Brain-AI Memory v0.4.0

Brain-AI Memory v0.4.0 centers the public package on its implemented core: an installable, local, provider-neutral reference kernel for typed operational memory in long-running agents.

Highlights

• Ontology v3 requires explicit memory or control categories, validates category values, and reports observable counts; the bundled schema declares the canonical five-memory plus two-supporting-control split.
• Optional entity scope now reaches harness and fallback sequence gates, so supplied entity-bound rules are evaluated at the execution boundary.
• Ablation reproducibility now verifies normalized semantic outcomes and recorded-source provenance for the ten tested mechanisms.
• English and Korean documentation, the graphical abstract, and the social preview now separate the managed-memory path from the optional memory-to-action bridge.
• Runtime, package metadata, and citation versions now share a CI-verified release contract.

Compatibility

Custom ontology v2 files must add category: memory or category: control to every component before upgrading.

Evidence boundary

The 20/20 versus 1/20 ablation result is authored contract conformance, not evidence of better LLM answer quality or superiority over RAG. Automatic transcript ingestion, token-budgeted context injection, autonomous lifecycle scheduling, physical deletion, and production action enforcement remain host responsibilities.

Download the wheel below and install it with:

python -m pip install ./brain_ai_memory-0.4.0-py3-none-any.whl