Portkey provides a robust and secure gateway to facilitate the integration of various Large Language Models (LLMs) into your applications, including all the text generation models supported by Huggingface’s Inference endpoints.

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 through a virtual key system.

Provider Slug. huggingface

Portkey SDK Integration with Huggingface

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

1. Install the Portkey SDK

Add the Portkey SDK to your application to interact with Huggingface’s API through Portkey’s gateway.

npm install --save portkey-ai

2. Initialize Portkey with the Virtual Key

To use Huggingface with Portkey, get your Huggingface Access token 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"]
    virtualKey: "VIRTUAL_KEY", // Your Huggingface Virtual Key
    huggingfaceBaseUrl: "HUGGINGFACE_DEDICATED_URL" // Optional: Use this if you have a dedicated server hosted on Huggingface
})

3. Invoke Chat Completions with Huggingface

Use the Portkey instance to send requests to Huggingface. You can also override the virtual key directly in the API call if needed.

const chatCompletion = await portkey.chat.completions.create({
    messages: [{ role: 'user', content: 'Say this is a test' }],
    model: 'meta-llama/Meta-Llama-3.1-8B-Instruct', // make sure your model is hot
});

console.log(chatCompletion.choices[0].message.content);

Next Steps

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 Huggingface requests requests
  3. Tracing Huggingface requests
  4. Setup a fallback from OpenAI to Huggingface APIs