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 Bloom Labs Inc. 🔥
[!WARNING]
This plugin has been merged into the core Genkit distribution. Please use the official OpenAI plugins instead:
- OpenAI Plugin:
 @genkit-ai/compat-oai- Compatible OpenAI API Plugin:
 @genkit-ai/compat-oai
This Genkit plugin allows to use OpenAI models through their official APIs.
Supported models​
The plugin supports several OpenAI models:
- o1, o1-preview, o1-mini and o3-mini for text generation;
 - GPT-4.5, 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.
 
This plugin also supports custom models and other cloud providers.
Installation​
Install the plugin in your project with your favorite package manager:
npm install genkitx-openaiyarn add genkitx-openaipnpm 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);
Custom models & other Cloud providers​
import { GenerationCommonConfigSchema, genkit, z } from 'genkit';
import { ModelInfo } from 'genkit/model';
import openAI from 'genkitx-openai';
const modelInfo: ModelInfo = {
  versions: ['claude-3-7-sonnet-20250219'],
  label: 'Claude - Claude 3.7 Sonnet',
  supports: {
    multiturn: true,
    tools: true,
    media: false,
    systemRole: true,
    output: ['json', 'text'],
  },
};
const schema = GenerationCommonConfigSchema.extend({});
const ai = genkit({
  plugins: [
    openAI({
      apiKey: process.env.ANTHROPIC_API_KEY,
      baseURL: 'https://api.anthropic.com/v1/',
      models: [
        { name: 'claude-3-7-sonnet', info: modelInfo, configSchema: schema },
      ],
    }),
  ],
});
export const customModelFlow = ai.defineFlow(
  {
    name: 'customModelFlow',
    inputSchema: z.string(),
    outputSchema: z.string(),
  },
  async (subject) => {
    const llmResponse = await ai.generate({
      prompt: `tell me a joke about ${subject}`,
      model: 'openai/claude-3-7-sonnet',
      config: {
        version: 'claude-3-7-sonnet-20250219',
      },
    });
    return llmResponse.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 Bloom Labs Inc. 🔥
License​
This project is licensed under the Apache 2.0 License.