Lingyi (01.ai)

Portkey provides a robust and secure gateway to facilitate the integration of various Large Language Models (LLMs) into your applications, including Lingyi (01.ai).

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: lingyi

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Portkey SDK Integration with Lingyi Models

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

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1. Install the Portkey SDK

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

• NodeJS
• Python

npm install --save portkey-ai

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2. Initialize Portkey with the Virtual Key

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

• NodeJS SDK
• Python SDK

import Portkey from 'portkey-ai'

const portkey = new Portkey({
    apiKey: "PORTKEY_API_KEY", // defaults to process.env["PORTKEY_API_KEY"]
    virtualKey: "VIRTUAL_KEY" // Your Lingyi Virtual Key
})

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3. Invoke Chat Completions with Lingyi

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

• NodeJS SDK
• Python SDK

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

console.log(chatCompletion.choices);

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Managing Lingyi Prompts

You can manage all prompts to Lingyi in the Prompt Library. All the current models of Lingyi 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.

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

You’ll find more information in the relevant sections:

1. Add metadata to your requests
2. Add gateway configs to your Lingyi requests
3. Tracing Lingyi requests
4. Setup a fallback from OpenAI to Lingyi APIs