JavaScript AI Agents Framework

A production-ready Multi AI Agents framework for JavaScript

PraisonAI is a production-ready Multi AI Agents framework for JavaScript, designed to create AI Agents to automate and solve problems ranging from simple tasks to complex challenges. It provides a low-code solution to streamline the building and management of multi-agent LLM systems, emphasising simplicity, customisation, and effective human-agent collaboration.

Diagram

JavaScript

Quick Start

Simple Usage
npm
```
npm install praisonai
```
yarn
```
yarn add praisonai
```

With Configuration

bash

export OPENAI_API_KEY=xxxxxxxxxxxxxxxxxxxxxx

Create File

Create app.js file

## Code Example

Single Agent

const { Agent } = require('praisonai');
const agent = new Agent({ instructions: 'You are a helpful AI assistant' });
agent.start('Write a movie script about a robot in Mars');

Multi Agents

const { Agent, Agents } = require('praisonai');

const researchAgent = new Agent({ instructions: 'Research about AI' });
const summariseAgent = new Agent({ instructions: 'Summarise research agent\'s findings' });

const agents = new AgentTeam({ agents: [researchAgent, summariseAgent] });
agents.start();

Run Script
bash
```
node app.js
```

Usage Examples

Single Agent Example

Create and run a single agent to perform a specific task:

javascript

const { Agent } = require('praisonai');

// Create a simple science explainer agent
const agent = new Agent({
  instructions: "You are a science expert who explains complex phenomena in simple terms.",
  name: "ScienceExplainer",
  verbose: true
});

// Ask a question
agent.start("Why is the sky blue?")
  .then(response => {
    console.log('\nExplanation:');
    console.log(response);
  })
  .catch(error => console.error('Error:', error));

Multi-Agent Example

Create and run multiple agents working together:

javascript

const { Agents, Agent } = require('praisonai');

// Create a story agent and a summary agent
const storyAgent = new Agent({
  instructions: "You are a creative storyteller. Create engaging stories.",
  name: "Storyteller"
});

const summaryAgent = new Agent({
  instructions: "You summarize stories into brief, engaging summaries.",
  name: "Summarizer"
});

// Create multi-agent system
const agents = new AgentTeam({
  agents: [storyAgent, summaryAgent],
  tasks: [
    "Create a short story about a magical forest",
    "Summarize the story in 2 sentences"
  ]
});

// Run the agents
agents.start()
  .then(responses => {
    console.log('\nStory:');
    console.log(responses[0]);
    console.log('\nSummary:');
    console.log(responses[1]);
  })
  .catch(error => console.error('Error:', error));

Task-Based Agent Example

Create agents with specific tasks and dependencies:

javascript

const { Agent } = require('praisonai');

// Create a task-based agent
const agent = new Agent({
  name: "TaskMaster",
  role: "Assistant",
  goal: "Complete tasks efficiently",
  instructions: "You are an AI assistant that helps complete tasks step by step."
});

// A task is a plain object — agent.execute reads its description
const mainTask = {
  name: "Write Blog Post",
  description: "Write a blog post about artificial intelligence",
  expectedOutput: "A complete blog post"
};

// Execute the task
agent.execute(mainTask)
  .then(response => {
    console.log('\nBlog Post:');
    console.log(response);
  })
  .catch(error => console.error('Error:', error));

Running the Examples

Set Environment Variables
bash
```
export OPENAI_API_KEY='your-api-key'
```
Create Example File
Create a new JavaScript file (e.g., app.js) with any of the above examples.
Run the Example
bash
```
node app.js
```

TypeScript

TypeScript overview

Getting Started

Getting Started overview

JavaScript AI Agents Framework

JavaScript

Quick Start

Usage Examples

Running the Examples

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