Cerebras

Portkey provides a robust and secure gateway to facilitate the integration of various Large Language Models (LLMs) into your applications, including the models hosted on Cerebras Inference API.

Provider Slug: cerebras

Portkey SDK Integration with Cerebras

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

1. Install the Portkey SDK

NodeJS

npm install --save portkey-ai

Python

pip install portkey-ai

2. Initialize Portkey with Cerebras

To use Cerebras with Portkey, get your API key from here, then add it to Portkey to create the virtual key.

NodeJS SDK

import Portkey from 'portkey-ai'

const portkey = new Portkey({
    apiKey: "PORTKEY_API_KEY", // defaults to process.env["PORTKEY_API_KEY"]
    virtualKey: "CEREBRAS_VIRTUAL_KEY" // Your Cerebras Inference virtual key
})

Python SDK

from portkey_ai import Portkey

portkey = Portkey(
    api_key ="PORTKEY_API_KEY",  # Replace with your Portkey API key
    virtual_key="CEREBRAS_VIRTUAL_KEY" # Your Cerebras Inference virtual key
)

3. Invoke Chat Completions

NodeJS SDK

const chatCompletion = await portkey.chat.completions.create({
    messages: [{ role: 'user', content: 'Say this is a test' }],
    model: 'llama3.1-8b',
});

console.log(chatCompletion.choices);

Python SDK

completion = portkey.chat.completions.create(
    messages= [{ "role": 'user', "content": 'Say this is a test' }],
    model= 'llama3.1-8b'
)

print(completion)

---

Supported Models

Cerebras currently supports Llama-3.1-8B and Llama-3.1-70B. You can find more info here:

Overview - Starter KitStarter Kit

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 Cerebras requests
3. Tracing Cerebras requests
4. Setup a fallback from OpenAI to Cerebras