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 { tool } from "llamaindex";
import { agent } from "@llamaindex/workflow";
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.data.result); // Baby Llama is called criaEvent Streaming
Agent Workflows provide a unified interface for event streaming, making it easy to track and respond to different events during execution:
import { agentToolCallEvent, agentStreamEvent } from "@llamaindex/workflow";
// Get the workflow execution context
const events = jokeAgent.runStream("Tell me something funny");
// Stream and handle events
for await (const event of events) {
if (agentToolCallEvent.include(event)) {
console.log(`Tool being called: ${event.data.toolName}`);
}
if (agentStreamEvent.include(event)) {
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 agentdescription: Purpose description used for task routingtools: Array of tools the agent can usecanHandoffTo(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 { tool } from "llamaindex";
import { multiAgent, agent } from "@llamaindex/workflow";
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"
);
console.log(result.data.result);The workflow will coordinate between agents, allowing them to handle different aspects of the request and hand off tasks when appropriate.
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