o-reasonable

O-Reasonable 🧠

A lightweight reasoning agent designed to mimic logical planning and problem-solving capabilities using cost-effective OpenAI models. It generates step-by-step plans, executes them sequentially, and synthesizes a final answer.

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Features

• 🎯 Dynamic model selection with sensible defaults
• 📋 Structured step-by-step planning
• 🔄 Sequential execution of reasoning steps
• 🎨 Clean and informative console output
• ⚡ Built with TypeScript and Vite

Installation

npm install o-reasonable

Configuration

You'll need to set up your OpenAI API key as an environment variable:

export OPENAI_API_KEY=your-api-key-here

Or create a .env file in your project root:

OPENAI_API_KEY=your-api-key-here

Usage

import { runAgent } from 'o-reasonable';

// Basic usage with default model (logs enabled by default)
const result = await runAgent("What would be the impact of implementing a four-day work week?");

// Using a custom model with logs disabled
const result = await runAgent("Analyze the pros and cons of remote work", {
  model: "gpt-4o-mini",
  enableLogs: false
});

// The result contains steps and final answer
console.log(result.steps);         // Array of step results
console.log(result.finalQuestion); // The final question asked
console.log(result.finalAnswer);   // The final synthesized answer

Configuration Options

The runAgent function accepts a configuration object with the following options:

interface OReasonableConfig {
  model?: string;     // OpenAI model to use (default: "gpt-4o-mini")
  apiKey?: string;    // Optional API key override
  baseURL?: string;   // Custom base URL for OpenAI-compatible APIs
  enableLogs?: boolean; // Enable/disable console logs (default: false)
}

Using OpenAI-Compatible APIs

O-Reasonable supports any OpenAI-compatible API by specifying a custom baseURL. Here are some examples:

Local Models (Ollama, LM Studio, etc.)

import { runAgent } from 'o-reasonable';

// Using Ollama with a local model
const result = await runAgent("Explain quantum computing", {
  baseURL: "http://localhost:11434/v1",
  model: "llama2", // or any model available in Ollama
  apiKey: "ollama" // Ollama requires any non-empty key
});

// Using LM Studio
const result = await runAgent("What are the benefits of TypeScript?", {
  baseURL: "http://localhost:1234/v1",
  model: "local-model",
  apiKey: "lm-studio"
});

Azure OpenAI

const result = await runAgent("Analyze market trends", {
  baseURL: "https://your-resource.openai.azure.com",
  model: "gpt-35-turbo", // Azure deployment name
  apiKey: process.env.AZURE_OPENAI_API_KEY
});

Other OpenAI-Compatible Providers

// Example with any OpenAI-compatible service
const result = await runAgent("Create a project plan", {
  baseURL: "https://api.your-provider.com/v1",
  model: "your-model-name",
  apiKey: "your-api-key"
});

Return Type

The runAgent function returns a promise that resolves to an AgentResult:

interface AgentResult {
  steps: string[];      // Results from each reasoning step
  finalQuestion: string; // The final question that was asked
  finalAnswer: string;  // The synthesized final answer
}

Development

To set up the development environment:

git clone https://github.com/chihebnabil/o-reasonable.git
cd o-reasonable
npm install
npm run dev

Building

npm run build

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT

Credits

Created with ❤️ by Chiheb Nabil