Agent-native database with causal memory, composite-scored recall, and storage-layer policy enforcement
Project description
meta-agents-db
Agent-native database with causal memory, composite-scored recall, and storage-layer policy enforcement.
The first database designed for autonomous AI agents.
Install
pip install meta-agents-db
Quick start
from meta_agents_db import MetaAgentsDB
db = MetaAgentsDB("./data")
event_id = db.write(content="SPY broke below 200-day MA", tags=["signal", "SPY"])
results = db.recall("SPY bearish signals", top_k=10)
chain = db.trace_cause(event_id, direction="backward", max_depth=5)
Features
- Causal DAG — every memory links to its causes; trace full decision chains
- 5-signal composite recall — vector similarity + recency + causal proximity + importance + tag overlap
- Storage-layer policy — risk caps, budget caps, rate limits enforced at write time
- HNSW vector index — sub-millisecond approximate nearest neighbor search
- Session caching — deduplicates repeated recalls within a pipeline cycle
- MVCC — snapshot isolation for concurrent readers/writers
- WAL + SSTables — crash-safe append-only log with background compaction
License
Apache-2.0
Project details
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