v1.0.0 — Initial Architecture Release

Overview

v1.0.0 marks the first stable release of the Local-first AI Memory System.

This project demonstrates a schema-driven architecture for converting raw dialog into structured memory artifacts that can be deterministically rebuilt over time.

The system is designed as a transparent and reproducible memory pipeline rather than a black-box storage mechanism.

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Architecture Highlights

• Contract-first memory artifacts using stable JSON schemas
• Dialog → Facts → Topic Memory → Global Memory pipeline
• Append-only storage model enabling deterministic rebuilds
• Versioned prompt specifications acting as schema compilers
• Local-first design without dependency on external vector databases

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Key Design Principles

Rebuildable Memory

Higher-level memory layers can always be regenerated from lower-level artifacts.

Schema Stability

All outputs follow explicit JSON contracts to prevent format drift.

Append-only Traceability

Every memory entry remains auditable and reproducible.

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Repository Structure

memory/
├─ src/memory_app/          Core memory pipeline implementation
├─ prompts/                 Versioned prompt definitions
├─ examples/                Example dialogs and generated artifacts
├─ docs/                    Architecture documentation
├─ settings.json            System configuration template
└─ README.md                Project overview

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Intended Use

This repository is primarily intended as:

• a reference architecture for AI memory systems
• an example of schema-driven LLM pipelines
• a demonstration of AI systems engineering practices

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Future Directions

Potential future iterations may include:

• evaluation pipelines for memory extraction quality
• structured memory query interfaces
• integration with AI workflow orchestration systems

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Initial development completed in 16 days as a focused architecture prototype.