Agent Workflows

Agent Workflows are a powerful system that enables you to create and orchestrate one or multiple agents with tools to perform specific tasks. It's built on top of the base Workflow system and provides a streamlined interface for agent interactions.

Usage

Single Agent Workflow

The simplest use case is creating a single agent with specific tools. Here's an example of creating an assistant that tells jokes:

import { agent, tool } from "llamaindex";
import { openai } from "@llamaindex/openai";
 
// Define a joke-telling tool
const jokeTool = tool(
  () => "Baby Llama is called cria",
  {
    name: "joke",
    description: "Use this tool to get a joke",
  }
);
 
// Create an single agent workflow with the tool
const jokeAgent = agent({
  tools: [jokeTool],
  llm: openai({ model: "gpt-4o-mini" }),
});
 
// Run the workflow
const result = await jokeAgent.run("Tell me something funny");
console.log(result); // Baby Llama is called cria

Event Streaming

Agent Workflows provide a unified interface for event streaming, making it easy to track and respond to different events during execution:

import { AgentToolCall, AgentStream } from "llamaindex";
 
// Get the workflow execution context
const context = workflow.run("Tell me something funny");
 
// Stream and handle events
for await (const event of context) {
  if (event instanceof AgentToolCall) {
    console.log(`Tool being called: ${event.data.toolName}`);
  }
  if (event instanceof AgentStream) {
    process.stdout.write(event.data.delta);
  }
}

Multi-Agent Workflow

An Agent Workflow can orchestrate multiple agents, enabling complex interactions and task handoffs. Each agent in a multi-agent workflow requires:

name: Unique identifier for the agent
description: Purpose description used for task routing
tools: Array of tools the agent can use
canHandoffTo (optional): Array of agent names or agent instances that this agent can delegate tasks to

Here's an example of a multi-agent system that combines joke-telling and weather information:

import { multiAgent, agent, tool } from "llamaindex";
import { openai } from "@llamaindex/openai";
import { z } from "zod";
 
// Create a weather agent
const weatherAgent = agent({
  name: "WeatherAgent",
  description: "Provides weather information for any city",
  tools: [
    tool(
      {
        name: "fetchWeather",
        description: "Get weather information for a city",
        parameters: z.object({
          city: z.string(),
        }),
        execute: ({ city }) => `The weather in ${city} is sunny`,
      }
    ),
  ],
  llm: openai({ model: "gpt-4o-mini" }),
});
 
// Create a joke-telling agent
const jokeAgent = agent({
  name: "JokeAgent",
  description: "Tells jokes and funny stories",
  tools: [jokeTool], // Using the joke tool defined earlier
  llm: openai({ model: "gpt-4o-mini" }),
  canHandoffTo: [weatherAgent], // Can hand off to the weather agent
});
 
// Create the multi-agent workflow
const agents = multiAgent({
  agents: [jokeAgent, weatherAgent],
  rootAgent: jokeAgent, // Start with the joke agent
});
 
// Run the workflow
const result = await agents.run(
  "Give me a morning greeting with a joke and the weather in San Francisco"
);

The workflow will coordinate between agents, allowing them to handle different aspects of the request and hand off tasks when appropriate.

Agent Workflows

Usage

Single Agent Workflow

Event Streaming

Multi-Agent Workflow

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