KAIKO EQ+ Agent Framework

KAIKO extends the ElizaOS framework with advanced emotional intelligence (EQ+) and custom database systems for sophisticated AI agent interactions.

Overview

KAIKO's implementation enhances ElizaOS with:

  • 🧠 EQ+ System - Advanced emotional intelligence and pattern recognition

  • 🔄 Neo4j Integration - Graph-based memory and emotional context storage

  • 🎯 Adaptive TDL - Trait-directed learning with emotional awareness

  • 📊 Enhanced Memory System - Sophisticated state management with emotional context

  • 🔌 API Integration Framework - Emotion-aware API interactions

Key Components

1. EQ+ Emotional Intelligence

The EQ+ system provides:

  • Emotional state tracking and analysis

  • Complex emotion derivation

  • Emotional memory persistence

  • Adaptive response strategies

  • Emotional pattern recognition

2. Custom Database Architecture

KAIKO implements:

  • Neo4j-based emotional memory storage

  • Graph relationships for context tracking

  • Efficient embedding search

  • Temporal decay for emotional memories

  • Custom entity type support

3. Enhanced Agent Runtime

Extensions to ElizaOS include:

  • Emotional context in agent responses

  • Trait-emotion mapping

  • Adaptive behavior based on emotional patterns

  • Enhanced memory retrieval with emotional context

Quick Links

Basic Integration Example

Here's a minimal example of integrating an API with emotional awareness:

import { IAgentRuntime, EmotionalContextService } from '@kaiko/core';
import { YourExistingAPIClient } from './your-api';

class EmotionalAPIAdapter {
  private emotionalContext: EmotionalContextService;

  constructor(
    private client: YourExistingAPIClient,
    private runtime: IAgentRuntime
  ) {
    this.emotionalContext = runtime.eqplus.contextService;
  }
  
  async executeRequest(method: string, params: any) {
    // Get current emotional context
    const emotions = await this.emotionalContext.getCurrentState();
    
    // Execute request with emotional awareness
    const result = await this.client.request(method, params);
    
    // Store response with emotional context
    await this.runtime.eqplus.memoryManager.storeMemory({
      content: result,
      emotionalContext: emotions,
      type: 'api_response'
    });
    
    return result;
  }
}

Architecture Overview

graph TB
    A[Agent Runtime] --> B[EQ+ System]
    A --> C[Neo4j Memory]
    B --> D[Emotion Classifier]
    B --> E[Emotional Context]
    B --> F[Adaptive TDL]
    C --> G[Graph Storage]
    C --> H[Embedding Search]
    E --> I[Response Generation]
    F --> I

Getting Started

  1. Install the KAIKO core package:

npm install @kaiko/core

  1. Configure EQ+ system:

import { createKaikoRuntime } from '@kaiko/core';

const runtime = await createKaikoRuntime({
  eqplus: {
    enabled: true,
    emotionalAnalysis: true,
    adaptiveTDL: true
  },
  neo4j: {
    uri: process.env.NEO4J_URI,
    username: process.env.NEO4J_USERNAME,
    password: process.env.NEO4J_PASSWORD
  }
});

Key Features

Emotional Intelligence

  • Real-time emotion classification

  • Complex emotion derivation

  • Emotional pattern recognition

  • Adaptive response strategies

Memory System

  • Graph-based emotional memories

  • Temporal context awareness

  • Efficient similarity search

  • Automatic memory decay

Integration Capabilities

  • Emotion-aware API adapters

  • Contextual action handlers

  • Emotional state persistence

  • Pattern-based learning

Documentation Structure

  1. Core Concepts

    • EQ+ System Architecture

    • Emotional Memory Management

    • Adaptive TDL System

    • Neo4j Integration

  2. Implementation Guides

    • Creating Emotional Adapters

    • Configuring Memory Systems

    • Implementing Custom Actions

    • Testing and Monitoring

  3. API Reference

    • Core Interfaces

    • Emotional Types

    • Utility Functions

    • Database Schemas

This documentation is specific to KAIKO's implementation of ElizaOS. For general ElizaOS documentation, visit docs.elizaos.com.

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