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Persistent Local Memory Engine

Generic chatbots suffer from amnesia. Coral AI implements a sophisticated Local Vector Memory database stored securely on your hard drive.

Core Architecture

How It Works Under The Hood

The Persistent Local Memory Engine module is built on a highly optimized C++ and Python bridge. By bypassing standard Windows UI restrictions, Coral AI directly interfaces with system memory, native Win32 APIs, and DOM structures to achieve near-zero latency execution.

Vector SQLite DB

Stores context locally on your C: drive, ensuring no private facts are uploaded to the cloud.

Dynamic Recall

Automatically queries past memory files when a related task is requested.

Explicit Forget Tools

Total control over what it remembers via the `delete_memory` execution tool.

Workflow Persistence

Can remember sequence of actions to recreate macros instantly.

Diagnostics

Execution Trace

~ > coral execute --module persistent-local-memory-engine --verbose
0.00ms [INFO] Initializing C++ memory hooks... OK
2.14ms [INFO] Bypassing UI thread restrictions... OK
5.89ms [INFO] Allocating vector buffer for LLM context...
8.22ms [WARN] Elevating privileges to Admin ring...
14.01ms >>> Execution payload delivered successfully.

Technical Specs

  • Latency< 15ms
  • RuntimeC++ / Py 3.11
  • PrivilegeRing 3 / Admin
  • Offline ModeRequires Internet

Agentic Integration

This module does not operate in isolation. It is dynamically invoked by the Coral PlannerAgent via JSON-RPC, allowing it to be chained endlessly with vision and memory modules.