Serverless AI APIs Using Cloudflare Workers

Question

Pulumi · Accepted Answer

To create serverless AI APIs using Cloudflare Workers with Pulumi, you'll need to set up a few resources. Cloudflare Workers are scripts that run on Cloudflare's edge locations around the world. They allow you to modify your site’s HTTP requests and responses, make parallel requests, or generate responses from the edge.

To build this, we will create a Cloudflare Worker script, route the script to a URL pattern, and set up any necessary resources like key-value (KV) storage if your API requires state.

Here is a step-by-step Pulumi program in Python on how to accomplish this:

1. **Worker Script**: This is the actual serverless function that will process the incoming requests and compute a response. Use the `cloudflare.WorkerScript` resource to deploy your code to Cloudflare's edge network.
   
2. **Worker Route**: The `cloudflare.WorkerRoute` resource associates your Worker Script with a specific URL pattern, so that any requests to that pattern are processed by your script.
   
3. **(Optional) Workers KV Namespace**: If your API needs to store or retrieve state, you can use Cloudflare's Workers KV. The `cloudflare.WorkersKvNamespace` resource sets up a new storage namespace.
   
4. **(Optional) Workers KV**: To put or fetch data from a KV namespace, you'll need to interact with the KV API in your Worker Script code. This isn't a Pulumi resource, but it's part of the runtime API for your Worker.

Now, let's translate this into a Pulumi program:

```python
import pulumi
import pulumi_cloudflare as cloudflare

# Replace these with your actual values
account_id = "your-account-id"
zone_id = "your-zone-id"
worker_script_name = "my-ai-api-script"

# This script content would be your own Worker JavaScript or WASM code
# For AI APIs, you can include your algorithms here or make calls to AI services.
worker_script_content = """
addEventListener("fetch", event => {
  event.respondWith(handleRequest(event.request))
})

async function handleRequest(request) {
  // Your serverless AI logic goes here
  return new Response("Hello World!")
}
"""

# Create a Cloudflare Worker script that contains your serverless function
# More about WorkerScript: https://www.pulumi.com/registry/packages/cloudflare/api-docs/workerscript/
ai_worker_script = cloudflare.WorkerScript(worker_script_name,
    account_id=account_id,
    name=worker_script_name,
    content=worker_script_content
)

# Map the worker script to a URL pattern so that any requests to the pattern
# trigger the worker.
# More about WorkerRoute: https://www.pulumi.com/registry/packages/cloudflare/api-docs/workerroute/
ai_worker_route = cloudflare.WorkerRoute(f"{worker_script_name}-route",
    zone_id=zone_id,
    pattern="yourwebsite.com/ai-api/*",
    script_name=ai_worker_script.name,
)

# If your API requires state you can init a KV namespace for it
# More about WorkersKvNamespace: https://www.pulumi.com/registry/packages/cloudflare/api-docs/workerskvnamespace/
ai_kv_namespace = cloudflare.WorkersKvNamespace("my-ai-kv-namespace",
    account_id=account_id,
    title="my-ai-kv-namespace"  # This will be your identifier for the namespace
)

# KV bindings need to be added to the Worker script, but this is something
# that is currently done through the Cloudflare dashboard or API, not directly
# through Pulumi's cloudflare provider.
# Make sure you update your worker with the appropriate binding like:
# { "name": "MY_KV_NAMESPACE", "namespace_id": "<YOUR_KV_NAMESPACE_ID>" }

# Export the live URL of the Worker route so you can easily access it.
pulumi.export("live_url", ai_worker_route.pattern)
```

This code sets up a serverless AI API using Cloudflare Workers and optionally KV storage. When you deploy this Pulumi stack, the script will be published, and the API endpoint will be live at the specified URL pattern.

Remember to replace placeholders like `your-account-id`, `your-zone-id`, and `yourwebsite.com` with your actual Cloudflare account details and target domain. The Worker script content (`worker_script_content`) should include your actual server-side logic for the AI API you want to offer.

After deploying, any requests matching the specified pattern will execute your Worker script, where you can implement the logic for your AI services.

Lastly, ensure you have the Pulumi CLI installed and configured with Cloudflare access for this to work seamlessly.