AuraSDK
AuraSDK turns fragile prompt-only agents into auditable, memory-aware, production-ready systems
Deterministic · No fine-tuning · No cloud training · <1ms recall · ~3 MB
Your AI model is smart. But it forgets everything after every conversation.
AuraSDK is a local cognitive runtime that runs alongside any frozen model. It gives agents durable memory, explainability, governed correction, bounded recall reranking, and bounded self-adaptation through experience — all locally, without fine-tuning or cloud training.
pip install aura-memoryfrom aura import Aura, Level
brain = Aura("./agent_memory")
brain.enable_full_cognitive_stack() # activate all four bounded reranking overlays
# store what happens
brain.store("User always deploys to staging first", level=Level.Domain, tags=["workflow"])
brain.store("Staging deploy prevented 3 production incidents", level=Level.Domain, tags=["workflow"])
# recall — local retrieval with optional bounded cognitive reranking
context = brain.recall("deployment decision") # <1ms, no API call
# inspect advisory hints produced from stored evidence
hints = brain.get_surfaced_policy_hints()
# → [{"action": "Prefer", "domain": "workflow", "description": "deploy to staging first"}]
