memory

🛠️ Complete Tool Usage Reference

Core Memory Tools

1. init_model

interface InitModelParams {
  inputDim?: number; // Default: 768
  hiddenDim?: number; // Default: 512
  memoryDim?: number; // Default: 1024
  transformerLayers?: number; // Default: 6
  numHeads?: number; // Default: 8
  ffDimension?: number; // Default: 2048
  dropoutRate?: number; // Default: 0.1
  maxSequenceLength?: number; // Default: 512
  memorySlots?: number; // Default: 5000
  similarityThreshold?: number; // Default: 0.65
  surpriseDecay?: number; // Default: 0.9
  pruningInterval?: number; // Default: 1000
  gradientClip?: number; // Default: 1.0
}

const response = await callTool("init_model", {
  inputDim: 768,
  memorySlots: 10000,
  transformerLayers: 8,
});

1. forward_pass

interface ForwardPassParams {
  x: number[] | string; // Input vector or text
  memoryState: {
    shortTerm: number[];
    longTerm: number[];
    meta: number[];
    timestamps: number[];
    accessCounts: number[];
    surpriseHistory: number[];
  };
}

const { predicted, memoryUpdate } = await callTool("forward_pass", {
  x: "const x = 5;", // or vector: [0.1, 0.2, ...]
  memoryState: currentMemory,
});

1. train_step

interface TrainStepParams {
  x_t: number[] | string; // Current input
  x_next: number[] | string; // Next input
}

const result = await callTool("train_step", {
  x_t: "function hello() {",
  x_next: "  console.log('world');",
});

1. get_memory_state

interface GetMemoryStateParams {
  type?: string; // Optional memory type filter
}

const state = await callTool("get_memory_state", {});
// Returns:
{
  stats: {
    meanActivation: number;
    patternDiversity: number;
    surpriseScore: number;
    timestamps: number[];
    accessCounts: number[];
  },
  capacity: number;
  status: "active" | "pruning" | "error";
}

1. manifold_step

interface ManifoldStepParams {
  base: number[];    // Base memory state
  velocity: number[]; // Update direction
}

const newBase = await callTool("manifold_step", {
  base: memory.meta,
  velocity: [0.1, 0.2, ...] // or analysis.stats.meanActivation
});