> ## Documentation Index
> Fetch the complete documentation index at: https://docs.portkey.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Monster API

> MonsterAPIs provides access to generative AI model APIs at 80% lower costs. Connect to MonsterAPI LLM APIs seamlessly through Portkey's AI gateway.

Portkey provides a robust and secure gateway to facilitate the integration of various Large Language Models (LLMs) into your applications, including [MonsterAPI APIs](https://developer.monsterapi.ai/docs/getting-started).

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](/product/ai-gateway/virtual-keys) system.

<Note>
  Provider Slug. `monsterapi`
</Note>

## Portkey SDK Integration with MonsterAPI Models

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

### 1. Install the Portkey SDK

Add the Portkey SDK to your application to interact with MonsterAPI's API through Portkey's gateway.

<Tabs>
  <Tab title="NodeJS">
    ```sh theme={"system"}
    npm install --save portkey-ai
    ```
  </Tab>

  <Tab title="Python">
    ```sh theme={"system"}
    pip install portkey-ai
    ```
  </Tab>
</Tabs>

### 2. Initialize Portkey with the Virtual Key

To use Monster API with Portkey, [get your API key from here,](https://monsterapi.ai/user/dashboard) then add it to Portkey to create the virtual key.

<Tabs>
  <Tab title="NodeJS SDK">
    ```js theme={"system"}
    import Portkey from 'portkey-ai'

    const portkey = new Portkey({
        apiKey: "PORTKEY_API_KEY", // defaults to process.env["PORTKEY_API_KEY"]
        virtualKey: "VIRTUAL_KEY" // Your MonsterAPI Virtual Key
    })
    ```
  </Tab>
</Tabs>

### **3. Invoke Chat Completions with** MonsterAPI

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

<Tabs>
  <Tab title="NodeJS SDK">
    ```js theme={"system"}
    const chatCompletion = await portkey.chat.completions.create({
        messages: [{ role: 'user', content: 'Say this is a test' }],
        model: 'TinyLlama/TinyLlama-1.1B-Chat-v1.0',
    });

    console.log(chatCompletion.choices);
    ```
  </Tab>

  <Tab title="Python SDK">
    ```python theme={"system"}
    completion = portkey.chat.completions.create(
        messages= [{ "role": 'user', "content": 'Say this is a test' }],
        model= 'mistral-medium'
    )

    print(completion)
    ```
  </Tab>
</Tabs>

## Managing MonsterAPI Prompts

You can manage all prompts to MonsterAPI in the [Prompt Library](/product/prompt-library). All the current models of MonsterAPI 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.

## Supported Models

[Find the latest list of supported models here.](https://llm.monsterapi.ai/docs)

## Next Steps

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

<Note>
  [SDK](/api-reference/portkey-sdk-client)
</Note>

You'll find more information in the relevant sections:

1. [Add metadata to your requests](/product/observability/metadata)
2. [Add gateway configs to your MonsterAPI requests](/product/ai-gateway/configs)
3. [Tracing MonsterAPI requests](/product/observability/traces)
4. [Setup a fallback from OpenAI to MonsterAPI APIs](/product/ai-gateway/fallbacks)