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Overview

Our OpenAI integration allows you to easily perform AI-powered tasks, such as summarizing text, answering questions, generating images, fine tuning and much more.

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Installing the OpenAI packages

npm install @trigger.dev/openai@latest

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Authentication

To use the OpenAI API with Trigger.dev, you’ll need an API Key from OpenAI. If you don’t have one yet, you can obtain it from the OpenAI dashboard.

import { OpenAI } from "@trigger.dev/openai";

const openai = new OpenAI({
  id: "openai",
  apiKey: process.env.OPENAI_API_KEY!,
});

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Tasks

Once you have set up a OpenAI client, you can add it to your job and start using the provided tasks:

client.defineJob({
  id: "openai-job",
  name: "OpenAI Job",
  version: "1.0.0",
  trigger: invokeTrigger(),
  integrations: {
    openai, // Add the OpenAI client as an integration
  },
  run: async (payload, io, ctx) => {
    // Now you can access it through the io object
    const completion = await io.openai.chat.completions.create("completion", {
      model: "gpt-3.5-turbo",
      messages: [
        {
          role: "user",
          content: "Create a good programming joke about background jobs",
        },
      ],
    });
  },
});

As you can see above, we’ve replicated the API of the OpenAI TypeScript SDK, with a crucial difference of adding the Task Cache Key as the first parameter.

We’ve also added a few convenience methods to make it easier to work with the OpenAI API, especially in a serverless environment. For example, you can run a Chat Completion task in the background with backgroundCreate():

const completion = await io.openai.chat.completions.backgroundCreate("completion", {
  model: "gpt-3.5-turbo",
  messages: [
    {
      role: "user",
      content: "Create a good programming joke about background jobs",
    },
  ],
});

See our full task reference below:

Chat Completions

Given a list of messages comprising a conversation, the model will return a response

Assistants (Beta)

Build assistants that can call models and use tools to perform tasks

Files

Upload files to use with assistants and fine-tuning

Images

Given a prompt and/or an input image, the model will generate a new image

Fine Tuning Jobs

Manage fine-tuning jobs to tailor a model to your specific training data

Models

List and describe the various models available in the API

Completions (Legacy)

Given a prompt, the model will return one or more predicted completions.

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Usage as Universal Client

You can use our OpenAI integration as a universal client to interact with other OpenAI-compatible APIs, such as Perplexity.ai

import { OpenAI } from "@trigger.dev/openai";

const perplexity = new OpenAI({
  id: "perplexity",
  apiKey: process.env["PERPLEXITY_API_KEY"]!,
  baseURL: "https://api.perplexity.ai",
  icon: "brand-open-source",
});

Since Perplexity.ai is compatible with OpenAI, you can use the same tasks as with OpenAI.

client.defineJob({
  id: "perplexity-tasks",
  name: "Perplexity Tasks",
  version: "0.0.1",
  trigger: eventTrigger({
    name: "perplexity.tasks",
  }),
  integrations: {
    perplexity,
  },
  run: async (payload, io, ctx) => {
    await io.perplexity.chat.completions.create("chat-completion", {
      model: "mistral-7b-instruct",
      messages: [
        {
          role: "user",
          content: "Create a good programming joke about background jobs",
        },
      ],
    });

    // Run this in the background
    await io.perplexity.chat.completions.backgroundCreate("background-chat-completion", {
      model: "mistral-7b-instruct",
      messages: [
        {
          role: "user",
          content: "If you were a programming language, what would you be and why?",
        },
      ],
    });
  },
});

And you’ll get the same experience in the Run Dashboard when viewing the logs:

Perplexity.ai logs

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Example jobs

Code examples

Check out pre-built jobs using OpenAI in our API section.

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