Otherone

This product is dedicated to my best her! She loves sunflowers 🌻

🎯 Vision

otherone-agent is not just another AI framework. It's a paradigm shift in how developers build intelligent agents.

We believe AI agent development should be:

• Simple - 8 lines to production
• Powerful - Enterprise-grade features out of the box
• Extensible - Plugin architecture for unlimited possibilities
• Efficient - Intelligent context management saves 80% token costs

The Problem

Current AI frameworks force you to choose between simplicity and power. You either get a toy example that doesn't scale, or a complex enterprise solution that takes weeks to understand.

The Solution

otherone-agent gives you both. Start with 8 lines of code, scale to millions of users.

📦 Installation

npm install otherone-agent

🚀 Quick Start

💡 AI Quick Development Tip: You can send this prompt to AI for rapid development:

"Read this link: https://github.com/wuyoujae/otherone-agent, please help me quickly develop a conversational agent with webui using otherone-agent"

Basic Usage

import { veloca } from 'otherone-agent';

// Create a new conversation
const sessionId = veloca.CreateNewSession();

// First turn
await veloca.InvokeAgent(
    { sessionId, contextLoadType: 'localfile', contextWindow: 128000 },
    {
        provider: 'openai',
        apiKey: process.env.OPENAI_API_KEY,
        baseUrl: 'https://api.openai.com/v1',
        model: 'gpt-4o-mini',
        userPrompt: 'What is 2+2?',
        stream: true
    }
);

// Second turn - automatically loads history
const response = await veloca.InvokeAgent(
    { sessionId, contextLoadType: 'localfile', contextWindow: 128000 },
    {
        provider: 'openai',
        apiKey: process.env.OPENAI_API_KEY,
        baseUrl: 'https://api.openai.com/v1',
        model: 'gpt-4o-mini',
        userPrompt: 'Multiply that by 3',
        stream: true
    }
);

console.log(response.content); // "12"

Usage Example

With Tools

const tools = [{
    type: 'function',
    function: {
        name: 'get_weather',
        description: 'Get current weather',
        parameters: {
            type: 'object',
            properties: {
                location: { type: 'string' }
            }
        }
    }
}];

const tools_realize = {
    get_weather: async (location: string) => {
        return `Weather in ${location}: Sunny, 72°F`;
    }
};

const response = await veloca.InvokeAgent(
    { sessionId, contextLoadType: 'localfile', contextWindow: 128000 },
    {
        provider: 'openai',
        apiKey: process.env.OPENAI_API_KEY,
        baseUrl: 'https://api.openai.com/v1',
        model: 'gpt-4o-mini',
        userPrompt: 'What is the weather in San Francisco?',
        tools,
        tools_realize,
        stream: true
    }
);

That's it. You now have:

• ✅ Multi-turn conversation memory
• ✅ Automatic context management
• ✅ Streaming responses
• ✅ Tool calling support
• ✅ Intelligent context compression
• ✅ Production-ready persistence

📚 Advanced Features

Context Compression

Veloca automatically compresses conversation history when approaching token limits:

const response = await veloca.InvokeAgent(
    {
        sessionId,
        contextLoadType: 'localfile',
        contextWindow: 128000,
        thresholdPercentage: 0.8  // Compress at 80% capacity
    },
    {
        provider: 'openai',
        apiKey: process.env.OPENAI_API_KEY,
        baseUrl: 'https://api.openai.com/v1',
        model: 'gpt-4o-mini',
        userPrompt: 'Continue our conversation...',
        // Compression LLM config (optional)
        compact_llm_model: 'gpt-4o-mini',
        compact_llm_temperature: 0.3,
        stream: true
    }
);

Custom Storage

// Read session data
const sessionData = veloca.ReadSessionData(sessionId);

// Get all sessions
const allSessions = veloca.GetAllSessions();

// Manual entry writing
veloca.WriteEntry({
    storageType: 'localfile',
    sessionId,
    role: 'user',
    content: 'Custom message'
});

🔥 Core Features

🧠 Smart Context Management

• Automatic Compression: Summarizes conversation history when approaching token limits
• Token Estimation: Built-in token counting to help you stay within limits
• Configurable Thresholds: Set when compression should trigger (default 80%)

🔄 Multi-Provider Ready

• OpenAI: Full support with streaming
• Anthropic: Coming soon
• Custom APIs: Extensible architecture for your own LLM

🛠️ Simple Tool Calling

• Easy Definition: Define your tools, we handle the execution loop
• Type Safe: Full TypeScript support for better DX
• Error Handling: Built-in retry and error management

💾 Zero-Config Storage

• Local File: JSON-based storage, no setup required
• Session Management: UUID-based conversation tracking
• History Tracking: Complete audit trail of interactions

🏗️ Why otherone-agent?

Lightweight: No heavy dependencies, just the essentials you need.

Developer-Friendly: Sensible defaults mean you can start with minimal configuration.

Modular: Use only what you need - token estimation, context management, or the full agent loop.

Transparent: Simple, readable code. No magic, no surprises.

✨ Features

• 🚀 Support for streaming and non-streaming responses
• 🔧 Automatic tool loop processing
• 💾 Flexible context management and compression
• 📦 Modular design, easy to extend
• 🔌 Support for multiple AI providers (OpenAI, Anthropic, Fetch)

🎯 Roadmap

✅ Completed

• Core agent loop
• OpenAI integration
• Context management
• Tool calling
• Local file storage
• Streaming support

🚧 In Progress

• MCP server integration
• Skills system
• Web UI

📋 Planned

• More provider support (Anthropic, Claude, etc.)
• Database storage adapter
• Advanced caching strategies
• Plugin marketplace
• ...and more!

📄 License

MIT