# Cloudflare Workers AI

Our Gemma-SEA-LION-v4-27B-IT model is now supported on the Cloudflare Workers AI for on-demand inferencing, subject to Cloudflare's [Data Usage](https://developers.cloudflare.com/workers-ai/platform/data-usage/) and [Pricing Plans](https://developers.cloudflare.com/workers-ai/platform/pricing/).

This quickstart guide will instruct you through setting up your Workers AI account and REST API to easily experiment with Gemma-SEA-LION-v4-27B-IT. For more detailed information, you can refer directly to the latest guide on Cloudflare [here](https://developers.cloudflare.com/workers-ai/models/gemma-sea-lion-v4-27b-it/)

### Step 1. Create a Cloudflare Account

Sign up for a [Cloudflare account](https://dash.cloudflare.com/sign-up/workers-and-pages) if you have not already done so.

### Step 2. Get Cloudflare API token and Account ID

You need your API token and Account ID to use the REST API.

To get these values:

* In the Cloudflare dashboard, go to the `Workers AI` page and select `REST API`:

<figure><img src="/files/rOJe5f1Dixcc9GSYBPlo" alt="" width="100%"><figcaption></figcaption></figure>

* Get your API token:
  * Select Create a Workers AI API Token.
  * Review the prefilled information.
  * Select Create API Token.
  * Select Copy API Token.
  * Save that value for future use.
* For Get Account ID, copy the value for Account ID. Save that value for future use.

### 3. Run Gemma-SEA-LION-v4-27B-IT via Cloudflare Workers AI API

After creating your API token, authenticate and make requests to the Worker AI API using your API token in the request.

{% tabs %}
{% tab title="curl" %}

```bash
curl https://api.cloudflare.com/client/v4/accounts/{$CLOUDFLARE_ACCOUNT_ID}/ai/run/@cf/aisingapore/gemma-sea-lion-v4-27b-it \
  -X POST \
  -H 'Authorization: Bearer {$CLOUDFLARE_AUTH_TOKEN}' \
  -d '{
    "messages": [
        {
            "role": "system",
            "content": "You are a friendly assistant"
        },
        {
            "role": "user",
            "content": "Tell me a Singlish joke!"
        }
    ],
    "stream": false
    }'
```

{% endtab %}

{% tab title="python" %}

```python
import os
import requests

ACCOUNT_ID = os.environ.get("CLOUDFLARE_ACCOUNT_ID")
AUTH_TOKEN = os.environ.get("CLOUDFLARE_AUTH_TOKEN")

prompt = "Tell me a Singlish joke"
response = requests.post(
  f"https://api.cloudflare.com/client/v4/accounts/{ACCOUNT_ID}/ai/run/@cf/aisingapore/gemma-sea-lion-v4-27b-it",
    headers={"Authorization": f"Bearer {AUTH_TOKEN}"},
    json={
      "messages": [
        {"role": "system", "content": "You are a friendly assistant"},
        {"role": "user", "content": prompt}
      ]
    }
)
completion = response.json()
print(completion["result"]["choices"][0]["message"]["content"])
```

{% endtab %}
{% endtabs %}

Cloudflare also supports OpenAI compatible endpoints for text generation (/v1/chat/completions)

{% tabs %}
{% tab title="curl" %}

```bash
curl --request POST \
  --url https://api.cloudflare.com/client/v4/accounts/{$CLOUDFLARE_ACCOUNT_ID}/ai/v1/chat/completions \
  -H 'Authorization: Bearer {$CLOUDFLARE_AUTH_TOKEN}' \
  -H 'Content-Type: application/json' \
  -d '{
      "model": "@cf/aisingapore/gemma-sea-lion-v4-27b-it",
      "messages": [
        {
          "role": "user",
          "content": "Tell me a Singlish joke"
        }
      ]
    }'
```

{% endtab %}

{% tab title="python" %}

```python
from openai import OpenAI

ACCOUNT_ID = os.environ.get("CLOUDFLARE_ACCOUNT_ID")
AUTH_TOKEN = os.environ.get("CLOUDFLARE_AUTH_TOKEN")

client = OpenAI(
    api_key=AUTH_TOKEN,
    base_url=f"https://api.cloudflare.com/client/v4/accounts/{ACCOUNT_ID}/ai/v1" 
)

completion = client.chat.completions.create(
    model="@cf/aisingapore/gemma-sea-lion-v4-27b-it",
    messages=[
        {
            "role": "user",
            "content": "Tell me a Singlish joke!"
        }
    ]
)

print(completion.choices[0].message.content)
```

{% endtab %}
{% endtabs %}


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.sea-lion.ai/guides/inferencing/cloudflare.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.