, + "memory://user/memories/notes/paris", + "The user is travelling to Paris in April.", + ) + + read = backend.dispatch( + store, MemoryOpRead(uri="memory://user/memories/preferences/dark_theme") + ) + assert isinstance(read, MemoryReadResult) + assert "late-night coding" in read.data + + listed = backend.dispatch( + store, MemoryOpList(uri="memory://user/memories/preferences") + ) + assert isinstance(listed, MemoryListResult) + assert {(entry.name, entry.is_dir) for entry in listed.entries} == { + ("coffee", False), + ("dark_theme", False), + } + + tree = backend.dispatch(store, MemoryOpTree(uri="memory://user/memories", depth=1)) + assert isinstance(tree, MemoryListResult) + assert "memory://user/memories/preferences" in {entry.uri for entry in tree.entries} + assert "memory://user/memories/preferences/dark_theme" in { + entry.uri for entry in tree.entries + } + + found = backend.dispatch( + store, MemoryOpFind(query="reading code at night without burning my eyes") + ) + assert isinstance(found, MemoryFindResult) + assert found.hits + assert found.hits[0].uri == "memory://user/memories/preferences/dark_theme" + + +def test_search_delegates_to_find_and_honors_target_uri( + backend: MilvusMemoryBackend, + store: MemoryStore, +) -> None: + _write( + backend, + store, + "memory://user/memories/preferences/dark_theme", + "The user prefers dark mode at night.", + ) + _write( + backend, + store, + "memory://agent/memories/preferences/dark_theme", + "The agent should use dark logs in diagnostics.", + ) + + res = backend.dispatch( + store, + MemoryOpSearch( + query="dark mode", + target_uri="memory://agent/memories/preferences", + top_k=3, + ), + ) + assert isinstance(res, MemoryFindResult) + assert [hit.uri for hit in res.hits] == [ + "memory://agent/memories/preferences/dark_theme" + ] + + +def test_invalid_uri_and_missing_read_surface_typed_failures( + backend: MilvusMemoryBackend, + store: MemoryStore, +) -> None: + invalid = backend.dispatch( + store, MemoryOpWrite(uri="memory://bogus_scope_xyz/x", content="x") + ) + assert isinstance(invalid, MemoryExecutionFailure) + assert invalid.kind == "invalid_uri" + + missing = backend.dispatch( + store, MemoryOpRead(uri="memory://user/memories/preferences/missing") + ) + assert isinstance(missing, MemoryExecutionFailure) + assert missing.kind == "not_found" + + +def test_reopens_existing_lite_collection( + tmp_path: Path, +) -> None: + collection = _collection_name() + uri = str(tmp_path / "milvus.db") + + first_backend = MilvusMemoryBackend() + first = first_backend.open( + MemoryStoreSpec( + options={ + "uri": uri, + "collection_name": collection, + "embedding": _FakeEmbedding(), + } + ) + ) + _write( + first_backend, + first, + "memory://user/memories/preferences/persisted", + "This memory should survive reopening the Milvus Lite file.", + ) + first_backend.close(first) + + second_backend = MilvusMemoryBackend() + second = second_backend.open( + MemoryStoreSpec( + options={ + "uri": uri, + "collection_name": collection, + "embedding": _FakeEmbedding(), + "drop_on_close": True, + } + ) + ) + try: + read = second_backend.dispatch( + second, MemoryOpRead(uri="memory://user/memories/preferences/persisted") + ) + assert isinstance(read, MemoryReadResult) + assert "survive reopening" in read.data + finally: + second_backend.close(second) + + +def test_existing_collection_dimension_mismatch_returns_failure( + tmp_path: Path, +) -> None: + collection = _collection_name() + uri = str(tmp_path / "milvus.db") + + first_backend = MilvusMemoryBackend() + first = first_backend.open( + MemoryStoreSpec( + options={ + "uri": uri, + "collection_name": collection, + "embedding": _FakeEmbedding(), + } + ) + ) + _write( + first_backend, + first, + "memory://user/memories/preferences/dim", + "A three dimensional record.", + ) + first_backend.close(first) + + second_backend = MilvusMemoryBackend() + second = second_backend.open( + MemoryStoreSpec( + options={ + "uri": uri, + "collection_name": collection, + "embedding": _FakeEmbedding2D(), + "drop_on_close": True, + } + ) + ) + try: + res = second_backend.dispatch( + second, + MemoryOpWrite( + uri="memory://user/memories/preferences/bad_dim", + content="A two dimensional record.", + ), + ) + assert isinstance(res, MemoryExecutionFailure) + assert res.kind == "internal" + assert "dimension" in res.message + finally: + second_backend.close(second) + + +_HAS_LIVE_KEY = len(os.environ.get("OPENAI_API_KEY", "").strip()) >= 8 +_live_only = pytest.mark.skipif( + not _HAS_LIVE_KEY, + reason="OPENAI_API_KEY not set (live embedding tests)", +) + + +@_live_only +@pytest.mark.live_llm +def test_live_openai_embedding_smoke(tmp_path: Path) -> None: + from rath.llm.embedding import EmbeddingProvider, RathOpenAIEmbeddingClient + + api_key = os.environ["OPENAI_API_KEY"].strip() + base_url = os.environ.get("OPENAI_BASE_URL", "").strip() or None + model = os.environ.get("OPENAI_EMBEDDING_MODEL", "").strip() or None + embedding = RathOpenAIEmbeddingClient( + EmbeddingProvider( + api_key=api_key, + base_url=base_url, + model=model or "text-embedding-3-small", + ) + ) + backend = MilvusMemoryBackend() + store = backend.open( + MemoryStoreSpec( + options=_store_options( + tmp_path, + embedding=embedding, + collection_name=_collection_name(), + drop_on_close=True, + ) + ) + ) + try: + first = backend.dispatch( + store, + MemoryOpWrite( + uri="memory://user/memories/preferences/milvus", + content="Milvus stores vector embeddings for scalable semantic retrieval.", + ), + ) + if isinstance(first, MemoryExecutionFailure) and first.kind == "transport": + pytest.skip(f"live embedding endpoint unavailable: {first.detail}") + assert isinstance(first, MemoryWriteResult) + + second = backend.dispatch( + store, + MemoryOpWrite( + uri="memory://user/memories/preferences/tea", + content="The user drinks jasmine tea on Friday afternoons.", + ), + ) + if isinstance(second, MemoryExecutionFailure) and second.kind == "transport": + pytest.skip(f"live embedding endpoint unavailable: {second.detail}") + assert isinstance(second, MemoryWriteResult) + + res = backend.dispatch( + store, + MemoryOpFind( + query="Milvus vector embeddings for semantic retrieval", + top_k=1, + ), + ) + if isinstance(res, MemoryExecutionFailure) and res.kind == "transport": + pytest.skip(f"live embedding endpoint unavailable: {res.detail}") + assert isinstance(res, MemoryFindResult) + assert res.hits[0].uri == "memory://user/memories/preferences/milvus" + finally: + backend.close(store) diff --git a/tests/memory/unit/test_no_backend_crossimport.py b/tests/memory/unit/test_no_backend_crossimport.py index 04095e1..f0975a8 100644 --- a/tests/memory/unit/test_no_backend_crossimport.py +++ b/tests/memory/unit/test_no_backend_crossimport.py @@ -107,6 +107,8 @@ def test_rath_memory_registry_only_contains_optional_extras(): for name in names - {"local"}: if name == "openviking": importlib.import_module("openviking") + elif name == 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