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

> Use your API keys for providers like OpenAI, Anthropic, etc

# Bring your own API keys

<Tip>
  We currently recommend that you bring your own keys for production traffic, as you may require higher provider API rate limits than Auto is able to provide.
</Tip>

You can use LLMs through Auto in two ways:

* **Use Auto's keys:** We pay the LLM provider, and then bill you for the usage.
* **Use your own API keys:** We use your provider API keys, and you're billed directly for usage.

Your keys are never used for experiments & evals that Auto runs - only for your own traffic.

To bring your own keys, include one or more keys in your API request, for example:

```typescript Fetch API (.ts) theme={"system"}
const response = await fetch("https://api.auto.venki.dev/api/v1/chat/completions", {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${process.env.AUTO_API_KEY}`,
    "Content-Type": "application/json",
    // This key will be used for this request
    "X-OpenAI-Api-Key": process.env.OPENAI_API_KEY, 
    "X-Auto-Prompt-Id": "summarize-webpage"
  },
  body: JSON.stringify({
    model: "openai/gpt-4o",
    messages: ...,
    temperature: 0
  })
});
```

## Multiple API keys

You can include multiple API keys - and only the relevant API keys will be used.

```typescript Fetch API (.ts) theme={"system"}
const response = await fetch("https://api.auto.venki.dev/api/v1/chat/completions", {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${process.env.AUTO_API_KEY}`,
    "Content-Type": "application/json",
    // This key will be used for this request.
    "X-OpenAI-Api-Key": process.env.OPENAI_API_KEY, 
    // This key will not be used.
    "X-Anthropic-Api-Key": process.env.ANTHROPIC_API_KEY, 
    "X-Auto-Prompt-Id": "summarize-webpage"
  },
  body: JSON.stringify({
    model: "openai/gpt-4o",
    messages: ...,
    temperature: 0
  })
});
```

## Supported API keys

* OpenAI: `X-OpenAI-Api-Key`
* Anthropic: `X-Anthropic-Api-Key`
* Google Gemini: `X-Gemini-Api-Key`
* Google Vertex AI: See below.

## BYOK for Google Vertex AI

Instead of using a simple API key, Google Vertex AI requires the use of service account credentials instead.
To pass them in, simply URI-encode the JSON service account key, and pass it in as `X-Vertex-Credentials`. Pass the project and location as `X-Vertex-Project` and `X-Vertex-Location` respectively.

```typescript Fetch API (.ts) theme={"system"}
const response = await fetch("https://api.auto.venki.dev/api/v1/chat/completions", {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${process.env.AUTO_API_KEY}`,
    "Content-Type": "application/json",
    // "credentials" is your service account JSON object with top-level fields such as "client_id" and "private_key"
    "X-Vertex-Credentials": encodeURIComponent(JSON.stringify(credentials)),
    "X-Vertex-Project": process.env.VERTEX_AI_PROJECT,
    "X-Vertex-Location": process.env.VERTEX_AI_LOCATION,
    "X-Auto-Prompt-Id": "summarize-webpage"
  },
  body: JSON.stringify({
    model: "vertex_ai/gemini-2.0-flash",
    messages: ...,
    temperature: 0
  })
});
```