"""长期记忆画像向量的 Milvus 客户端。 与 `MilvusKnowledgeWriter` 分开:那个适配器的 `upsert` 签名绑定知识集合的 `knowledge_id` 主键与字段表,而画像投影的主键是 `memory_uuid`、且需要先 `query` 按版本判重。两者共用一套连接口径(惰性连接 + 失败一律 `RecoverableAgentError`), 但不硬把两种 schema 塞进同一个类。 与召回侧的客户端也分开:写路径不与检索进程共用连接(读写物理隔离,向量库故障 不能从写路径传染到问答主链路),与 `get_milvus_knowledge_writer` 的取向一致。 """ from typing import Any from app.core.errors import RecoverableAgentError class MilvusProfileVectorClient: """满足 `MilvusProfileProjection` 所需的 `query` / `upsert` / `load_collection`。""" def __init__(self, uri: str, token: str = "") -> None: self._uri = uri self._token = token self._client: Any = None async def _ensure(self) -> Any: if self._client is None: try: from pymilvus import AsyncMilvusClient # type: ignore[import-untyped] except ImportError as exc: # pragma: no cover - 依赖已声明,缺装是环境问题 raise RecoverableAgentError("pymilvus 未安装,无法写入画像向量") from exc try: self._client = AsyncMilvusClient(uri=self._uri, token=self._token or None) except Exception as exc: raise RecoverableAgentError("Milvus 画像写客户端初始化失败") from exc return self._client async def load_collection(self, *, collection_name: str) -> None: """把集合载入内存后再查/写。 集合不存在时抛 `RecoverableAgentError`:由 outbox 退避重试并最终判死信, 而不是静默跳过——"集合没建"是装配问题,必须可见。 """ client = await self._ensure() try: await client.load_collection(collection_name=collection_name) except Exception as exc: raise RecoverableAgentError("画像向量集合不可用") from exc async def query(self, **kwargs: Any) -> list[dict[str, Any]]: """按 filter 查询;返回空列表表示无匹配(不是错误)。""" client = await self._ensure() try: raw = await client.query(**kwargs) except Exception as exc: raise RecoverableAgentError("画像向量查询失败") from exc return list(raw or []) async def upsert(self, **kwargs: Any) -> Any: client = await self._ensure() try: return await client.upsert(**kwargs) except RecoverableAgentError: raise except Exception as exc: raise RecoverableAgentError("画像向量写入失败") from exc