Portkey provides a robust and secure gateway to facilitate the integration of various Large Language Models (LLMs) into your applications, including Featherless. Featherless.ai is one of the largest AI inference access to 11,900+ open source models. You can instantly deploy at scale for fine-tuning, testing, and production with unlimited tokens With Portkey, you can take advantage of features like fast AI gateway access, observability, prompt management, and more, all while ensuring the secure management of your LLM API keys Portkey’s model catalog.
Provider Slug. featherless-ai

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Portkey SDK Integration with Featherless AI Models

Portkey provides a consistent API to interact with models from various providers. To integrate Featherless AI with Portkey:

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1. Install the Portkey SDK

Add the Portkey SDK to your application to interact with Featherless AI’s API through Portkey’s gateway. 
npm install --save portkey-ai

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2. Initialize Portkey with the Virtual Key

To use Featherless AI with Portkey, get your API key from here, then add it to Portkey to create the virtual key. 
import Portkey from 'portkey-ai'

const portkey = new Portkey({
    apiKey: "PORTKEY_API_KEY", // defaults to process.env["PORTKEY_API_KEY"]
    provider:"@PROVIDER" // Your featherless provider slug from model catalog
})

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3. Invoke Chat Completions with Featherless AI

Use the Portkey instance to send requests to Featherless AI. 
const chatCompletion = await portkey.chat.completions.create({
    messages: [{ role: 'user', content: 'Say this is a test' }],
    model: 'google/gemma-3-4b-it',
});

console.log(chatCompletion.choices);d

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Managing Featherless AI Prompts

You can manage all prompts to Featherless AI in the Prompt Library. All the current models of Featherless AI are supported and you can easily start testing different prompts. Once you’re ready with your prompt, you can use the portkey.prompts.completions.create interface to use the prompt in your application.

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Supported Models

The complete list of features supported in the SDK are available on the link below.

SDK

 You’ll find more information in the relevant sections:
  1. Add metadata to your requests
  2. Add gateway configs to your Featherless
  3. Tracing Featherless requests
  4. Setup a fallback from OpenAI to Featherless APIs