Tasks - PraisonAI

Tasks define specific work for agents to complete with clear objectives.

Quick Start

Simple Usage

import { Agent, Task } from 'praisonai';

const agent = new Agent({
  instructions: 'You research and summarize topics'
});

const task = new Task({
  description: 'Research AI trends in 2024',
  agent: agent
});

const result = await task.execute();
console.log(result.output);

With Configuration

const task = new Task({
  description: 'Analyze sales data',
  expectedOutput: 'A summary with top 3 insights',
  agent: analyst
});

User Interaction Flow

Configuration Levels

// Level 1: String - Simple description
const task = new Task({
  description: 'Write a blog post about AI',
  agent: writer
});

// Level 2: Dict - With options
const task = new Task({
  description: 'Write a blog post',
  expectedOutput: '500 words, engaging tone',
  agent: writer
});

// Level 3: Instance - Full control
const task = new Task({
  description: 'Write a blog post',
  expectedOutput: '500 words',
  agent: writer,
  context: [researchTask],  // Use output from other tasks
  callback: (result) => console.log('Done!')
});

Task Options

Option	Description
`description`	What the task should accomplish
`expectedOutput`	Format/structure of result
`agent`	Agent assigned to the task
`context`	Other tasks to use as input
`async`	Run without blocking

API Reference

TaskConfig

Task configuration options

Task

Task class documentation

Best Practices

Be specific in descriptions

“Write 500-word blog post about AI benefits” beats “Write about AI”.

Define expected output

Telling the agent what format you want improves results.

Use context for dependencies

Chain tasks by passing earlier outputs as context.

Workflows

Multi-step workflows

Teams

Multi-agent teams

​Quick Start

​User Interaction Flow

​Configuration Levels

​Task Options

​API Reference