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.