AgentTeam

Multi-agent orchestration with sequential or parallel execution

AgentTeam coordinates multiple agents working together, executing tasks sequentially or in parallel.

AgentTeam replaces Agents and PraisonAIAgents as the recommended class name. The old names still work as silent aliases.

Quick Start

1. Install

   npm install praisonai
   
2. Create Team

   import { Agent, AgentTeam } from 'praisonai';
   
   const researcher = new Agent({
     name: 'Researcher',
     instructions: 'Research the topic thoroughly'
   });
   
   const writer = new Agent({
     name: 'Writer',
     instructions: 'Write based on research findings'
   });
   
   const team = new AgentTeam({
     agents: [researcher, writer]
   });
   
   const results = await team.start();
   

---

How It Works

Mode	Behavior
Sequential	Each agent runs after the previous completes, sharing context
Parallel	All agents run simultaneously, results collected together

---

Configuration Options

import { Agent, AgentTeam } from 'praisonai';

const team = new AgentTeam({
  agents: [agent1, agent2],
  tasks: ['Research AI trends', 'Write summary'],
  process: 'sequential',
  verbose: true,
  pretty: true
});

Option	Type	Default	Description
agents	Agent[]	required	Array of agents to orchestrate
tasks	string[]	[]	Custom tasks for each agent
process	'sequential' | 'parallel'	'sequential'	Execution mode
verbose	boolean	true	Enable logging output
pretty	boolean	false	Enable formatted output
llm	string	Agent default	Default LLM for all agents

---

Common Patterns

Array Syntax

import { Agent, AgentTeam } from 'praisonai';

const agent1 = new Agent({ instructions: 'Analyze data' });
const agent2 = new Agent({ instructions: 'Summarize analysis' });

// Simple array syntax
const team = new AgentTeam([agent1, agent2]);
const results = await team.start();

Sequential

const team = new AgentTeam({
  agents: [researcher, analyst, writer],
  process: 'sequential'
});

// Research → Analysis → Writing
const results = await team.start();

Parallel

const team = new AgentTeam({
  agents: [sentimentAgent, summaryAgent, keywordsAgent],
  process: 'parallel',
  tasks: [
    'Analyze sentiment: "Great product!"',
    'Summarize: "Great product!"',
    'Extract keywords: "Great product!"'
  ]
});

// All run simultaneously
const [sentiment, summary, keywords] = await team.start();

With Custom Tasks

const team = new AgentTeam({
  agents: [agent1, agent2],
  tasks: [
    'Research the latest AI developments',
    'Write a blog post based on the research'
  ]
});

const results = await team.start();

---

Best Practices

Use sequential for dependent tasks

When agents need context from previous agents, use sequential mode.

const team = new AgentTeam({
  agents: [researcher, writer],
  process: 'sequential'  // Writer gets research context
});

Use parallel for independent analysis

When tasks are independent, parallel mode is faster.

const team = new AgentTeam({
  agents: [analyzer1, analyzer2, analyzer3],
  process: 'parallel'  // All analyze simultaneously
});

Match tasks to agents

Provide one task per agent for explicit control.

const team = new AgentTeam({
  agents: [agent1, agent2, agent3],
  tasks: ['Task 1', 'Task 2', 'Task 3']
});

---

Backward Compatibility

All old names work as silent aliases with no deprecation warnings.

// All of these are equivalent
import { AgentTeam, Agents, PraisonAIAgents } from 'praisonai';

const team1 = new AgentTeam([agent1, agent2]);
const team2 = new Agents([agent1, agent2]);
const team3 = new PraisonAIAgents([agent1, agent2]);

// They are the same class
console.log(AgentTeam === Agents);           // true
console.log(AgentTeam === PraisonAIAgents);  // true

---

Related

Agent

Single agent documentation

AgentFlow

Step-based workflows

AgentOS

Deploy as web service