genkitx-openai
Firebase Genkit - OpenAI Plugin
OpenAI Community Plugin for Google Firebase Genkit
genkitx-openai
is a community plugin for using OpenAI APIs with
Firebase Genkit. Built by The Fire Company. 🔥
This Genkit plugin allows to use OpenAI models through their official APIs.
Supported models​
The plugin supports several OpenAI models:
- GPT-4o, GPT-4 with all its variants (Turbo, Vision), and GPT-3.5 Turbo for text generation;
- DALL-E 3 for image generation;
- Text Embedding Small, Text Embedding Large, and Ada for text embedding generation;
- Whisper for speech recognition;
- Text-to-speech 1 and Text-to-speech 1 HD for speech synthesis.
Installation​
Install the plugin in your project with your favorite package manager:
npm install genkitx-openai
yarn add genkitx-openai
pnpm add genkitx-openai
Usage​
Initialize​
import dotenv from 'dotenv';
import { genkit } from 'genkit';
import openAI, { gpt35Turbo } from 'genkitx-openai';
dotenv.config();
const ai = genkit({
plugins: [openAI({ apiKey: process.env.OPENAI_API_KEY })],
// specify a default model if not provided in generate params:
model: gpt35Turbo,
});
Basic examples​
The simplest way to generate text is by using the generate
method:
const response = await ai.generate({
model: gpt4o
prompt: 'Tell me a joke.',
});
console.log(response.text);
Multi-modal prompt​
const response = await ai.generate({
model: gpt4o,
prompt: [
{ text: 'What animal is in the photo?' },
{ media: { url: imageUrl } },
],
config: {
// control of the level of visual detail when processing image embeddings
// Low detail level also decreases the token usage
visualDetailLevel: 'low',
},
});
console.log(response.text);
Text Embeddings​
import { textEmbeddingAda002 } from 'genkitx-openai';
const embedding = await ai.embed({
embedder: textEmbeddingAda002,
content: 'Hello world',
});
console.log(embedding);
Within a flow​
import { z } from 'genkit';
export const jokeFlow = ai.defineFlow(
{
name: 'jokeFlow',
inputSchema: z.string(),
outputSchema: z.string(),
},
async (subject) => {
const llmResponse = await ai.generate({
prompt: `tell me a joke about ${subject}`,
});
return llmResponse.text;
}
);
Tool use​
import { z } from 'genkit';
// ...initialize genkit (as shown above)
const createReminder = ai.defineTool(
{
name: 'createReminder',
description: 'Use this to create reminders for things in the future',
inputSchema: z.object({
time: z
.string()
.describe('ISO timestamp string, e.g. 2024-04-03T12:23:00Z'),
reminder: z.string().describe('the content of the reminder'),
}),
outputSchema: z.number().describe('the ID of the created reminder'),
},
(reminder) => Promise.resolve(3)
);
const result = await ai.generate({
tools: [createReminder],
prompt: `
You are a reminder assistant.
If you create a reminder, describe in text the reminder you created as a response.
Query: I have a meeting with Anna at 3 for dinner - can you set a reminder for the time?
`,
});
console.log(result.text);
For more detailed examples and the explanation of other functionalities, refer to the examples in the official Github repo of the plugin or in the official Genkit documentation.
Contributing​
Want to contribute to the project? That's awesome! Head over to our Contribution Guidelines.
Need support?​
This repository depends on Google's Firebase Genkit. For issues and questions related to Genkit, please refer to instructions available in Genkit's repository. :::
Reach out by opening a discussion on Github Discussions.
Credits​
This plugin is proudly maintained by the team at The Fire Company. 🔥
License​
This project is licensed under the Apache 2.0 License.