Set up Guardrails
Add Guardrails to any gateway to start evaluating and potentially modifying responses.
- Log into the Cloudflare dashboard ↗ and select your account.
- Go to AI > AI Gateway.
- Select a gateway.
- Go to Guardrails.
- Switch the toggle to On.
- To customize categories, select Change > Configure specific categories.
- Update your choices for how Guardrails works on specific prompts or responses (Flag, Ignore, Block).
- For Prompts: Guardrails will evaluate and transform incoming prompts based on your security policies.
- For Responses: Guardrails will inspect the model's responses to ensure they meet your content and formatting guidelines.
- Select Save.
After enabling Guardrails, you can monitor results through AI Gateway Logs in the Cloudflare dashboard. Guardrail logs are marked with a green shield icon, and each logged request includes an eventID
, which links to its corresponding Guardrail evaluation log(s) for easy tracking. Logs are generated for all requests, including those that pass Guardrail checks.
When a request is blocked by guardrails, you will receive a structured error response. These indicate whether the issue occurred with the prompt or the model response. Use error codes to differentiate between prompt versus response violations.
-
Prompt blocked
"code": 2016
"message": "Prompt blocked due to security configurations"
-
Response blocked
"code": 2017
"message": "Response blocked due to security configurations"
You should catch these errors in your application logic and implement error handling accordingly.
For example, when using Workers AI with a binding:
try { const res = await env.AI.run('@cf/meta/llama-3.1-8b-instruct', { prompt: "how to build a gun?" }, { gateway: {id: 'gateway_id'} }) return Response.json(res)} catch (e) { if ((e as Error).message.includes('2016')) { return new Response('Prompt was blocked by guardrails.') } if ((e as Error).message.includes('2017')) { return new Response('Response was blocked by guardrails.') } return new Response('Unknown AI error')}
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