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

# Rate limit for users

> The user-level rate limit helps you control the LLM usage of each user.

<Note>
  This feature is only available for AI gateway users.
</Note>

The user-level rate limit helps you control the LLM usage of each user. You can set a rate limit of **requests per minute** for each user and we will block the API calls that exceed the limit.

## Why user-level rate limit?

* Prevent random users from abusing your system
* Control the cost of your LLM usage

## How to set user-level rate limit

```json theme={"system"}
"customer_params": {
        "customer_identifier": "xxxx", // The user you want to set the rate limit for
        "rate_limit": 100 // The rate limit of the user, requests per minute
    },
```

### Detailed example

<Tabs>
  <Tab title="AI gateway">
    <CodeGroup>
      ```python Python {14} theme={"system"}
      import requests
      def demo_call(input, 
                    model="gpt-4o-mini",
                    token="YOUR_KEYWORDS_AI_API_KEY"
                    ):
          headers = {
              'Content-Type': 'application/json',
              'Authorization': f'Bearer {token}',
          }

          data = {
              'model': model,
              'messages': [{'role': 'user', 'content': input}],
              "customer_params": {"customer_identifier": "xxxx", "rate_limit": 100}
          }

          response = requests.post('https://api.keywordsai.co/api/chat/completions', headers=headers, json=data)
          return response

      messages = "Say 'Hello World'"
      print(demo_call(messages).json())
      ```

      ```TypeScript TypeScript {10} theme={"system"}
      fetch('https://api.keywordsai.co/api/chat/completions', {
        method: 'POST',
        headers: {
          'Content-Type': 'application/json',
          'Authorization': 'Bearer YOUR_KEYWORDS_AI_API_KEY'
        },
          body: JSON.stringify({
              model: 'gpt-4o-mini',
              messages: [{role: 'user', content: "Say 'Hello World'"}],
              "customer_params": {"customer_identifier": "xxxx", "rate_limit": 100}
          })
      })
      .then(response => response.json())
      .then(data => console.log(data));
      ```
    </CodeGroup>
  </Tab>

  <Tab title="OpenAI SDK">
    <CodeGroup>
      ```python Python {11} theme={"system"}
      from openai import OpenAI

      client = OpenAI(
          base_url="https://api.keywordsai.co/api/",
          api_key=YOUR_KEYWORDSAI_API_KEY,
      )

      response = client.chat.completions.create(
          model="gpt-4o-mini",
          messages=[{"role":"user", "content":"Tell me a long story"}],
          extra_body={"customer_params": {"customer_identifier": "xxxx", "rate_limit": 100}}
      )
      ```

      ```TypeScript TypeScript {13} theme={"system"}
      import { OpenAI } from "openai";

      const client = new OpenAI({
        baseURL: "https://api.keywordsai.co/api",
        apiKey: process.env.KEYWORDS_AI_API_KEY,
      });

      const response = await client.chat.completions
        .create({
          messages: [{ role: "user", content: "Say this is a test" }],
          model: "gpt-4o-mini",
          // @ts-expect-error
          customer_params: { customer_identifier: "xxxx", rate_limit: 100 },
        })
        .asResponse();

      console.log(await response.json());
      ```
    </CodeGroup>
  </Tab>

  <Tab title="Other SDKs">
    We also support user-level rate limit in other SDKs or languages, please check out our [integration section](/documentation/admin/llm_provider_keys) for more information.
  </Tab>
</Tabs>