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JuniorMemSys-Suite v0.4.0

Sovereign Topological Memory Palace SDK

Apple Silicon Native · MLX-first · TDA + SVD · Bit Drift Inference · MCP Ready

JuniorMemSys-Suite is a production-grade topological memory system built for AI agents and enterprises. It combines Topological Data Analysis (TDA), Singular Value Decomposition (SVD), and Bit Drift quantization to create memory retrieval systems that are:

  • Power-efficient on Apple Silicon
  • Logic-dense and enterprise-auditable
  • Language-agnostic (Python SDK, Swift client, MCP-compatible)

🚀 Quick Start

1. Installation

git clone https://github.com/cloudcover95/JuniorMemSys-Suite
cd JuniorMemSys-Suite
pip install -e ".[dev,playground,benchmarks]"

2. Bootstrap the Node

The omega_boot.sh script handles environment alignment and target service initialization.

./omega_boot.sh --ui          # Launch Streamlit / Gradio TDA Sandbox
./omega_boot.sh --grpc        # Start gRPC receiver for Swift TrueDepth/ARKit
./omega_boot.sh --web         # Start FastAPI MCP / WebRTC bridge

🛠 Architecture & Directory Tree

JuniorMemSys-Suite/
├── 📦 junior_memsys_suite/          # Core installable SDK
│   ├── core/                        # TDA Engine & Math Kernels
│   │   ├── palace.py                # MemoryPalace logic (Provenance + Storage)
│   │   ├── tda_mesh.py              # SVD + Bit Drift Manifolds
│   │   ├── encoder.py               # MLX-Native Sovereign Encoder
│   │   └── audit.py                 # Enterprise Integrity & Benchmark Engine
│   └── pipelines/                   # Data integration layer (DatasetMiner, Chunker)
├── 🖥️ playground/                   # Streamlit Dashboard & Globe Brain Viz
├── 🔬 benchmarks/                    # LongMemEval QA & Scaling Tests
├── 🛠️ scripts/                       # Harvester, Kernel Builders, and Seeders
└── server.py                        # MCP Protocol / FastAPI Server

⚖️ Technical Baseline

JuniorMemSys utilizes Bit Drift instead of cosine similarity. Tensors are projected via SVD and quantized to a ±1 binary signature. Retrieval computes the mean Feature Distance across the manifold, enabling sub-millisecond lookups on embedded systems.

Example: Storing a Memory

from junior_memsys_suite.core import MemoryPalace

palace = MemoryPalace()

palace.store(
    wing="alpha", 
    hall="directives", 
    room="root_node",
    content="Optimize for power-efficient, logic-dense engineering.",
    z_score=2.5
)

📡 Integration Points

1. Native Python SDK

Import and use directly in your agent loops.

2. MCP Tool Integration

JuniorMemSys serves as a native tool for Claude or Cursor. Connect to the local node:

GET http://localhost:8000/mcp/tools

3. Server Integrity Audit

Prove data consistency across your memory fabric:

junior-memsys audit --wing alpha

🗺 Roadmap (v0.5+)

  • Incremental Indexing: Automated file-watching and delta-etching
  • Distributed Swarm: Local mesh synchronization across multi-agent clusters (Orange Pi/Linux)
  • Native Swift SDK: Direct TrueDepth/ARKit memory capture
  • Quantum Kernel Mode: Adaptive bit-width for constrained devices

📝 License

MIT License — See LICENSE file for details.

About

High-fidelity Topological Memory Palace SDK. Uses Bit Drift & TDA Meshes via the Sovereign Omni Math kernel. Optimized for M4 Apple Silicon & Starlink edge nodes.

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