Spaces:
Running
Running
| """Long_term — Qdrant-backed long-term memory interface. | |
| Provides the process-wide MemoryRetriever singleton over vector_memory.py; | |
| long-term records live only in Qdrant, while per-day short-term files are | |
| summarized and indexed at day handoff. | |
| Architecture: consumed by brain.py and the engine for retrieval; paired | |
| with Short_term.py (operational memory) and vector_memory.py (storage). | |
| Design: deliberately no JSON archive reader — Qdrant is the single | |
| long-term source of truth. | |
| """ | |
| from __future__ import annotations | |
| from typing import List, Optional, Protocol, runtime_checkable | |
| from src.core.log import get_logger | |
| logger = get_logger(__name__) | |
| class MemoryRetriever(Protocol): | |
| """Contract consumed by planning, conversation, and tick cognition.""" | |
| def store(self, agent_id: str, text: str, *, kind: str = "observation", | |
| importance: Optional[float] = None, date_str: Optional[str] = None) -> None: ... | |
| def retrieve(self, agent_id: str, query: str, k: int = 5) -> List[str]: ... | |
| def rolling_summary(self, agent_id: str, days: int = 3, | |
| before_date: Optional[str] = None) -> Optional[str]: ... | |
| _retriever_singleton: Optional[MemoryRetriever] = None | |
| def get_retriever() -> MemoryRetriever: | |
| """Return the process-wide Qdrant retriever. | |
| The retriever is intentionally fail-soft for reads: an unavailable cloud | |
| service yields no recalled context rather than allowing a memory outage to | |
| stop the simulation. It never reads a local long-term JSON archive. | |
| """ | |
| global _retriever_singleton | |
| if _retriever_singleton is None: | |
| from src.agents.vector_memory import VectorMemoryRetriever | |
| _retriever_singleton = VectorMemoryRetriever() | |
| logger.info("[Long_term] using Qdrant-only long-term memory") | |
| return _retriever_singleton | |