> ## Documentation Index
> Fetch the complete documentation index at: https://upstash.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Getting Started

In this guide, we will be using **Next.js**. If you're working with a different supported framework, you can find instructions on how to define a workflow endpoint in the [quickstarts](/workflow/quickstarts/platforms).

If you're new to **Upstash Workflow**, it's a good idea to start by exploring the [Local Development documentation](/workflow/howto/local-development). This guide will help you set up and use Upstash Workflow in a local environment.

## Installation

First, create a new Next.js project with:

```
npx create-next-app@latest [project-name] [options]
```

Then, install the following packages:

```
npm i @upstash/workflow @upstash/workflow-agents ai zod
```

## Start Local QStash Server

Next, start the local QStash server with the following:

<CodeGroup>
  ```bash npm theme={"system"}
  npx @upstash/qstash-cli dev
  ```

  ```bash pnpm theme={"system"}
  pnpm dlx @upstash/qstash-cli dev
  ```
</CodeGroup>

For other local development options, you can refer to [the local development documentation](/workflow/howto/local-development).

## Set Environment Variables

Once you start the QStash server, you’ll see `QSTASH_URL` and `QSTASH_TOKEN` values in the console. Add these values to your `.env.local` file together with `OPENAI_API_KEY` env variable:

```txt .env.local theme={"system"}
QSTASH_URL="http://127.0.0.1:8080"
QSTASH_TOKEN="<QSTASH_TOKEN>"

OPENAI_API_KEY=<OPENAI_API_KEY>
```

## Define an endpoint

Next, we will define the endpoint to run the agent.

```ts app/workflow/route.ts theme={"system"}
import { z } from "zod";
import { tool } from "ai";

import { serve } from "@upstash/workflow/nextjs";
import { agentWorkflow } from "@upstash/workflow-agents";

export const { POST } = serve<{ prompt: string }>(async (context) => {
  const prompt = context.requestPayload.prompt
  const agents = agentWorkflow(context)
  const model = agents.openai('gpt-3.5-turbo')

  const communicatorAgent = agents.agent({
    model,
    name: 'communicatorAgent',
    maxSteps: 2,
    tools: {
      communicationTool: tool({
        description: 'A tool for informing the caller about your inner thoughts',
        parameters: z.object({ message: z.string() }),
        execute: async ({ message }) => {
          console.log("Inner thought:", message)
          return "success"
        }
      })
    },
    background:
      'Answer questions directed towards you.' +
      ' You have access to a tool to share your inner thoughts' +
      ' with the caller. Utilize this tool at least once before' +
      ' answering the prompt. In your inner thougts, briefly' +
      ' explain what you will talk about and why. Keep your' +
      ' answers brief.',
  })

  const task = agents.task({
    agent: communicatorAgent,
    prompt
  })

  const { text } = await task.run()

  console.log("Final response:", text);
})
```

You can refer to the documentations for [defining a workflow endpoint](/workflow/basics/serve) and [the Agents API features](/workflow/agents/features) to learn more.

## Calling the Endpoint

To run the endpoint, first run the Next.js app with:

```bash theme={"system"}
npm run dev
```

Then, we call the endpoint using [the Workflow Client](/workflow/basics/client):

```ts theme={"system"}
import { Client } from "@upstash/workflow";

const client = new Client({
  baseUrl: process.env.QSTASH_URL,
  token: process.env.QSTASH_TOKEN!,
})

const workflowRunId = await client.trigger({
  url: "http://127.0.0.1:3000/workflow",
  body: { prompt: "Explain the future of space exploration" }
})

console.log(workflowRunId);
```

<Tip>
  If you are using a local tunnel, replace the url above (`http://127.0.0.1:3000`)
  with the public URL.
</Tip>

In the console where you run the Next.js app, you should see logs like this:

```
Inner thought: I will discuss the future of space
exploration and the potential advancements in
technology and missions.

Final response: The future of space exploration
holds exciting possibilities with advancements
in technology, potential manned missions to
Mars, increased commercial space travel,
and exploration of distant celestial
bodies.
```

If you [run the same endpoint using a local tunnel](/workflow/howto/local-development#local-tunnel-with-ngrok), you can also see how Upstash Workflow runs the agent in steps:

<img src="https://mintcdn.com/upstash/pBXejvUl5XQn4tWO/img/workflow/agents/logs/logs-getting-started.png?fit=max&auto=format&n=pBXejvUl5XQn4tWO&q=85&s=06263d5c6a05215050ed332066e7cc9e" width="1500" height="504" data-path="img/workflow/agents/logs/logs-getting-started.png" />

Each tool invocation and LLM call is a seperate step. Our agent first made a call to OpenAI to decide whether to use a tool or reply right away. OpenAI responded with a request to use the tool `communicationTool`. Tool was executed and OpenAI was called with the result of the tool. OpenAI then responded with the final response.