Huggingface

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

pip install 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 your Huggingface 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 Access Token
    huggingfaceBaseUrl: "HUGGINGFACE_DEDICATED_URL" // Optional: Use this if you have a dedicated server hosted on Huggingface
})

from portkey_ai import Portkey

portkey = Portkey(
    api_key="PORTKEY_API_KEY",  # Replace with your Portkey API key
    virtual_key="VIRTUAL_KEY",   # Replace with your virtual key for Huggingface
    huggingface_base_url="HUGGINGFACE_DEDICATED_URL" # Optional: Use this if you have a dedicated server hosted on Huggingface
)

from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

client = OpenAI(
    api_key="HUGGINGFACE_ACCESS_TOKEN",
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        api_key="PORTKEY_API_KEY",
        provider="huggingface",
        huggingface_base_url="HUGGINGFACE_DEDICATED_URL"
    )
)

import OpenAI from "openai";
import { PORTKEY_GATEWAY_URL, createHeaders } from "portkey-ai";

const client = new OpenAI({
  apiKey: "HUGGINGFACE_ACCESS_TOKEN",
  baseURL: PORTKEY_GATEWAY_URL,
  defaultHeaders: createHeaders({
    provider: "huggingface",
    apiKey: "PORTKEY_API_KEY",
    huggingfaceBaseUrl: "HUGGINGFACE_DEDICATED_URL"
  }),
});

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);

chat_completion = 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
)
    
print(chat_completion.choices[0].message.content)

chat_completion = client.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
)

print(chat_completion.choices[0].message.content)

async function main() {
    const chatCompletion = await client.chat.completions.create({
        model: "meta-llama/meta-llama-3.1-8b-instruct", // make sure your model is hot
        messages: [{ role: "user", content: "How many points to Gryffindor?" }],
    });
    console.log(chatCompletion.choices[0].message.content);
}

main();

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:

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Last updated 6 days ago