Zen - An Advanced Conversational LLM Framework

Table of Contents

• Overview
• Core Features
• Extension Points
• Quick Start

Overview

Zen is a highly modular AI conversation engine built in Go that emphasizes pluggable architecture and platform independence. It provides a flexible foundation for building conversational systems through:

• Plugin-based architecture with hot-swappable components
• Multi-provider LLM support (OpenAI, custom providers)
• Cross-platform conversation management
• Extensible manager system for custom behaviors
• Vector-based semantic storage with pgvector

Core Features

Plugin Architecture

• Manager System: Extend functionality through custom managers
  • Insight Manager: Extracts and maintains conversation insights
  • Personality Manager: Handles response behavior and style
  • Custom Managers: Add your own specialized behaviors

State Management

• Shared State System: Centralized state management across components
  • Manager-specific data storage
  • Custom data injection
  • Cross-manager communication

LLM Integration

• Provider Abstraction: Support for multiple LLM providers
  • Built-in OpenAI support
  • Extensible provider interface for custom LLMs
  • Configurable model selection per operation
  • Automatic fallback and retry handling

Platform Support

• Platform Agnostic Core:
  • Abstract conversation engine independent of platforms
  • Built-in support for CLI chat and Twitter
  • Extensible platform manager interface
  • Example implementations for new platform integration

Storage Layer

• Flexible Data Storage:
  • PostgreSQL with pgvector for semantic search
  • GORM-based data models
  • Customizable fragment storage
  • Vector embedding support

Toolkit/Function System

• Pluggable Tool/Function Integration:
  • Support for custom tool implementations
  • Built-in toolkit management
  • Function calling capabilities
  • Automatic tool response handling
  • State-aware tool execution

Extension Points

1. LLM Providers: Add new AI providers by implementing the LLM interface

type Provider interface {
    GenerateCompletion(context.Context, CompletionRequest) (string, error)
    GenerateJSON(context.Context, JSONRequest, interface{}) error
    EmbedText(context.Context, string) ([]float32, error)
}

2. Managers: Create new behaviors by implementing the Manager interface

type Manager interface {
    GetID() ManagerID
    GetDependencies() []ManagerID
    Process(state *state.State) error
    PostProcess(state *state.State) error
    Context(state *state.State) ([]state.StateData, error)
    Store(fragment *db.Fragment) error
    StartBackgroundProcesses()
    StopBackgroundProcesses()
    RegisterEventHandler(callback EventCallbackFunc)
    triggerEvent(eventData EventData)
}

Quick Start

1. Clone the repository

git clone https://github.com/soralabs/zen

2. Copy .env.example to .env and configure your environment variables
3. Install dependencies:

go mod download

4. Run the chat example:

go run examples/chat/main.go

6. Run the Twitter bot:

go run examples/twitter/main.go

Environment Variables

DB_URL=postgresql://user:password@localhost:5432/zen
OPENAI_API_KEY=your_openai_api_key

Platform-specific credentials as needed

Architecture

The project follows a clean, modular architecture:

• engine: Core conversation engine
• manager: Plugin manager system
• state: Shared state management
• llm: LLM provider interfaces
• examples/: Reference implementations